NBS SPECIAL PUBLICATION 395

Vau of

U.S. DEPARTMENT OF COMMERCE / National Bureau of Standards

Simulation and

Gaming
NATIONAL BUREAU OF STANDARDS

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Maryland, unless otherwise noted; mailing address
15 1974

Simulation and Gaming

Proceedings of the 12th Annual Symposium

National Gaming Council

and the

4th Annual Conference

International Simvilation and Gaming Association

Held at the National Bureau of Standards,

Gaithersburg, Md., September 17-19, 1973

Edited by

John E. Moriarty

Technical Analysis Division

tl .5> National Bureau of Standards

Washington, D.C. 20234

Sponsored by the National Bureau of Standards

In Cooperation With

The United States Environmental Protection Agency

Washington, D.C. 20460 and

Rutgers University,

New Brunswick, N.J. 08903

; U.S. DEPARTMENT OF COMMERCE, Frederick B. Dent, Secretary

I NATIONAL BUREAU OF STANDARDS, Richard W. Roberts, D/recfor

Issued June 1974

I
Library of Congress Cataloging in Publication Data

National Gaming Council. Simulation and gaming.

(National Bureau of Standards Special Publication 395) "Sponsored by the National Bureau of Standards in cooperation with the United States Environmental Protection Agency . . . and Rutgers University."

Supt. of Docs. No. €13.10:395.

1. Game theory—Congresses. 2. Simulation methods

Congresses. I. Moriarty, John E., ed. II. International Simulation and Gaming Association. III. United States. National Bureau of Standards. IV. United States. Environmental Protection Agency. V. Rutgers University,

New Brunswick, N.J. VI. Title. VII. Series: United States. National Bureau of Standards. Special Publication 395. QC100.U57 No. 395 [QA269] 389'.08s [519.3] 74-7048

National Bureau of Standards Special Publication 395

Nat. Bur. Stand. <U.S.), Spec. Publ. 395, 458 pages (June 1974)

CODEN: XNBSAV

U.S. GOVERNMENT PRINTING OFFICE

WASHINGTON: 1974

For sale by the Superintendent of Documents, U.S. Government Printing Office, Washington, D.C. 20402 (Order by SD Catalog No. C13.10:395). Price $4.25 Stock Number 0303-01300
TABLE OF CONTENTS

Ppae

FORIVARD

'

1\ELC0MING ADDRESS , 1

INTRODUCTION 3

THEORY AND EVALUATION TASK GROUP 21

Facilitator's Statements 21

1. Theory and Evaluation, Richard A. Schusler 21

2. Evaluation: Classroom Uses: Training Planning and Research

Uses, Jay C. Thcmpson, Jr., Charles H. Postma 22

3. Evaluation Sub-group Facilitator's Statement, Sivasailam

Thiagarajan 24

4. Evaluation Facilitator's Statement, Patricia Y. Martin 26

5. Sub-group Title: Theory and Evaluation Facilitator's

Statement, Steven H. Woolard 28

Formal Papers 30

1. Simulating a Model of Perception to Shape Problem Recognition

Behavior, Steven H. Woolard 30

2. The What and Why of Gaming, A Taxonomy of Experimental

Learning Systons, Brent D. Ruben 40

3. Conflict Resolution: From Power to Peer Relations in the

Helping Professions, Patricia Y. Martin and Marie W.

Osmond 56

I 4. A Preliminary Investigation of the Use of Prince -- A ManComputer Simulation of International Relations --in High

School Courses, Steven J. Kidder, Richard E . Horowicz,

and Gary M. Kiselewich 74

5. Obstacle Course, John T . Foster, Jr 82

6. Simulation: An Analysis of Student Cognitive Retention and

II Student Teacher Affective Perceptions, Charles H. Postma,

' and Jay C. Thompson, Jr 91

7. Simulating an Urban School and Ccanmunity for Use in Teacher

Education, Frank P. Diulus 103

8. Design, Development, and Validation of Anticipation Games,

Melvyn I. Semmel and Sivasailam Thiagarajan 113

I 9. Using Simulation to Implement TABA's Cognitive Theory,

Richard A. Schusler 128

10. The Effect of Instructional Gaming Upon Absenteeism: The

First Step, Layman E. Allen and Dana B. Main 135

11. Simulation/Gaming: An Autotelic Inquiry Technique,

Ron Stadsklev 159

iii
DESIGN TASK GROUP

Facilitator's Statements

1. Developing Computer-Based Simulations, Facilitator's

Statonent, Roy I. Miller

2. Designing Conputer -Based Simulations, Facilitator's

Statement, Marshall H. Whithed

3. Frame Games: Design and Redesign, R. H. Armstrong,

Margaret Hobson

4. Frame Games: Design and Redesign, Earl S. Niilley

5. Decision: Futures Modeling, Dennis L. Little

6. Designing Interactive Social Simulations, Facilitator's

Statanent, Georgeann Wilcoxson

7. Sub-group: Selecting and Developing Media in Simulation

Design, Charles H. Adair |; 8. Student Designed Games, Facilitator's Statement, ! Harriet Tamminga .....

9. Computer-Based Gaming Model.s, Phillip D. Patterson ....... |: 10. Unstructured and Game -Generating Games, Facilitator's

Statement, Klaus F. Dette ]

Formal Papers 1

1. A Process for Designing, Developing, and Evaluating Social

Simulation, Charles H. Adair ] 2. A Model for Selecting Optimun Media as Part of the

Simulation Design Process, Charles H. Adair 1 3. Where All Else Fails - An Approach to Defining the Possible

Uses of Gaming -Simulation in the Decision-Making Process,

R.H.R. Armstrong and Margaret Hobson 2 4. Simulated Universities, H. A. Becker 2 5. The Data Behind Simulation Models, H. A. Becker I 6. Simulating Alternative Futures for American Education,

Jerry Debenham I 7. A Guide for Simulation Design, Charles H. Adair and

John T. Foster, Jr I

APPLICATIONS TASK GROUP Ij

Facilitator's Statements ^

1. Applications: Research, Facilitator's Statenent,

Richard L. Dukes > 2. Medicine and Social Welfare, Facilitator's Statement,

John T. Foster, Jr. . ' 3. Teaching -Training: Urban Planning, David E. LaHart .... f 4. Teaching -Training: Elementary -Secondary Education, ' Harriet E . Arnold l»i

iy
5. Community and Public Policy Applications of Gaming

Simulation, J. Robert Hanson 308

6. Community and Public Policy Applications, George M. McFarland . 7. Issues in Game Use: What Values are Conveyed by Game

Designers and Users, George M. McFarland 309

Formal Papers 312

1. Simulations and Games as Growth Group Experiences,

Judith F. Karslimer 312

2. The Disorganized Health Clinic as a Simulation, John T.

Foster, Jr 316

3. Simulation and Gaming as Aids in Regional and InterCommunity Problem Solving, Herman Sievering and

James Sinopoli 324

4. Paying the Piper or Pay Us Again, Sam, Stuart Cipinko 335

5. Public Policy Applications, George McFarland 341

6. Massive Management Gaming, Richard F. Barton 343

7. Simulating Sexism: Unintentional (?) Replication of Reality,

Nancy D. Glandon 352

8. Advocacy - A Community Planning Game for the Ranking of

School System Goals and Training Needs, J. Robert Hanson . . 358

9. Learning Tools to Research Instruments: A Research Package

for Starpower, Richard L. Dukes 365

10. A Pedagogical Schema for the Development and Use of Conputer

Simulation Technology, Dana B. Main, Robert Stout,

D. W. Rajecki, Howard Eichenbaum and Trudy Villars 374

11. Education and Training for Contemporary Urban Planning

Systems: The Impact of Interactive Simulation,

Robert M. Sarly 382

12. The Publication and Distribution of Simulation Games,

Irving B. Naiburg, Jr 397

TASK GROUP SUNMARIES 398

Design Sub-group Summary: Computer -Based Gaming Simulations,

Philip D. Patterson 398

Urban Planning Sub-group: Summary Paper, David E. LaHart 405

Teaching and Training Sub-grotqD: Business Summary State of the

Art, Myron Uretsky, Richard F. Barton 407

Research Applications of Simulation Games: Summary Paper,

Richard L . Dukes 409

IgAME demonstration DESCRIPTIONS 413

Scenario - Game 413

ILIST OF ATTENDEES 443

V
ABSTRACT

This volume contains the Facilitator's Statements and Formal Papers

presented at a Conference on Sim.ulation and Gaming sponsored by the

Technical Analysis Division of the National Bureau of Standards in

cooperation with the United States Environmental Protection Agency and

Rutgers University and held from September 17 to 19, 1973.

There are five Facilitator Statements and eleven formal papers on

the theory and evaluation of Simulation Gaming, ten Facilitator

Statements and twelve fomal papers on Gaming Applications, along with

Task Group Summaries and Game Demonstration Descriptions.

The formal papers and Facilitator Statements are presented by both

United States and foreign authors and represent a significant treatise

on the world-wide "state of the art" in Simulation and Gaming.

Key Words: Cognitive Retention; Computer; Decision-making; Education;

Elementary -secondary education; Gaming; Health; Instructional

Learning systems; Management; Medicine; Model; Public policy;

Recognition behavior; Regional; Research applications; Sex;

Simulation; Social simulation; Teacher- training; Urban;

Validation; Welfare

vi
FORWARD

These proceedings are the results of a conference held on

September 17-19, 1973 at the National Bureau of Standards. The conference

was a working conference in which members of the National Gaming Council

and the International Simulation and Gaming Association share their ideas

between the participants and other interested parties.

The conference stressed the theory, design, and applications

of simulation and game design along with live demonstrations of computerized games. The contributions to these proceedings are many and varied.

Each major section contains both formal papers and transcripts of the various

panel meetings and working sections.

The editor wishes to acknowledge the cooperation of the staff of

the United States Environmental Protection Agency and the staff of the

Sociology Department, Douglass College, Rutgers University. Special

thanks for the tireless effort by the Program Chairman, Dr. Cathy Greenblat

and Co-chairman for Proceedings and Arrangements, Dr. Peter House.

Finally, the Conference Coordinators, Mr. Albert Pines, Mr. Martin Brossman,

of the Environmental Studies Division , Washington Environmental Research

Center, and Miss Carol Naas , Mrs. Diane Beall, and Mrs. Mary Abbott of the

NBS staff deserve the thanks of all concerned for their cooperation and

dedication

.

John E . Moriarty

Technical Analysis Division

National Bureau of Standards

January 16 . 1974

vii

WELCOMING ADDRESS TO THE NATIONAL GAMING COUNCIL AND THE INTERNATIONAL

SIMULATION AND GAMING ASSOCIATION -- September 17, 1973

By Ernest Ambler, Deputy Director, National Bureau of Standards

i

I I am pleased to welcome you on behalf of Richard Roberts, the Bureau's

I Director, and all the staff of the National Bureau of Standards. It is a

j pleasure to host the first Joint Conference of the National Gaming Council

I and the International Gaming and Simulation Association. I would like

I to extend a special welcome to those visitors who come from overseas and to

those of you who are here at the Bureau of Standards for the first time.

i As many of you know, the Bureau of Standards is one of the largest

and most technologically diversified laboratories of the government. It was

j founded in 1901, when uniformity of measurements was a very acute problem

in this country. In Brooklyn there were no less than four measures for the

foot, while people were selling commodities with the slogan: "Buy from

j us; our pound is bigger than our competitor's." At the same time industrial

I developments were reaching the point where accurate measurements and

reliable data were sorely needed. The Bureau's charter was designed to

j attack these problems. The charter was very broadly written, has served

i us well and has needed very little amendment through the years. Among

the many things that we are enjoined to do is to support other government

j agencies, particularly in the application of science and technology for

I the public's benefit.

Today, the Bureau, with some modifications, provides the same basis

of measurement that it has since its inception in 1901. For example,

j we deal with the technical basis, both nationally and internationally,

for measurement systems; we provide scientific and technological services

to government and industry; we attempt to provide a technical basis

for equity in trade; and we provide technical services to promote public

safety.

There is a definite connection between the past and present contributions

II of the Bureau of Standards and your special interests here at this Conference,

l' As early as 1954 we were engaged in the development and implementation of

I simulation models. These initial efforts were largely in support of Defense

programs, and some of you might recall that the earliest computer war games

were run on the Bureau-of- Standards -built SEAC computer. A portion of the

,| work was concerned with the simulation and replication of experiments in

j the basic sciences and engineering. These and other developmental activities

pointed to the requirement for mathematical algorithms, statistical tools,

numerical analysis techniques, distribution tables, and random number

generators. NBS has made many contributions in these areas.

I
Moving to the 60 's the direction of the work and that of the

simulation community in general expanded to the civil sector. Here at

the Bureau large network analysis problems were undertaken and simulation

techniques for resource allocations were developed and tested. Concurrent1> our competence and capabilities in the areas of computer science and

operations research were expanded to meet these and other challenges. In

the 70 's we are now faced with supporting a host of new society-related

programs such as fire, housing, law enforcement, and so on. Mathematical

modeling and simulation are important tools in helping attack these problems

For example, our charter to reduce the hazards of fire-related injury,

death, and property loss requires that we investigate, through mathematical

modeling, the physical phenomena of fire growth and spread. We also seek

solutions to operational problems in fire protection such as the most

appropriate locations for fire stations. Our programs in criminal justice

and consumer product safety have clarly demonstrated the utility of the

simulation approach in concert with engineering oriented developmental

activities

.

^^y remarks are intended to illustrate that a broad range of technical

programs at the Bureau are modified and developed to suit the times. Many

of these show a strong and continuing commitment in gaming and simulation,

where competence has been developed and challenging problems have been

identified. However, in order to benefit from what has been done, the i exchange of ideas, information, and techniques must occur and for this reasor this joint meeting on the grounds of the Bureau of Standards is most

appropriate. This Conference represents a kaleidoscope of interests in the

theory, design and application of modeling games and we feel there is much

to be gained from the exchange of ideas and information that will occur over

the next few days. We are very pleased that you are here, that you selected

NBS as the site for your conference, and we wish all the participants an

interesting and valuable conference.
INTRODUCTION: THE STRUCTURE AND PROCESS OF THE 1973

JOINT MEETINGS OF THE NATIONAL GAMING COUNCIL

AND THE INTERNATIONAL SIMULATION AND GAMING ASSOC I API ON

Cathy S. Greenblat

Department of Sociology

Douglass College, Rutgers University

New Brunswick, New Jersey 08903

Program Chairman, 1973 Joint Meetings: NGC-ISAGA

The structure and mode of operation of this year's meeting

grew out of the conviction that the most important aspect of many

professional meetings is the opportunity they provide for people

with similar interests and problems to meet with one another.

j Hence the meetings were designed to create a WORKING conference

one in which we could maximize the sharing of ideas between

j participants. "Formal papers" were deliberately kept to a minimum,

I being offered as springboards to further discussion rather than as terminal presentations. Each presenter was asked to serve as a "facilitator" in a small group discussion following his or her

presentation. At this time questions and challenges could be

explored and amplification of ideas presented in the paper could

: take place. Other knowledgeable persons were identified in advance

I to also serve as "facilitators" in these sessions.

The initial formulation of possible topics for papers and/or

discussion groups was as thorough as could be developed. The major

(I themes around which we wished the conference to be organized —

theory, evaluation, design, applications, and resources — were

made the center sectors in a wheel- which attempted to delineate

the relevant aspects of gaming in 1973. Fanning out from these

j major sectors were subdivisions with increasing detail as one moved

f from the center of the circle.

This conceptual wheel, modelled from those being developed

by Richard Duke, was made the major element of the preliminary

announcement of the meetings and the call for papers. Recipients

were informed that the wheel provided a graphic overview of the

possible range and scope of topics for the conference, and that particular aspects would be selected in accordance with the interests

and expertise of the participants. They were then invited to help

'I shape the program by Informing me of their interests and Intended

contributions.

A number of people responded to this invitation, suggesting

at times what they hoped to do and at other times what they hoped

others would present! These responses led to the formulation of the

final program. Those topics of "across-the-board" interest were

ij made the subjects of general symposia. One was offered each day

with no conflicting offerings. Three major Task Groups were set up

by combining Theory-Evaluation and by dealing with Resources through

|j one of the symposia, a display table, and a series of gamingI simulation demonstrations on both Monday and Tuesday evenings.

5
The final program then evolved as follows:

. GENERAL SYMPOSIA

\. INTERNATIONAL DEVELOPMENTS IN GAMING SIMULATION

Synopses of the state-of-the-art and of new developments in

gaming in several countries.

Robert H.R. Armstrong, England; ^ ^" ' Hank Becker, Netherlands;

Margrit Kennedy, Germany: "

, /

' Allan Feldt, United States.

2. TOWARD A THEORY OF GAMING

A thematic introduction to the conference and to the task groups.

Richard D. Duke, University of Michigan.' -.

3. PRESENT AND FUTURE RESOURCES IN GAMING-SIMULATION

A pragmatic session led by representatives of major outlets of

information and games.

Don Coombs, S i mu I at i on/Gam i ng/News ; Gail Fennessey, Academic Games Associates, and Simulation and

Games: An Internationa! Journal ; Clark Rogers, Document Retrieval Service, University of Pittsburgh;

I rv Naiburg, Appleton Century Crofts.

4. DEVELOPMENTS AND PROSPECTS IN THEORY-EVALUATION, DESIGN, AND APPLICATIONS

Summaries of the work of the three task groups.

TASK GROUPS \ .

'

THEORY-EVALUATION: This task group explored the related elements

of the theoretical bases and relationships of gaming (e.g.

learning theory, communications theory, socialization theory,

systems theory, operations research, etc.) and evaluation of . . the outcomes of gaming activities.

DESIGN: This task group addressed itself to a number of dimensions

of the modelling-design-construction process.

APPLICATIONS: This task group addressed itself to questions of the

extent and manner in which gam i ng-s i mu I at i ons are being utilized

in a variety of contexts. The three major arenas of application

which formed the basic sub-groupings were: (I) teaching and training;

(2) community and public policy applications; and (3) research.

The first was further sub-divided by interest area.

A full listing of the activities within the sub-groups follows:

4
N. G.C. - LSiAjGA

5
THEORY-EVALUATION TASK GROUP

PANELS:

1. THE WHAT AND WHY OF GAMING

Ron Stadsklev, Institute of Higher Education Research and

Services, Alabama

Layman Alien, University of Michigan

Gerry Gutenschwager , Washington University, St. Louis

2. GENERAL PROBLEMS IN EVALUATION OF GAM I NG-S I MULAT I ON

Dan Klassen, State University of New York, Stony Brook;

Norman Hummon, University of Pittsburgh;

3. NEW FINDINGS FROM EVALUATIVE STUDIES

Layman Allen, University of Michigan; , •' Steve Kidder, Abt Associates; - Frank Diulus, University of Pittsburgh;

Patricia Martin (and Marie Osmand), Florida State University;*

Richard Schusler, University of Kansas;

Melvyn Semmel and Sivasailam Thiagarjan, Indiana University;

Charles Postma, Ashland College and Jay Thompson, Bail State

University;

William Stembler, Silver Springs;

Steven Woo lard, Florida State University. . ; ,;

SUB-GROUP MEETINGS AND FACILITATORS:

1 . THEORY

Facilitators: members of pane! 1 above.

2. EVALUATION

Facilitators: members of panels 2 and 3 above.

DESIGN TASK GROUP

PANELS:

1. MODELS OF THE GAM I NG-S 1 MULAT I ON DESIGN PROCESS

Charles Adair, Florida State University;

Erwin Rausch, Didactic Systems, Inc.

2. CONCEPTUAL MODELLING AND VALIDATION OF MODELS

Hank Becker, Sociologisch Instltuut dan de Ri jkuniversitat,

Utrecht, Netherlands;

Peter House, Environmental Protection Agency;

Jerry Debenham, University of Utah;

Klaus Dette , University of Manchester Institute of Science

and Technology, England;

6
SUB-GROUP MEETINGS AND FACILITATORS:

1. GENERAL DIMENSIONS OF DESIGN

Charles Adair, Florida State University;

Erwin Rausch, Didactic Systems, Incorporated.

2. DEVELOPING COMPUTER-BASED SIMULATIONS

Marshall Whithed, Temple University;

Roy Miller, Environmental Simulation Laboratory, University

of Michigan;

Phil Patterson, Environmental Protection Agency.

3. UNSTRUCTURED AND GAME-GENERATI NG GAMES

Fred Goodman, University of Michigan;

Klaus Dette , University of Manchester Institute of

Science and Technology;

4. DESIGNING INTERACTIVE SOCIAL SIMULATIONS

Armand Lauffer, University of Michigan;

Georgeann Wilcoxon, Presbyterian Board of Christian Education.

5. FUTURES MODELLING

Jerry Debenham, University of Utah;

Dennis Little, Long Range Planning Dept., Social Security

Admi n i strat i on

6. STUDENT-DESIGNED GAMES

John Hershey, University City Science Center;

Harriet Tamminga, University of Denver

7. FRAME GAMES: DESIGN AND REDESIGN

Robert H.R. Armstrong (and Margaret Hobson), Institute of

I Local Government, University of Birmingham,- England;*

Fred Goodman, University of Michigan;

Gini Buus, Lutheran Campus Ministry;

Ear! f-lulley. Center for Simulation Studies;

Richard D. Duke, University of Michigan and Cathy S.

Greenblat, Rutgers University.

APPLICATIONS TASK GROUP

5 PANELS:

j I. ISSUES IN GmE USE: WHAT VALUES ARE CONVEYED BY GAME DESIGNERS

AND USERS?

Nancy Glandon, University of Red lands;

Stuart Cipinko, University of Redlands;

George McFarland, Simulation Sharing Service.

7
USES OF GAMING-SiriULATION FOR RESEARQJ

Richard Dukes, University of Colorado;

Robert Sar!y, Central PolytGchnic of London;

Gail Fennessey, Academic Games Associates: -

' Conrad Weiler, Temple University.

PUBLIC POLICY APPLICATIONS OF GAM I NG-S ! MULAT ! Ori Robert H.R. Armstrong, Institute of Local Government,

University of Birmingham, England;

Robert Hanson, Scientific Management Associates;

Richard McGinty, Project COMEX, University of Southern

Ca I i f orn i a

;

Jim Sinopoli (and Herman Sievering), Governor's State

University; * Gini Buus, Lutheran Campus Ministry.

NEW DEVELOPMENTS IN TEACHING AND TRAINING

Dana Main, (Robert Stout, D.W. Rajecki , Howard Eichenbaum,

Trudy ViMars), University of Michigan; * Richard Barton, University of Texas;

Judy Karshmer, University of Massachusetts School of Nursing.

SUB-GROUP MEETINGS AND FACILITATORS:

1. COMMUNITY AND PUBLIC POLICY APPLICATIONS

Facilitators: members of panel 3 above.

2. RESEARCH

Facilitators: members of pane! 2 above.

3. TEACHING AND TRAINING:

A. Elementary and Secondary Education

Carl Rinne, University of Michigan - Plint;

Harriet Arnold, Florida State University

B. Urban Planning

Allan Feldt, University of Michigan;

Robert Sarly, Central Polytechnic of London;

David La Hart, Bureau of Environmental Studies, Florida

C. Health and Social Work:

Armand Lauffer, Universi+y of f-lichigan;

Shirley Smoyak, Rutgers University Medical School;

Judy Karshmer, University of Massachusetts School of

rJursing.

8
D. Business

Richard Barton, University of Texas;

Myron Uretsky, New York University.

E. Mi I i tary

John Honig, Department of the Army

(*co-authors not present at the meetings are indicated in parentheses).

There were two additional types of sessions: business meetings

and informal social events. The NGC business meeting drew about

40-50 people. Several important decisions were reached at that time:

(I) the 1974 NGC meetings will be held in Pittsburgh, sponsored by

a consortium of i ns i ttut i ons . Arrangements are being made by

Dr. Clark Rogers, Department of Urban Affairs, University of

Pittsburgh. Clark welcomes suggestions from all interested in

the forthcoming meetings. (2) The 1975 meetings are tentatively

scheduled for Los Angeles. It was hoped that with advance time

such as this decision would provide, some of the problems of conference

organizing could be mitigated. The person to contact about these

meetings is Dr. Richard McGinty, Project COMEX, University of

Southern California. (3) A committee was set up to investigate

modes of formalizing the National Gaming Council. Incorporation,

becoming a sub-group of another organization, or developing into a regional chapter (North American) of ISAGA were discussed and will

be investigated by this committee. Richard D. Duke, School of

Natural Resources, University of Michigan is coordinating this

comm i ttee

.

The ISAGA business meeting was attended by about 30 conference

participants. Endorsement of the proposal to hold the 1974 ISAGA

meetings in West Berlin, arranged by Margrit Kennedy, will be carried

back to the European membership for final ma i

I -vote decision. Sites

for future meetings were discussed and further suggestions will be

elicited from members. Finally, membership, finance, and development

of the organization were explored.

Last, but surely not least important, the conference included

several informal social events. Although registration for the

conference did not take place until Monday morning, the meetings

officially began on Sunday evening with a ''games party". In accord

with the argument many of us give that games are good for generating

interaction between people who don't know each other, a series of

games were put out on tables to help the travel -weary relax and meet

old and new friends. Most of the games presented at that time were those designed for entertainment, rather than for teaching, research

or policy applications. Only those games that could be left "alone"

on tables for those who wished to see or play them were used; those

that were to be demonstrated by their designers were saved until

Monday and Tuesday evening.

9
Several games publishers and manufacturers donated their products for use at this party:

Parker Brothers - Salem, Massachusetts.

Kontrel ! Industries

Route 9

Cold Springs, New York

3M Company

St . Pau I , Mi nnesota

Selchow and Righter Co.

Bay Shore, New YOrk

Ava I on Hill Company

Baltimore, Maryland

Academic Games Associates

Balti.more, Maryland

Simulations Publications

New York, K'ew York •

;

We are all indebted to them for their assistance.

The other opportunity for informal gathering was at the cash-bar parties

following the two evenings of demonstrations.

The totai program, then, fell into place as shown in the following

chart which conference participants used as a guide to what was transpiring at any given time.

10
EPILOGUE

Perhaps it is too soon to write an epilogue, reviewing the

meetings and assessing their impact. I surely hope so, for if the

program "worked" it provided no easy answers but triggered a large

number of questions, gave some provisional hints about seeking the

answers, and established for those in attendance a set of contacts

and ties with others to help in the searches they undertake.

The comments made to me during and following the conference suggest

that in these terms the conference was a success.

About 120 people gathered for the meetings, wending their ways

through the program, combining sub-groups where there was a desire for

a broadened perspective, di'-/iding them up where greater depth on

an aspect was desired. Sub-groups had been given the task of

producing State-of-the-Art papers summarizing where we were in their

part of the field, and facilitators were asked to assume responsibility for preparation of these. I am sure they will be incomplete

in total number, and that those that are included here will give

only hints of what transpired. But this is due not only to the very

limited time each sub-group had to work in, but as well to the

far-ranging explorations characteristic of all those I saw. While

they were extremely fruitful for those who met together, then, they

were hard to summarize and present to those not present.

This summary and the epilogue port ion of it would not be complete

without the usual thanks and reminders that those thanked for their

assistance are not to be blamed for the shortcomings! While the

buck stops here, then, I must thank several people for their contributions.

My first enterprise as Program Chairman was to.. send a letter loaded

with questions to a number of friends, asking for their comments on former meetings and their suggestions for this one. Those who took

the time to respond are far too numerous to list here, but their

help was invaluable. Through much of the planning phase, conversations with

and ideas from David Rosen, Richard Budd, and Brent Ruben, all of

Rutgers University helped turn a general commitment to a working

conference into an actua! plan for one. My several lunches and many

more telephone "test i ngs''cc>i th Brent added much not only in content but

also in belief that such arsiructure would work. He is responsible for

the form of the prel irai nannd tanouncement and call for papers, as well.

As frustrations arose and"atio?icern at coordination of the multiple

activities became fearful, -the offers of Dana Main to assist in anything

that needed doing were most gratefully received and went a long way to

reassuring me that it would all work out! From the day I agreed to

develop the program until the final Symposium concluded the enterprise,

Richard Duke was a great source of ideas, suggestions, and support.

And of course none of this could have been more than an outline

on paper without the work of Peter House, Marty Brossman, and Al Pines

from the Environmental Studies Division, and of John Moriarty from

our host, the National Bureau of Standards.

To all, my warm appreciation.

11

October 9, 1973
8; 00 P.M. SUNDAY NIGHT SEPT. 16

WELCOME PARTY: BEER, WINE, & GAMES!

at the Washingtonian

MONDAY SEPT. 17

THEORY-EVALUATION TASK-GROUP DESIGN TASK-GROUP

8:00-9:30 9:30-10:00

10:00-11:30

11:30-12:15

12:15-1:00

1:00-2:00

12:30-1:30

1:30-2:30

2:30-3:00

3:00-5:00

APPLICATIONS TASK-GROUP

REGISTRATION, COFFEE, EXHIBITS OFFICIAL WELCOMES - NGC - ISAGA - CONFERENCE

STATE-OFTHEART GENERAL SYMPOSIUM NO. I: INTERNATIONAL DEVELOPMENTS IN GAMING-SIMULATION

THEMATIC INTRODUCTION: "TOWARDS A GENERAL THEORY OF GAMING"

2:00-3:00

3:00-3:30 3:30-4:30

4:30-6:00

6:00-8:00 8:00-10:00

10:00

9:30-11:00

11:00-12:30

12:30-1:30

1:30-2:45

2:45-3:15

3:15-4:30

4:30-6:00

6:00-8:00 8:00-10:00

10:00-

9:30-11:00

11:00-12:30

LUNCH

PANEL: THE WHAT AND WHY OF

GAMING-SIMULATION:

THEORETICAL BASES

PANEL: MODELS OF THE DESIGN PROCESSPANEL: ISSUES IN GAME USE: WHAT VALUES ARE

CONVEYED BY GAME DESIG NERS AND USERS?

PANEL: GENER.AL PROBLEMS IN EVALUATION OF GAMING- SIMULATION

ORGANIZATION AND PLANNING

OF lASK-GROUP ACIIVITIES & SUB-GROUPS

ORGANIZAIION AND PLANNING

OF TASK-GROUP ACTIVITIES AND

SUB-GROUPS COFFEE BREAK

ORGANIZATION AND PLANNING

OF TASK-GROUP ACTIVITIES AND

SUB-GROUPS

SUB-GROUP MEETING:

Ocneral dimensions of dcsi)^ Computerbased simulationUnstructured and

game-i;en(.Tatinf{ games

PANEL; USES OF GAMINGSIMULATION FOR RESEARCH

ISAGA BUSINESS MEETING

DINNER GAME DESCRIPTIONS AND DEMONSTRATIONS

CASH BAR COCKTAIL PARTY TUESDAY SEPT. 18

STATE OF THE-ART GENI-:RAL SYMPOSIUM NO. 2: PRESENT AND FUTURE RESOURCES IN GAMING-SIMULATION

PANEL: NEW FINDINGS FROM

EVALUATIVE STUDIES SUB-GROUP MEETINGS:

Designing inle active social simulations

Comuuler

based

simulations

Unstructured gamc-genc rating I!"""

SUB-CROUP MEETINGS: THEORY I EVALUATION LUNCH

PANEL: CONCEPTUAL MODELLING

AND VALIDATION OF MODELS

SUB-GROUP MEETINGS: CONTINUED AS ABOVE

COFFEE BREAK

SUB-GROUP MEETINGS

CONTINUED AS ABOVE

SUB GROUP MEETINGS

Designing intcr- aaivc social simulations

Computerbased

simulations

Futures modelling

PANEL; PUBLIC POLICY & COM- MUNITY APPLICATIONS OF

GAMING

NGC BUSINESS MEETINGS DINNER GAME DESCRIFI IONS AND DEMONSTRATIONS

CASH BAR COCK! AIL PARTY WEDNESDAY SEPT. 19

SUB-GROUP MEETINGS; THEORY

Learning, communications, etc.Systems

theory, operations

research

EVALUATION

Claisroom,

training Planning,research

SUB-GROUP MEETINGS:

Student

designed games

Pragmatics of game devel- opment : costs

8c dissemination

PANEL: NEW TEACHING- TRAINING DEVELOPMENTS

SUB-GROUP MEETINGS

TEACHING-TRAINING

(SAME AS TUESDAY)

Community. Pubbc Policy

Research LUNCH

FULL TASK-GROUP SUMMARY

MEETING: THEORY

EVALUATION

FULL TASKGROUP SUMMARY

MEETING: DESIGN FULL TASK-GROUP SUMMARY

MEETING; APPLICATIONS

COFFEE BREAK

STATE-OF THE AR r GENERAL SYMPOSIUM NO. 3: DEVELOPMENTS AND PROSPECTS IN THEORY-EVALUATION,

DESIGN, AND APPLICATIONS OF GAMING

12
TOWARD A GENERAL THEORY OF GAMING

By Professor Richard D. Duke

Environmental Simulation Laboratory

School of Natural Resources

The University of Michigan

Ann Arbor, Michigan 48104

[. THE PROBLEM

Humankind is a little harried of late. The naked ape barely blinked

only to discover that his animal being has moved from the cave to the moon with precious little time for adjustment, measured in evolutionary terms.

It is difficult to derive a valid "alienation index" for a society, perhaps

impossible for different points in historical time. None-the-less , evidence

abounds that all is not right with western civilization as it is currently

structured; further, the situation has deteriorated markedly in the past

quarter century. The tune-out, drop-out, cop-out syndrome is ever apparent

although the recurrent waves of enthusiasm (e.g., populist activity in

environmental concerns) give reason to believe all is not lost. But even

in such cases where enthusiasms are high and a general sense of urgency

and responsibility exists at the level of the individual, there is pervasive

frustration. The individual needs to be part of those processes affecting

his life, but is currently devoid of any effective means to alter things or join the dialogue about potential change. This situation reveals some dimensions of life today that were not previously true:

-The problems of today are infinitely more complex, involving systems

and interacting sub-systems that go beyond normal human ken and which

do not yield to conventional jargon or traditional forms of

communication

.

-ITie sheer quantity of individuals who want to be effectively part

of the dialogue is large and growing rapidly.

-There is a growing personal urgency because the solutions pursued

today constitute a more pervasive intrusion in the individual's

life. (In earlier times the king's men may have come periodically

for the taxes, but in the interim period, life was constrained only

by the elements and by whatever circumstances might exist within a personalized clan; today, the Internal Revenue Service comes every

week and unknown Big Brother, in a thousand ways, constrains the

daily actions of our lives.)

This situation, of course, is not new. Without too much difficiilty

man's struggle for the personalized control of his life can be traced

through the Magna Carta and the decline of the king's power to the

Parliament to the Declaration of Independence and resulting constitutional

governmental forms (whose painfully won gains are now threatened by a technical aristocracy, the high priests of 1984). Even the great urban

political bosses performed a valid personalizing influence buffering the

citizen from the emerging systems and technologies that must control his

world (sadly, only vestiges of this humanizing function remain, witness the

light years between the individual and national politics —can it be other

than Alice in Wonderland with spy versus spy, body counts from a constitutionally non-existent war, complexity of domestic programs that

boggle the expert mind while dominating in strict inverse relation, the

lives cf the least able citizen.ry)?

13
At the vei7 momenc V7hen man seerued to have garnered the power to

control his personal destiny by his own hands, he has been caught unawares

in the grinding pinchers movement of the complexity of societal survival in

modern times and the inevitable technological response. This crunch has

been on its way since the industrial revolution, but its very rapid

progression was precipitated by World War II, in particular by the spin-offs

in computer technology and the resultant elaboration of the concept of

"systems" and related, evolving technologies. Now the high priests of

technology speak only to the high priests of technology, God is dead, and

the citizen, no matter how strongly motivated, can hardly get a vvorJ in

edgewise!

Problems of the management of modem western society (and in a particula

sense the great urban centers) have generated the modern equivalent of the

biblical Tower of Babel. To unravel the present "vzant structure" in human

terms, to harness appropriate technologies and to manage a successful and

continuous response in an on-going societal context generates a communication

net (non-net?) that is truly unimaginable and certainly unmanageable.

Society's failure to respond to individual need is, in large part, a communication problem.

The naked ape waved and grunted and we do little better. He lived in a relatively simple world, and over many centuries developed what have been

viewed as sophisticated languages but which in reality are only involved

extensions of sequential form (including not only a written and spoken

English, but also the sophisticated artificial languages of mathematicf

,

computer programming, musical notation, etc.) to deal with this non-co'uplex

environment. The naked (now harried) ape of today still employes these

simple sequential tongues, but in a world several magnitudes more complex,

it leaves him speechless. The highly constrained and sequential languages

of the past, and their related technologies (even in their highest forms)

fail at conveying gestalt, and so the complexity of today cannot be

comprehended or communicated except with the greatest of effort, and then

only by a new elite. For example, consider our great urban centers as they

exist today, multi-systems within multi-systems, alternative upon alternative

presenting an incomprehensible, many futured state (s); the tongues of many

men, some unborn, in- migrant and out, being daily rearticulated as perception

of the possible change; a great multi-faceted sphere of complexity that can- not be managed, but must be. Societal response, predictably, has been

of four concurrent dimensions: false dichotomies, professional elitism,

increasing dependency on technology and gigantism. The inevitable, but

false dichotomies appear first: pare out of the total fabric of society

some element of great urgency; if we can neither understand nor solve the

totality, we can solve some definable part, no^ matter that other evils are encount ered , the i eas t of which may be_ inefficiency , the mos t dangerous

irrelevancy (witness "education" as a system currently practiced in the

inner cxty) . As the Bureaucracy (Education, Transportation, Health, Housing,

ad nauseam) transforms life into disconnected cells, society loses not only

in the more obvious negative harvest (the "solution" of Urban Renewal,

originally conceived as a simple-minded clearance problem, now yields to more sophisticated approaches at a cost of two decades only to be replaced

by the "solution" of an "interstate highvjay system" rather than an "interstate transportation system"); but, also, in a positive sense since such

dichotomy leaves little room for subtlety of solution.

14
And with the dichotomy came the armies of the professional elite and

with them their empires, and the resulting gigantism dwarfs and smothers

the citizen. The fiction of alternatives (witness State Highway Engineering)

may seduce the generalized citizen, but the poor beggar in front of the

bulldozer soon discovers the moment of truth. And as he turns into the

jaws of this giant beast trying to locate some isolable canponent unit that

will be responsive, he is put down by the elites- -the professional who quite

literallly speaks another language and he is put off by a technology that

appears antihuman; his only alternative is to join together with fragmentary

bands to throw slingshots at the giant. And, occasionally, their aim is

true! First one, then anotlier, public scheme is beat back not to be replaced

with positive alternatives, but to a frustrated stand-off where the great

urban administrations survive through non-action and the great creaking

structure grinds through time, the moans of unresolved needs and of endless

counter-productive conflict emanating fran the incongruous mass.

And who is to comprehend it all? Or who is to speak of it all? And

to whom? Is there any remote possibility of establishing a real dialogue

about this multi-faceted dynamic gargantua, even among the elite, substituting

future time-frame for future time-frame in advance of reality, permitting

positive management to replace a negative reactionary reality? And is there

anyway to enlarge the dialogue to include the activist citizen or someone who might conceivably be called his "representative" in that he transmits

a personal translation of ideas for his limited and personally known

constituency?

Of course not, not if we insist on restricting ourselves to the

languages of the caveman.

But there is hope that the possibility for a quantum jump exists; that

communication can move from its rigid and limiting sequentiality to a gestalt mode, and that this sipra- language can be used as a simultaneous

translation for our modem Tower of Babel.

ESTABLISHING THE NEED FOR FUTURE 'S LANGUAGE

"Future Shock" has become part of the popular lexicon. Alvin Toffler

in 1970 introduced the concept in a book by that name in which he stresses

the death of permanence and the coming of the age, not of Aquarius, but of

transience. The book documents in detail his thesis that the world of

tomorrow will be significantly different fron the world of yesterday along

many dimensions. Toffler quotes from Kenneth Boulding: "as far as many

statistical series related to activities of mankind are concerned the date

that divides human history into two equal parts is well within living

memory" . . . "The world of today . . . is as different from the world in

which I was born as that world was from Julius Caesar's. I was bom in the

middle of human history, to date, roughly. Almost as much has happened

since I was born as happened before."

The temptation to document, here, the proof of this accelerated change

and its impact on our lives; but the thesis will either be accepted

or rejected without elaboration since it is a familiar one. To place its

IS
significance to gaming in proper perspective 1 would like to allude to a simple graph. The horizontal axis would represent centuries starting

perhaps with the year 0 in our current system of counting; the vertical

column would represent an index, however, obtained, which would attempt to convey complexity, transicence, and rate of change confronting the typical

citizen. Using a logrithmic scale a curve is plotted which attempts to illustrate this change (perhaps the number of new things which must be

assimilated in the lifetime of a given citizen). The curve would start in

the extreme lower left hand comer and be virtually a straight line with a slight incline upward, barely perceptable, until perhaps 1900; incremental

jumps might be noted at the time gunpov/der was introduced and certainly as the industrial revolution impacted on society. The curve turns vertical

during the period 1900-1940 with a sharp increase during the period of

World War II. Subsequent to World War II the curve would be increasing at a near vertical rate implying change flowing on change at a totally

unprecedented rate. Curiously, a number of authors have independently

noted World War II as being the approximate time of the pivet from the

trend line through antiquity to the modem trend line.

0 500 1000 1500 2000

YEAR

Virtually all our language forms have come from antiquity and have

sufficed, in spite of their sequentiality, because they rely heavily on analogy and the analogies employed are predicated on historic circumstance

which is not expected to change, except by minor adjustments through time.

Note that the curve in the post World War II period, a situation far more involved, particularly in the several dimensions of complexity, future

orientation, thoughtful consideration of alternatives, and the inevitable

recognition of the nature of systems and inter-locking sub-systems which are affected. Necessity is the mother of invention, and the post World War II period has shown many innovations in communication which attempt to deal

with this communications problem; each relect an attempt to convey gestalt,

or at least to excape from the harsh burden of strict sequentiality of the

V7ritten and spoken language forms. If one were to plot the advent of gaming

as Indicated by the new games which appear in the various cataloging efforts

the curve mimics rather accurately the curve of accelerated change with

perhaps a 10 or 15 year lag. This reflects, in my judgment, a spontaneous

solution, "gaming," by many people in many problem situations to the

problem of developing a gestalt communication form. In short we have a new language form, a language form which is "future" oriented. If this

premise holds, to date we have seen no general statement or theor>' which

V70uld explain the wide diversity of materials which appear as games, or which might guide the neophyte in efforts to develop effective games for

their own communication purpose.

The need for conveying holistic thought, or gestalt, is urgent; the

coming decade will increase this urgency considerably. Perhaps the most

16
trenchat statement on this need is by R. F, Rhvne in an article

"Communicating Holistic Insights" published in Fields Within Fields Within

Fields . While describing the need for holistic conmiunication Rhyne states

"There is a Macro problem, an inter-weaving of adverse conditions that is more extensive, more richly structured by interior lines of interaction,

and more threatening than any circumstance faced before by all mankind."

Rhyne 's article was formuated "to stimulate exploration of the means whereby

appreciations of complex wholes may be more quickly and more reliably told

to others." He, too, rejects our ancestral language forms as being

inadequate to the task and argues that new forms must be invented. Arguing

that decision is a gestalt event and not a logically determinable process,

he believes that the citizen or the policy researcher or other decision

maker must first comprehend the whole, the entirety, the gestalt, the

system, before the particulars can be dealt with. Rhyne suggests a variety

of approaches to this problem and alludes to games as having a particular

potential.

We learn through games because, if properly designed, they represent

abstract symbolic maps of multi-dimensional phenomenon which serve as a basic reference system for tucking away the bits and pieces of detail which

are transmitted and in particular by assisting in the formulation of inqui.ry

from a variety of obtuse angles or perspectives which are meaningful to the individual making the inquiry and which can only be transmitted through

an "N"-dimensional, abstract, symbolic-mapping procedure. If the prior

observations on the character of change in the world since World War II are valid, they could perhaps be summarized as follov7s: prior to World

War II the need for pragmatic information and fact, learned by rote, was

imperative; in the new era the need is urgently for the acquisition of

heuristics or a flexible set of highly abstract conceptual tools which will

let the participant view new and emerging situations, having no precedent,

in a way that permits comprehension. We learn through games, then, because

it is a relatively safe environment which permits the exploration of many

perspectives chosen by the individual, expressed in the jargon of the

individual, and subject to fairly prompt feedback in "what-if " contexts.

These concepts gain strength when reviewing the work of Moore and Anderson

in "Some Principles for the Design of Clarifying Educational Environments"

as they conduct research on learning environments. Curiously enough, they

pinpoint the time of change in society as being dramatically correlated with

the decade of the forties. Properly designed, games have a strong basis

in learning theory, which supports their potential as a communication form.

The simultaneous invention of games of a wide diversity of subject

matter and technique is a response to a felt need for an improved communication

form to deal with problems of gestalt or holistic thought. Just as the

folk models alluded to by More and Anderson emerged in a societal context

as needed, games become a modern equivalent.

III. WmT IS A FUTURE'S LMIGUAGE

For the aioment, let me identify seven basic requirements that must be

met by any future's language:

17
1. Ability to convey gestalt or holistic image.

2. Permit the specification of detail at any appropriate level,

in the context of the holistic image.

3. Structured to permit the pulsing of specific, tangible inquiries or alternatives to permit correlation with the holistic image and

any significant detail.

4. The ability to display, make explicit, or permit the recording of

explicit linkages between major segments of the holistic imagery;

the creation of an awareness of feedback.

5. A non-elitiest, universal possibility for use; a basic catholicity

of design.

6. A future orientation (implying any time frame past cr future other

than the present)

.

7. They must be basically transient in format to permit the

restructuring or more careful articulation of the problem as vie\jed

by those participating.

Clearly, gaming has not pre-empted as the future's language. However,

if certain rules, concepts, or principles are employed consistently, the

game product can certainly qualify in a wide variety of situations.

IV. GAMING—THE FUTURE' S LANGUAGE

There are two charts attached. The first, "conveying complex systenis,"

formulates the rational for the game as a supra-language. A language is

defined as a symbol set and the conventions governing their use. A supralanguage is defined as a hybrid consisting of one or more conventional

languages and one game-specific language. The game-specific language implies

the need for the development of an explicit symbol set appropriate to the

context of the game as well as the rules governing the use of these new

symbols. In game design, careful attention must be devoted to the precise

formulation of this game-specific language and care must be taken to convey

it thoughtfully and early on to the game participants. Only then will thzy

share a vernacular which permits them to jointly share an investigation of a complex system. The game, then, which has as its objective conveying

complex reality, has as its result the conveyance of an imagery which may be

close to, or distant from, reality; therein lies an excellent device for

evaluating a game after construction. The second chart entitled "Gaming--The

Future's Language" is a consolidation of the elements which are being

advanced as the logical components of a general theory of gaming and game

design.

Time will not permit a careful exposition but the main theme can be

advanced. First, the' character of the problem must be stated in communication:

terms. This problem must be interpreted against the "Communications

Continuum" to verify that a less specific and therefore less costly

communication form cannot be employed in lieu of a game. If thoughtful review

indicates that the gaming medium is appropriate we then advance to the game

design process, center page. Most game designers approach their problem as though it wera a conf c.'--:-.d mul ti-dincr.sion simultaneous equa tica. Il:e result is an elongated process and sometimes a confused prodeuct. The game

design process is itself relatively straight forv/ard and may be somewhat mere

18
or less complicated than the illustration might suggest depending on the

problem at hand and the character of the game being developed. None-the-less,

the game designer is well advised to make a preliminary pass through the

entire process at least intellectually to sort things cut before attempting

game construction. The game components in the lower left hand side of the

chart have an approximate correlation with grammar in the context of spoken

or written English, In particular, the symbolic structure employed is a very significant decision on the part of the game designer. If it is too

complex the audience may be lost; too simple, the audience put-off or not

able to comprehend the nature of the basic system. If the symbolism employs

terms in conventional use in an attempt to convey new ideas there will be a built-in distortion which will slow the progress of the game and which may

or may not ultimately be overcome. Games are iterative in nature and the

procedures for play must be clear both to the game designer and to the

participants. Mechanics are somewhat flexible and should be differentiated

from rules which must be constant. Scenario, of course, implies a substantive

content and may be a replaceable element in the instance of frame games.

The repertoire of techniques illustrated in the lower right hand corner

is intended as a systematic strucutrc v/hich will enable the neophyte game

designer to evaluate or interpret existing games in a systematic fashion.

The particulars of any given game will vary tremendously in style, technique

and paraphernalia; none-the-less, any game can be interpreted through the

characteristics which are presented.

CONCLUSION

Finally, the upper right hand comer illustrates interpretive criteria.

The suggestion is made that the time is at hand for gamers to adopt a set of

conventions which require the designer to present in orderly fashion a basic

set of information which would be useful to the potential user as a way for

speculating on the character of the game prior to play. Contrast the

conventions currently in use in conjunction with "book"' with the enormous disarray of "game". The consistent format of "book" which has emerged over

a long period permits the ready and quick interpretation of the book for

its potential to the user; the average game today is a morass which is

unintelligible to the potential user until completion of play.

Finally, some basis for evaluation should be formulated by the game

designer and explicitly included in each game product. This evaluation would

require an explicit statement on the part of the designer explaining the

reality which the game addresses, and explicitly an abstracted form of that

reality (conceptual map) as interpreted by the designer in the construction

of the game.

These thoughts' are offered in the most tentative fashion, in the hopes

that they will prompt a dialogue leading toward the development of a general

theory of gaming.

The want of an organized, generalized perspective which adequately

accounts for the incredible diversity of games is and will remain an impediment to their intelligent use. While several perspectives have been

in, vogue, they inevitably account for only a small segment of what we

generally refer to as games. The time has come to wrestle with this problem.

19
CONVEYING COMPLEX SYSTEMS

Complex System Reality

Reality as Perceived by

Designer

Model of Reality

Perception

Received

Reality

Progress of Abstraction

Conceptual

Map

Supersymbols Conventions Symbols 'Conventions

Game-Sp

Langii

ecif ic

age

J

I

Conveiitioi'ia]

j Language

Communication

Tecnologies Languages

Hybrid Form of Communication

Technology

Holistic Image of The

Conceptual Map Deprived

ThrouGh Play

Sup ra-Language

(Game)

Gestalt Communication Process Through

A Gaming Environment

I Conveyed Perception

I of Reality

20
FACILITATOR'S STATEMENT

THEORY AND EVALUATION TASK GROUP

Tl-EORY AND EVALUATION

IN THE FIELD OF EDUCATION IVE ARE FAST MOVING TO A POSITION OF TEACHING

TECHNICAL SKILLS AND HARD OBJECTIVE EVALUATION. JUDGING TEACHING COMPETENCIES AND THE IVRITING OF BEHAVIORAL OBJECTIVES APPEARS TO BE RESTRICTIVE DEVICES UPON BROAD AND CRLaUVE AVENUES OF LEARNING. IN THE

MILIEU OF THE CLASSROOM THIS THRUST IS TAKING THE FORM OF SHORT EVALUATIVE MEASURES WITH A DESIGNATED SCORE FOR MOVING FROM ONE COMPLETED AREA

TO ANOTHER. INHERENT IN THIS SYSTEM ARE SKILLS FOR SURVIVAL. LEARNING

TO REACT FAST IN A LEARNING SITUATION, SKIMMING, SCANNING AND ANALYTICAL

READING SKILLS, LESS INTERACTION WITH THE MATERIAL ITSELF AND MAXIWI

REWARDS PLACED UPON RIGHT ANSWERS SEEM TO BE THE MODE OF THE DAY.

FURTHER, THE TEACHING SKILLS THAT WILL HAVE TO BE ACCOUNTED FOR IN THIS

WAY (IVRITING DOWN EXACTLY WHAT THE TEACHER INTENDS TO ACCOMPLISH AND THEN

TESTING TO SEE IF IT WAS ACCOMPLISHED) CANNOT BE SKILLS AT A LEVEL WHERE

MUCH TIME IS DEMANDED FOR LEARNING NOR WILL THEY BE RELEGATED TO THE AFFECTIVE DOMAIN OF DECISION MAKING SKILLS. FROM PRESENT DATA AVAILABLE

IT APPEARS THAT MOST TEACHING WILL REGRESS TO TECHNICAL SKILLS AT THE

KNOWLEDGE AND COMPREHENSION LEVEL.

IT IS IMPERATIVE THEREFORE BECAUSE OF THE ROLE OF GAMES IN THIS SCHE^^E

THAT AT THIS TIME IVE ALSO MAKE A DECISION ABOUT THE USE OF THEM IN THE

CLASSROOM. TO USE THEM IN THE TECHNICAL SENSE mERE REWARDS ARE IMTiEDIATE AND THE NfECHANICAL FEATURES OR HOW TO PLAY THE GAME ASSUMES TOO

MUCH IMPORTANCE IS CERTAINLY ONE USE FOR THEM. THIS MODE IS USUALLY

ACCOMPANIED BY STRICT RULES AND CONCISE STRUCTURE. THE INPUT OF THE

PLAYER IS ONLY THROUGH THESE AVENUES AND THE OUTCOMES PRESCRIBED FOR HIM.

ANOTHER WAY TO MAKE USE OF GAMES AND SIMULATIONS IS TO APPLY THEM SO AS

TO MAKE A MINIMAL STRUCTURE TO THE EVENT SO AS TO MAXIMIZE INPUT AND

THEREFORE OUTPUT BY THE PLAYER. ENDS IN GAMES IVHERE DECISION MAKING IS

A CULMINATING ACTIVITY AND ANY LOGICAL DECISION IS GIVEN WORTH AND THAT

DECISION IS NOT DETERMINED ENTIRELY BY THE GAME BUT BY THE PERSON PLAYING

THE GAME, IS A MOVE IN THIS DIRECTION.

THE QUESTION EMERGES AS:

1. ARE GAMES BEING USED AS A RESTRICTIVE OR EXPANDING MODE OF

LEARNING?

2. ARE GAMES BECOMING A TECHNOLOGICAL DEVICE THAT ENHANCES THE

OBJECTIVE TECHNOLOGICAL THRUST SO PRESENT IN EDUCATION TODAY?

RICHARD A. SCHUSLER

' School of Education

Dept. of Curriculum ^ Instruction

j Kansas University

I Lawrence, Kansas, USA 66044
EVALUATION: CLASSROOM USES: TRAINING

PLANNING AND RESEARCH USES

Jay C. Thompson, Jr.

Area of Curriculum and Instruction

Teachers College

Ball State University

Muncie, Indiana 47306

Charles H. Postma

Division of Education

Ashland College

Ashland, Ohio 44805

Facilitator's Scatement

The effectiveness of simulation and gaming in achieving cognitive and

affective objectives is uncertain. Results of the research studies

which were conducted during the 1960 's and early 1970 's that focused

attention on the achieving of cognitive and affective learning out comes were inconclusive.

Educators presently have considerable expertise in cognitive measurement of subject matter acquired in traditional ways. The measurement

of knowledge and concepts is only one aspect of evaluation, and probably not the most important. However, at this time affective outcomes

in classrooms are not measured adequately. Many classroom simulations

and games are thought to have significaant affective components and/or

outcomes. Failure to adequately assess these outcomes is a problem

that must be faced by professionals interested in evaluation of simulation and gaming techniques.

To measure students' affective learning outcomes, three evaluation com- ponents are essential:

1) The evaluator should determine what pupils judge is happening to them

because they participate in predetermined activities. Principles of

learning suggest that what a person perceives as important, is important

to him. Therefore, it is necessary in the evaluation assessment to

attempt to determine what students judge is happening to them. Pupils

may need instruction and practice at self analysis.

2) The evaluator must attenpt to determine what teachers and other professional personnel do that has an impact on pupils. Ryans, Hughes,

Travers, Flanders, and others contend that a method for measuring a program's effectiveness is to measure what is judged to be good teaching.

3) The important cognitive and affective experiences which exist outside

of organized knowledge must be measured. A pupil learns to seek or avoid

intellectual activities on the basis of whether he finds them rewarding

and challenging or obscure and irrelevant. A student partially decides

his own worth on the basis of the value teachers and other pupils extend

to him.

22
The classroom implications for simulation and gaming from such components

as these must be analyzed; instruments must be designed to increase the

effectiveness of evaluation for cognitive and affective outcomes in simulation and gaming. Affective outcomes in classrooms are of great importance. Too little attention has been focused on this outcome. This

position is not to inply that cognitive outcomes are of lesser importance;

but that educators have spent considerable time and effort analyzing such

outcomes, frequently at the "expense" of affective outcomes in which we have too little skill at measurement.

23
EVALUATION SUB-GROUP

FAC I LITATOR • S STATEMENT

SIVASAILAM THIAGARAJAN

Coordinator, Instructional Development Laboratory

Center for Innovation in Teaching the Handicapped

Indiana University

Bloomington, Indiana, USA 47401

BEHAVIORAL OBJECTIVES, SIMULATION/GAME DESIGN AND GOAL-FREE EVALUATION

As an instructional developer brought up on specific behavioral objectives and criterion-referenced evaluation, I have always had ambivalent

feelings about the design and evaluation of simulation/games. It has

been a frustrating experience to balance the attainment of predetermined

objectives and elegance of simulation/game design. The final form of

most creative simulations/games we produced bore very little resemblance

to the initial set of objectives, suggesting two alternative approaches:

One was to abort the simulation/game and come up with another whose out- comes matched the objectives more closely (but usually less interestingly). The second was to dump the objectives and derive another set

from the simulation/game itself. Usually we chose the latter procedure,

not without a sense of guilt.

While in search of conceptual clarification, I came across Scriven's

(1972) concept of goal-free evaluation (GFE) and became intrigued by

its applicability to the evaluation of the instructional effectiveness

of simulation/games. Basically, in GFE an independent evaluator sets

out to identify the outcomes of the simulation/game without being told

what the designer's goals are. Once the outcomes are identified, they

are compared with the needs- -of the consumer, the society, or the subject-matter discipline--to determine their importance. Scriven draws

an analogy between double-blind experiments in medicine and GFE in education and points out that increased objectivity results in both cases. Specifically, in the evaluation of simulation/games, the goal -free evaluator is neither misled by the grandiose goals, nor blinded by trivial

behavioral objectives. By matching the outcomes of the simulation/game

with the needs of a larger segment of society, the evaluator successfully integrates what usually is a two-step process of evaluating the

validity of the goals and the efficacy of the game. An independent

| evaluation agency- -perhaps under the auspices of NGC--can be set up to

undertake such summative evaluation and report to the consumers what

the product really does rather than reprint the claims of the producers.

Formative use of GFE results in useful feedback for the revision of the

game. I am not recommending that the design of simulation/games should

be a purposeless activity. The designer should have a purpose beyond

the mere play of the game, but this need not be "set in concrete."

24
Once he comes up with a reasonable prototype of the game, it should be

evaluated by an impartial expert who, uncontaminated by a statement of

its goals, is left to identify the actual outcomes. If these outcomes

match the designer's goals, his mission is accomplished. If they do

not match, but appear relevant and important in fulfilling some felt

need in the field, the designer has new leads and an uncompleted task.

He may develop the simulation/game to exploit and strengthen its un- anticipated effects and reconsider alternative instructional approaches

to the attainment of his initial set of objectives. GFE thus elevates

the process of game design into a more creative act.

25
EVALUATION | FACILITATOR'S STATEMENT:

PATRICIA Y. MARTIN

Department of Social Work and

Institute for Social Research

Florida State University

Tallahassee., Florida, 32306

James Coleman (19 69) has noted recently that social simulation games are superior to laboratory experiments for two major reasons. First is the

fact that laboratory experiments ordinarily abstruct a much smaller part

of a social process for study, with the result that the activity is nonself-sustaining and non-self-regulating. By contrast, in a social simulation game, the players themselves constitute a micro-social system, which

regulates itself without interference from the outside. Second, Coleman

notes that in laboratory experiments, the motivation for action must

ordinarily be imposed from outside, through directivss f rom the experimenter.

In social-simulation games, however, the motivation arises as an intrinsic

aspect of the miniature social system. Specifically, the mark of a good

game ". . .is that the individual goals which are induced by the rules bring

about action which results in the system's functioning—just as the mark of

a good organization is that in which individuals in satisfying their own

goals contribute to the functioning of the social organization" (p. 102).

Coleman's comments raise a number of issues worthy of serious consideration by gamers interested in evaluation—whether for teaching, training,

planning, or research purposes. A number of them are as follows.

1) To what extent do our games actually "shape" behavior? That

is, is behavior genuienly "induced" by game rules and goals or do games merely provide a forum for "acting-out" by the

individuals involved of their various personal preferences,

inclinations, and so forth? Is the extent to which behavior

is shaped by the game constant for all rounds of play, or does it vary?

2) Should social-simulation games aim at "teaching": (a) strategie!

of knowledge acquisition (or of social interaction process,

etc.) or (b) substantive content about some topic, or (c) both?

Are the evaluative methods appropriate for one of these

end-products suitable for both?

3) In order to secure evidence of true change in our subjects

due to actual game-play, should we:,

a) employ pre and post measurements, to avoid claims

of spuriousness?

b) devise precise-enough game-scoring methods to allow

players to serve as their "own controls"? (that is,

if scoring is precise enough to reflect a given

strategy, then subjects' can serve as their own controls by comparing later scores with earlier

ones.

)

26
which, aspect of a gaming-mo del has the most potent impact

on results of game-play: (a) rules of the game, which specify

resources, rights, limits, etc., or (h) goals, the ends toward

which behavior is aimed? Should more attention be given to

this question?

As games become more isomorphic with reality—and thus, more

complex—what are the attendant problems in evaluation of

outcomes?
SUB-GROUP TITLE: THEORY AND EVALUATION

FACILITATOR'S STATEMENT:

By Steven H. Woolard

Department of Science § Human Affairs

College of Education

The Florida State University

Tallahassee, Florida 32306

What do simulators look for when evaluating a simulation game?

How good of an evaluator are you? Below is a test designed to

measure your "Evaluation Know-how."

DIRECTIONS: Circle "T" if you believe the statement to be true.

Circle "F" if you believe the statement to be false. After com- pleting the test, check your accuracy by using the key at the

bottom of the last page. Calculate your score and rate yourself

by using the following scale:

13 - 12 You deserve a $1000 bonus

11 - 10 You deserve a $400 raise

9 - 8 You deserve a loss in pay

7 or Below You're fired!

True False

1. Isomorphism is the most significant com- ponent in any evaluation design.

2. If the behavior of participants in the

simulation -game does not conform to the

conceptual model, then the model, not the

simulation, needs revising.

3. Too many rules in a simulation-game con- fuse the players; so the fewer the rules

the better.

4. Player behavior in a learning simulationgame is shaped primarily by the rules;

so the rules should be clear and concise.

5. If participants learn from the simulation

game, then the simulator has accanplished

his chief purpose.

6. Simulation is an acceptable scientific

technique, if it can be proven that

the simulation is highly isomorphic

to the conceptual model.

7. It is not important for participants to

learn the model in a learning simulationgame.

28
T F

T F

T F

T F

T F

T F

8. If in a pre -post -test analysis there is a

significant change in the participants*

attitude toward the subject matter of

the simulation, the simulation-game is a

success.

9, If behavior in the simulation-game

coincides with the predicted behavior

in the model, then the simulation is

valid.

10. When evaluating a simulation, the relationship between motivational factors,

such as interest satisfaction, coping,

achievement motivation, and cognitive

growth, and performance is of little

consequence. ^ 11. When evaluating their s imulat ion -game

,

most simulators are not concerned about

applying carefully developed criteria to

check validity.

12. Most s imulat ion -games do not measure up

to generally acceptable criteria of validity.

13. High fidelity is a desirable quality in

a s imulat ion -game

.

I

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29
FORMAL PAPERS

THEORY AND EVALUATION TASK GROUP , _:. SIMULATING A MODEL OF PERCEPTION

TO SHAPE PROBLEM RECOGNITION

BEHAVIOR

Steven H. Woolard

Department of Science and Human Affairs

College of Education

The Florida State University

Tallahassee, Florida 32306

Many simulations available in the public market place today focus on

one or more aspects of social theory. Relatively very few deal specifically with theories and models of the psychological world. What

follows is a brief expository and descriptive statement that centers on the realm of psychology.

Introduction

Proponents of reflective inquiry and problem solving have examined

the logic underlying these processes. Little attention has been devoted, however, to one of the initial steps in such activity—recognition of a problem. This recognition, as delineated in this paper,

involves the perception of incongruity. Rather than describing perception as mere reaction to sensory stimuli, as conventionally treated,

this paper will explore the concept from the stimulus as well as the

behavioral perspective. Therefore, this paper has a three-fold purpose

1) to set forth a theory of perception as one explanation of how this

recognition occurs; 2) to describe a prototype simulation as a means

of empirically testing the theory; and 3) to report initial findings

of field tests of the prototype.

The Theory and Model

To many educational theorists John Dewey's model of reflective thinking

stands as an exemplar in the field of inquiry and problem solving. -'- Outside of the domain of reflective inquiry, but yet an integral part

of the model, is a pre-reflective stage called problem recognition.

Problem recognition refers to the perception of a situation as puzzling

or problematic.^ Since this stage appears to be a crucial initial

component of all inquiry and problem solving activity, the question

is raised: how does this perception take place?

Jerome Bruner's hypothesis-theory of perception has provided at least

one explanation of behavior during problem recognition.^ The basic

theory can be separated into three parts.

30
Pha<=;e 1 Tuni TiCT HvDothe'^i'?

Phase 2 Information Input

Phase 3 Confirmation/Infirmation

Fig. 1

During Phase 1 the individual confronts stimuli with a hypothesis

that "tunes him in" on what to expect. This "Tuning Hypothesis"

represents an expectancy about an anticipated event. At the same time there is a tendency to "tune out" any part of the stimuli not

relevant to the hypothesis. For example, in an experiment by Bruner

and Postman, individuals were shown a trick card (a red ace of spades)

under a tachistoscope. ^ Several individuals continued to identify

the card as a black rather than a red ace of spades.^ These individuals

had "tuned out" any discrepancy between their expectations and what

actually appeared.

In Phase 2, infomation input, the individual selects from the stimulus

certain information or cues which are used to confirm or infirm the

tuning hypothesis or expectancy. These cues are fitted against the

characteristics of an existing set of percepts. A percept is an abstraction used to organize sensory experiences, and includes those

meanings and understandings which the perceiver attributes to it. The

color red, a door, and a man are examples of percepts, and may be

maintained as part of an individual's repertoire of percepts. In the

experiment described above individuals used color and shape of the

stimulus as cues which were fitted against an existing percept—ace

of spades. Because the discrepancy between expectation and what

actually appeared under the tachistoscope was "tuned out", confirmation

of the expectancy occurred in Phase 3.

From the basic theory evolved a model that could be operationalized

in the form of a simulation.*^ The model provided not only the form

but also the functions to be replicated in the simulation, and helped

determine the type of media that was needed. The model appears

below in diagram form.

Drawing on much of Bruner ' s theoretical analysis, the model of perceptual readiness denotes a process of organizing and categorizing

stimuli according to an existing set of percepts. As depicted in the

model, this process involves a four-part cue-utilizing strategy where

stimulus cues are linked inferentially with a set of percepts. Cuesearching occurs, however, unconsciously unless the event is low in

probability and/or the fit between stimulus cues and specifications of

a set of percepts is imprecise. For example, in the trick card

experiment the red ace of spades was not a typical expectancy, and

the fit between the stimulus And the individual's category for the

31
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32
object was imprecise. Therefore, individuals were forced to look

consciously for cues that would permit accurate identification of

the incongruency

.

Also identified in the model are four psychological mechanisms which

serve as mediators of perception. Collectively, these mechanisms

regulate estimates of probable occurrence or expectancy and the ordering

of these estimates, and the processing of stimulus cues. By working

in concert with the cue-utilizing strategy, these mediators help

shape perceptual readiness.

Operationalizing the model in the form of a simulation gave rise to

two important questions. Is there a general category of students

(e.g., college students vs. high school students, or academically

talented vs. "slow" students) for whom a simulation of this type might

be ideally appropriate? Is there a specific form of media which would

be more appropriate than another to examine the perceptions of a selected category of students? "Slow learners," operationally defined

as those students who score in the bottom 1/3 percentile on a standardized aptitude test, in social studies classes in secondary schools were selected as subjects, on the assumption that they have more

difficulty recognizing incongruity than more able students. Cartoons

were selected as the basic medium to present problem situations

with incongruities, since they possess desirable motivational qualities

and would permit observation of appropriate behavior. Outlined and

described below is the general structure of the simulation.

The Simulation -

Basically, the simulation is self-pacing and includes the following

components

.

Cartoon Packet The packet contains eight cartoons (dry mounted

on posterbaord) , each portraying a social

situation (e.g., a person getting high on drugs,

or a land developer destroying trees and

creating a massive erosion problem). However,

each cartoon contains an incongruency, e.g. , an individual injecting a hypodermic needle in his

arm with the following caption overhead: "No

escaping the- real world for mel I like it just

fine!

Xpect Deck For each cartoon there is a set of six cards. The

and Title Card first is a title card (e.g. , in the first cartoon

an approp'i'iate title would be "No Copout"); two

of the five remaining cards contain a statement

that describes what an individual would expect

logically to see in the cartoon. For example, — given the above title, an appropriate Xpect card

33
might contain the following: A teenager who

"thinks things out" and turns down drugs. One

of the two cards describes something exactly

the opposite of the scene in the cartoon, as in the above example. The other three cards

contain nonsense statements.

PR Cards Enclosed in an envelope adjacent to each

cartoon are 5 "Perceptual Response"

cards. One of the cards describes

accurately the incongruency in the cartoon

(e.g., the correct PR card for cartoon #1

reads: The guy in the cartoon is freakin'

out, although he doesn't think so); The

remaining four may or may not be related

to the cartoon. If the participant can identify the incongruency before looking

at any PR cards , he detaches a wooden match

fastened to the posterboard and places it in

the corresponding slot in the Response Box

(described below)

.

Cue Questions The structure of these questions follows the

cue-utilization strategy presented in the

model. Presented on the back of each cartoon,

these questions force the participants to

examine the cartoon more closely, i.e., look

consciously for cues which will help them

recognize the incongruency. These questions

function as a sub-routine component of the

simulation.

Response Box Data are collected by means of a cardboard

box. The box is approximately 14" x 16"

and contains eight slots in the lid numbered

to correspond with the cartoon exercise. A

ninth slot is entitled "Discard" and serves

such a purpose. The inside of the box is

subdivided by cardboard sections so that

each slot in the lid corresponds to a subsection of the box. At the right side of the

box is an envelope containing plastic objects

used by the participant when responding to cue questions described above.

A flowchart of the simulation appears at the end of the paper. Once

the conceptual leap from the model to the flowchart was accomplished,

specific questions, in the form of hypotheses, were raised about the

application of the model. For example:

Is there a positive relationship between a commonality of

expectancies (selecting one or both of the Xpect cards logically

34
consistent with the title card) and the frequency of correct

perceptual responses (selecting the PR card that describes the

incongruency)

Do participants who identify the cartoon as puzzling (i.e.,

drop the match in the appropriate slot in the box) make correct

perceptual responses more frequently than those who do not?

Do participants who enter the siib-routine function (i.e., respond

to the cue questions) toward the end of the simulation make correct

perceptual responses more frequently than when they entered the

subroutine at the beginning?

Is there a positive relationship between a favorable disposition

toward the simulation and performance, i.e., making correct

perceptual responses?

While other empirical questions (e.g., I.Q., and performance in the

simulation) about the basic model and the simulation might be raised,

the preceding were among the chief questions of concern to the author.

Presented below are the field testing procedures and initial field

test results.

Field Test Procedure and Initial Results

Schools in three Florida counties—Leon, Escambia, Dade—were selected

as field test sites. "Slow learners," as previously defined, enrolled

in social studies classes during the 1973 summer school session in

three schools in the above counties were selected as participants. Grade

level of participants ranged from 9th through 12th grades. Before

formal field tests were conducted in Escambia (Pensacola—Woodham High

School) and Dade (North Miami Beach—North Miami Beach High School)

Counties, a preliminary tryout of materials was held in Leon County

(Tallahassee—Rickards High School) during June 1973. At that time the

reactions to students, who were predominantly Black, to the content

of the cartoons and the vocabulary in the captions led to general

changes in the cartoons. Instead of ten cartoon exercises, as decided

earlier, only eight were necessary, since approximately ^5 minutes was

still required to complete the 8 rounds. Initially five sets of

materials were developed with the expectation that the simulation

would be administered in groups of five students with one judge. The

preliminary tryout of the entire package of materials at Rickards

revealed, however, that a 1-5 ratio was inadequate. Each student

required more careful guidance by the judge at the beginning of play

than could be provided in the larger group; a 1-2 ratio seemed more

appropriate. At the end of each play data were recorded on an observation sheet.

During mid-July, 1973, Woodham High School served as the second field

testing site. Eighteen students (4 Blacks and 14 whites) enrolled in

35
social studies classes for grades 9-12 served as participants. One

judge per two students proved to be more effective than the larger

ratio of 1-5, since each judge could assist the student more easily at

the appropriate time. Following this series of field tests, changes were

made in some of the Xpect and PR cards , since several participants

were obviously hung up on three or four of the exercises. Changes were

made also in the directions to improve the flow of play. The judge was asked also to emphasize that careful reading of the cue questions

would improve the participant's chances of making a correct perceptual

response the second time. These changes, collectively, were considered

necessary to improve the overall operation of the next series of field

tests.

The third series of field tests were conducted late in August, 1973,

at North Miami Beach High School (Dade County) . Fourteen "slow learners"

from social studies classes were used as participants. Slightly over half

were Black and Cuban-Americans , while all participants were in grades

9-12. As in Escambia County, the simulation was administered on a 1-2

ratio—one judge per two participants. At the end of each play, as in

previous field test situations, as the data were recorded on an observation

sheet.

Because the last series of field tests were held so close to the completion

of this paper, none of the data have been treated thoroughly in a statistical fashion. The following observations have been made, and appear

to be warranted somewhat by a crude examination of the data from the

field tests in Dade County.

1. Most of the participants tended to select at least one of the

two Xpect cards logically related to the cartoon title. When

this was the case, participants tended to be more likely to

identify the incongruency than if none of the selected Xpect

cards were logically related to the title card. Consequently,

there may be evidence to show that individuals who maintain

a given expectancy are more likely than not to perceive a related incongruency. A more careful analysis of the data

is required.

2. There does not appear to be much consistency between those

who initially perceive the cartoon as puzzling (dropping the

match in the appropriate slot) and correct perceptual response.

The inconsistency in the data may be the result of a malfunction of a component in the simulation. While particpants

were reminded frequently during play to "drop the match" if

they saw the cartoon as puzzling, some of them may have

ignored the directions. A modification in the m^dia or rules should correct any malfunction.

3. On the surface, participants who enter the subroutine do not

necessarily make more frequent correct perceptual responses

toward the beginning of the simulation than toward the end.

Consequently, experience with additional cartoon exercises may

36
or may not impipove the participant's perception of incongruity.

However, the last few cartoons are more complex and incongruency is more subtle; therefore, the benefits attributed

to experience with more cartoon exercises may be negated, in

part, by the increased difficulty level of the cartoon.

4. In general, participants did express a favorable disposition,

as revealed through an opinionnaire , toward the simulation.

Scores on the questionnaire by participants at Woodham revealed

an extremely favorable disposition toward the simulation.

Although the evidence is somewhat shallow, there does appear,

at least on the surface, to be a positive relationship between

performance in the simulation and player disposition.

In general, a more careful examination and statistical treatment of

the data and additional field testing are necessary before more definite

conclusions can be reached. Presented in this paper, however, is a general model of perception whose applicability and credibility should

be more thoroughly tested. But if this brief paper has stirred someone's

curiosity and imagination, then, perhaps, at least one purpose has

been accomplished.

A paper presented in the panel "New Findings from Evaluative Studies,"

12th Annual Symposium of the National Gaming Council and 4th Annual

Conference of the International Simulation and Gaming Association,

September 17-19, 1973. Sponsored by the U. S. Environmental Protection

Agency and Rutgers University.

37
FOOTNOTES

1. John Dewey, How We Think (Boston: D. C. Health and Company,

1933) , pp, 12-14.

2. John Dewey, Logic : The Theory of Inquiry (New York: Henry

Holt and Company, 1938), pp. 107-9=

3. Jerome Bruner , "Personality Dynamics and the Process of Perceiving

in Perception: An Approach to Personality , ed. by Robert Blake

and Glenn Ramsey (New York: The Ronald Press Company, 1951,

pp. 122-143.

4. A tachistoscope is a device with which visual material can be

presented to subjects for durations as short as one one-hundredth

of a second

.

5. Jerome Bruner and Leo Postman, "On the Perception of Incongruity:

A Paradign," in Perception and Personality: A Symposium , ed. by Jerome Bruner and David Krech (Durham: Duke University

Press, 1949), pp. 213-21.

6. Jerome Bruner, "On Perceptual Readiness," Psychological Review , LXIV (1957) , 123-141.

7. Ibid., 131.

38
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39
The What and Why of Gaming

A Taxonomy of Experiential Learning Systems

By Brent D. Ruben

Institute for Communication Studies - - Rutgers University

New Brunswick, N.J. 08903

It is difficult -- perhaps impossible -- to contribute much significance

to the theory or philosophy of instructional games and simulations, without

considering both in teims of the more generic concept of experiential or

experience-based learning. Frcm such a perspective, simulations and games, along

with structured group exercises, role playing activities and encounter groups, are

all instances of purposeful, structured, information-processing environments where

learning is an intended outcome.

The conceptual roots of contemporary thought regarding experiential

learning date to the works of John Dewey V and Maria Montessori 2^/ both of whom

emphasized the role of experience and communication in classroom learning

environments nearly three quarters of a century ago. However, the current

interest in experience -based learning would seem to be much less a direct conse- quence of those early developments, and more a reflection of complementary

influences in various spheres of activity in more recent times.

One such thrust has come from the business and industrial community

where in the past several decades an increased emphasis has been placed upon

organizational development, human relations, internal communication, and employee

and management in-service training, in general. In searching for training

techniques which seemed theoretically sound and operationally compelling, games,

simulations, role playing activities and encounter sessions of various intensities

proved attractive.

Social psychologists, sociologists and individuals in the fields of

communication and management provided another influence as a consequence of their

study of group dynamics, leadership and group decis ion -making . Experiential

learning, and in particular the encounter group design, found growing acceptance

also with psychiatrists, social workers, counselors, religious leaders and tohers

who applied the techniques in therapeutic training contexts.

An additional source of influence came from work in the area of games

and simulations. As Tansey and Unwin V note, the use of simulation and games

has a lengthy heritage, dating perhaps to the development of chess as a symbolic

tactical encounter between opposing factions. War games of various sorts were also used widely in World War II, particularly by the Japanese and Germans and

later by the United States and Soviet Union. V

Perhaps the single greatest thrust has come as a result of a broadlybased questioning of traditional educational values, systems of instruction and

approaches to learning. The scholarly contributions of BrunerV and Rogers^/

have been particularly impactful in this regard, along with the more popular

works of such individuals as Postman and Weingartner, 7/ Riesman, 8/ Goodman 9/

and Holt 10/ to mention only a few. The following passage from the student

authored Chanpaign Report provides a succinct statement of some of the concerns which have since been voiced by many:

40
The artificial gulf between ideas and action must be

bridged so that learners learn ideas for action.

Faculty members ought to try taking a student to lunch

sometime.

Smallness or largeness have no inherent value in an

institution , but continued opportunity for contact with diverse

primary groups must be offered to all students.

Efficiency has been overrated as an educational device

,

and chaos has been underrated.

We must develop devices for continued examination of what

is significant and what is insignificant learning

.

Base learning on problem solving . Get a bunch of freshmen

together and tell them: We have a problem and we want you to work

on it for the next four years . How do you feed the world? At the

end of that time , you'll have sociologists and botanists and

engineers and political scientists , and God knows what , but they

will have learned because they had an important question to answer

and because they thought their particular discipline might shed

some light on it . 11 /

In response to these and other suggestions , experience-based

learning has been perceived as one potent means of rejuvenating and restyling the standard class room learning environment.

Nourished by these and other influences , experiential learning has

continued to grow in popularity and acceptance. And, as has been noted

often in the literature , experience-based learning , at face value at least

,

has numerous advantages over alternative instructional methods . For one

thing , simulations and games are generally constructed with a problem focus

and participants frequently seem well motivated as a consequence. Experiencebased learning , it has been said , fosters questioning , inquiry and structural

learning in addition to teaching specific content. Another frequently mentioned

virtue of experiential settings is the capability for minimizing space and time

constraints often present in alternative training contexts . Students need not

wait days , months , or years to gain a sense of the consequences of their

decisions and actions. Experience-based environments also seem to be particularly useful for helping students come to understand and learn to cope directly

with change and ambiguity . And, of course , in laboratory environments risks , responsibilities and severity of outcomes can be controlled to make it possible

for participants to "fail" without full consequence.

41
A TAXONOMY

In spite of the widespread application of the specific techniques of

gaming, simulation, role playing and encounter groups, relatively little

attention has been directed toward considering the more generic category

,

experience-based learning. The remainder of this paper is directed toward

this goal. 12/ Presented is a classification scheme for categorizing experiential learning systems in terms of the structure of the activity and the instructional objectives of the facilitator. As the substance of this paper argues,

these dimensions are critical both to the conception and operationalization of

any experience-based learning environment.

The Structure of Experience-Based Learning Environments

Experiential techniques come in any number of different packages and

with a variety of purposes . All experience-based instructional activities can be

thought of as contrived human communication systems, and as such, all share

in common a number of structural elements which are crucial to their operation.

The five elements are:

1. roles

2. interactions

3. rules

4. goals

5. criteria

Structurally , simulations and games and other experiential designs

involve: 1) participants case in roles , 2) interactions between those roles

,

3) rules governing those interactions 4) goals with respect to which the

interactions occur, and 5) criteria for determining the attainment of the goal

and the termination of the activity

.

Role

Experiential environments require participants . Except for those

unique situations in which one participant "plays" against himself, there are always two or more individuals involved. The term role refers here to the

identities individuals assume while taking part in a simulation , game , or encounter group

.

In a number of games and role playing exercises, rather definitive

and elaborate role descriptions are provided by the designer. In SENSITIVITY ,

for example , a portfolio containing a fictionalized biographical sketch is distributed

to each player . Participants are asked to assume the role of the character described

in the folio as best they can . The structural element of role is particularly crucial

to this game , and all player activities revolve around their actions and reactions

to one another in their assumed roles

.

42
The players , taken all together then become a group of

very troubled people , who meet to gain some help and insights from

each other. Each tries to make his character understandable to

the group , communicating as much about himself and his problems

as he can. 14/

15/ SIMSOC — is an example of a more complex social simulation in which

roles , specified in great detail , are extremely important to the functioning of

the activity from both an operational and instructional standpoint. SIMSOC

participants serve in roles in one of seven basic groups. Two of the groups are

industrial units, and two are political parties. The other three are: an employee interest group, a mass media group and a judicial council. Additionally , a specified proportion of participants in the simulated society must

be affiliated with one of the two political units and with the group of independents.

Members of the Party of the People (POP) are told that they are to

emphasize individual autonomy and decentralized decision-making. "They

are not rigid about such opposition , and are willing to accept planning and

centralized coordination if it appears absolutely necessary ." 16 /

Members of the Society Party (SOP) are encouraged to emphasize

central planning . "Its members believe that it is necessary for individuals

and groups to yield some of their autonomy in order that effective leadership

be provided and anarchy avoided . " ]_7/ Independents are told they have no

strong opinions one way or another about these issues

.

Both SENSITIVITY AND SIMSOC are examples of experience-based

instructional systems in which roles are prescribed rather specifically and

have a crucial and generally predictable impact on the overall operation of

the activity.

The encounter group, in idealized form, represents an experiencebased environment, which differs dramatically with respect to the origin of

the role definitions players assume , 18^/ Roles — the way participants are

to act — within such a group are not specified on an a priori basis , nor are they prescribed by the designer. The same is true, although to a lesser extent with two-team variations of PRISONERS DILEMMA 19/ and some versions

of WIN AS MUCH AS YOU CAN . 20/ In each context , the nature of participant

roles emerge primarily as a product of whatplayers bring with them to the

activity , and as a consequence of the interpersonal transactions that occur

as the activity progresses.

91 / 22/ STAR POWER — and THEY SHOOT MARBLES DON'T THEY —

provide examples of structured environments which fall somewhere between

the two extremes, with regard to role delineation, tending perhaps toward

the less specified , less structured end of the continuum

.

43
Interactions

The operation of all games and simulations depend upon the interrelating of participants. The manner in which these relationships originate and

develop may vary from one game or simulation to the next as does the method

,

procedures and channels available for transactions between players.

23/ MONOPOLY , — for example, utilizes a large number of devices to

foster interactions between players including tokens, play money, "houses,"

"hotels," property deed cards, community chest and chance cards.

The availability and necessity of using multiple channels of communication is crucial to the functioning of MONOPOLY and to many instructional

games and simulations.

In other games and simulations interaction channels and means for

their utilizations may be less prescribed and specified. This is, for example,

the case with most role playing exercises , where a wide range of verbal and

nonverbal interactions are available to players as a part of the activity . The

range and diversity of transactions between player roles are limited more by

the range of a participant's ingenuity than by the design of the game or

exercise.

24/ HANG-UP — is an example of a game which utilizes diverse channels

of interaction. The game is designed to focus upon and increase participant

sensitivity to the subtleties of racial differences. Participants react to a series of hypothetical "crisis situations," described on cards, as they think

typical whites or blacks would. In turn, participants charade their reactions

to the various crisis situations while others involved in the game try to guess

the player's "hang-up" , and whether he is playing the role of a white or black.

INTERACT, —^and its immediate predecessor INTERMEDIA,

provide an instance of simulation environment which utilizes emergent and

diverging interaction channels . Both simulations involve a laboratory society

,

the basic industries of which are communication and mass communication enterprises. Participants serve as Individual Agents, members of Mass Communication Organizations, Communication AGencies or an Executive Council. In

addition , all participants serve as Consumers for communication products

developed by the various Communication Organizations.

Together, Individual AGents and managers of the Communication

Organizations negotiate , prepare and present their resulting communication

products to the Consumers, according to a predetermined timetable. The

Consumers are exposed to and in turn evaluate the products of each Communication Organization relative to one another and award income or subsistence

points based upon their assessments . The points each Communication Organization accumulates are distributed among the members of its staff in whatever

manner the organization selects.

44
In addition to this basic interaction pattern , a wide range of alternatives are possible. Essentially, any individual or group of individuals can provide

any communication product or service to any group within the society so long

as they are able to accumulate enough income points for their efforts to survive

in the economy of the simulated society

.

Rules

The interactions between participant roles in experiential contexts are governed by a series of rules or guidelines. Rules are typically specified by the

designer and presented to the player as "instructions" for play. The number

and specificity of rules governing the interactions vary greatly from one experiential activity to another . Rules may enumerate actions which are permitted

of players, or they may list only those activities which are precluded, leaving

open the possibility for all other actions

.

This distinction is an important one. Those rules which specify and

enumerate actions and behaviors which are permitted and necessary for participants can be termed prescriptive. Those rules which prohibit certain participant actions leaving all other possible behaviors open are prescriptive

.

In some instances , the designer utilizes the rules and behavioral

guidelines players bring to the situation as a primary source of rules for

the game or simulation exercise . The encounter group may be an extreme form

of this variety of rule generation. Particularly where one conceives of an encounter group as a simulation of the communication processes involved in

social organizing, rules are generated from the participants' assumptions

as to how the encounter group should progress , what activities and behaviors

ought to be allowed and which should be excluded. At a minimum, several

meta-rules must be imposed by the encounter designer or trainer. Individuals

must , for example , agree to participate in the formation of the group and to

react to subsequent activities occurring as the group develops. Additionally,

a common rule limits content of discussions to issues of present relevance to members of the group, while excluding discussion of "back home" situations.

This "rule" is often referred to as a "here and now" norm. As a group develops

around even this minimal set of conditions , many more rules evolve , some of

which are explicit — many others implicit. This process develops in much the

same fashion in the encounter group as it does in a society or in any other social

enterprise

.

In other sorts of experience-based instructional exercises , traditional

and direct means for interactions between participants are intentionally excluded

by the rules in order to focus on particular issues. This is the case with the

widely used COOPERATION SQUARES exercise, which has the following rules:

1 . No member may speak

2. No member may ask for a card or in any way signal

that he wants one

3 . Members may give cards to others TIJ

45
Participants in this exercise are divided into five-person groups.

Each group member receives an envelope containing several puzzle cards.

When assembled, the puzzle cards possessed by the members of the group

form five equal squares. No one member of the team has all the cards necessary

to complete a puzzle-square. Only through exchanging pieces with other participants can the task of assembling five squares of equal size be completed.

1 The exercise and the discussion which follows is intended to focus

j upon the issues involved in communication and effective cooperation , and to I help participants become more aware of how particular behaviors may help or I hinder group problem solving

.

- ! Goals '

j While goals are crucial to the design and implementation of experiencebased activities in general, the extent to which they are overtly presented to

' participants varies greatly from one simulation or game to the next.

'

I In the cooperation squares exercise discussed previously , the ' activity goal is stated rather directly: ^

Each person should have an envelope containing pieces for

| forming squares. At the signal, the task of the group is to form ! five squares of equal size. The task is not complete until everyone I has before him a perfect square and all the squares are the same S size. 28/ i

Often the goal of an exercise , game or simulation is given in the

instructions, stated as "the objectives" of the game. Where two or more

' individuals are involved , the goal often takes the form of a statement of what ' one must do "to win." ,

^

In contradistinction , the goals of an encounter group or to a lesser » extent of simulations such as THEY SHOOT MARBLES DON'T THEY, INTERACT,

or INTERMEDIA, depend primarily upon the decisions participants make and

often emerge at a point well into the development of the activity. In such

situations , the goals may never be articulated in the group as a whole , and it is not necessary for each individual's goal(s) to be identical with the goals of i others .

^

Somewhere between these two extremes are games and simulations with

multiple goals, prescribed by the designer. SIMSOC is an example. As indicatec^

earlier, all SIMSOC participants serve in one of two political parties — ' or as an independent. The Participant's Manual reads: ^

If you are assigned to one of the two political parties , you

are to consider the achievement of the party's program one of your

own personal goals and to work for this when it appears appropriate

to do so. 29/

46
In addition to participation in one of seven basic groups with attendant

goals , and political affiliation with additional goals , each participant must also

select one of three personal goals — power ,

, wealth or popularity — to emphasize in playing the game

.

A participant adopting a power goal tries to influence what happens in

the society as much as possible. Those electing to seek wealth try to accumulate

as much of the currency of the society as possible by the end of the game. The

third alternative is to emphasize popularity and strive to become as well liked

by other stimulation participants as possible.

Criteria

Experiential activities must have a means of ending . A determination

is made that the goals have been reached using certain criteria and this

signals the end of activity. Some games and simulations rely heavily upon

the use of fixed and prescribed criteria for determining when goals have been

met and activity is to terminate . Others make use of the ambiguity that results

when criteria for determining the achievement of goals are unclear , changing

and highly personal. The criteria can be prescribed by the designer in

advance or may emerge from the decisions of players.

In games where the goal is rather directly stated, often in terms of

winning , the criterion is typically an announcement by a participating individual

that in his assessment he has fulfilled the goal. "Bingo" is an example. A

pronouncement of this sort is also used with the COOPERATION SQUARES

exercise discussed previously.

In many cases the criterion for determining when the goal has been reached

depends upon time constraints. This is the case in an encounter group or INTERACT where the length of time available is a primary factor in determining the termination of activity. Others, such as STARPOWER are terminated

at the discretion of the facilitator with or without input from participants.

Internal and External Parameters

While all experience-based learning systems involve considerations

relative to roles, interactions, rules, goals and criteria, not all experiencebased environments apply these design parameters in the same manner.

Experience-based learning environments can be designed and utilized

such that control of parameters is centralized in the hands of the designer as

is the case with many canned or pre-programmed games and exercises , or

control can be diffused among participants

.

47
The dimension of control, so essential to an understanding of the

instructional system , is also important to the appropriate design and utilization of instructional simulations and games. It would seem to be largely

the deployment of parameter control which operationally distinguishes the more

content-centered and predictable games and simulations from those which would

seem to foster more generic an individualized learning. In those experiential

activities where primary control of the parameters rests with the designer or

instructor, the game or simulation can be said to be externally parametered.

Where the control for establishing and modifying role, interaction, rule, goal

and criterion parameters resides primarily with the participants, the activity

is internally parametered.

Examples of external parameter games and simulations include the

many structured, often computer-assisted, social and management simulations,

games and related exercises where the participant strives to learn the designer's

theory of a particular phenomenon. The participant in external parameter

experiential environments , typically tries various strategies and procedures

in an effort to arrive at a particular winning combination which has been predetermined by the designer or instructor.

External parameter simulations are frequently relatively simple, low

ambiguity situations, with specified and prescribed role descriptions. The

"right" and "wrong" strategies for behaving and interacting are fixed, or are varied in predictable ways known and controlled by the designer or educator.

The criteria for winning are externally imposed.

Both the problems with which a participant deals , and the solutions to those problems have been determined on an a priori basis by the designer and

have little or nothing to do with the actions and reactions of the participants. The

correct strategies are essentially the same from one iteration of the game or simulation to the next

.

While games and simulations which are externally parametered are numerous, there are few internal parameter games sv-d simulations in existence.

In idealized form, the encounter group represents one of the clearest examples.

What it is that is to be learned, and the ways the learning is to occur are not

specified or pre-determined by a designer, instructor or trainer, but rather

depend almost totally upon what the participants decide to do and the ways in

which they reach those decisions. Variation is tolerated and encouraged in

internal parameter simulations. Problems are defined through participant

thoughts and actions and are solved in a similar sense , rather than being imposed

by the design of the game. In games and simulations where parameters are internal

the activity of the participants generates and modifies the roles, interactions,

rules, goals and criteria.

Figure 1 presents some major differences between the external and

internal parameter experiential designs. (See page 68)

48
Figure 1 Structural Elements and Design Characteristics

of Experience-Based Systems

Externally Farametered Internally Farametered !

Roles assigned emergent

rigid flexible

low ambiguity high ambiguity

| simple corfiplex

Interactions channels specified channels emerge

patterns prescribed patterns emerge 1

lew ambiguity high ambiguity

few channels available multiple channels availe±>le

predictable unpredictable

Rules prescriptive pros criptive

fixed flexible |

constant changing

low ambiguity high ambiguity

specified emergent

Goals imposed emergent

uniforro individual

single multiple

clearly defined ambiguously defined

Criteria predictable unpredictable

uniform individual

single multiple

likely to involve "winning" unlikely to involve "winning"

clearly defined ambiguously defined

49
Instructional Objectives

Clearly, no game or simulation is at the extreme position of being

entirely parametered externally nor of being totally internally parametered.

It must be noted that to some extent, all learning environments are participant

controlled, whether that control is delegated explicitly be design or not. What

is learned and the way that learning occurs always depends ultimately upon

the learner. The game designer or user provides the necessary but not

sufficient conditions for learning.

Notwithstanding this important point , the instructor or facilitator must

continually make decisions as to the design and utilization of instructional

methods — including games , simulations and similar experience-based

activities. Curricular decisions are made upon the basis of learning goals,

and it would seem reasonable that decisions to design or utilize particular

kinds of experiential systems be made on a similar basis

.

The relative appropriateness of internal versus external parameters

likewise would seem to depend upon the particular learning goals involved.

External parameter simulations seem generally better suited for teaching

specific content, while internal parameter games and simulations appear more

appropriate for the learning of problem-solving processes.

Where the learning goals suggest that what is to be learned is specific , prescribable , predictable , and determinant , external parameter environments

are appropriate in that the designer or implementing instructor wants all

students to learn the target facts, strategies and procedures in the same way.

The structural elements of the game or simulation will therefore need to be

controlled and manipulated intentionally , to insure that participants deal with

specific issues, using specific interactional channels, according to prescribed

rules, in order to achieve the designer's predetermined goals.

Take for example a role playing exercise designed to help students

learn the content of a particular historical decision, experientially . The

structural elements of the exercise would need to be controlled such that

participants were unlikely to introduce "creativity" into the exercise, which

might lead them to arrive at a decision quite unlike that which actually took

place

.

External parameter activities are generally appropriate when the learnir,

desired is in the form of answers or decision which are fixed , constant over time

and tend to be technical in nature.

Internal parameters , on the other hand, are generally better suited than

external parameters in instances where the learning is to be structural , general , not prescribable , unpredictable and indeterminant .

50
Experience-based activities designed to help students learn about the

processes of decision-making , might utilize historical role playing exercises

similar to that discussed previously. In this case, however, that which is to be learned is a process and learning specific content of decisions would be

dysfunctional. Given this kind of learning goal, creativity is highly desirable,

and it is not necessary -- nor desirable — for all participants to learn the same

things about decision-making in the same way from the exercise. Neither is it necessary for all of the individuals who participate to come to the same conclusions

as to what were the "right" and "wrong" decisions.

Internal parameters seem generally more appropriate for teaching such

things as communication , questioning , inquiry , leadership , decision-making , and social and organizational competence. These sorts of competencies and

knowledges are situational, and the judgment of "rightness" or "wrongness,"

of an individual's style of attacking a problem, or coping with other people,

is highly subjective and must always be evaluated relative to the context.

There are several additional criteria which are useful for distinguishing

between circumstances appropriate to the use of external and internal parametered

games and simulations. These depend upon the learning system meta-goals.

Where the attempt within an instructional system is toward fostering homogeneity , uniformity and interchangeability among students external parameters are in

order. Internal parameters are more appropriate where the meta-goal is to

provide an environment which encourages heterogeneity , diversity , and

individual uniqueness . Externally parametered simulations and games are

therefore suggested where it is desirable for all participants to learn more or

less the same things in more or less the same way — as with specific content.

If it is desirable for all participants to learn different things in diverse ways —

as with processes of problem-solving then an internal parameter design is

probably better suited for the purposes

,

Concluding Remarks '

Hopefully , the preceding framework has some direct utility for

classifying experience-based learning systems along the dimensions of structural

composition and parameter control. By indirection, the scheme may also serve

several subtle, heuristic functions:

1) It suggests that in addition to games and simulations , a wide range of

techniques which at first glance appear unrelated, can be meaningfully subsumed within the category of experience-based learning

.

2) It implies the potential relevance of theory and research from these

diverse areas for understanding the scope , functions and outcomes of games and

simulations

.

51
3) It indicates the necessity of designing , utilizing and evaluating experiential techniques in a manner consistent with thoughtfully articulated

instructional objectives.

4) It implies that the instructor or facilitator's posture within an experient:

learning environment can be crucial to the nature and outcome of the total

experience.

In my opinion , these four issues and the myriad of questions that they | suggest , circumscribe a critical area of concern upon which comprehensive

gaming theories of the future must ultimately focus.

52.
Notes

1 Readers Interested in pursuing these notions In depth may wish to examine

John Dewey: Lectures in the Philosophy of Education, 1899 by Reginald D. Archambauit (New York: Random House, 1966), especially Lectures VI and VII,

pp. 59-75.

On pages 65-66 of that volume Dewey says: "There seems a very practical

existing tendency in the direction of the recognition of this principle, that

fundamentally speaking, the educative process must be the same within and without the school wal 1 s. . . .Vihen we say the materials and methods are the same it

is not that all distinction must be wiped out or overlooked, but it does mean

that the school has for its function the organization in a more conscious and

thorough going way the resources and the methods and materials that are used

in the more unconscious and haphazard way outside."

See also John De^'ey, Expe rience and Education (Hew York: Macmlllan, 1938) and

Democracy and Education (flew York: The Free Press, 19^6).

2 Readers interestec! in writings of Maria Montesscri miy wish to examine The

Montessori Meth od (New York: Schocken Books, 196^) and Spontaneous Activity in Education (New York: Schocken Books, 1965).

3 P. J. Tansey and Derick Unwin, Si mulations and Gaming in Education (London:

Metheun Education, Ltd., 1969), p. 1

.

^ John R. Raser, Simulation and Society: An Exploration of Scientific Gaming

(Boston: Allyn and Bacon, 1S69) , p. ]

.

5 See especially T he Relevan ce of Education J. S. Bruner (New York: V/. V/. Norton

6 Co. , 1971); Learnin g Abou t Learning: A Conferen ce Report , J. S. Bruner (ed.)

(Washington: U. S. Government Printing Office, ; J. S. Bruner, The Process

of Education (Cambridge, Mass.: Harvard Press, 1961); J. S. Bruner, Toward

a Theory of Instruction (New York: Norton, I966); and J. S. Bruner, Rose R.

. Oliver and Patricia M. Greenfield, et. al . , Studies In Cognitive Growth

New York: John Wiley 6 Sons, I966).

6 See especially Encounter Groups , Carl Rogers (New York: Harper and Row, 1970);

"The Characteristics of a Helping Relationship," excerpted from On Becoming a Person by Carl Rogers (Boston: Houghton Mifflin, I961), Chapter 3, PP. 39*50;

Carl Rogers, Freedom to Learn (Columbus, Ohio: Charles E. Merrill Publishing

Co., 1969); Carl Rogers, "Interpersonal Relationships: U.S.A. 2000." This

papsr was part of a symposium sponsored by the Esalen Institute, San Francisco,

entitled "USA 2000" on January 10, I968. See also Carl R. Rogers, "The

Process of the Basic Encounter Group," In Challenges of Humanistic Psychology , James F. T. Bugental (ed.) (New York: McGraw-Hill, 1967).

7 Neil Postman and Charles Weingartner, Teaching as a Subversive Activity (Nev/

York: Delacorte Press, I969), PP. xlli-xlv.

8 Especially Constraint and Variety in American Educa tion , David Riesman,

(Lincoln, Nebr. : University of Nebraska Press, I968).

9 Especially Compulsory Mis-education , Paul Goodman (New York: Vintage Books,

Random House, 1962).

53
10 Especially How Children Learn, John Holt, (New York: Pitman Publishing Co.,

1967). —

1 1 Champaign Report: A Conference on Educational Reform, A Student View , Pau

1

Danish (ed.) , (Champaign, 111.: September, 1966), pp. 6-7.

12 A more extensive development of the ideas presented in this paper, with

particular attention to the design and implementation of internal parameter

simulations is provided in "The General Problem Solving Simulation," Brent

D. Ruben, in Experience Learning , Robert S. Lee, ed., (New Yorl<: Basic Books,

in press)

.

13 The game Sens i t i vi ty was designed and developed by Jor,^h Kalb and David Viscott

in 1969 and is distributed by Sensitivity Games, Inc. of Boston. Information

included in this chapter on sensitivity is based upon the instructions furnished

with the game.

I'* "Instructions," the game of Sensitivity .

15 V/illiam A. Gamson , SIMSOC: Participant's Manual (New York: The Free Press, I969)

and SiHSOC: Instructor's Manual (New York: The Free Press).

16 Ibid . , p. 13.

17 Ibid . , p. 13.

18 A provocative discussion of the encounter group as an instructional simulation

is provided by Richard W. Budd in a recent paper entitled "Communication,

Education and Simulation: Some Thoughts on the Learning Process," Institute

for Communication Studies, Iowa City, Iowa, December, 1970.

19 One variation of PRISONERS' DILEMMA for use with groups is provided in Human

Communication: Simulation and Games , Brent D. Ruben and Richard W. Budd,

(New York: Mayden Books, in press).

20 WIN AS MUCH AS YOU CAN is described in A Handbook of Structured Experiences fo r Human Relations Training , J. William Pfeiffer and John E. Jones, (Iowa City,

Iowa, 1970)

21 STARPOV/ER was developed by R. Garry Shirts and is distributed by Western

Behavior Sciences Institute.

22 THEV SHOOT MARBLES DON'T THEY is available from Learning A. and M. , Ann Arbor,

M i ch i gan

.

23 The game of Monopoly is distributed by Parker Brothers, Inc.

2^^ The game of Hang-Up Is distributed by the Unitarian Universal ist Association

of Boston, Mass.

Information included in this chapter about Hang-Up is based upon the instructions furnished with the game.

54
25 The INTERACT simulation is described in INTERACT, Brent D. Ruben, (Kennebunkport

,

Maine: Mercer House Press, 1973).

26 The INTERMEDIA simulation is described in INTERMEDIA, Brent D. Ruben, Albert D. Talbott, Lee M. Brown and Henry G. LaBrie Ml, (Iowa City, Iowa: University

Associates Press, 1970). Descriptions of abbreviated versions of INTERMEDIA are The Communication System Simulation , Albert D. Talbott and Brent D. Ruben,

(Iowa City, Iowa: University of Iowa School of Journalism, 1969) » and In Human Communication: Simulations and Games , Brent D. Ruben and Richard W. Budd,

(New York: Hayden Books, in press).

27 Dorothy J. Mia I and Stanley Jacobson, 10 Interaction Exercises for the Clas sroom

(Washington: National Training Laboratory, Institute for Applied Behavioral

Science.

Information included in this chapter is based upon the instruction sheet provided with "Experiment in Cooperation."

. This exercise is also discussed in Human Communication: Simulations and

Games , Brent D. Ruben and Richard V/. Budd, (New York: Hayden Books, in press) , and in J. William Pfeiffer and John E. Jones, A Handbook of Structured

Experiences for Human Relations Training, Volume I (Iowa City, Iowa

University Associates Press, 1969).

28 Ibid .

29 Gamson, op. cit ., p. 13.

55
CONFLICT RESOLUTION: FROM POWER TO PEER

RELATIONS IN THE HELPING PROFESSIONS

- -

• ! Patricia Yancey Martin and Mane Withers Osmond

The Florida St9,te University, Tallahassee » Fla. 32306

I Summary . The present paper develops the position that I clients in search of needed social services are: (1) in a relatively powerless —dependent, subordinate--position visa-vis the professionals who provide these services; and

(2) in conflict with the service-providers over the type, ' quantity, and quality of services which they will receive. . Building on Blau's theory of social exchange and power, ^ conditions which sustain (or, allow one to avoid) a power " relationship are reviewed. With the aim of identifying • means for decreasing the power of the professional over

the client, experiments were conducted which utilized two f basic versions of a "mixed-motive" (prototype) social ^ simulation game. Results of play by 214 undergraduate ' students suggest that greater accountability of professionals I, to clients and to society—for their actions and the results

of their actions—will diminish the power of the professional

over the client and enhance the bargaining position of the

client. Conclusions are in terms of additional means for

changing professional-client associations from power to

peer relations, to make professions more responsive to client

wishes and needs. This study demonstrates the great utility

of social simulation games as a research method for testing

exchange theory, and encourages us toward construction of

more precise games for use in future research.

The sociological literature on social and health service

provision abounds with evidence that the individual person

in need of services is, in essence, at the mercy of the

service providers. From Goffman's (1962) asylums (where

persons with emotional problems are taught to be mental

patients) to Scott's (1969) agencies for the visually

handicapped (where persons with sight problems are taught

to be "blind men"), the situation is similar. Persons who

find themselves in need of help or assistance from others

often find themselves in a powerless position as a result of

their needs. Their powerlessness stems from the fact that

they approach a given professional with specific needs to

be met, while the professional, who needs clients to be

sure, comes to them as only some among many possible clients

any of whom would "fill the bill" equally as well. This

i

c

56
results in the clients' greater dependence on the

professional than vice versa, and leads to their occupancy

j of a subordinate position in relationship to the professional.

I As Blau (1964) has noted, the individual in a dyadic

! association who is less dependent has power over the one

! who is more dependent. Thus, we characterize the helperi helpee relationship in general--including social workerI client, physician-patient, and even teacher-student--as a power relationship. Associations on which both parties

I are equally dependent, or nearly so, are characterized

I as peer relations. As stated by Blau (1964:29), "while

reciprocal services create an interdependence that balances

power, unilateral dependence on services maintains an

imbalance of power."

The present paper is based on Blau's theory of social exchange

and power (1964) . Central to this theory is the assumption

that conflicting as well as common interests and goals are

an integral aspect of associations in everyday life. In

the professional-client relationship,! conflicts of interest

are perhaps more numerous than common ones. Of course, both

professional and client have a minimal common interest in

effecting and maintaining an association: the professional,

because he needs clients to maintain a practice, make money,

and/or fulfill job or organizational quotas regarding caseloads,

j and so forth; the client, because he has need for assistance

or services which he hopes the professional will provide.

j Beyond this minimum base, however, conflicts seem to predominate. The client desires the professional's full

attention, best services, and most effective results--

depending on the nature and extent of the needs with which

he approaches the relationship. The professional, on the

other hand, may already be over-burdened with clients, or

may be more interested in making money or influencing associates

than with meeting client-needs. And to some extent, from

the professional's viewpoint, one client is as good (or

I bad) as another; it does not really matter who the clients

are, so long as there are sufficient numbers —and proper

' kinds —of them available to meet whatever goals he has for

himself in practicing his profession or trade.

jl In short, a client's interest in his relationship with a

i;', prof essional is more intrinsic than is the professional's

j interest in him. The client approaches the relationship

'With a personal need—and often, an urgent one--for counseling,

!' for surgery, for rent money, dental care, or clothes for the

•-The terms "professional" and "client" are used here

'and throughout this paper in the broadest general sense.

; They refer to service-provider and service-seeker (or

' recipient) in all manner of education, health, and social

service arenas.

57
children. The professional's interest in the client,

however, is more extrinsic than intrinsic; while he does

need clients with proper problems, it is really immaterial

to his practice exactly which clients come.

Given the conflicts of interest between professional and

client, and given the client's greater dependence on the

professional--which places him in a position of subordinance--

what can be done to lessen the power of the professional and

to increase that of the client, in the helping process?

Short of drastic institutional change, we suggest that the

most reasonable direction at present is to increase the

professionals' dependence on the outcomes of his services

to clients. The central theme of this paper is that movement

toward greater accountability of the service provider--for

his actions and the results of his actions--to service

providee is the most feasible means of changing associations

in the helping process from power to peer relations.

Exchange and Power in Social Life

"To speak of social life is to speak of the associations

between people--their associating together in work and in

play, in love and in war, to trade or to worship, to help

or to hinder" (Blau, 1964:12). Basically, it is the forces

of social attraction—whether intrinsic, extrinsic, or both--

that bring persons into association with one another. Once

in each others presence, the primary process via which

social structure--or relationships--emerge is that of social

exchange. Social exchange, as defined by Blau (1964:91),

"

. . . refers to voluntary actions of individuals that are

motivated by the returns they are expected to bring and

typically do in fact bring from others."

The major aspects of exchange theory on which the present

study is based are as follows. (1; Unspecified obligations . The most significant distinction between economic exchange

and social exchange is that the latter entails unspecified

obligations, while the terms or products of economic exchange

are generally specified or explicit. Social exchange

involves the principle that when one person does another a service, though there is a general expectation of some future

return, its exact nature is definitely not stipulated in

advance. (2) Trust . A consequence of the unspecified nature

of obligations inherent in social exchange is the necessity

for trust in interpersonal transactions. Blau notes, "Since

there is no way to assure an appropriate return for a favor,

social exchange requires trusting others to discharge their

obligations" (1964:94). (3) Symmetry . The symmetry of a social relationship is defined as the extent to which the two

58
parties are equally committed to it. If they are not so

committed, the party with the least commitment has an

j advantage over the other, and the relationship may be

i characterized as one involving power. If the parties are

!egually--or reciprocally--committed, the relationship is

I known as a peer relation. In a power relationship, the

j partner who is least committed may utilize the advantage he

J has thereby, to exploit or otherwise take advantage of the

{more committed member. It is of central concern here to

[identify those features of institutionalized professionalI client relations which can be altered to attenuate the

j chances of exploitation of the client.

j (4) Attraction . The "attraction" dimension of social

'transactions refers essentially to the reason (s) of the

I parties for entering and/or remaining in the relationship.

These can vary along a dimension from purely intrinsic to

j purely extrinsic. Most associations have elements of both

•i types of attraction in them, though one type or the other

may predominate. While the professional-client relationship

I is essentially extrinsic in character, we noted earlier that

i the client's reasons for participation generally have more

; of an intrinsic aspect to them than does the professional's,

j (5) Functions . There are two general functions of the social

j exchange process. One is to establish bonds of friendship

j (or peer relations) and the other, to establish superordinatior

I over others (or power relations). Since the major goal here

I is to explore measures by which professional-client relations

'can be transformed from power to peer relations, a review of

^1 the basic conditions which sustain a power relationship is

I in order.

Power Relations: Their Formation and Persistence

Power is defined here as " . . . the ability of persons or

'groups to impose their will on others despite resistance"

j (Blau, 1964:117). One of the most prevalent means of

I attaining power is through providing needed benefits which

'others cannot easily do without. Thus, when a client goes to

an "expert" for services or help, he goes needing these

benefits from the professional expert more so than the latter

: needs anything from the individual client in return. One of

! the reasons the professional's need of the client is less

than vice versa, is that depending on the professional's

j employment setting, he holds himself--and his actions

J accountable not so much to the client, as to his employer,

firm or organization, professional association, colleagues,

and so forth. Observation of this fact in a number of health

and welfare settings prompted Stanton to conclude that in

59
most service arenas, it is the clients' welfare that "comes

last" (1970)

.

Of course, any professional must exhibit a minimum of

expertise and concern for the welfare of his clients. Otherwise, clients may cease to utilize his services, bring law-suit

against him, or damage his reputation to the extent that

he cannot secure enough clients to sustain his professional

activities. What are some of the options available, then,

to the client who wishes to avoid the role of subordinate to

the professional in a helping relationship? Blau, following

Emerson (1962), notes that an individual has four alternatives.;

First, if the client possesses enough strategic resources, ] he can offer the professional a service that the latter wants

badly enough to offer his services in return. For instance,

a client with great wealth may be able to secure needed

services from a professional without becoming subordinate to

him in the process--if the professional is interested in j making money and if the client is willing to expend it. j Exchanges of this type allow each side to retain their

^ independence and the relation becomes one involving peer ,

jj exchange rather than power. [

I' Second, assuming there are alternative suppliers of the i service, a client may seek the needed service elsewhere. A

poor family, for instance, in need of extra cash for a crisis | situation would have to approach a welfare agency as a subordinate, but might borrow from a relative as a peer. i The disdain which most persons show toward dependence on ) welfare funds--even among those currently receiving them (see i Grigg, et^ al . , 1972) --may be accounted for by persons' i preferences, in general, to avoid a relationship in which

they must play the subordinate role. i A third option of the client is to coerce the professional 3 to furnish the needed services or benefits, providing the ; client is able to do so. In effect, the use of compulsion 3 or force to gain services would establish the domination of ; the client over the professional. While physical force or

the threat of violence are prohibited—by both normative ji and legal standards —there are other means of coercion which ; are acceptable in our society. For instance, the recent 3 organization of Welfare Rights and Senior Citizens groups 1 to demand and procure needed social and medical services ; provides examples of specialized client groups who, in

essence, are publicly disclaiming their subordinate role in ; the social and health service arenas. l

i

60
The fourth possibility is that of doing without the needed

service; that is, learning to get along without it or else

finding some substitute for it. As Blau notes, taking this

option would require that the clients change the values which

determine their needs (1964:119). It may be that this is a tack currently taken by many persons in our society. The

refusal of the poor and elderly to apply for public

assistance—even when they qualify for it and need the money

or to visit a physician or go to a hospital—even though

they are sick and could do so at society's expense —may be

an example of this very option: getting along without a needed service, in order to avoid paying the price of

subordinance to obtain it.

Experiments With a "Mixed-Motive" Social

Simulation Game

In an effort to explore the effects of symmetry and goals

on the professional-client relationship, two basic versions

of a prototype, mixed-motive social simulation game were

employed. The two game versions reflect different values of

Blau's concept of symmetry (that is, the degree of commitment

of the parties to the relation) , which is taken here as the

major independent variable in the social exchange process.

Game Model I reflects an asymmetrical situation, where the

professional has the advantage by virtue of his sole right

to make behavioral decisions for the pair. Model II reflects

a symmetrical situation, where neither professional nor

client has a built-in advantage over the other, since the

role of behavioral decider is determined by chance at the

beginning of each round of play. An attempt was made to hold

constant all other social and personal resources of the

participants by having partners "match" on these before play

of the game began. (For the steps in the "mixed-motive"

game as related to sex-roles, see Osmond, 1970; and Osmond

and Martin, 1973. The present game consists of an adaptation

of the profile cards, conflict issues, and behavioral

alternatives to the professional-client relationship)

.

Within each of the game models, variations were also made

according to the goals of play. In one variation, we

encouraged clients--and likewise, the prof essionals--to

think only of their own welfare, while in the other we

stressed the importance of the relationship per se, in

addition to individual success. Essentially, this reflects

an emphasis on relatively zero-sum goals versus relatively

multiple-sum ones. Table 1 presents the four game-models

utilized, showing variations on both symmetry and goals.

61
TABLE l.--Game Models by Symmetry and Goals

Nature of Goals

Degree of

Symmetry Individual Only Individual and Relationship

Asymmetrical

(Model I)

lA. Asymmetrical , individual

only

IB. Asymmetrical

,

individual plus

couple goals

Symmetrical

(Model II)

IIA. Symmetrical

,

individual

only

IIB. Symmetrical

,

individual plus

couple goals

Exchange theoretical principles would lead us to predict

that players of version lA. (representing a potential power

relationship with relatively zero-sum goals) would exhibit

the least success in terms of total points scored and the

greatest amount of exploitation (of the partner lacking an j advantage by the partner with one) . Players of version IIB.

(representing a peer relationship with individual but also | relationship goals) would be expected to achieve the highest

individual and couple scores and to show the least amount of

exploitation.

The specific questions of this research effort are as follows.

(1) Does an asymmetrical relationship lead to greater exploitation of a client than a symmetrical one does? And, (2) can

goals make a difference in the outcomes of the professionalclient exchange process, independently of the symmetry of

the relationship? These two questions reflect, in part, the

first and fourth of Emerson (1962) and Blau's (1964) options

for avoiding a dependent relationship (that is, strategic , resources and values) . Our experiments do not deal with the

second and fourth possibilities —alternatives and coercion— , though more is said of these in the discussion, following

presentation of the results. . - ...

The Mixed-Motive Game

The "Mixed-Motive" game prototype is a social simulation game j based on Blau's theory of social exchange. Structural elements

are built into the game both by the role obligations of the

players as well as by the game's rules. Cultural elements

of relevance are reflected in the "goals" of the game, toward i which the players' behavior is oriented. The major concepts ' of exchange theory are incorporated in the game as follows.

(1) The game assumes that the interpersonal relationships beingj

62
simulated are primarily extrinsic (on the " attraction " dimension) in character. (2) The " obligations " of social

exchange remain unspecif ied ^ through the players' keeping

secret their individual value-weightings on the conflict

issues. (3) The major independent variable of the game is

Blau's symmetry of the relationship, which is experimentally

manipulated by altering the players' behavioral opportunities

(via Model I and Model II) . (4) The intervening variable in

the theoretical model is the " degree of trust " between the

professional and client. Though trust is not of central

concern to the present study, it is an important aspect of

the service-provision/service-receipt process and has been

elaborated on elsewhere (see Bidwell, 1970; Martin and

Osmond, 1973) . Trust is incorporated into the game via the

option of the "behaver" to violate agreements or demands

("to cheat"), and that of the "demander/checker " to check

(and "punish") the behaver, if and when violations are

suspected. (5) And last, the dependent variable of the

theoretical and gaming models is the extent to which peer

(versus power) relations (the "functions" of exchange)

emerge from the interaction process.

The "mixed-motive" game can be played by any number of twoperson dyads and requires three rounds to complete. Scores

are posted at the end of each round of play, so that participants can assess their performance in relation to others

playing a similar role. The game assumes a conflict of

interests (and/or behavior preferences) between the client

and the professional, but also a desire on the part of each

to preserve the relationship. Given the conflicts of interest,

it follows that some degree of compromise—coordination,

cooperation--is necessary for the relationship to remain

viable. The reward structure (or scoring system) of the game

encourages the players toward a multiple-sum form of

compromise (see Osmond, 1972) . That is, a dyad—as well as

an individual player--achieves its highest score if each

member insists on his way on those issues of greatest

importance to himself, but allows the other to have his v/ay

on issues of greatest importance to himself.

Players of all game models were instructed that "points

achieved" in the game reflected success in meeting their

goals . For clients, success consisted of receiving desired

services; for professionals, fulfilling professional goals.

Relationship goals were articulated as "achieving success

in providing for client needs while enhancing the client's

approval of and respect for the professional." In games

where only individual goals were stressed, clients were

instructed to compete only with other clients for success; and

professionals, only with other professionals. Partners in

all four game variations were explicitly instructed that they

were not in competition with each other—thus our description

63
of Models lA and IIA as only relatively zero-sum in comparison

with Models IB and IIB. In the games where relationship

goals were stressed, players were instructed that any dyad

not scoring 1,000 points by Round 3 was failing in its efforts

to have a successful professional-client relationship.

The Subjects and the Data

The subjects for this study consisted of 214 undergraduate

students at a large southern university, enrolled in courses

taught by one of the instructors in the 1972-73 school year.

The courses ranged in nature from the sociology of the family

to research methodology and statistics, and were taught by

the authors in the Departments of Social Work and Sociology.

Though the sample is small in size and nonrandomly selected,

we hold that the fit of the data with the predictions of the

theoretical model lends credence to its validity. Further,

the results reported here exhibit a pattern consistent with

data from other experiments utilizing the "mixed-motive"

prototype game on the subjects of sex-roles and parent-child

relationships (see Osmond & Martin, 1973; and Osmond, 1969)

.

The data utilized in the analysis consists of the actual

scores which the players achieved and utilized as feedback

during play of the game. "Success points" were selfrecorded by each player at the end of each round of play,

and scores for both individuals and dyads are utilized here

as indicators of the conflict resolution strategies which

they employed. Exploitation--of the client by the

professional--is measured by the difference between the

professional's score and the client's score, at the end of

each round. A positive difference indicates that the

professional was scoring higher than the client, and a negative one that the client's score was higher than the

professional's. It is recalled that a successful strategy

in the "mixed-motive" conflict resolution game would be

indicated by an overall decrease in exploitation over the

three rounds of play.

The Results

The data in Table 2 indicate that the symmetry of the

prof essional- client relationship is indeed important in

determining the functions of the social exchange process.

By the end of the second round, players of the symmetrical

game (Model II) were exploiting each other very little and the

pattern held through the third round. In fact, in the last

two rounds, clients were scoring—on the average —slightly

higher than professionals. Players of the asymmetrical game.

64
however, exhibit a pattern of increasing exploitation from

the first to third rounds. Clients increased their

exploitation of professionals from Rounds 1 to 2, while

in the third round the professionals apparently asserted

their advantage and .shot ahead of the clients. In fact,

the size of the exploitation value in the third round of

the asymmetrical game is larger than for any other round of

either game model (42 points). The tendency to exploit, as

reflected by the data of the asymmetrical game, seems to be

"encouraged" by a relationship in which one member is more

dependent than the other. Thus, the evidence suggests that

clients would gain the most from their relationships with

professionals if they had enough strategic resources to

establish a peer relationship with them. Given that this

is generally not possible, let us turn to an examination of

the effects of goals.

TABLE 2. —Average Amount of Exploitation (of Client by

Professional) By Symmetry Model and Round of Play

Round Model I: Model II:

of Play Asymmetrical Symmetrical

(N=51) (N=56)

1 -14 + 34

2 -27 -3

3 + 42 -10

The goals of the professional-client relation appear to have

less of an impact on the functions of exchange than

symmetry does. Table 3 indicates that by the third round

of play, professionals are exploiting clients to some extent

regardless of whether goals were for individual success only

or for both individual and relationship success. However,

caution should be utilized in interpreting these data. In

order to examine the effects of goals, we combined games with

different structures (Models lA . and IIA. ; and IB. and IIB.);

The result that clients exploited professionals in

the first two rounds of the asymmetrical game is paralleled

by our data on sex-roles, involving male-female interaction.

Blau's theory provides an explanation for this outcome. When

persons have a built-in advantage--as the professionals do

here--they are hesitant to use it, up to a point. However,

when the occasion calls for it (and here, it is winning or

losing the game) , they will use their advantage and thus

establish, or re-establish, the structure of the relationship.

65
thus, the effects of symmetry on exploitation patterns may

well cover-up—or over power —the effects of goals of the

partners.

TABLE 3. --Average Amount of Exploitation (of Client by

Professional) By Goals of Game and Round of Play

Round of Individual Individual Plus

Play Goals Only Relationship Goals

(N=22) (N=85)

1 -37 + 40

2 -35 0

3 + 13 + 8

The data in Table 4 clarify the picture to some extent. Here

it becomes obvious that although the goals of the relationship

have a systematic effect on exploitation, the evidence is

not clear-cut. Comparing Models lA. and IB. , we note that

when a relationship is asymmetrical, having multiple-sum

goals in addition to individual ones is associated with a reduced amount of professional dominance, by the third round

of play. In fact, there is about one-half as much exploitation

in Model IB. as in Model lA. (a difference of 28 points as

compared to 52) . These data provide an affirmative answer

to the second question of this study, indicating that goals

of a relationship can have an important influence on the

functions of social exchange—which is independent of the

symmetry of the relationship.

TABLE 4. —Average Amount of Exploitation (Of Client by

Professional) By Symmetry and Goals, and By Round of

Play

Model Model Model Model

lA. IB. IIA. IIB.

Round (Asym. , Ind) (Asym. , Both) (Sym. , Ind) (Sym. , Both)

of Play (N=15) (N=36) (N=7) (N=49)

1 -51 + 42 -5 + 40

2 -5 -60 -99 +16

3 + 52 + 28 -71 + 2

66
Questions are raised rather than answered, however, by a comparison of the two symmetrical models (IIA. and IIB.)-

In the game with both individual and relationship goals,

exploitation by professionals decreases consistently from

the first to third rounds; in fact, there is practically

none at all by Round 3. In the game with individual goals

only, however, exploitation increases from Rounds 1 to 3--

but it is exploitation of the professional by the client

rather than vice versa . We are unable to offer a satisfactory

explanation for this result--if, indeed, one exists. The

data are based on such a small N (only seven couples) that

perhaps we should dismiss them as unreliable. However, they

may indicate something of worth which, at the least, should

be investigated by future research. When individuals

accustomed to a subordinate role in a given type of relationship find they are now "equals" with their partners; and when

these same persons have a goal of enhancing only their

individual welfare, perhaps they pursue these goals with a

certain amount of ruthlessness . This might constitute an

instance of "oppressed" persons seeking revenge, once they

become aware that their "oppressors" no longer enjoy an

advantage over them. At any rate, the possibility that the

results of game Model IIA. are meaningful deserves attention

in future research on the effects of goals and symmetry on

the social exchange process.

Discussion

Long, commenting on the welfare delivery system in this country

has noted that "... the powerlessness of clients (customers)

is not only dysfunctional for them [the clients] but is coming

to be regarded as dysfunctional for the production of desired

system states. Effective customers may be a necessary

variable for the achievement of planned system states that

are generally desired" (1970:202). The results of this study

offer some insights into the social conditions which produce

"powerless clients" and point us toward specific actions which

will facilitate the emergence of "effective customers" in the

health, education, and social service arenas. Specifically,

we believe our data provide evidence in support of increased

"accountability" of service-providers to the clients —or

customers—whom they serve.

Our data indicate affirmative answers to both of the research

questions posed. That is, (1) asymmetrical relationships

result in greater exploitation of clients, by professionals,

than symmetrical relations do. And, (2) given the typical

1 67
asymmetrical character of professional-client relations

(cf. Parsons, 1970:3; Bidwell, 1970:39; and Rosengren, 1970:

216), multiple-sum goals for the dyad's members result in

less exploitation of the client than do goals of a relatively

zero-sum nature. A conclusion suggested by the first result

(which is directly related to Emerson and Blau's first option

for avoiding the dependent role in a power relationship) is

that clients can approach a service-provider on a peer basis

if they are able to marshall enough strategic resources to

offer needed services to the professional in return for those

sought. Since professionals tend to acquire prestige and

respect on the basis of the status characteristics of their

clients, high status clients would have a valuable asset with

which to bargain in the exchange process. However, as Rosengre

has noted (1970:206), ". . . many clients are ill, infirm,

very young, impoverished, under educated , discriminated against,

legally constrained, and otherwise unable to mobilize . . . resources on their behalf and on their terms." Thus, the

chances for many persons in our society to escape the subordinate role in their relationships with prof essionals--or

even to attenuate the effects of such asymmetrical relations--

are minimal to zero.

Our second finding suggests a more plausible, and logically

possible, alternative for improving the clients' bargaining

position vis-a-vis the professional service purveyor. If we

can encourage, or enforce, multiple-sum goals for professionalclient relations, although the professional would retain the

advantage in the relation (and thus remain in power) , his

tendencies to exploit clients would diminish. The primary

responsibility for articulation and enforcement of such goals

would ultimately rest with the prof essional--either on the

organization for which he (or she) works or on the professional

association to which his actions are currently held accountable

(see American Hospital Association, 1973). Parsons (1970:8-10)

in a comment on the effectiveness of professionals' decisions

regarding solutions of client problems, notes the following.

"Since, typically, the client is relatively low on power, this ' means the superordinated components of the organization must ' act in a leadership capacity to ensure ..." effective

decisions on behalf of the client. Such "responsible leadership" would best be facilitated by the institutionalization of i a relevant set of "client-rights" —in the sense of "civil ' rights"--which would be recognized as legitimate by all parties'

involved. As Parsons further notes, "Client membership [in

' the professional-client relationship] is grounded in rights

to the primary output of the system; 'staff membership is

grounded in functional contributions to bring about that output'

[emphasis the authors'].

j To encourage professionals toward such a recognition of 1 client-rights —

to the primary output of the system. " entailing

68
"effective decisions on their behalf" —service and professional

organizations might begin by making grants of social honor

and other rewards contingent upon the consequences of service

provision efforts. Such a strategy would logically include

inputs and feedback from clients regarding feelings of respect,

approval, and gratitude toward the professional. As Blau

notes (1964), we are more likely to grant such "social rewards"

to persons who treat us well than to those who do not. Thus,

direct evaluation by clients should become an institutionalized

aspect of the reward structure within which service purveyors

practice. In essence, we conclude that "responsible leadership"

of the superordinate professional organization would entail

some elements of direct accountability of professionals to

the clients whom they service. Extrapolating from the present

research, while such accountability would likely not eliminate

exploitation of clients by professionals, it would result in a

significant reduction in the amount of such exploitation.

Specific possibilities for prodding service organizations to

institute such accountability systems are several—ranging

from the mobilization of public opinion, to the passage of

specific laws, to the organization of client-groups for the

purpose of pressuring recalcitrant organizations. General

public dissatisfaction and pressures on law-makers—over failure

of services to produce promised results; rising costs with no

visible improvement in service quality, and so forth—have

resulted already in legislative requirements that federally

funded programs "account" for themselves in terms of demonstrabl

"outputs." On the client-level per se, two of Blau and

Emerson's options (coercion and utilization of alternative

services) seem pertinent. Collective organization of the

clientele of various social service organizations might

enhance professional responsiveness to client needs by, for

example, waging effective publicity campaigns; calling for

boycotts of certain agencies; or restricting patronage to

the more effective organizations. A problem here, however,

as noted by Bidwell (1970) is that the chances for clients

to effectively organize are diminished in those organizations

which service their clients ser iatim--and where clients are

non-members of the organization and thus interact with each

other very little—as compared with organizations which service

in "batches," where the clients are members (for example,

schools, hospitals, prisons) and thus have greatly enhanced

opportunities for collective organization and action.

Nonetheless, even in agencies of the former type, special

interest groups with specific goals have organized and in some

instances had a significant impact on the programs against

which they took action. (See, for example, Steiner's account

of the National Welfare Rights Organization, 1971; also, see

Orden, 1973; Shapiro, 1971; Kramer, 1969; Levitan, 1969; and

Purcell and Specht, 1965)

.

69
Conclusions

The present study points to the need for further reseatch into

the conditions which attenuate professional dominance and whicl

facilitate effective (and efficient) service provision to

clients. Moreover, attention needs to be given to the extent

to which presumed professional "authority" —that is, legitimate

power--is in fact "granted" by clients, and to the actual role

of client trust in the professional-client relationship (see

Freidson, 1968 and 1970, on the "impurity of professional

authority"; and Parsons, 1970, on the importance of client

trust in professional-client relations) . The conditions under

which client grants of authority and trust flourish and/or

wane should be investigated. For example, do these vary by: ' type of service being sought; by the characteristics of the

service-provider's occupational setting (such as whether "free

professional" or organizational bureaucrat; or whether in

the health, social service, or educational arenas) ; by the

social characteristics of the service-seeker (such as age,

social class, race or sex) ; by the social characteristics of

the service provider; and so forth. Answers to these questions'

require a comparative framework and call for the empirical

investigation of several service-provision arenas at once.

Further, it is our hope that future research on professionalclient relations will be conceptualized within a dynamic (or

process) theoretical framework (as exemplified here by social

exchange theory; or otherwise by conflict theory or general j systems theory, etc.), and tested via a dynamic research method

(as exemplified here by the employment of a social simulation

game) . This hope springs from our own dissatisfactions with

typological theories and survey research methods; and from

| our enthusiasm over the rich potential of the social simulatior

gaming technique for theory construction and research (see

Coleman, 1969; and Walaszek, 1972) . Rather than having to

rely on what people "say" they do (or have done) , a method

such as simulation gaming allows one, in essence, to monitor

and observe the emergence of social organization--and thus to

literally assess the amount of cooperation, exploitation,

trust -or mistrust as it occurs —within the structure of the

interaction setting. While theorizing about professionalclient relations is at a fairly advanced level, the dynamics

of such relations have been little explored, and empirical

data on the development and progression of such relationships

are lacking. In closing, we concur with Parsons' comment

that: "The theme of the nature and importance of solidarity,

across the service-client line of service-rendering organizations thus seems . . . to be one of the most important with

which social scientists who care about the future of society

can concern themselves" (1970:16).

70
References

American Hospital Association.

1973 A Patient's Bill of Rights. Chicago, Illinois:

American Hospital Association.

Bidwell, Charles E.

1970 "Students and schools: Some observations on client

trust in client-serving organizations." Pp. 37-69 in

W. R. Rosengren and M. Lefton (eds.), Organizations

and Clients. Columbus, Ohio: Charles E. Merrill

Publishing Company.

Blau, Peter M.

1964 Exchange and Power in Social Life. New York: John

Wiley and Sons.

Coleman, James S.

1969 "The methods of sociology." Pp. 65-93 in Robert

Bierstedt (ed.) A Design for Sociology: Scope,

objectives and methods. Philadelphia: The American

Academy of Political and Social Science.

Emerson, Richard.

1962 "Power-dependence relations." American Sociological

Review, 22 (February ): 31-41.

Freidson, Eliot.

1970 "Dominant professions, bureaucracy, and client

services." Pp. 71-92 in W. R. Rosengren and M.

Lefton (eds.). Organizations and Clients. Columbus,

Ohio: Charles E. Merrill Publishing Co.

Goffman, Erving.

1961 Asylums: Essays on the Social Situation of Mental

Patients and Other Inmates. New York: Doubleday

Anchor Books.

Grigg, C. M. , P. Y. Martin, M. G. Horton, and M. W. Osmond.

1972 A Follow-up Study of Four Rehabilitation Projects

for Disabled Welfare Clients. Tallahassee, Florida:

Institute for Social Research.

Kramer, Ralph M.

1969 Participation of the Poor. Englewood Cliffs, New

Jersey: Prentice-Hall, Inc.

Levitan, Sar A.

1969 The Great Society's Poor Law: A New Approach to

Poverty. Baltimore: The Johns Hopkins Press.
Long, Norton.

1970 "Rigging the market for public goods." Pp. 187-204

in W. R. Rosengren and M. Lefton (eds.). Organizations

and Clients. Columbus, Ohio: Charles E. Merrill.

Orden, Susan R.

1973 "The impact of community action programs on private

social service agencies." Social Problems 20 (Winter)

364-81.

Osmond, Marie W.

1969 "COM-PAC: A two-person communication game." Mimeo.

1970 "The method of simulation games in family life

education." Experimental Publication System, 9

(December) :Ms. No. 346-45.

1972 "The simulation of rational exchange: An extension

of Schild's model." Pp. 134-38 in Proceedings of the

National Gaming Council's Eleventh Annual Symposium.

Report No. 143, Center for Social Organization of

Schools. Baltimore: Johns Hopkins University.

Osmond, M. W. , and P. Y. Martin.

1973 "From closed to open-systems: Game simulation of

sex-role behavior." Under review.

Parsons, Talcott.

1970 "How are clients integrated in service organizations?"

Pp. 1-16 in W. R. Rosengren and M. Lefton (eds.)

Organizations and Clients. Columbus, Ohio: Charles

E. Merrill.

Purcell, F. P. and Harry Specht.

1965 "The house on sixth street." Social Work, 10

(October) : 69-76

.

Rosengren, William R.

1970 "The social economics of membership." Pp. 205-22 in

Rosengren and Lefton (eds.) Organizations and Clients.

Columbus, Ohio: Charles E. Merrill.

Scott, Robert A.

1969 The Making of Blind Men. New York: Russell Sage

Foundation.

Shapiro, J. H.

1971 Communities of the Alone. New York: Association

Press

.

72
Stanton, Esther.

1970 Clients Come Last: Volunteers and Welfare

Organizations. Beverly Hills, California: Sage

Publications

.

Steiner, Gilbert Y.

1971 The State of Welfare. Washington, D. C: The

Brookings Institution.

Walaszek, Z. A.

1972 "Theory-games-reality." Pp. 60-73 in Proceedings of

the National Gaming Council's Eleventh Annual

Symposium. Report No. 143, Center for Social

Organization of Schools. Baltimore: John's Hopkins

University.

Weiss, Robert S.

1973 "Helping relationships: relationships of clients with

physicians, social workers, priests and others."

Social Problems, 20 (Winter ): 319- 28

.

73
A PRELIMINARY INVESTIGATION OF THE USE OF PRINCE

-- A MAN -COMPUTER SIMULATION OF INTERNATIONAL RELATIONS -- IN HIGH SCHOOL COURSES

Steven J. Kidder, Ph.D.

Abt Associates Inc.

55 Wheeler Street

Cambridge, Massachusetts 02138

Richard E. Horowicz

Northern High School

2201 Pinwood Avenue, Zone 14

Baltimore, Maryland 21214

Gary M. Kiselewich

John Hopkins University

Baltimore, Maryland 21218

This paper reports on research designed to analyze the adaptability of a college- level man-computer simulation to the high shcool level. The simulated environment incorporated in this study was PRINCE (Programmed InterNational Computer Environment) . PRINCE is a man-computer simulation of

international relations developed at Syracuse University by Coplin and

O'Leary (1972). The application of PRINCE at the high school level also

involved the development of a preliminary instructional model for the use

of simulation games in classrooms. This paper reports on the use of PRINCE

and the students' achievement in the international relations course.! Following a brief introduction to the PRINCE simulation, the paper continues

with the Study Approach, Grades and Testing, Results, and Discuss ion.

2

The PRINCE Model

As noted above, PRINCE is a man-computer simulation of international relations. The players assume the role of foreign policy maker for the United

States and cope with various issues within a framework of domestic and

international reactions.

The domestic component of PRINCE consists of various Policy Influencing

groins (PI groups) which represent various political, economic and bureaucratic interests within the United States. The international component

simulates the reactions of five nations (Russia, China, India, France,

Pakistan) to the decisions of the U.S. policy -makers on different international issues. The issues themselves are stated in teims of a specific

outcome which the players attempt to achieve or block, according to their

interests.

A brief description of the instructional model used in this study can be

found in Appendix A. For a detailed description, see Kidder (1973a, 1973b)

.

t ^These sections are based on Report No. 153, "An Instructional Model for I the Use of Simulation Games in the Classroom," by S.J. Kidder, R.E. Horowicz,'

and G.M. Kiselewich, Center for Social Organization of Schools, The Johns

Hopkins University, May 1973.
Three basic types of decisions are made during the play of PRINCE; Issue

Positions, Influence Attempts and Transaction Acts. The players make these

decisions for the U.S. and the computer formulates these decisions for the

five simulated nations. Issue Positions (IPs) state a nation's general

attitude toward a specific issue and are rated on a scale of -10 (strongly

disagree and will attempt to block the issue) to +10 (strongly agree and

will attempt to achieve the issues as stated) . Influence Attempts (lAs) are made by a nation to sway the Issue Position of another country so that

it will more closely represent its own attitude on that issue. Influence

Attempts can be friendly (+10) or range to unfriendly (-10) . Transaction

Acts (TRs) are economic moves made between countries in the form of AID

(in millions of U.S. dollars) or RESTRICTION (restricting the natural flow

of goods and services by a stated percentage)

.

These decisions are coded and run through the PRINCE program. New Issue

Positions, Influence Attempts and Transaction Acts are formulated for the

simulated nations and are given to the players for study. The reaction of

the various Policy Influencer groups on specific individual decisions are given along with a conglomerate picture of the domestic reaction as ex- pressed in a Public Opinion Poll. The PI groups rate individual actions on

a scale of +10 (strongly approve) to -10 (strongly disapprove) . The Public

Opinion Poll shows the percentages of the U.S. "populace" that approve or disapprove of the players' overall performance. Additionally, the computer

may make recommendations for future actions. All of the above is included

on the computer output, which the players study as a basis for future

decisions. Overall, players are attempting to resolve issues in their

favor while maintaining satisfactory domestic and international relations.

Study Approach

The purpose of the study was to apply a controlled instructional approach

to the use of simulations at the high school level in order to examine:

(1) how the instructional model would fare in actual use, and (2) how the

class using the model and game approach would compare to a traditionallytaught class.

The basic materials for a one semester course in International Relations

were made available from the International Relations Program at Syracuse

University. A thorough study of the Manual and background data suggested

that further instructional materials should be developed. Issue packets

containing current new articles that were relevant to the PRINCE issues were constructed for student use in the classroom. The students were

divided into teams, to increase their motivation to operate effectively in

the course. Each team received identical issue packets. The modified

curriculum called for data on seven of the fourteen issues in the PRINCE

instructional materials.

Lesson plans were written to introduce the students to the basic concepts

I of international relations, e.g., nationalism, sovereignty, power. The

introduction took over a week's time. Following this, the rules and proce75
dures for playing the simulation game were taught. Sample computer "dry

runs" of the simulation were examined to prepare the students for the I decision-making periods. Actual game playing began the following week,

with the students' decision-making restricted to one issue. (See instructional model, above. It is important to begin the decision-making at a low

conceptual level.) One new issue was added each subsequent week, thus

increasing the complexity of the learning task over time. Additional aids

were developed to facilitate playing the PRINCE game.

Three groups of twelfth grade students participated in the study. Group 1 received a traditional course in International Relations, Group 2 received

the complete experimental course involving the PRINCE computer simulations;

Group 3 (in another school, but taught by the same teacher) also received

the experimental treatment. From the beginning of the study, it was as- sumed that there would be an increase in student ability from Group 1 (low)

,

through Group 2 (medium) and Group 3 (high) . An analysis of covariance was performed in order to determine the relationship between student ability

and the effect of the instructional approach.

The experimental groups were separated into teams of five to eight players.

One team member was chosen as a chairman and the other members were assigned

other tasks, such as becoming an "expert" on a particular country or issue. , The teams were given one day to research the new issue and another day to

arrive at group decisions on the various actions that can be taken when

playing PRINCE. Those decisions were then given to a programmer who handled the computer runs. (It was impossible for the students to interact i with the computer directly.) While the computer runs were being completed,

the students attempted to predict the effects of their decisions on the

simulated international and domestic environments. (The act of prediction

or becoming aware of the outcomes of various strategies has been emphasized

as an important component of learning from simulation games. See Fletcher,

1971, p. 443.) In addition, the students compared strategies and talked

about the issue in a general class discussion. This activity was followed

by a discussion of the computer feedback in light of their predictions and

class discussion. This process continued until all seven issues were being

dealt with in the course

.

I

Grades and Testing '

Students were informed that grades would be based on a combination of their

group effort (as reflected in the Opinion Poll on the computer feedback

sheets) and by their own individual effort in class. A final exam was administered to all experimental and control groups at the close of the course. The exam consisted of 100 objective items (mostly multiple-choice

with some matching) and four essays. The results of the data analysis are provided below. The experimental design involved a univariate analysis of

covariance, with I.Q. as the covariate. The dependent variable was the

student's score on the final exam.

76
Results

Table 1 contains the observed cell means for the Control Class, who received

a conventional course in International Relations; Experimental Class I, who

received the PRINCE instructional package; and Experimental Class II, who

studied the PRINCE instructional materials in another school, taught by the

same teacher. One readily observes the need for controlling I.Q.

Table 1. Observed Cell Means for Control and Experimental Classes

I.Q. Final Exam

Control 102.68 52.11

Exp. I 106.74 61.42

Exp. II 116.74 74.73

Table 2 contains the statistics for the regression analysis of I.Q. on final exam. Approximately 13% of the variance in final exam scores is

accounted for by I.Q.

Table 2. Statistics for Regression Analysis of I.Q. on Final Exam

Variable Square Mult R Mult R F P Less Than

Final Exam .135 .368 8.30 .006

Degrees of freedom for hypothesis = 1 Degrees of freedom for error - 53

Table 3 contains the statistics for the analysis of covariance determining

the relative effects of the Experimental I and II Classes versus the Control Class. The Experimental II Class resulted in a treatment effect

Table 3. Statistics for Analysis of Covariance:

Covariate is I.Q., Dependent Variable is Final Exam

EXPERIMENTAL I versus CONTROL

Mean Square = 4.31, F = .02, with 1 and 53 df, P less than .90

EXPERIMENTAL II versus CONTROL

Mean Square = 2048.44, F = 7.22, with 1 and 53 df, P less than .01

77
(p < .01) even after the effects due to I.Q. have been eliminated. Thus,

the model plus complex simulation game is only effective with above average

students. Nevertheless, the differences remain even after the effects due

to ability have been removed statistically.

Discussion

The experimental treatment increased class perfoarmance over a conventional

approach to teaching international relations. However, the instructional

model incorporated a man-computer simulation of high complexity, designed

for college students, which seems to have dampened the effect of the model

with average high school students. However, the study is exploratory; now

that successful application of the model has been shown, future research

should be conducted to determine the effect of the model with diverse simulation games, varied team structure and scoring techniques. All that has

been examined here is the total effect of the model; the importance of

these elements is yet to be determined. The model plus man-computer simulation game was most effective with the high ability students. Even though

the effect obtained with average students was not statistically significant,

it should be noted that they did successfully complete the coxirse of instruction and obtained rather good grades, compared to the conventional

class with average students. It is encouraging to find average ability

high school students handling complex man-computer simulation games designed

for college students.

Decision-making and problem- solving skills are important learning outcomes

which were not examined in the present study, but may yield interesting

results in future studies . The suggested instructional model emphasizes

the importance of making decisions and predicting the effects of these

decisions before feedback is received. Simulation games seem to provide a natural environment for "exercizing" such higher-level cognitive skills.

The emphasis on these skills may be justified on the basis of their generalizability to new problem situations that require immediate decisions for

resolution. In complex simulations, problems continually confront the

participant while the solution rests on cogent decision-making. If students

receive more instruction in these skills in simulated environments, perhaps

their performance in real-life will improve.

Although the instructional approach emphasized in the present paper resulted

in increased student performance, research must be conducted to determine

the relative effects of each element within the model. The effectiveness

of the model may have been due to the effects of the teams, the gradual

increase in complexity of the model (for maintaining motivation) , or the

simulation game itself. A clarification of the effects of these elements

within the model can be made with programatic research.

78
REFERENCES

Mills, S.L., O'Leary, M.K., PRINCE: Participants' Guide , Concepts, Environments, Procedures , International Relations

Program, Syracuse University, Syracuse, New York, March

1972.

"Simulation Games as Learning Environments," Simulation & Games, December 1971.

"An Instructional Model for the Use of Simulations and Games

in the Classroom," Abt Associates Inc., A paper presented

at the American Educational Research Association meeting in

New Orleans, 1973a.

Horowicz, R.E., and Kiselewich, G.M., "An Instructional

Model for the Use of Simulations and Games in the Classroom," Report #153, Center for Social Organization of

Schools, The Johns Hopkins University, Baltimore, Maryland,

DecemJ^er 1973b.

79
APPENDIX A

AN INSTRUCTIONAL MODEL FOR SIMULATION GAMES

To date, instructional models have dealt with the acquisition of knowledge

by students. These models usually involve a clarification of instructional

objectives, measures on the entering abilities of the students, the actual

instruction, an evaluation, and feedback. It is tacitly assumed that the

student is motivated to learn and that higher level thinking (application,

analysis, synthesis, and evaluation) will be used and improved during a unit of instruction. The instructional model outlined below does not assume that students are always motivated to learn, nor that higher level

abilities are called into play during most classroom experiences. The essence of the model is that instruction should consist of two main phases,

the first concerned with the acquisition of basic skills and knowledge, and

the second concerned with an application, elaboration, and liberalization

of the first phase. This type of model differs from traditional instructional models because the second phase requires the use of higher level

abilities of application, analysis, synthesis, and evaluation in an "applied" but simulated environment. The first phase consists primarily

of traditional classroom approaches to teaching (lecture, discussion); the

second phase consists of an experience with a simulation game that increases

in complexity and involvement over time.

The two phases are developed in a way that reduces the effect of another

major problem in most classrooms; namely, lack of motivation. The phases

are structured so that learning in phase one will improve the student's

functioning in phase two. That is, a student's performance in phase two

(the game, or simulation) will improve if he understands all the information dealt with in phase one (the traditional classroom approach). Thus,

the goal of optimum performance in the liberal phase (or any other goal

embedded in the simulation or game) may sustain motivation to learn in the more traditional phase

.

The basic steps involved in the model include: (1) determine student com- petence (entering behavior) ; (2) introduce the unit at broad conceptual

levels; (3) introduce new concepts: gaming environment, team structure,

scoring (based on performance criteria in simulation or game and class work)

roles, and types of decisions to be made; (4) complete one round of decision

making with model; (5) have students try to predict results of decisions;

(5) inform students of their relative performance as teams and individuals;

(7) discuss effects of students' decisions, determine their understanding,

and clarify their misconceptions; (8) repeat steps 4, 5, 6, and 7 at the

next higher conceptual level of model. Note that the basic curriculum

phases into an "applied" curriculum during the students' experience with

the simulated environment. Figure 1 provides a schematic representation of

the initial model.

80
BEGIN

Determine Entering Behavior (1) \

Broad and Comprehensive

Introduction (2)

Introduction to Gaming

or Simulation Environment (3)

Complete One Round of

Decision-Making (4)

Predict Results of Decisions (5)

i

Evaluate and Feedback

to Students (6)

I

I ~ ^

I Clarify Misconceptions (7)

Figure 1, Schematic Representation of the Simulation and Gaming Instructional Model.

81
October 1, 1972

REPORT OF FIELD TEST

Obstacle Course: A Family Planning Delivery Services Gajne

John T. Foster, Dept. of Sociology, Florida A^M University,

Tallahassee, Florida 32307

Overview

fhe early prototypes of Obstacle Course were played in undergraduate

Social Welfare classes at the Florida State University, From this experience the author gained hueristically much infomation about the media and

functions of the game. Modifications were made and more elaborate materials

were then prepared.

This report of the first of two field tests has produced insight into

game weaknesses and strengths in accord with the simulation evaluation

strategy. Most of the concerns for the effectiveness of rules in causing

players to perform properly were allayed. The role of judge, created after

earlier trials, is of even greater importance than realized by the designer.

The game was played twice by eight groups of nurses and welfare workers

at the Public Health Clinics of the Public Health Department, Polk County,

Florida on September 2 5, 1972.

Description of the Procedures

Arrangements had been made on month prior (9/26/72) to the field test

to cause participants to play without personal inconvenience or cost. The

arrangements for play were located in comfortable rooms adjacent to the

clinics and an informal, congenial atmosphere prevailed. The players had

no other duties or interruptions during the game.

Players were encouraged to set at the table of their choice, to have

some coffee, smoke if they wished and to read the players manual. No help

interpreting the game was offered, but procedural questions received a courteous answer, "Look here in the rules."

82
After completing the first play of the game the groLf) was urged to

"play it again" and they did. Upon completing the second play the observer

collected the judge's notes, added them to his notes and asked the players

five questions (see "Player's ^^uiz") , The quizes were collected.

Four groups played at the Lakeland, Florida Clinic in the morning and

four groups played at the Winter Haven, Florida Clinic in the afternoon of

September 25, 1972, .

.

The Data

Description of the Sample

Participants: 44 women, 2 men

25 Public Health Nurses

11 Welfare Workers

10 Others (paraprofessionals, midwife, med, librarian)

Average age: about 35

Age Range: about 21-60

Comments: The field test participants were quite divided in what appears to be their aptitude as gleened from nondescript observation. The nurses were typically bright and alert, the

welfare workers were polite and cooperative; and the paraprofessional personnel employed to contact family planning

clients in the field (outreach) were quiet and threatened

. by the necessity to read aloud. Age and sex seoned to have no affect on player behavior.

Description of Time elements (speed of play)

Group No. of Players 1st Play 2nd Play Total time

#1 6 45 25 75

2 6 30 30 60

3 6 35 25 60

4 6 25 30 55

5 5

6 5

7 5 30 25 55

83
Post Test Results

Group Score: Cognitive Achievonent Score: Attitude Vocation

#1 #2 #3 Total

#1 3 4 4 11 0 PHN

2 0 3 5 + PHN 1 1 0 2 3 + PHN

il 1 2 3 6

PT4M 1 0 0 1 0 sw ! 3 0 0 , 3

- PHN li mean 4". "8

#2 4 4 3 11 0 SW '

4 3 2 9

+ sw \ 4 3 1 8 + sw

2 2 4

oo sw

A 4 3 11 + sw

3 3 1 7 0 ORW

mean 9

#3 2 1 4 7

- PHM

3 2 4 9

- Midwixe

4 3 3 10 0 ORW

2 3 7 +

DUlvT rHlN 4 4 4 12 0 PHN

4 4 2 10 + PHN

mean 9.2

#4 3 4 3 10 +

. SW

4 3 4 11 + PHN

1 3 2 6 + ORW

3 3 3 9 SW

1X 3 3 1 + PHN

1 3 2 6 + SW

mean 8.2 ———————

#5 0 0 2 2

- ORW

2 2 2 6 0 ORW

3 2 2 7 rnlN

2 3 3 8

_ PHN

3 3 3 9 0 PHN mean 6.4 •

#6 2 3 3 8 + PHN

2 3 3 8 + Med. Bookk

2

7J

•z fio ORW

2 2 4 8 + PHN

i 3 1 3 7 + PHN

1 mean 7.8

\—

#7 1 2 2 . 5 + PHN

2 3 1 6 + PKN

i 2 0 3

+ SW

2 3 2 7 + PW

3 3 3 9 + PHN

84
Group r ntrn "i 1 1 VP A chi PVPinpnt Score

Atti tude Vocation

#1 #2 #3 total

f

# o

X 2 3 8 + SW

4 3 2 9

Ml ] f Ti 1" i nn i q 1" IN UA L 1 J_ L-X Wl iX 0 L

•7J 2 3

o8 nu PHN

1 2 0

•7 PHN

XJ 4 4 11 PHNA Ail A4 1 7 nu PHN

4 2 4 10 0 PHN

mean 8.7

? 7 2.34 2.33 7.55 + n 22 12 8

PHN = Public Health Nurse

SW = Social Welfare Worker

ORW = Outreach Worker

85
Description of the Emotional Reactions of players as they read the cards

Note: The cards provide the actual language of disgust and despair employed

by clients and the game puts players in frustrating situations.

1. The emotions ranged from nervous laughter to utterances made with

conviction. Most players choose a card with serious anticipation

after having read one or two.

Comments: An assessment of the data in the table above suggests

that only a very small relationship between mean total scores of groups and dispositions of groups could exist.

In rank order of scores:

Gr. . , Cog X

#2 9.3 + #3 9.2 0

#8 8.7 + #4 8.2 + #6 7.8 + #5 6.4

#7 6.0 + #1 4.8 +

one might conclude that some relationship exists between

cognitive achievement and disposition. The total data

pertaining to dispositions are

+ 0

- 22 12 8

PHN Performance

Disposition Number Mean Cog. Ach.

+ 15 8.8

0 6 10.3

26 9.14

Comments: It would appear that there is no relationship between

cognitive achievenent, on the first three questions, and

positive or negative dispositions towards playing the

game. With Public Health Nurses, neutral dispositions

tend to be linded with high scores by members of this profession .

86
SW Performance

Disposition Number Mean_ C og . Ach . +

0

82

11

16.5

6.0

8.0

13.81

Comments: A positive relationship appears to exist between disposition toward the game and cognitive achievement of Social

Welfare workers

.

'Others" Performance

Disposition Number Mean Cog . Ach . +

0

3

4

2_9

11,0

7.75

5.50

8.33

Comments: In this trial a relationship does seem to exist between

dispositions and cognitive achievement yet this is affected by the diverse backgrounds of the nine subjects. To

be neutral rather than positive or negative appears to be

destructive to learning.

Comparison of Players by Vocation

Social Workers responded in a more favorable manner to Obstacle Course

than other professionals. That is 73% of this group expressed positive dispositions about it while only one person was negative. This latter individual, who is employed as a social worker, does not have formal training in

this area.

In harmony with their longer academic records social workers had higher

mean cognitive scores than nurses and others. The lowest scores are associated

with the least educated segment.

It also seems relevant to note the high incidence of neutrality and

negativism among the heterogeneous "Other" category. Obstacle Course was not

well received by the midwives, outreach workers, and etc.

87
The nursing positioi_ displayed a mixed reaction to simulation with

15/26 positive, 6/26 neutral, and 5/26 negative.

General Comments of Observers

1 . The number of response cards should be doubled to maintain the

curiosity of players and enlarge the number of (disgusted) responses

to be read aloud.

2. An unrealistically small number of clients dropped out to Rocky Road.

3. A better system of recording client actions and game results by the

judge needs to be devised.

4. The observer's schedules need to be revised by omitting many of the

functional expectations which were overwhelming by complied with.

5. Clients should pay the $350 immediately upon having a child.

6. The child birth payment schedule should be revised.

Recommenaations for improvement of the game

I. The application of two accreditation type evaluation models to Qbs tacle

Course should be considered. The field test coordinator should interview

casually at least one very alert person to determine the extent that the

game is "Optimum" for players as well as "Useful" and "Appropriate".

A. Harlod Larrabbie's "Optimum Conditions for Observing"

1. Nature of Subject Matter

2. Access to Subject Matter

3. Observer's Sensory Equipment

4. Observer's Perceptual Equipment

B. Eiogene Mechon's "Criteria for Evaluating Simulations - Adopted"

1. Usefulness

a . Scope

b. Precision

c. Power

d. Reliability

2 . Appropriateness

a. Isomorphism

b. Compatability

c. Redictiveness

d. Purposefulness

II . Change in Media

A. The boards should be surfaced to prevent marking and arranged to fold

up.

B. Double the number of response cards and make a large number Rocky Road

antecedents

.

88
C. Prepare a Judge's Report Form to cue judges, tabulate client data

and record game results

.

D. Color code response cards which direct players to go to Rocky Road.

III. Change in Rules

A. A player should only pay $250 for each child and the "birth schedule"

should be changed to

5th roll - add one child

10th roll - add one child

15th roll - add one child

RecQmmendations for Second Field Test

1. Modify the game board and player instruction in accordance with remarks

above

,

2. Increase the number of verbal response cards.

3. Prepare a "Judge's Log" form that will possess three provisions to aid

in data collections:

a. A simple checkoff system to note the number of the die rolled by

each player at each turn.

b. Cues for the judge to remind him/her to enforce key rules.

c. Fill-in blanks to record date, place, time of play (start-stop)

.

4. Prepare a short "quiz" to be administered by the game monitor immediately

after the second play of the game. A tabulation (data recording) form

should be included to aid the Field Test Coordinator.

5. Conduct the second field test in at least 12 clinics representing a full

range of conditions existing in the Family Planning Delivery System in the

state

.

Analysis of Data

Summative

Upon completing the second field test, which will take 2-4 months, the

data should be placed in a format appropriate for automatic data processing.

Independent variables (age, vocation, etc.) will be ccmpared to dependent

variables (cognitive achievement, cognitive growth, interest satisfaction.

89
coping, disposition toward client behavior, etc.) by using both parametric

and nonparametric statistical analysis.

Fomative

Mediating variables (frequency of turns in getting to the clinic, on

the "Dropout Road," and in the clinic; and frequency of turns in "Rocky Life

and "Freedom Circle") will be compared with independent and dependent

variables through analysis of variance techniques.

90
SIMULATION: AN ANALYSIS OF STUDENT COGNITIVE RETENTION

AND STUDENT TEACHER AFFECTIVE PERCEPTIONS

I

! Charles H. Post ma

I Division of Secondary Education

' Ashland College, Ashland, Ohio 44805

Jay C. Thompson, Jr.

Area of Curriculum and Instruction

I Teachers College, Ball State University

I Muncie, Indiana 47506

INTRODUCTION

IiDuring the 1972-73 academic year, 295 students and six teachers

iparticipated in a projectl which attempted to measure the effect

!of simulation on students' cognitive retention and pupil-teacher

affective perceptions of the learning experience. The primary

ipurposes of the study were:

J 1. To determine, in a field testing environment consisting

jof twenty-five hours of treatment, what effect the use of sim-

'ulation in high school United States History classes had on

students' cognitive retention of facts, concepts, and principles.

2. To determine what effect simulation had on students' affective perceptions of the learning process in which they were

Involved.

I 3« To determine what effect simulation had on participating

'teachers' affective perceptions of simulations as pedagogical

itools for learning.

iiThe investigation utilized a mult ivariable technique to determine what effect simulation had on students' cognitive retention

and affective perceptions of the learning experience. A multivariable technique was also utilized to determine the participa-

:ting teachers' perceptions of simulation as a pedagogical tool.

DISCUSSION OF PREVIOUS RESEARCH

ttPrevious studies pertaining to simulation and its effect on the

jiaffective and cognitive processes were inconclusive ani contradictory.

Much of this research therefore is difficult to analyze. Many of

these studies confined themselves to laboratory settings rather than

field testing situations; therefore, the environments v;ere carefully

j'controlled by the researcher. Some researchers used self-designed

lisimulations or "pet games" to test their hypotheses concerning

itsimulation and learning. Other researchers used participants who

jiwere above average in academic achievement. In a few cases the experimental treatment period

This paper is a brief description of the research conducted.

Additional data and information is available from the authors.

91
was not sufficiently long enough to justify "conclusive** results

.

In other research the researchers taught both the control and

experimental classes rather than using classroom teachers. Also

a number of the research designs did not incorporate a delayed

interval post-test; those studies that did^ frequently allowed

too short a time between the post-test and delayed interval posttest. Nevertheless J in deference to these limitations several

interesting findings emerged from the research.

Baker (1968)2 and Anderson (1970) found that the simulation ' technique did enhance cognitive achievement and retention. Baker

using junior high school students, reported that students involved in simulation learning activities, when compared with students

taught through a traditional method, demonstrated a superior degr

of cognitive retention on a delayed interval post-test measure.

Anderson, using high school students, contended that students'

ability to answer factual questions was enhanced as effectively

by simulation activities as by traditional classroom teaching

activities

.

McKenney and Dill (I966), Garvey and Seller (I966), Wing (I966),

Heinkel (1970), and Went worth (1972) reported that simulation

activities did not enhance the students' ability to retain cognitive knov;ledge. McKenney and Dill concluded that simulation

experiences were not enough as students tended to play "conservative strategies" and this detracted from long terra learning.

Garvey and Seller maintained that the control group students scoi

ed higher on the post-experimental test than did the students in 1, the experimental group using simulation. Wing's study revealed

no significant difference in the amount of learning that had

occurred between the traditionally taught students and those that

were taught through the method of computerized simulation.

Heinkel reported no significant difference between the achievement scores of the experimental (simulation) group and the contrc

(lecture-discussion) group. Wentworth found that students'

ability to learn economics had been significantly retarded by 1 their participation in the game.

Research studies conducted by Boocock (1963)5 Cherryholmes (1963]

and Robinson, Anderson, Snyder, and Snyder (1966) found that

simulation participants demonstrated more interest in simulation

exercises than in traditional learning activities. These researchers concluded that participants did demonstrate a high degree : of interest and reacted very positively to simulations.

2See complete citation of previous research in References.

92
Hall and Shirts (I961), Anderson (I966), Cherryholmes (1966),

and Boocock (I966) concluded that students demonstrated a

significantly higher degree of motivation when taught by the

simulation method. Edwards (1971) and Harpstrite (1971) reported that the use of simulation increased the motivational

level of students who were enrolled in a normal school environment. Harpstrite also concluded that teachers who used simulation techniques perceived simulation as being an innovative

teaching method and an important pedagogical tool.

METHODOLOGY

The subjects who participated in the study were eleventh grade

students attending five high schools in Indiana. The subject

population at the inception of the study consisted of 295 students of which 160 vfere females and 135 were males. One hundred

forty-two students were enrolled in the control classes and 152

were enrolled in the experimental classes. The subjects in the

twelve classes (six control classes and six experimental classes)

had a mean I.Q. score of I06 and were grouped as general ability

students.

To obtain a socially diverse subject samplings three socially

different school populations were selected. Four classes consisted of students whose environment was categorized as ruralsmall town. These subjects lived primarily on farms in tovms

with a population of 10,000 or less. Four classes consisted of

subjects whose social environment was categorized as medium size

city population. The socio-economic background of these subjects

was lov7er class to middle class, and they lived in a city with a

population of 85,000. The remaining four classes consisted of

subjects who lived in a major metropolitan area within the state

of Indiana. These subjects came from a lower class to upper

middle class socio-economic background. They lived in a city

with a population of over 170,000.3

Six teachers, one female and five males, who were not skilled in

the use of simulations, volunteered to participate in the study.

The teachers were veteran teachers; each had three or more years

of teaching experience and five of the teachers had completed

the Master's Degree.

Twelve classes in the five high schools were chosen by the researchers to participate in the study. Six classes were randomly

assigned as control classes and six classes were randomly assigned as experimental classes.

3This aspect of the data has not been analyzed at the time of

this writing.

93
The study was structured around a five-week (25 classroom hours)

experimental treatment period. During this period of time, the \ experimental subjects were taught United States pomestic History , (I87O-I915) through the use of simulation games. The control

subjects were taught the identical period of United States Domes- , tic History through the use of a lecture-discussion teaching for- | mat. Both the control and experimental classes were assigned the! , normal textbook readings as a supplement to the teaching methodologies. 1 5 Each of the six teachers involved in the study taught a control | class and an experimental class. This procedure was utilized j by the researchers as a control for the teacher variable. Prior j to the beginning of the experimental treatment period, each tea- , , Cher received instruction in the use of the three simulations. '

j This in-service training consisted of working through the pro- c cedures for playing the games, the goals of each simulation ex- J ercise, and the utilization of debriefing sessions at the con- ^ elusion of each simulation. „ . ^ The teachers were instructed to assign the students in the experj imental and control groups the normal textbook readings. The '

^ lectures in the control classes were derived from readings and ; 1 the textbook material. The teachers spent part of the period 1 each day lecturing and the discussion evolved out of the lecture ^ and textbook material. This procedure was a normal pattern for : the control classes during the five weeks. The experimental : „ classes spent the entire period using the three simulations and

debriefing them. During the period of the delayed interval, eachj

teacher v/as instructed to return to their normal classroom pro- | ^ cedures and not to utilize the simulation technique.

For the purpose of testing the stated objectives of the study, j ; four null hypotheses were developed. The hypotheses were stated [ as follows : ^

1. At the conclusion of a five-week experimental period, there - will be no significant difference between the control group (lec- c ture-discussion format) and the experimental group (simulation

format) on a measure of cognitive achievement.

2. Following a delayed intervG.1 of ten weeks, at the conclusior

of the experimental period, there will be no significant differenc

betv:een experimental and control groups on a measure of cognitive g retention.

'

^Three commercially packed simulations were utilized in the experimental classes. The three simulations were: "The Game of

Farming, " High School Geography Project: Manufacturing and

Agriculture (Toronto : The Maciviillan Co., FJ69) ; ""Promotion,

American HiJotory Games (Cambridge: Abt Assoc., Inc., I97O):

and The Cities Game (Del Mar, California: Communications, Research, Machines Inc., I97O).

94
3- At the conclusion of a five-week experimental period^

there will be no tna.rked difference between experimental and

control groups on a measure of affective perception.

4. Following a delayed interval of ten weekSj at the conclusion of the experimental periods there will be no marked difference between experimental and control groups on a measure of

affective perception.

The testing procedure consisted of apre-test, post-test^ delayed

interval post-test sequence. The Cognitive Achievement Instrument5 and the Student Affective Perception Instrument were utilized for the three testing periods. The Cognitive Achievement

Instrument included thirty questions concerning industrialism,

agriculture politics, cities, social problems, and domestic reform. This instrument had a reliability factor of .7971- The

Student Affective Perception Instrument consisted of twenty-eight

response items. These questions were designed to measure the

experimental and control students' affective perceptions of the

two teaching methods. The rationale for the creation of this

instrument was identical to the rationale utilized in the creation of evaluation instruments by the Ball State University

Curriculum Evaluation Team. This evaluation model suggested that

"an evaluation must be based on a description of what pupils and

teachers and other professional personnel think is happening in

schools '.'^

The Teacher Perceptions of Students and Teacher Behaviors Instrument consisted of thirty-six response items. These questions

attempted to measure the teacher's perceptions of the student

and teacher behaviors in the experimental and control classes.

7

Fifteen percent of the total number of students in the experimental and control classes were personally interviewed by the researchers and their verbal responses recorded. The questions

5a11 instruments were developed by the authors and field tested

prior to their use in the research design. All instruments were

based on models used by the Area of Curriculum and Instruction^

Ball State University, in program evaluation.

^Richard C. Kunkel and James H. McElhinney, "A Rationale for the

Evaluation of Curriculum, " (Unpublished paper. Ball State University, 1970), 5.

7The rationale for the creation of this instrument was identical

to the rationale utilized in the creation of the Student Affective Perception Instrument.

95
utilized were parallel to those included in the Student Affective

Perception Instrument. The ten questions in this interview

allowed the randomly selected students to verbalize their perceptions of the classroom activities which occurred during the

treatment period.

Twelve administrative and guidance personnel were asked to observe

the control and experimental classroom activities. The observers

were not told vrhich groups of students were participating in the

experimental or control group activities. Each observer was requested to attend the class sessions in his building at least

twice during the treatment period and to record his observations

on the In-Classroom Observation Instrument continuum.

o

Analysis of the data was computed to determine the significance o: difference for Null Hypotheses One and Tv/o by means of the Univariate and Multivariate Analysis of Variance and Covariance Program Package. 9 This prepared program allowed the researchers to

obtain adjusted mean scores and F-ratios for the Post-test and

Delayed Interval Post-test variables of treatment and sex. 10

For the collected data regarding Hypotheses Three and Four_, frequencies and percentages were used in order to facilitate the

description of model responses, such that potential differences

betv/een the groups being compared might be readily identified and

localized. A difference spread between groups of ten percent or

more was judged to be a meaningful index of marked difference . '-^

i Because of the insignificant number of computations required on

the Teacher Perceptions of Student and Teacher Behaviors Instrument,, the researchers tabulated these responses manually. The

data collected on the In-Classroom Observation Instrument was

tabulated and all frequencies of responses reported. The verbal

responses collected on the Student Interview Instrument were . summarized and the most frequent responses reported.

8a minimum of twenty observations were necessary for this instru

raent

.

^Univariate and iMultivariate Analysis of V.>.riance and Covariance

Program Packag e (Buffalo: Computing Center, State University i of New York, I968). .

j l^The two covariates in this computation procedure were pre-test

scores and I.Q. scores.

^-^Each item on the Student Affective Perception Instrument was

dealt with individually. Hypotheses Three and Four were supported or rejected for each item at a difference spread of ten

percent or greater. Such a difference was considered to be a

marked difference sufficient to reject the hypotheses. j

96
COGNITIVE RESULTS

Null Hypotheses One was supported. On the basis of the treatment applied^ it was evident from the F-ratios that no significant difference bet^^;een the experimental and control groups

occurred at the .05 level on the post-test measure of cognitive

achievement for the variables of treatment and sex.

Table 1

ANALYSIS OP COVARIANGE TABLE SHOWING THE

RESULTS OBTAINED FOR HYPOTHESIS ONE

Source SS DF MS P P(.05)

Treatment 0.0661 1 0.0061 0.0005 0.9824

Sex 0.7219 1 0.7219 0.0583 0.8095

Error 2923.568 236 12.388

*Significant at .05 level •

Table 2

ANALYSIS OF COVARIANGE TABLE SHOWING THE

RESULTS OBTAINED FOR HYPOTHESIS TWO

Source SS DF MS F P(.05)

Treatment

Sex

Error

949.3708

11.4844

3542.360

1

1

236

949.3708

11.4844

15.010

63.2476

0.7651

0.0001*

0.3826

^Significant at the . 05 level

.

97
Null Hypothesis Two was rejected. The P-ratio of 63.2476 was

large enough to indicate a significant difference beyond the

.05 level. That is^ there was a significant difference betvreen

the experimental and control groups on the delayed interval

post-test measure of cognitive achievement. This significant

difference favored the experimental group. Hov;everj no significant difference at the .05 level occurred in the variable of

sex.

The data reported in Table 1 and 2 supported the following conclusions : 1. Students in United States History classes where a simulation teaching method is used perform as well on a post-test measure of cognitive achievement of facts,, concepts^ and principles

as do students in United States History classes where the traditional lecture-discussion teaching method is used.

2. Students in United States History classes where a simulation method is used perform significantly better on a delayed

interval post-test measure of retention of cognitive achievement

of factSj concepts^ and principles than do students in United

States History classes v;here the traditional lecture-discussion

method is used.

3. Students in United States History classes where either a

sim.ulation method or a traditional lecture-discussion method is

used do not perform differentially according to sex on posttest or delayed interval post-test measures of cognitive achievement of facts^ concepts^ and principles.

It is evident from the data^ that simulations do have potential

to facilitate student cognitive achievement and retention in

social studies classrooms. It is important to note that both

sexes benefited in the cognitive domain from the utilization of

simulation in the daily activities of the public school classroom.

AFFECTIVE PUPIL- TEA CHER RESULTS

It was evident from the data collected on the twenty-eight item

Student Affective Perception Instrument that Hypothesis Three

was rejected for sixteen response items. Each of these items

revealed a marked difference between the control and experimental

groups of ten percent or greater and the data for each of the

sixteen items favored the experimental group.

The data supported the follov/ing conclusions:

Students in United States History classes where a simulation

method is used report:

1. Markedly more a.ctive classroom particips tion than do students in United States History classes where the traditional lecture-discussion method is used.

98
2. No marked increase in their time spent preparing for daily

classroom activities.

3. Markedly more interest tov:ard the subject of history than

do students in United States History classes where the traditional

lecture-discussion teaching method is used.

k. No marked increase in their use of library materials.

5. Markedly more positive attitudes tov;ard the teaching method

being used than do students in United States History classes

where the traditional lecture-discussion teaching method is used.

6. More marked attitudes favoring learning useful knowledge

by vrorking together in peer groups than do students in United

States History classes where the traditional lecture-discussion

method is used.

7. No marked increase in their reading of outside materials

related to the topics studied in the class.

8. Markedly increased enjoyment of working with the classroom

materials; whereas, students in United States History classes

where the traditional lecture-discussion method is used do not.

9. Markedly increased positive opinions that they have acquired a variety of historical information upon v;hich to base their

judgments; whereas, students in United States History classes

where the traditional lecture-discussion method is used do not.

10. A more marked increase in the exchange of ideas and information with their peers than do the students in United States

History classes where the traditional lecture-discussion method

is used.

11. A more marked increase in their active participation in

their own learning process than do students in United States

History classes where the traditional lecture-discussion method

is used.

12. Females and males perceive differentially some aspects--

such as learning useful knov/ledge from peers, classroom participation, enjoyment of history, and interest--of the learning

experience.

It was apparent from the data collected on the Student Affective

Perception Instrument that Hypotheses Four was rejected for

twelve response items. Each of these items revealed a marked

difference between the control and experimental groups of ten

percent or greater and the data for each of the twelve items

favored the experimental group.

The data supported the following conclusions:

Students in United States History classes where a simulation

method is utilized report:

1. Markedly decreased active classroom participation upon

return to the traditional teaching method.

2. Markedly decreased interest toward the subject of history

upon return to the traditional classroom methods.

3. Markedly more negative attitudes toward traditional teaching methods being used upon return to such methods.

99
^. A marked decrease in attitudes favoring the traditional

teaching methods upon return to the experience of the traditional methods

.

5. Markedly decreased enjoyment of working with the classroom

materials upon return to the experiences of the traditional

methods

.

6. Markedly decreasing their exchange of ideas and information

with their peers upon return to the experiences of the traditional

methods

.

7. Markedly decreasing their active participation in their own

learning process upon return to the experiences of the traditional methods

.

Analysis of the data collected from the six teachers on the

Teacher Perceptions of Student and Teacher Behaviors Instrument

supported the following conclusions:

1. Teachers of United States History classes who use the

simulation teaching method perceive simulation as a valuable

pedagogical tool.

2. Teachers perceive more about the varied abilities of their

students

.

3. Teachers perceive the simulation method as one which allows

students a better opportunity for self-expression and divergent

thinking than does the more traditional method of lecture and

discussion.

It was evident from the data that the simulation teaching technique v;as a useful pedagogical tool for motivating content

interest^ classroom participation^ problem-solving^ and selfexpression. Simulation activities allowed students to internalize through realistic situations their learning experiences.

These realistic situations created environments in which students

did practice decision-making and problem-solving skills. The

simulation technique assisted in creating a more personalized

environment within the classroom; it v/as evident from the data

collected in this study that both sexes bendfitted in the affective domain from the utilization of classroom simulations.

SUMMARY AND CONCLUSIONS

The data collected for the present study,, regarding cognitive

achievement and retention, supported the findings of Baker and

Anderson. The present study v-j-as not supportive of the reported

studies of McKenney and Dill, Garvey and Seller, Wirig, Heinkel,

and Wentworth. It was apparent from the data that students

involved in simulation learning activities, when compared with

students taught through a traditional method demonstrated a superior degree of cognitive retention on a delayed interval posttest measure.

100
The findings of the present study concerning student motivation

and interest supported previous findings of Boocock, Cherryholraes,

Robinson^ Anderson,, Snyder and Snyder^ Hall and Shirts^ Edwards,

and Harpstrite. It was apparent from the findings of the present

study that students exposed to simulation activities were more

willing to participate in classroom activities and to increase

markedly their responses to teacher asked questions than were

traditionally taught students. The students exposed to simulation demonstrated a marked increase in positive attitudes towards

the teaching method being used in their classroom. The students

exposed to the simulation teaching method reported that learning

in peer group situations was important and that useful knowledge

could be learned from their peers. The findings also supported

the conclusion that students involved in simulation activities

increased their interest in classroom activities, increased

their enjoyment of classroom activities, and increased their

interest in subject matter and content. In addition, the researchers found that participating teachers perceived simulation

as being a valuable pedagogical tool and innovative teaching

method

.

REFERENCES

Anderson, Lee. Combining Simulation and Case Studies in the

Teaching of American Foreign Policy . Evanston: Northwestern

University, 19^^ • Boocock, Sarane S. and Schild, E. 0., ed. Simulation Games in

Learning . Beverly Hills: Sage Publications, Inc . , l^b'd . Boocock, Sarane S. "An Experimental Study of the Learning Effects

of Two Games with Simulated Environments.'' American Behavioral

Scientist, X (October, I966), 8-I7.

Cherryholmes, Cleo H. "Some Current Research on Effectiveness of

Educational Simulations: Implications for Alternative Strategies." American Behavioral Scientist , X (Oct, I966), ^-7.

Edwards, Keith. Students' Evaluations of a Business Simulation

Game as a Learning Experience . Report liO . 121 . Baltiiuore

Center for Social Organization of Schools, 1971.

Garvey, Dale M. and Seller, William H. A Study of Effectiveness

of Different Methods of Teaching International Relati ons to

~ High School Students^ Emporia: Kansas State T3achers College, 19bb

.

101
Harpstritej James J. "An Analysis of Selected Simulation Games

and the Assessment of the Subjective Feelings of Students

and Teacher's Who Use Simulation Games in Social Studies Instruction." Unpublished Doctoral Dissertation, Michigan

State University, Lansing, 1971.

Heinkel, Otto A. "Evaluation of Simulation as a Teaching Device."

The Journal of Experimental Education, X^(XVIII, 3 (Spring,

T970), 32-36.

Kunkel, Richard C, and iMcElhinney, James H. "A Rationale for

the Evaluation of Curriculum." Unpublished paper. Ball

State University, Muncie, 1970.

McKenney, James L. and Dill, William R. "influences on Learning

in Simulation Games." American Behavioral Scientist , X.

(November, I966), 5-9.

"Promotion", American History Games . Cambridge: Abt Associates

Inc., 197^"^

Robinson, James A., and Anderson, Lee F., Snyder, Margaret G.,

and Snyder, Richard C. "Teaching with Inter-Nation Simulation and Case Studies." The American Political Science

Review, LX (March, I966), 53-^5-

The Cities Game . Del Mar, California: Communications, Research,

Machines Inc., 1970.

"The Game of Farming." High School Geography Proje ct: Manufacturing and Agriculture^ Toronto : The MacMillan Co . , T969

.

Thorpe, Gerald! L. "A Brief Survey of Research in Learning Through

the Use of Simulation Games." The High School Journal , LIV

(April, 1971), l4-5k-k68.

Univariate and Multivariate Analysis of Variance and Covariance

Program Package . Buffalo : Computing Center, State University of New York, I968.

Wentworth, Donald R. and Lev:is, Darrell R. "A Review of Research

on Institutional Games and Simulation in Social Studies Education." Social Education, XXX/II (May, 1973 )j ^32-440.

Wing, Richard. "Two Computer-Based Economic Games for Sixth

Graders." American Behavioral Scientist , X (November, I966),

31-34.

102
SIMULATING AN URBAN SCHOOL AND COMMUNITY^

FOR USE IN TEACHER EDUCATION

Frank P. Diulus

Department of Foundational Studies

S.U.N.Y. College at Buffalo

Buffalo, New York 14226

The author has designed a role play simulation game of the

urban school and community in crisis, and this interactive

simulation, entitled The Three Rivers School Simulation Game,

has "been employed in several teacher education courses. In

this paper the design process and product will be briefly

described. This essay will especially focus on the results

of action research on two groups' playing of the simulation

game. Empirical research on the kinds and frequency of

learnings promoted by the playing of the simulation game

indicate that students experienced dynamic processes of a

typical urban school and community and they practiced behaviors in a safe context. Action research demonstrates

that students clarified attitudes toward self, others, the

teaching profession, and issues in school and society. There

is also evidence of significant skill development in interpersonal communication, negotiation, decision making, and

problem solving. The action research suggested several

critical areas for theoretical analyses.

In designing The Three Rivers School S imulation Game there

was a conscious effort to incorporate some aspects of most of

the critical structural elements, key characters, and pressing

issues in contemporary urban schools and communities. The

author is aware that the basic structure of the simulated

urban school emerged from his own school experiences as both

a student and a teacher. The author' s research on the

critical design elements focused upon the urban schools in

Pittsburgh, Pennsylvania, It is assumed that the critical

variables isolated in the simulation game design reflect some

key elements from all schools and especially from schools in

other urban centers throughout the United States. By involvement in four different urban education projects in Pittsburgh,

the author was able to broaden his perceptions of the present

situation. However many new sources were investigated to

insure as realistic a simulation as possible of the key

variables in the urban school and its social context. Sources

of input included: administrators, counselors, teachers, and

students from the Pittsburgh city schools, the textbook used

in the course Social Foundations of Education, the students'

compilation of key issues in education and society, and the

students' written descriptions of actual teachers and students

they had known. In order to add greater reality, accuracy,

and validity to the simulation, a detailed study was made of

one Pittsburgh school that seemed to illustrate most of the

characteristics of the present urban school crisis.

103
In The Three Rivers School Simulation Game there are fortyrole descriptions including several students, teachers,

administrators, and parents. Within the role descriptions

there are emphases on the issues of racial conflict, the

politics of change, curriculum reform, conflicting instructional strategies, and bussing. From both the simulation

game design and empirical results of several groups' playing

the simulation game there is evidence that The Three Rivers

School Simulation Game enables most players to confront and

make decisions about the following topics: power, authority,

curriculum planning, teaching methods, programmed instruction,

tests, grading, homework, tracking, evaluation of the school.

Black studies, sex education, vocational education, athletics,

discipline, dress codes, racial prejudice, safety in the

schools, bussing, drugs, faculty governance, teacher strikes,

and the hiring and dismissal of teachers.

There is significant empirical evidence that all of the

general behavioral objectives for The Three Rivers School

Simulation Game were well achieved. Players are given the

following list of instructional objectives in the game manual:

1. To comprehend the realities of teaching in a particular

school and community context.

2. To analyze the key problems of an urban school in crisis.

3. To synthesize one's personal feelings and understandings

about learning theories, school models, and social forces

of education.

4. To clarify one's attitudes toward self, others, and the

teaching profession.

5. To develop comprehension and empathy for one's role and

for the opposite point of view.

6. To develop an awareness of process.

7. To respond to the problems by choosing one's priorities

and seeking solutions together with others.

8. To develop communication and negotiation skills.

9. To evaluate the various behaviors with which one has

experimented.

Each player in Group One and Group Two compiled lists of what

he or she learned by playing The Three Rivers School Simulation Game. Comparing lists of the top ten most frequently

mentioned learnings by Group One and Group Two, both groups

included the following six learnings:

1. The simulation game dealt with real problems and responses

in typical school situations.

2. Change is a slow process.

3. Negotiation is an effective means of bringing about change

4. A variety of teaching methods are needed to motivate

students

.

5 . Curriculum planning should include consideration of individual student's interests and needs.

6. People's opinions are more emotionally charged than they

are supported by rational thinking.

104
Two of the most important instructional objectives for the

simulation game were clarification of one' s attitudes toward

! self and others and choosing one's value priorities. Playing The Three Rivers School Simulation Game and reflecting

upon one's experiences during each session gave the players

many opportunities to clarify their values. Such development,

choosing, and acting upon values constitutes the highest

levels of affective learning. There were numerous written and

oral expressions of value learnings. To illustrate further

the affective learnings during the instructional simulation

game, responses to one of the debriefing exercises were

analyzed according to Krathwohl, Eloom, and Masia' s taxonomy

of the affective domain. Group Two was asked at the end of

the fourth session: "How much are you really like the person

you are representing in your attitudes, prejudices, beliefs,

feelings, convictions, and the things you say and do?" One

quotation is cited for each level of valuing to illustrate

the effectiveness of playing this simulation game for affective

learning objectives:

3.1 Acceptance of a value

I am pro-Blacks and pro-civil rights and consider

myself non-prejudiced towards any race or creed. However, I am anti-militant and detest violence as a means

to any end. Violence can only breed hatred and more

violence and it will never result in any stable or meaningful change. Therefore I could not support any kind of

militant student power movement, be it black or white.

3.2 Preference for a value

I really do not differ from my role. I'm in favor

of Black Power —meaning the power to acquire quality education and an equal standing in society. Yes, I shall

become boisterous about the achievements of my people and

of my pride in being Black.

3.3 Commitment

The simulation game reinforced my dislike for rigid

and pre-programmed learning in schools. I am a firm

believer in the open classroom —it' s more life oriented,

more conducive to understanding and achieving educational

goals that are personally set. It allows the pupil to

establish some self-esteem and rapport with others.

4.1 Conceptualization of a value

In some ways I guess I am more like my role than I at

first thought. I would say that my two main interests in

life are definitely not clothes and boys, but I am liberal

in my attitudes toward sex and drugs.

4.2 Organization of a value system

I find nothing similar in my own personality to my

role. I do not live in a plush house, and I very rarely

hold to the conservative line on any issue. The woman I

play seems to be particularly closed minded; she is comfortable in her life style and she is uncomfortable with

change. The issues she holds to be important would be at

the bottom of my list of priorities. I feel that I am

1 nc;
fairly open to conflicting opinions and changes. I'd

rather have a group of individuals than conformists.

5 .1 Generalized set

I feel that my personal character differs from the

person I am playing, hut ideologically we are quite

similar. I personally tend to be less provocative and

more interested in discussion than argument. My role

dictates an attempt to argue and criticize —that' s not

me. My open mindedness also offers a problem in that

I can agree and at least sympathize with what is said;

however my role has me contradicting and arguing with

issues I can personally agree with.

5.2 Characterization

I am always searching, reaching out for what is right,

establishing an idea about myself and my future, and

wanting to help someone —to feel others lives and joys and

sorrows, to grow into a new person by realizing that there

are some things about the old me that I didn't like.

Realization leads to communication and communication is

where it's at

.

In another debriefing instrument students from Group One were

asked: "Are you motivated to play this simulation game? Why

or why not?" Out of thirty-one responses there was unanimous

affirmation of their motivation to get involved in the game,

and several reasons were given for their interests. Most of

the students saw this role play simulation game as an occasion

to experiment with various behaviors, self-expressions, and

relationships with different types of people. Some were

primarily motivated by the study of the social issues of the

urban crisis; others sought to explore the possibilities of

change. Two students were enthused about their self -chosen

roles because they were seriously considering switching their

majors toward these careers. Several students mentioned that

the simulation game was a new and enjoyable experience of

learning.

To expand on the evaluation of the learning effects of playing

The Three River s S chool Simulation Game , a pre -test and a posttest were administered to Group Two. It is assumed that

significant changes in students' responses from the pre-test

to the post-test indicate learning effects caused by the experience of playing the simulation game. The test instrument

is reproduced in Table One.

Table one

pre-test and post-test administered

to group two

SELF-STUDY ATTITUDE STUDY Yes No

1. Do you usually feel comfortable with those in

authority over you?

2. Are you in favor of bussing?

3. Are you now adequately prepared to teach?

106
TABLE OWE—Continued

Yes No

4. Are you confident of your ability as an

agent of change?

5. Do you understand the Black's discontent?

6. Bo you think that compromise is the best

solution to conflict?

7. Is it a hopeless struggle to change a strong,

centralized power situation?

8. Vi/ould you like to teach in an urban , school?

9. Are you a good decision-maker?

10. Are you prepared to handle a school crisis?

11. Do you think that school is a pleasant place

to work?

12. Do typical faculty care about the personal

needs of the student?

13. Do you see yourself as a good leader?

14. Do you favor open classroom?

15. Are radical actions the best way to change

a situation?

16. Do you approve of affirmative action for

Blacks?

17. Are schools democratic?

18. Do you think that meetings are a good way to

resolve problems?

19. Are discipline and order a pre-requisite for

good education?

20. Do you favor programmed instruction?

21. Do you approve of hall guards?

22. Are you sympathetic with Black militants'

demands?

23. Is change easy to bring about?

24. Do the schools adequately prepare students

who are not going to college?

25 . Do faculty care about each other? - . 26. Do you have some racial prejudice?

27. Is there considerable chaos in typical

urban schools?

28. Does change usually happen quickly?

29. Are you a good negotiator?

30. Does the faculty control most of the power

in a school?

31. Are most students apathetic?

32. Do faculty care about administrators?

33. Do students have much power without the

support of some faculty?

34. bhould every school have a Black Studies

program?

107
TABLE ONE—Continued

Yes No

35. -Ooes the administration control most of the

power in a school?

36. Is a teacher autonomous in his or her teaching?

37. Are school hoards effective?

38. Do administrators care about faculty?

39. should sex education he taught in a school?

40. Do you know most of your classmates in this

class?

41. Is your role very different from yourself?

42. Do you feel that you can get into the facts

and feelings of your role?

43. Do the roles represent typical characters in a

school and community?

Name Role

The identical test was administered for both the pre-test and

the post-test on the same day of the week and during the same

class period. The pre-test was administered prior to any

discussion of the simulation game, and the test was taken at

the beginning of the period in which warm-up session one was

played. Immediately at the end of the playing of the last

session of the simulation game and prior to any debriefing

discussion for the last session, the post-test was taken. Because of some absentees for one of the tests or incomplete

responses on some tests, there are total pre-test and posttests for only twenty-four students out of a potential of

thirty-eight students. However there is sufficient and proportionate representation of roles among the test respondents,

for 60 per cent of the Students, 55 per cent of the Teachers,

64 per cent of the Administrators, and 83 per cent of the

Parents took both the pre-test and post-test.

The following tables summarize the results of the pre-test and

post-test. Table Two indicates the changes in response on each

question, and Table Three represents a rank ordering of the

total changes on each question.

TABLE TWO

RESULTS OF THE PRE-TEST AND POST-TEST ADMINISTERED

TO GROUP TWO: SUMMARY OF CHANGES

IN RESPONSE ON EACH QUESTION

Question Yes No Posi- Nega- Total Male Female

On On tive tive Change Change Change

Both Both Change Change

Tests Tests

1. 14 5 3 2 5 2 3

2. 7 13 2 2 4 1 3

3. 6 11 5 2 7 1 6

108
TABLE TWC-Continued

Ciuestion Yes No Posi- Nega- Total Male Female

On On tive tive Change Change Change

Both Both Change Change

Tests Tests

4. 12 7 3 2 5 2 3

5

.

15 3 5 i 6 1 5

6. 14 4 5 1

-6' 3 3

7. 1 20 3 0 3 1 2

8. 17 3 1 3 4 1 3

9. 18 3 2 1 '3 2 1 10. 10 11 2 1 3 1 2

11

.

15 3 3 3 6 2 4

12. 1 18 5 0 5 4 1 13. 18 4 1 1 2 1 1

14. 21 2 0 1 . ,1 1 0

15 . 0 19 3 2 . • : 5

' 1 4

16. 2 21 0 1 1 0 1

17. 1 23 0 0 0 0 0

18. 12 4 6 2: 8 4 4

19. 5 14 3 2 . 5 1 4

20. 3 17 1 3 4 i 3

21

.

2 20 1 1 2' 1 1 22

.

12 10 2 0 2 0 2

23

.

0 24 0 0 0 0 0

24. 1 22 1 0 . 1 1 0

25 . 4 12 7 1 8 4 4

26. 19 4 0 1 1 1 0

27

.

20 1 2 1 3 3 0

28. 0 24 0 0 0 0 0

29. 21 1 1 1 2 1 1

30. 8 9 3 4 2

31

.

16 3 3 2 5 2 3

32

.

6 7 5 6 11 3 8

33. 0 22 0 2 2 1 1

34. 18 2 3 1 4 1 3

35. 20 1 3 0 3 2 1

36. 1 14 3 6 9 4 5

37. 3 12 8 1 9 1 8

38. 6 12 3 3 6 2 4

39. 24 0 0 0 0 0 0

40. 13 2 9 0 9 7 2

41. 16 4 3 1 4 2 2

42. 19 1 2 2 4 1 3

43. 22 0 2 0 2 1 1

109
TABLE THREE

REbULT:^ CP THE PRE-TEbT AKD POST-TEST ADMINISTERED

TO GROUP TWO: RANK ORDERING OF THE TOTAL

CHANGE^ ON EACH QUEiiT I ON —SUMMARY

FREQUENCY DISTRIBUTION

Number of Changes Question Numbers

11 32

9 36, 37, 40

8 18, 25

7 3, 30

6 5, 6,11, 38

5 1, 4,12,15,19, 31

4 2,8,20, 34,41, 42

3 7,9,10,27, 35

2 13, 21, 22, 29, 33, 43

1 14,16,24,26

0 17, 23, 28, 39

VK'ithin a range of 11 changes, the median is 4.25 and the mean i is 4.12 per question. This change in learnings on each

question by the tested population of 24 students represents

a mean of 17 per cent.

Further consideration of the total changes by item suggests

that The Three R ivers School k>imulation Game gave the students

from Group Two a new experience of the realities of teaching

in a school. The modal question, number 32, and a total of | 80 per cent of the upper quartile of questions in Table Three,

refer to topics about the teaching profession that a prospective teacher would grow to understand especially through

first-hand experiences. The high number of changes on items

in the post-test dealing with teaching, school, and education

indicate that the simulation game promoted achievement of its

instructional objectives: to comprehend the realities of

teaching in a particular school and community context; to

analyze the key problems of an urban school in crisis; to

synthesize one' s personal feelings and understanding aboiit . learning theories, school models, and social forces of education; and to clarify one' s attitude toward the teaching

profession

.

There is also significant evidence from the test results to

support achievement of the simulation game' s instructional

objectives dealing with communication and negotiation skills

and the processes of change. Seven changes on question 30

concerning the faculty's power in a school reveal the players'

grappling with the various problems of authority and conflict

in a school, and seven changes on question 4, which asked

about the player' s ability as a change agent, suggest that the i players had new experiences in issue resolvement. The changes

110
on items 5, 15, and 18 show that more students would choose

dialog, meetings, and compromises rather than radical actions

to change a situation; and these learning effects indicate

some positive achievement of the simulation' s instructional

objective to clarify one's priorities and to seek solutions

together with others. In regard to accomplishing the objective to develop empathy for the opposite point of view,

there were five positive changes on question five concerning

understanding of the Blacks' discontent.

Wine positive changes on question 40 concerning whether an

individual knows most of his classmates constitutes a 38 per

cent increase in interpersonal communication, knowledge, and

group cohesiveness . Many students indicated in their journals

that the simulation game was an enjoyable experience of discovery learning among their peers.

The action research has indicated several critical areas for

theoretical analyses. What are the effects of the experiential and behavioral qualities of this teaching method? What

are the sources of motivation and enthusiasm to play the role

play simulation? What are the unique teaching and learning

effects of role playing and negotiation? What are some of

the critical sources of growth in the affective domain by

playing the role play simulation game? Results of detailed

theoretical analyses by the author are hereby summarized.

Analysis of the uniqueness of role play simulation games

indicates that they are a discovery method of teaching

providing student-directed inquiry into and behavioral experiences of operational models of real world systems. This

method unites thought, feeling, and action in a learner'

s

transaction with an environment. Active involvement and

manipulation of simulated variables produces instant feedback, leading to reflection and the reconstruction of one'

s

experience.

Role play simulation games are intrinsically motivating because of several characteristics of this teaching method.

Active involvement and direct control over the elements of

an environment give rise to intrinsic reward and competence

awareness. Games are goal oriented, and players incidentally

learn content that is directly and logically related to the

achievement of the goals of a game. The competitive nature

, of role play simulation games heightens desire for success,

while cooperation emphasizes lively communication and peer

I learning. Motivation also derives from the unity of thou'ght,

feeling, and action in playing role play simulation games.

!| The method of role play simulation games can enable signifi-

' cant self-study of attitudes, growth in self concept, and

skill development in interpersonal communication. This

educational method draws special attention to the emotional

111
controls of behavior. Role playing promotes experiences

and internalizations of several social roles and role expectations, and players of simulation games can grow in

awareness of sfelf through communication with others.

Difficulties in role involvement and inter-role conflicts

tend to give rise to value clarification. A student can ' express his uniqueness through decision choices among

pressure groups and strategic options and also hy "becoming i a relational thou for others.

In conclusion it seems appropriate to offer suggestions for

future research in areas related to this work. In regard to

The T hre e Rivers School Simulation Game, more fundamental ! research is needed to validate further its effectiveness in

promoting a variety of different learnings. A long-term

longitudinal study with control groups could determine the

effectiveness of its use in several competency areas of

teacher education. More fundamental research is also needed

on the comparative effects of behavior-based and experiential

teaching methods versus expository teaching methods in

teacher education programs. The method of role play simulation games also offers a fertile field of inquiry for philosophy

of education. Further description and analyses of the processes

and essential elements of learning in simulation games can not

only enrich the educational theory of simulation games but also

may provide unique discoveries about the nature of education. I

112
DESIGN, DEVELOPMENT, AND VALIDATION OF ANTICIPATION GAMES

Melvyn I. Semmel and Sivasailam Thiagarajan

Center for Innovation in Teaching the Handicapped

Indiana Univerisity, Bloomington, Indiana 47401

Anticipation games require players to predict the behaviors of different

subgroups of the target population in different situations. The players* success in the game is directly related to the accuracy of his anticipations

in comparison to empirically established norms. At the Center for Innovation in Teaching the Handicapped, different versions of the anticipation

games have been produced to help teachers better understand handicapped

children in their classrooms. The design and development of these games

involve the three stages of analyzing people and situations, establishing

a normative data base, and selecting suitable game formats. A basic study

on the anticipation of the responses of different types of children by

college students indicates that sex, age, experience, and education are related to the accuracy of anticipation. Three studies on the learning and

transfer effects of playing anticipation games suggest that while teacherplayers improve on their accuracy of anticipations within the context of

the game, transfer of this skill to their own classrooms is not at a significant level.

ANTICIPATION AND UNDERSTANDING

The psychologist, the lawyer, the salesclerk, or any other professional has

to understand his clientele in order to efficiently fulfill his role.

Understanding, however, is a vague term and it may be partly operational

ized through the notion of anticipation. The degree to which a person is

able to anticipate accurately what is going to happen is a valid indicator

of his understanding of people and events. There is ample evidence in the

literature to indicate that individuals differ in the quality of their an- ticipations and that there is generally a positive correlation between the

accuracy of anticipation and efficiency of performance. Anticipatory skill

is of special importance to the teacher who has the duty of keeping his/her

learners inside the optimal area between frustrating challenge and boring

simplicity. The teacher of the handicapped needs to anticipate all the

more in order to protect his/her children from continuously experiencing

failure.

Kelly's (1955) development of a cognitive dissonance model of personality

and DeCharm's (1968) notion of the attribution process suggest how a

^This developmental activity was supported by grant #OEG 9-242178-4149-032

from the U. S. Office of Education, Bureau of Education for the Handicapped

to the Center for Innovation in Teaching the Handicapped. Contractors

undertaking such projects under Government sponsorship are encouraged to

express freely their professional judgment in the conduct of the project.

Points of view or opinions stated do not, therefore, necessarily represent

official Office of Education position or policy.

113
person's understanding constantly undergoes modification through anticipation and reality testing: On the basis of his past experiences a person

derives a set of hypotheses, generalizations, and principles which constitute his understanding. From this base he anticipates the moves of others.

If the ensuing event coincides with and confirms his/her anticipation, the

person's understanding is strengthened; if it contradicts the anticipation,

the basic hypotheses are suitably modified to expand his/her understanding.

UNDERSTANDING

EXPANSION

I

ANTICIPATION -< STRENGTHENING

i

ACTUAL EVENT

contradiction confirmation

Figure 1. Relationship between understanding and anticipation.

An example by Baum (1973) illustrates how this process operates in the case!

of a teacher's understanding of retarded children in his/her classroom.

This teacher spends the first day of school having the students tell about j their summer experiences. One student speaks with above-average verbal

fluency while another has major problems in communication. This experience

provides a base of understanding for the teacher. On the second day of

school, the teacher asks the students to write their names, addresses, and

parents' first names. The teacher anticipates that the child who demonstrated superior verbal abilities on the previous day will perform well

and the other child poorly on this assignment. In evaluating the written

assignments, the teacher notes that his anticipation about the verbally

adept student is wrong: His writing is below average, just as poor as the

other child's. Lack of confirmation of the anticipation results in the

teacher's better understanding of the relationship between oral and written!

expression.

To Improve Understanding

This model suggests that understanding is expanded and strengthened through

making repeated anticipations and comparing them with actual outcomes. Ob- i viously, experience is a good teacher and on-the-job teacher training has I appealing face validity. However, some limitations become apparent: The ' teacher being trained on the job may have to wait a long time before he/she ' is able to experience the desired variety of outcomes. He/she may be under

pressure to cope with the current reality and may not have the time to

114
anticipate. The time lag between anticipation and the actual outcome may

be so great that the effects of the feedback are minimal.

The traditional approach to providing the teacher with an understanding of

children is through introductory courses. In lectures and textbooks, the

teacher trainee is presented various facts about individual and group differences among learners. This approach has been notoriously inefficient

and, in most cases, textbook principles have very little relevance to the

realities of the classroom. Principles taught in these courses are of

questionable validity. Further, this approach deprives the teacher of any

opportunity for learning through anticipating.

An alternative approach to providing knowledge and understanding to teachers

in training is becoming popular. This involves the use of protocol materials (Smith, 1969) which are recordings (usually on audio- or videotape) of

classroom interactions to exemplify educationally relevant concepts and generalizations. Through a study of these transcripts and reproductions of

real-life behavior, the teacher trainee acquires a deeper understanding of

such behavior. However, the actual use of protocols by themselves has

turned out to be inefficient because the trainee becomes a passive receiver

of information. He/she is not required to anticipate actively and check

actual events. Because of the nature of the concepts they portray, most

protocols are considered extremely dull.

At the Center for Innovation in Teaching the Handicapped, we have developed

a series of inexpensive card-and-board games (Semmel , 1972) which improve

upon the advantages of using protocols and on-the-job training. Specific

details of one of the games, THINK STRAIGHT , are given in the appendix.

The games require the player to anticipate repeatedly the responses of different types of children to different task requirements. Players receive

immediate feedback based on empirical data. The winner for each round of

the game is the player whose anticipation is the closest to the actual outcomes. The greatest instructional strength of the game lies in the fact

that the success of the player is judged not by expert opinion, nor by particular generalizations about children, but by actual normative data. Thus,

feedback to the player is as realistic as the feedback to the classroom

teacher. By providing a large number of anticipation-feedback cycles in a limited period of time, the game adds systematic efficiency to the reality

of the classroom.

DESIGN AND DEVELOPMENT OF ANTICIPATION GAMES

As we indicated earlier, a number of different anticipation games have been

produced at the Center for Innovation in Teaching the Handicapped. In the

process, we have also evolved a generalized procedure for the design and

development of such games. This procedure involves three stages: analyzing

people and situations; collecting normative data on the behavior of different people in these situations; and, choosing a suitable game format to

incorporate these norms.

115
Analysis

Although the Center's major interest is in the training of teachers of the

handicapped, anticipation games are usable in any situation where the

training objective calls for an understanding of people and their behavior.

There are two particular instructional situations where these games are especially effective: One is where previous experience and prejudices interfere with objective understanding and the second is where blind faith

in glowing generalities is likely to result in disillusionment.

Anticipation involves a person and a situation. In this analysis phase,

the target group of people is identified and categorized into subgroups on the basis of such variables as sex, race, age, education, or any other

relevant variable. Similarly, the situations in which the behavior of

these people is to be anticipated are also carefully analyzed and categorized .

Collecting Normative Data

The heart of the anticipation game is a number of situations representative

of those in real life where the target population's behaviors are to be an- ticipated. In the sample game described in the appendix, we are interested

in a test-like situation. This requires the creation of a set of cards

with test items from different subject-matter areas and at different levels

of difficulty. Once a suitable set of situations is created (i.e., test

items), the next step is to collect normative data on the actual behavior

of different subgroups of the target population. This process is very simi-:

lar to the standardization of a test. It involves locating appropriate ! groups, choosing random samples, having the subjects respond in standard j situations, collecting data on their behavior, and reducing them to con-

| venient norms. Although time consuming and expensive, this process is the [ most important one in the development of the anticipation game since it

guarantees external validity. Some short-cut procedures may be used to

speed up the process or at least provide the first approximation of norms:

1. Using existing data . Tables found in research literature are too con- densed to be of use in the development of anticipation games. Flowever,

original investigators may be contacted for their raw data. Such data, obtained during the standardization of tests in various subject-matter areas or from surveys and interviews, may be used as the base for anticipation

games. This approach was used in the development of the game described in

the appendix.

2. Student-collected data . Students may take part in the process of collecting data with the usual result of increased learning from the game they

helped to develop. By requiring individuals or small groups of students

enrolled in the course to collect data on a standardized form from various

subsections of the target population, a large data pool is generated.

3. Data on individual subjects . In appropriate situations, the anticipation game may concentrate on individual subjects instead of representative

groups. Although these norms may be of limited generalizability , developing

116
a game around individual subjects may prove to be of didactic value in em- phasizing individual differences and the variability of individual behavior.

4. Artificial data . Suitable "data" may also be generated on the basis of

a theoretical model or a conceptual framework. In the development of cer- tain games we have programmed a computer to print out normative data within

given parameters and with random variability. Unless the model used as the

base has empirical validity, such data may oversimplify reality and mislead

the student.

Choosing a Game Format

Normative data may be incorporated in a wide variety of different board-andcard game formats. The two dimensions of people and situations suggest

matrix game formats. The classification of either people or situations

indicates rummy-type games. We have experimented with over two dozen varieties and found each suitable to achieve a slightly different purpose. A

good anticipation game should have all the features of any good game:

simple and fair rules; optimum amount of chance; continuous participation

by all players; and, fast pace. In addition, to be effective in training,

these games should require players to make repeated anticipations, provide

them with scores which are inversely related to the differences between

actual and estimated values.

EVALUATION

The effects of anticipation games have been evaluated in a number of different studies at the Center for Innovation in Teaching the Handicapped.

The results of four studies are summarized below:

Study I

'

Semmel, Garret, D. Semmel, fi Wilcove (1973) undertook this study to determine how accurately different groups of college students anticipate educable

mentally retarded (EMR) and non-retarded children's responses to a set of

questions. Although no game was involved in this study, its findings

about individual variations in anticipation are of interest to the designer

and the user of the game. The study was undertaken in two phases: The

first phase involved collecting a normative data base; the second, investigating anticipation moves of college students.

Phase I : = ^

Subjects. Sixty-five boys between the ages of 11 and 14 with IQs ranging

from 60 to 89 were used as the EMR group. Sixty-six children (50 boys,

16 girls) between the ages of 10 and 14 with IQs ranging from 90 to 116 were

used as the non-retarded group.

Materials . Twenty-four test questions, each on an individual card, were

used in this phase.

117
Procedure . The test was administered orally to each individual child using

a standardized procedure. The children were assured that this was not a regular classroom test. Between administrations, question cards were shuffled to prevent any serial order effects.

Free responses of the children were recorded and the most frequent were identified. In 16 out of 24 questions, the most frequent

given by both the non-retarded and EMR groups were identical. Difresponding was the greatest with questions which required imaginaassociation responses, intermediate with problem-solving questions

than one correct solution, and the least with problem-solving

with only one correct solution.

Subjects . Seventy- seven men and 213 women from courses in undergraduate

educational psychology, undergraduate psychology, undergraduate special education, and graduate special education at Indiana University were involved

in this study.

Materials . A questionnaire, consisting of the 24 questions that were used

to collect the normative data base, was prepared. The 10 most frequent

responses of children were listed below each question and the subjects were instructed to indicate which response would be most commonly given by each

group of children.

Results . responses

responses

ferential

tive freewith more

questions

Phase II

Procedure . The questionnaire was presented during a regular class session.

Demographic information was also collected from each subject.

Results . The range of correctly anticipated responses of EMR children was

0-15; the range for non-retarded children was 5-18. Six subject variablessex, age, academic major, semester hours in special education courses, ex- perience with EMR children, and the course in which the subject was cur- rently enrol led --were analyzed individually in a two-way fixed analysis of

variance design with repeated measures over the effects of the two samples

of children (EMR and non-retarded). The results of these analyses and

Scheffe's post -hoc comparisons are given in Table 1.

118
Table 1. Effects of Subject Variable on Anticipation

Subject Variable Main effect of variable Interaction

Sex Significant (p<.05).

Women had higfTer scores

(mean = 9.5, s.d.= 2.6)

than men (mean = 8.9,

s.d., = 2.9).

Significant interaction

between sex and type of

children (£<.05).

Women scored significantly

better than men in anticipating the responses of

EMR children.

Age

(18-19, 20-21,

22-23, and 24+)

Significant (g<.05).

24+ group scored significantly better than

22-23 group (p< .05)

.

Academic major

(Special education,

elementary education,

secondary education,

psychology and other)

Significant (£<.001).

Special education

majors predicted more

accurately than psychology and other

majors

.

Semester hours in

special education

(0, 1-3, 4-6, 7-9,

10-12, and 13+)

Significant (jr<.01).

Post-hoc analyses

showed no significant

differences although

the 13+ group had the

greatest mean score while both the 0 and

7-9 groups had the

lowest scores.

Experience with EMR

children

(None, little, moderate,

and extensive)

Significant (]t<.01).

Subjects with extensive experience anticipated children's

responses better than

those with none (jrc.Ol) or little (£< .05)

.

Significant interaction

between experience and

type of children (£<.05).

Subjects with extensive

experience anticipated

EMR responses better than

those with none (£<.05).

Current course enrollment (undergraduate

special education, un- dergraduate educational psychology, undergraduate psychology,

graduate special education)

Significant (£<.05).

Post-Iioc analyses

showed no significant

differences although

undergraduate and graduate special education

courses had the highest scores.

Significant interaction

between type of course

and type of children

(l^<.05).

119
study II

This pilot study was undertaken by Semmel and Sivasailam (1971) during the

formative evaluation of the anticipation game TRUE GRID (Semmel, 1972).

The object of the study was to investigate the effects of repeated playing

of the game.

Subject . A single, foreign born, 20-year-old, female subject was used in

this study. The subject did not have any previous knowledge of, or ex- perience in, the education of handicapped children.

Materials . TRUE GRID is a two-person anticipation game which uses a 4 x 3

grid. Moves in the game involve anticipating the percentage of three different types of children (normal, 66-80 IQ group, and 50-65 IQ group) at

three different age levels (9, 11, and 13) who responded to questions from

four different subject-matter areas (arithmetic, language, reading, and

work-study) . The scoring system of the game discourages players from con- centrating on a specific subject-matter area or a specific type of child.

More than 150 questions are used in the game to prevent any practice effect.

Normative data on these questions came from an earlier study (Meyen S

Hieronumus, 1970) which surveyed 1,405 children.

Procedure . The experimental subject played a total of 20 games, each with

a different opponent, over a period of three weeks. Anticipations during

each round of the game were recorded on response sheets which provided a cumulative record for later analysis. At the end of each game, the subject

was debriefed and asked to list any new rules of strategy she discovered

during the play of the game.

Results . Each anticipated percentage was compared to the actual percentage

from tlie norms and a deviation score was computed. These deviation scores became smaller as a function of the number of rounds of the game played,

indicating increased accuracy in anticipation. The results revealed that

the rate of learning to anticipate was most rapid for the highest (normal)

and the lowest (50-65 IQ) groups respectively. The rate of learning to

anticipate for the intermediate (66-80 10) group was the slowest. There

was also a positive relationship between the rate of learning and the age of

pupils for whom predictions were made.

Of the 84 strategy statements listed by the subject during the debriefing

sessions, 27 dealt with game moves (e.g., "Begin with a corner cell and work

toward the center."). Among the remaining were developmental generalizations

(e.g., "There is very little difference between 11- and 13-year-old normal

children in their responses to these language questions."), principles re-

^ lating to IQ levels and performance (e.g., "Retarded children are harder to

predict. They are less stable."), insights into subject-matter areas

(e.g., "Arithmetic problems which involve fractions are the toughest for

all children."), and test characteristics (e.g., "If a child does not know

the answer he is more likely to choose the first or last alternative than

^ any of the middle ones."). Many of these principles discovered by the sub- , ject are comparable to those found in introductory textbooks on methods of

teaching retarded children. ;

120
Study III

Having informally established that the player does learn to make more accu- rate predictions as a result of playing TRUE GRID, another pilot study

(Zimmerman, 1973) was undertaken to investigate if this skill transfers

to the anticipation of student behavior in the teacher-player's classroom.

Subjects . Nine intern teachers from the University of Louisville were

involved^ in this study. They were randomly assigned to experimental (n=5)

and control (n=4) groups.

Materials . The TRUE GRID game was again used in this study. In addition,

a 24-item test which contained questions similar to the ones used in the

game was also constructed. The questions were from the areas of vocabulary,

spelling, and arithmetic. The test was available in two different forms:

One was for direct administration to retarded children and the other, a questionnaire for teachers' predictions.

Procedure . Five interns played TRUE GRID while the other four played an unrelated game in separate classrooms for a period of two hours. The groups

were brought back together and given the 24-itera questionnaire which required

them to predict the percentages of children in their classrooms who would

correctly answer each question. Each subject took back with him copies of

the test which contained the same 24 questions and administered it to the

children in his classroom using a standardized procedure. Children's re- sponses were returned directly to the investigator for analysis.

Results . Three 2x3 (treatments x content areas) analyses of variance

were performed on actual student performance (A) , teacher predictions (B)

,

and accuracy of anticipation (A - B) . There were no significant differences

in actual student performances. Teacher predictions of arithmetic scores differed significantly (£ < .05) between control and experimental groups.

There was a significant difference in the accuracy of anticipation in only

one of the three subject-matter areas. The results indicate that while there

was a trend toward transfer of anticipation skills from the game to the behavior of children in the teacher's own classroom, this was not conclusive.

Study IV

The lack of more impressive transfer of anticipation skills to the classroom

in the previous study could have been partly due to the normative data base

of the game differing from that of local students. Baum (1973) created a normative data base from local students to study the learning and transfer

from a game incorporating that data. In the most comprehensive study of

anticipation games undertaken to date, he also attempted to cross validate

the findings from earlier pilot studies.

Phase I: Collecting a normative data base

Subjects . Two hundred and ninety students in special classes for the educable mentally retarded (EMR) in five junior high and three senior high

121
public schools in Cincinnati, Ohio were used as subjects. One hundred and

sixty six of the sample were male and 124, female. Their ages ranged between 13 and 19, their IQs , between 50 and 80.

Material s . A 70-item multiple-choice test based on the Persisting Life

Problem areas identified in the Cincinnati curriculum guide for the EMR

was developed by the investigator.

Procedur(e. The test was administered to students in classrooms in the I absence of their teachers. The students were told that none of their teacher

would see their answers and their performance would not affect their grades.

The investigator presented each question orally and repeated it if requested

by any student. Demographic data were obtained from school records.

Results . Students were sorted into four groups according to age levels

(younger--13-15; older--16-19) and IQ levels (lower--50-64; higher 65-80).

Test results were analyzed and a frequency distribution in percentages was obtained for responses by each of the four groups of students.

Phase II: Treatment and assessment of anticipation skills

Subjects . Thirty teachers (whose students had been involved in Phase I) were subjects in this phase. Eighteen teachers were male and twelve, female.

All had training and experience in teaching EMR children. The teachers were randomly assigned, within their schools, to either an experimental or a control condition.

Materials . The normative data collected in Phase I was incorporated into a two-person anticipation game called BATTLE CHIPS. This game required

players to predict percentages for each of the four alternatives for each

multiple-choice question. These predictions were recorded in specially

designed response sheets for later analysis.

Procedure . Teachers were given a questionnaire for obtaining demographic

data. The experimental subjects played BATTLE CHIPS while the control

subjects played a two-person commercial game called PERCEPTION. During the

first session subjects played games from 25 to 45 minutes, depending upon

the free time available. Question cards used in this session were removed

before the next one began. This session terminated when each player complete

30 rounds of the game.

Results . A deviation score for each anticipation given by the experimental

players was calculated by subtracting the predicted percentages from the

actual values. The types of analyses and the results are summarized in

Table 2.

122
Variables Analysis Result

Effect of playing BATTLE Serial analysis of vari- Accuracy increased

CHIPS on accuracy of ance (7 dyads x 3 sets significantly

anticipation of ten rounds of the game) (£ < .05) as a function of num- ber of rounds

played.

Relationship between Correl

teacher characteristics

(age, sex, type of class

taught, educational

level, teaching ex- perience, and impressions of the game)

^ and accuracy of anticipation

ional analyses No significant

relationships.

Relationship between Correlational analyses No significant

teacher characteristics relationships,

and overestimates in

anticipation

.

Relationship between Analysis of variance No significant

student character- effects,

istics (age and IQ

level) and accuracy ^

, of anticipation.

Table 2. Effects of playing BATTLE CHIPS

Phase III: Transfer of anticipation skills

Subjects . Same as those in the previous phase.

Materials . A 20-item criterion test was developed from the earlier 70-item

test on the basis of a factor analysis which identified the five factors of

(a) map reading and arithmetic, (b) practical-functional, (c) spelling,

(d) synonyms, and (e) number usage. Items which had rotated factor loadings over .40 and which represented several areas of the curriculum were included in this criterion test.

Procedure . The names of five high-IQ- level and five low-IQ-level children

were selected randomly from the total homeroom class lists of each teacher.

These names were randomly listed at the top of the criterion test. Each

tsacher was required to predict which multiple-choice alternative each of

these children would choose for each test item.

123
Results, Predictions were scored as correct if the teacher selected the same alternative the particular student had chosen earlier. A comparison

of accuracy of anticipation between experimental and control subjects was accomplished through a one-way analysis of variance which did not yield

any significant difference

and the results of some of

A number of other hypotheses

these are summarized in Table were also tested

3.

i

Variables Analysis Result

]

Relationship between

students ' IQ levels

and accuracy of

anticipation

2x2 Analysis of

variance

Significant

(v < Oil Performance of highIQ EMRs were

^ more accurately

anticipated.

Relationship between

factor analytic

component of questions and accuracy

of anticipation.

2x5 Analysis of

variance and planned

comparison

Significant

(£ < .05)

Relationship between

teachers' assessment

of the general ability

levels of children

and accuracy of

anticipation

Correlational analysis Significant

< .01) i positive correla- | tion.

[

i

]

Table 3. Transfer effects of playing BATTLE CHIPS

FUTURE ACTIVITIES

The findings of the Seramel et al (1973) study demonstrate that anticipation

is a complex phenomenon warranting further investigation. While we study

individual differences among anticipators, our game development activities

continue to expand. From the cognitive verbal responses of children in testlike situations, we are moving into affective reactions of different children (e.g., emotionally disturbed) to different classroom climates presented

through videotape segments. In the evaluation of anticipation games, we are currently expecting three types of validation: internal validation which

measures the extent to which players learn anticipation skills within the con- text of the game; transfer validation which measures the transfer of these

skills to relevant classroom behavior; and payoff validation which measures

the effects of these increased skills on the n.GiiViivj.^i» aiid ifcarniiig of he

handicapped child.

124
References

Baum, R. B. The efficacy of an anticipation game in increasing teachers'

understandings of educable mentally retarded children. Center for

Innovation in Teaching the Handicapped, Indiana University, 1973.

DeCharms, R. Personal causation : The internal affective determinants of

behavior . New York: Academic Press, 1968.

Kelly, G. A. The psychology of personal constructs . New York: Norton,

1955.

Meyen, E. L. , m llieronumus, A. N. The age placement of academic skills

in curriculum for the EMR. Exceptional Children, 1970, 36 (5) , 333-339.

Semmel , M. I. Anticipation games (consisting of three instructional games:

True Grid, Over Easy, and Twenty-five, with variations). Center for

Innovation in Teaching the Handicapped, Indiana University, Spring, 1972.

Semmel, M. I., Garrett, C. S., Semmel, D., 5 Wilcove, G. Anticipation of

cognitive behavior of mentally retarded and normal children. Technical

report. Center for Innovation in Teaching the Handicapped, Indiana

University, 1973.

Semmel, M. I., ^ Sivasailam, C. The effect of playing anticipation games

on increasing the anticipation skill: A pilot study. Center for

Innovation in Teaching the Handicapped, Indiana University, 1971.

Smith, B. 0. Teachers for the real world . Washington, D. C: The American

Association of Colleges for Teacher Education, 1969.

Zimmerman, W. Effects of the anticipation game on intern teachers' predictions of their retarded students' performance. Pilot study, Center

for Innovation in Teaching the Handicapped, Indiana University, May, 1973.

125
APPENDIX

THINK STRAIGHT

Equipment

1, Question cards. There are question cards of three different colors

representing the three subject-matter areas of reading, language, and

arithmetic. On one side of the card there is a multiple-choice question.

The other side contains a table of percentages of children (grouped by

age and IQ level) responding correctly to the question.

129

Arithmetic Skills: Concepts

jChoose the best answer. |

Jack has 12 marbles and gave 25%

of them to Ralph. How many

marbles did he give to Ralph?

1) 3

2) 6

3) 9

4) 10

129

Age 9 10 11 12 13 14

EMR Group

50-65 IQ Group

66-80 IQ Group

Normal Group

14 11 13 15 12 16

15 14 12 24 11 16

13 10 14 13 12 16

19 41 58 71 80 71

Figure 2. A sample question card for the THINK STRAIGHT game

2. Board. The playing board is a 3 x 3 grid in which the rows represent

normal, 50-65 IQ group, and 66-80 IQ group; the columns represent the

three subject-matter areas of reading, language, and arithmetic.

3. Poker chips of two different colors.

126
Players

This game may be played by two players or two teams of players. Each player

or team is identified by poker chips of the same color.

Object

The object of the game is to get three poker chips of the same color in a straight line (vertical, horizontal or diagonal) on the board just as in

tic-tac- toe. Only one chip may occupy any given square.

i

1. Both players agree beforehand as to a specific age to be used in the

game. One of the players asks for a question for a given type of children

I in a given curricular area (e.g., "I want a work-study question for a normal

I child."). The other player removes a random card from the deck containing

questions on the specified area.

2. The first player writes down a percentage prediction. The other

player may challenge this by writing down a different figure.

3. The card is turned over to get the actual percentage. Whichever player

has a percentage prediction closest to the actual percentage wins the round

and places a chip of his color on the appropriate cell. If the first player

was not challenged, he wins if his prediction is within 5 percentage points

of the actual value.

4. Play continues with the other player specifying the cell he wants to

' play for. A player wins if he is able to get three of his chips in a straight line.

127
USING SlfUJLATION TO IMPLEFtENT TABA'S COGNITIVE THEORY*

Richard A, Schusler, Ph.D.

Kansas University

Lawrence, Kansas 66044 -

The Teaching Condition Today

In the present day scheme of education, there is a need to implement

liigher cognitive skills of thinking with children. For the most part

teachers teach the content of the curriculum at a descriptive level.

It is easy for all of us to recall how day after day in the classroom

we read word after word, did problem after problem, spelled word after

word, memorized data after data and wrote answer after answer from the

book. Teaching of this type is narrow and restrictive. It does not

demand much m.ore than the right answer and makes interaction with the

data a risk taking decision. It is strange that today, in this world

of fantastic banks of information and stores of knowledge, there is

appearing little evidence of decreased emphasis upon recall and over- whelming mechanics in tlie classroom.

As one visits the elementary classrooms of today, one sees little change

in the level of teaching. There is plenty of change in techniques, both

from the standpoint of the teacher himself and the materials he uses. Classrooms are full of manufactured materials for rewarding pupils for

giving right ansvi^ers from recall. Tokens, reading machines, computer

assisters and tapes all are geared for this type learning. Prescription

teaching, individualized instruction (in many cases) and programmed indexed material all promote basically recall learning.

Education is currently in one of its pendvilum swings. The thrust is now writing behavioral objectives for most learning tasks in the classroom.

Through this mode of teaching a fact emerges. Teachers mainly think of

teaching at the recall level and they write their behavioral objectives

at the recall level. Recall so many facts, do so many tasks are evaluative measures used at this level of learning.

As long as the theory exists that the human mind is basically an empty

vessel only and knowledge is like liquid that you use to fill the vessel

with no commitment as to \\rhetlier it is useful or what function it performs,

then the students we turn out will be the same as now. Is this fair to

the child? Could he learn to think at a higher cognitive level? The

answer is no, it is not fair because the child can be taught to think in

more complex terms and at higher cognitive levels. Thinking is a mind

organizing process and it can be learned just as making a cake or solving

a mathematical formula can be.

*A paper delivered at the International Simulation and Gaming Association Conference, Washington, D.C., September, 1973.

128
Benjamin Bloom-^ has neatly categorized several stages of cognitive development into knowledge, comprehension, interpretation, extrapolation, application, analysis, synthesis and evaluation. These stages represent a hierarchical sequence of learning and clearly point out to the teacher

what is desirable as educational outcomes. Tliey also point to the fact

that these educational outcomes are not being accomplished. The graduates

of our school systems today are for the most part just what we have taught

them to be: descriptionists

.

As a crux of the condition of the society at large, there has to be a massive reconstitution in educational methodology in our schools today.

We simply have to make the connection in our minds that what we have done

in school is related to v;hat people are when they leave school. While

Bloom gives us the educational objectives, he does little with the se- quential processes.

The process is the thing of learning. Two interesting research findings

shed some light on this. Flanders, an exponent of interaction analysis,

has found that teachers talk over seventy percent of the time. This time

is mainly spent in imparting content. Much less time is spent in using

pupils statements, encouraging remarks and other rewards. Questioning is

done at the recall level most. Schusler has found, using drawings of

normative gestures, positions and stances of teachers and asking pupils to

ascribe statements to them, that teachers make more housekeeping, disciplinary and emotive remarks than any other kind. Other evidence exists

that teachers spend much time in organizing, maintaining and controlling

pupils

.

The Place of Simulation in the Educational Milieu

A promising possibility of breaking this restrictive environment of the

classroom is the introduction of simulations. Gordon states:

Among recent innovations, educational games offer great promise

of furthering this change. Not only are they fun, but they re- quire that all players share in making decisions throughout the

game. Unfortunately, educational games are not well understood.

They are not widely available, and experience with them is neces- sarily limited; as a result, a mystique surrounds the technique.

To complicate matters, the use of games implies a seeming irreverance toward education.

Educational games are neither esoteric nor frivolous. But they

differ enough from most other classroom activities to raise

questions about the role of the teacher, the time and space re- quired, how to evaluate what games teach students, the benefits

and drawbacks of using games .

2

1. Benjamin S. Bloom, Taxonomy of Educational Objectives: Handbook I - The Cognitive Domain . (New York, David McKay, 1956.)

2. Alice Kaplan Gordon, Games for Growth (Palo Alto, Calif.: Science

Research Associates, 1970), pp. 2-3.

129
Simulations, and the term is used here as the all encompassing term for

games and simulations, bring into union thought and action; reminiscent

of the "learn by doing" of the John Dewey era in education. The validity | of this change is found in its type. Simulation does not (or should not)

| represent change in what materials to manipulate, but rather in how to

think. Now when Bloom's Categories of cognitive skills are reviewed, it can be seen that simulations provide the "how" or the process of achieving

these skills. ,

Simulations provide information. Facts are inherent in the designing of the

play. A period in history, a technological invention, a great man's life, or a trip to the moon all represent types of information. Even more important, pupils learn the existence of two or more sets of facts. Many \ times, these sets are opposed and the player can choose one to play with J and therefore incorporate into self. There is presented to the player also ? a repertoire of actions of his fellow player as knowledge. These are the ' facts of the affective or feeling domain. They are skills of a different ' nature, taught indirectly for the most part and most viable in the scheme ^ of living.

Simulations provide comprehension opportunities. The player must understand the worth and the function of his game knowledge in order to be an effective player. Alternatives in understanding knowledge is provided

through verbal exchange and observation of others. Coupled with compre- f hension is application. Once he understands, he must apply his knowledge f to the situation represented by the simulation to be effective in his play. i

The player learns skills of analysis and synthesis. In order to apply / knowledge in playing, decisions have to be made as to what, when, how or ' why. Situations must be analyzed and synthesized to take on an idiosyncratic mode. IVhen many avenues of play are open to him, he may, by ^ rejecting all ways, devise or synthesize a new way for him. This is one of

the exciting features of simulations. The synthesis or spin offs make

playing games the close approximation of life for which they are intended. *

Finally, in the cognitive domain, simulation provides an arena for evaluation?

"How was the material used", "Does this represent real life to you?" "UTiat

would you have done differently?" These questions are but a few of those

that can be asked in an evaluation, discussion or de-briefing session.

Evaluations of this sort are not generally available to the teacher of the

pupil in the traditionally taught classroom. In summary then, simulations

carry within their format all the basics and processes for developing

higher cognitive skills of learning and interaction.

Remote Island and the Taba Scheme

for Learning Higher Cognitive Skills

Taba states

There are a number of assumptions about the nature of thinking

which have tended to retard educational progress in development

of thinking skills. One has been that individuals must accumulate

150
a great deal of factual knowledge before he can "thinic" about

important problems related to himself and liis world. (A cor- ollary to this has been the assumption that learning to think

is memorizing the thoughts of others.) Another lias been that

thinking skills are only learned through so-called intellectually demanding subjects such as the physical sciences, mathematics and foreign languages. Still another has been that abstract thought is a capacity that only some individuals, usually

the very bright or "gifted" possess. A fourth has been that is

is futile to attempt to manipulate the environment in order to

improve thinking significantly .3

This popular assumption of educationists was not embraced by Taba. Another

set of beliefs became the basis for a logical set of cognitive thinking

skills: cognitive skills were seen as dynamic interaction between individuals and the stimulation he receives. Learning is not a passive approach

to the data. Thinking skills can be learned but they cannot be "given" to

pupils by teachers. Thinking is not relegated to any one subject but to

processing data. Precise teaching strategics can be developed that allow

thinking to be learned. A thinking process is a specific thing and should

be taught as such.

Based upon these general assumptions, Taba has developed a cognitive scheme

composed of three levels. The first level involves discriminating, listing,

grouping and labeling. The child, as his first learning task, separates

parts from the wholes or units. He discriminates dogs from an animal whole

composed of cats, lions, tigers and so forth. I!e lists the dogs by counting

and calls them dogs. That is, he groups and labels them. This thinking

concept, learned as a first way of thinking is carried througli life as a basic approach to all nev; situation problems. A person will invariably

want to know what are the component parts of any new situation, how many of

them there are and what they are called.

At the second level the pupil learns to interpret the data. He processes

the data by exploring relationships, causal factors and linkages to past

experiences. An example would be the type of topogranhy demanded for

certain living conditions. \'Jhy do people live where they do? From those

explorations of the data, a person formulates generalizations. He can then

use the data to test the universality of the concept. Does the generalization apply to all kinds of situations or to just some and under certain

conditions

.

Finally, the tlurd level has to do v;ith the application of what one knows,

to predict from known phenomena, or to hypothesize on causes and effects,

to theorize. Synthesizing solutions for innovating use fits into this

highest level of cognitive processing. Testing out solutions gives the

pupil a better chance at concreting proper fit, changing for fit or re- cognizing misfit of concepts. In most classrooms this approacli to learning

is not available to the pupil population in the present day scheme of education.

3. Hilda Taba, The Taba Curricul um Development Project in Social Studies

(Menlo Park, Calif., Addison-Wesley Publishing Company, 1969) p. 13.

131
This author lias attenpted to blend a practical technique to this cognitive

scheme in the form of a simulation called Remote I sland . Remote Island

is a map skills, .^eoprapliical relations and ecolojry decision making game.

Basically, Remote Island is a small group game played by six people. It concerns a hypothetical island located in the south Pacific and is divided

into three stages of jilay. In sequence one, basic data is given in the * form of history of the island: The island was discovered about 1750 when

a frigate was shipwrecked there. Later the surviving men were rescued.

The island was lush and inhabitable, fully to support life. During World

War II, Japan used it as a submarine refueling base and claimed ownership.

In 1950 United States gained ownership in a trade from Japan. Our government sold it to interested parties for 1500 dollars per acre with a maximun purchase of five acres allowed any one person, no companies could

purchase land. By 1970 the population of the island was 700,000 with a yearly increase of 10,000.

A problem exists on the island. Because no major industry has been allowed

on the island, the people are forced to import manufactured goods. This

causes money to leave the island and the standard of living is becoming

unsatisfactorily low. The inhabitants of the island have decided with

permission of the United States to allow industry to come into their com- munities. There is known to be large deposits of iron and tin located on the island. With this basic information sequence one continues with

the presentation to each member of the playing group of a map card con- taining one geographical feature of the island. Each card is different

from all the others. As each member of the group describes the content of

his card to other members, they copy his card's content on their master

map card. In this way Taba's first level of cognitive learning is achieved.

Each person at the end of this phase has the same primary information,

knows how many geographical features the -island has and their names.

In the second phase the players are directed to consider the geographical

features in placing three large cities and as many small cities as they

see necessary on their maps. They are also asked to place highways. In

this manner Taba's second level of cognitive skills is realized. The pupil

has to establish relationships between geographical structure and placement

of man's habitats, to predict longevity of the cities, activities of the

people. Through group activity they are able to better approximate realistic conditions of placing cities and transportation. The dynamics of

interacting with the material and other persons increases the viability of

the data. Learning in this mode is readily internalized. The teacher does i not liave to show where placement must be. The child learns by doing it.

He learns from using his own past experience that cities don't start where

arid conditions exist when there are other alternatives for locating.

During phase three, information is given to the group that a large iron

mine and smelter owner is interested in mining the iron and locating a smelter on the island for processing and selling the iron, lie promises a handsome profit. The group of players now become representative members of

the community. They are assigned role of a housewife who is mildly interests

in the activity, a hippie who has left the middle western United States

because of the way polution is being managed, a retired biology professor

132
from a middle western university who is an expert on ecology, a fisherman

who fishes the surrounding seas of the island, the owner of the mine and

smelter in the States and a small town politician who lives near the iron

deposit who can provide labor for the mine and smelter. The group becomes

a decision making group; the decision concerning whether to let the iron

be mined and smelted has to be decided by total consensus in the group.

Financial rev^ards, polution problems, balance of ecology, standards of

living, cultural growth, population growth are but a few of the ideas fed

into these discussions. Innovative solutions abound.

Debriefing is easily managed after this simulation is played. After ex- perience relating has taken place, questions are asked probing Taba's

scheme. Such questions at the first level might include: How many lakes

does the island have, how many rivers, what is an arid section of land

usually called, how many of these were there on this island?

At the second level questions might be: why is the desert located on the

south side of the mountains, why did you place the cities where you did,

where would you live on this island if you wanted to raise sheep? VJhen

the teacher wants to call indirect attention to level three, he might ask:

what does all this mean, will this island look like it does now in 50 years,

why do you think that?

Remote I s 1 and , as a simulation experience lends itself well to the Taba

scheme of cognitive development. In addition to this there are some additional features of learning for the child that are worth mentioning.

Social interaction skills in group work are learned indirectly in practice.

Modes of presentation of ideas, courtesy factors, group roles are all part

of this group process that are not available to pupils in a face-to-back

seating arrangement. Playing the game removes the teacher from the position

of authority on facts and puts him into the role of managing groups and

answering questions. The game is an accurate representation of skills

that are needs in life situations. Reading a map is a frequently used

technique. In depth reading of maps is a skill that is called attention

to by playing Remote Island .

The content of the simulation assumes a lesser place than the structure

and function. The cognitive processes represented by this game should be

present in all games and simulations to some extent and in some completely.

Stimmary

Presented in this paper was a stance on the type of games and simulations

that should be injected into the educational milieu. Activities of the

sort that are highly structured tliroughout with stringent rules and predetermined outcomes do little more than further the dilemma present in our present day classrooms. Restrictive learning is a predictive result.

These results are little better than what the high science of technology

is causing at the present time. Games can represent a departure from the

noninnovative way of teaching so present today. The question: will games

and simulations adopt the form of educational processes today, becomes now

valid. The use of games in tlie classroom is increasing.

133
There are cognitive schemes for designing these activities. One such

scheme is the Taba scheme of cognitive skill acquisition. Remote Island

was presented as a mind expanding activity. Facts were learned, relations

were established and data was used in decision making. A wide variety of

alternatives were available to the players.

134
THE EFFECT OF INSTRUCTIONAL GAMING UPON ABSENTEEISM: THE FIRST STEP

Layman E. Allen and Dana B. Main

University

Ann Arbor,

of Michigan

Michigan 48104

The good life is one inspired by love and

guided by knowledge.

- Bertrand Russell

Background

Focus of Study and Previous Studies

For Russell, the essential features of the good life are affective

and cognitive. We submit that these dimensions are also at the core

of good learning, which is a central part of human life. This study

focuses on the affective dimension as it is influenced by a learning

environment organized around instructional gaming.

Other studies have indicated the influence of such a learning

environment upon the cognitive dimension. Experimental seventh grade

classes using EQUATIONS, the game which is also used in this study,

and using the same arrangements with respect to cooperative teams and

conduct of tournaments, displayed significantly greater achievement in

the learning of mathematics (Edwards et al., 1972). With a different

but similar game — WFF 'N PROOF: The Game of Modern Logic — and the same other arrangements, groups of junior high and high school students

have experienced increases averaging more than 20 points on the nonlanguage parts of standard I.Q. tests (Allen et al., 1966 and 1970).

Still another study reports significant differences on I.Q. scores for

students using WFF 'N PROOF (Jeffryes, 1969). On the other hand, no significant changes occurred in either the affective or cognitive

dimension when the EQUATIONS and TAC-TICKLE games were used for a shorter period without the tournament procedure, which is designed to

individualize the problems presented to each learner and to equalize

the reinforcements achieved among all members of the class, and without

the cooperative features of tVie learning environment which are introduced by the games (Henry, 19 73).

135
The experimental learning environment arranged for this study emphasizes

the affective dimension as a facilitator of cognitive achievement. So

the initial question to be answered is whether a learning environment

organized around games has a positive effect upon students' attitudes

toward learning. That is the fundamental question to thich this studyis addressed.

There is some evidence that a learning environment involving EQUATIONS

and the appropriate tournament and team arrangements does have positive

effects upon students' attitudes toward mathematics learning, as measured

by students' responses to an opinion questionnaire (Edwards et al., 1972)

A more pervasive measure of student attitudes was sought in the current

study — a measure that would reflect student behavior every day throughout the school term. The student absentee rates in experimental and

control classes have been selected as the measure of students' attitudes

toward the learning environments of those classes. In addition to being

a nore pervasive measure than most indicators of attitudes, it is also a pragmatic one. For any program that seeks to enhance the school's effect

upon what students learn must first (and necessarily) get the students to come to school.

The Learning Environment Organized around Games

The learning environment arranged for this study contains three major

elements, each of which is assumed to be critical with respect to the

affective and cognitive effects: a problem-generating type of game; a tournament arranged to award reinforcements frequently and equally among

the participants as well as to individualize the learning experience for

each participant; and the organization of classes into teams designed to

elicit cooperation.

The EQUATIONS game used in this study is a problem-generating game in

exactly the same sense that both checkers and chess are. In each game,

when a player makes a choice on his turn to play, he constructs a problem

for the other player(s). When the other player responds, he attempts to

cope with the problem that has been posed for him. The choice that he

makes, in doing so, in turn constructs a problem for the next player.

That process continues throughout the course of play — successive generation, resolution, and further generation of problems by players. A

player who is seeking to win will pose for the other players -the most

difficult problem that he can imagine in the circumstances. So the level

of difficulty of problem confronting a learner will depend upon the imagina^

tlon and knowledge of the other players in the game. The more a player

knows about the game, the more difficult the problems he can pose for

others. In EQUATIONS, mathematical ideas are incorporated in the rules

in such a way that the more a player knows about mathematics, the more

difficult will be the problems that he can pose for other players.

136
This linkage between what a player knows and the level of complexity

of problem that he can generate by his choices in playing has an important implication: it affords a means for individualizing the

learning experience for every single student in a heterogeneous classroom. By controlling who plays with whom, one can control the level

of complexity of problem that is delivered to each learner, even though

the class consists of students of widely differing abilities and knowledge. It can be assured that each learner is confronted with problems

that are of the appropriate level of complexity for him.

The second element of the learning environment under study — namely,

the tournament — controls the complexity of problem delivered. If the

players in each game are evenly matched in terms of their understanding

of the game, they will tend to generate problems of the appropriate

level of difficulty for each other. In striving to win, each will seek

to construct the most difficult problem that he can imagine in the

situation. When player A constructs the most difficult problem he can

for player B — and they are evenly matched — player B will need to

struggle and think in order to cope with the problem posed. But — and

this is the important part — the probability will be relatively high

that B will in fact be able to cope with a -problem that he subjectively

perceives as a "tough" one. When a player is involved with problems

that he thinks are difficult but that he successfully copes with most

of the time, he is likely to generate an image of himself as one who

can handle difficult problems in whatever subject the game is about —

an "I can do it!" attitude. By structuring the tournament in such a way that the players are, and continue to be, evenly matched — even

though the students may learn at different rates — the attention of

each player is focused at the outer edge of what he now understands.

That is the objective of the tournament arrangement: to keep the

players evenly matched so that the problems delivered to each will be

on the frontier of what he currently comprehends. To achieve this

objective, the performance of each student is audited at the end of

every session.

At the beginning of the tournament the class is ranked according to

mathematical ability — by the teacher's judgment, by results on a test,

by trial play-offs of the game, or by any other reasonable means. It

is not especially important that this ranking be accomplished with great

exactitude, because the tournament rules provide for subsequent adjustments. The rank list is then used to assign students to the table where

each should play. The first three students should be assigned to Table 1,

the next three to Table 2, and so on until all players are assigned. If

there is one extra student, the last two tables should have two players;

if there are two extra students, only the last table should have two.

At the first session of the tournament, every student should play at the

137

II
table to which he has been assigned. At subsequent sessions a student's

table assignment will be determined by his performance in the previous

session. For a given session, there will be a high scorer (H) and a low scorer (L) in the game at each table. For the next tournament

session the H at Table 1 will remain at that table, the H's at all

other tables will move to the next lower-numbered tables (the H at

Table 2 will move to Table 1, the H at Table 3 will move to Table 2,

etc.), the L's at all tables except the last one will move to the next

higher-numbered table, and the L at the last table will remain there.

An absentee player is automatically the L at the table where he would

have played. At each table that has three players there will also be

a player who scores in the middle (M) . The M at each table remi^ins

there for the next session. This tournament procedure for moving

players about results in a player's shifting to more difficult problems

when he has performed well and to less difficult problems when he has

not

This tournament structure and its implications for the affective and

cognitive experiences of the learners is probably the most significant

aspect of the learning environment of this study. The tournament rules

have the result that in the long run each student in the class turns

out to be H about one-third of the time, M one- third of the time, and

L one-third of the time. In terms of the game, what amounts to "winning

and "losing" with respect to other players is shared evenly among all.

Each turns out to "win" half the time with respect to others, and to

"lose" half the time. In this manner the competitive aspect of this

learning situation is carefully controlled, In terms of "wins" and

"losses" for purposes of the game, the slow student is not overlydeprived and the fast student is not overly-indulged. Each receives

his fair share of each. Reinforcements are evenly shared among all

students in the classroom, not unduly heaped upon only a few of the

brightest.

Furthermore — and this may be the most important affective result

of this arrangement — the situation in which each is experiencing such

"winning" and "losing" leads the players to "discover" the positive side

of "losing." To the extent that participants learn that many deprivational situations may be opportunities for growth, they may be learning

one of the most important lessons for improving their problem-solving

in general. The player who loses at Table 5 because he did not understand how to subtract negative numbers, but learns how to do <so in the

process, will have an opportunity to use his new-found knowledge at

Table 6 — and probably to good advantage. On the other hand, the

player who wins at Table 3 and moves to Table 2 — where he may be

walloped by the wizards there — will become aware of the price attached

to "winning." l-Jhen these experiences occur repeatedly, players gain a

138
sense that "winning" is not an uninixed blessing and that "losing" does

not fail to have its compensations. They learn to cope with and "live"

with both outcomes. That is probably a useful capability for other

situations outside the games.

The third element of the learning environment used in this study introduces further cooperation into the situation by organizing the players

into teams. In a major sense, the playing of any game is the essence

of cooperation: in order to participate and really play a game everyone

must voluntarily agree to abide by the rules that def ine the game. If

someone does not, then he is not playing that game. If one tries to move a knight three spaces diagonally in chess, he is not really playing

chess; he is doing something else. But it is a different mode of cooperation that is introduced by the teams in an EQUATIONS tournament. They

provide a mechanism for further encouraging the learning from peers.

Game-play facilitates learning from peers of approximately equal ability.

Team organization elicits learning from peers of diverse abilities.

Whereas the games are played among students of homogeneous abilities,

the teams are made up of heterogeneous groups. Each team should have as members one fast learner, one slov7 learner, and a sprinkling of players

in between. The scoring in the tournament is arranged so that a win by

a slow-learning member of a team who plays at the high-numbered tables

counts every bit as much for the team score as a win by the fastest

learner on the team. The fast learner on each team soon learns that if

he wants his team to do well in the tournament, he needs to teach some

of the other members of his team some of the things that he knows.

Anyone who has ever tried to set up a situation in which bright students

teach slower ones knows exactly where the situation usually breaks down — and that is in keeping the bright students interested. But teams

bring into the structure of the tournament a continuing motivation for

bright students to teach slower students the relevant subject matter.

The members of a team do not play against one another except when two

of them accidentally move to the same table. Their team activities are cooperative in nature: working problems together, explaining ideas to

each other, working through Instructional Math Play kits together, or talking generally about their strategies for playing the games. Hence

the mixed cooperative-competitive environment that prevails in an EQUATIONS tournament involves competition only when homogeneous groups

interact (and even then, under the most careful control) and emphasizes

cooperation when the interacting group is heterogeneous.

One final comment is appropriate about the learning environmeht organized

around EQUATIONS for purposes of this study. The experimental situation

was imbedded in the school curriculum with no disruption of anything else

139
that would otheTOise be occurring. There was no special selection of

the students for the classes, nor did any of them cease their participation in any other usual activity. If reasons arose for adjusting a student's schedule at the end of the fall term and transferring him

into or out of the experimental or control classes, that was done; no control was exercised to prevent such changes for purposes of the

experiment. In other words, the experiment was adapted to the demands

of the school' — not vice versa. In this respect, if the results of

this experimental program seem to warrant adoption of such a program

in other schools, it will be capable of being fitted easily into existing

school programs. The data collected in this study were obtained not in an antiseptic laboratory environment, but in the ordinary day-to-day

setting of Pelham Middle School in inner-city Detroit. VJe are deeply

indebted to three extraordinary educators there for their cooperation

and superb efforts in making this study possible: Lewis Jeffries,

Principal; Gloria Jackson, Chairman, Mathematics Department; and William

Beeman, Mathematics Teacher.

Method

Educational Environments

Two kinds of mathematics classes were studied. The experimental group

devoted two mathematics sessions a week to an EQUATIONS classroom tournament; they heard lectures and worked problems during the other three

sessions per week. The control group heard lectures and worked problems

individually during all five sessions of the week. The principal difference, then, between the two groups was their activities during two class

periods a week.

Absentee Rate

The absentee rate, computed for each student participating in the study,

is the ratio of the number of days absent to the total number of possible

school days. Students participated in the study for one or two terms.

Approximately eighty school days per term were used in the study.

Subjects

The study was conducted at Pelham Middle School, Detroit, during the

1972-73 academic year. Every student was enrolled in only one mathematics

class, participated in no other mathematics enrichment program, and was enrolled for the full term or terms considered. Students wejre not tracked

according to ability and had no advance knowledge of which sessions would

be games or which, nongames . One section was an eighth-grade mathematics

class; all other sections were seventh-grade mathematics classes. No

seventh-grade student had prior knowledge of EQUATIONS; the eighth grade

class had participated in the seventh-grade program the previous year.

140
C lasses

In the X sections, the same teacher taught two games classes and two

nongames classes during the first and during the second terms. In

the Y classes, the same teacher taught four seventh-grade and one eighth-grade games classes during the first term and four seventhgrade and one eighth-grade nongames classes during the second term.

Although it would have been desirable for the experiment to retain

all students for both terms, several losses and additions were necessary between the first and second tenns because of other scheduling

commitments

.

Results ; Tables 1-3 contain descriptive statistics of the different groups

studied. Table 1 presents the descriptive statistics on those students

who remained with the same teacher for two terms. Teacher X taught two

games and two nongames seventh-grade sections concurrently. Iin:iereas 44

students were enrolled in her games classes for both terms, only 14

students were enrolled in her nongames classes for both terms. Note

that the average absentee rates of the 44 games students were .084 the

first term and .078 the second term. The standard deviations for both

terms are close: .093 the first term and .091 the second. Contrast

these to the mean absentee rates of the 14 nongames students: .252 the

first term and .295 the second — more than three times as much absenteeism. The differences are graphically summarized in Figure 1. Each term

is divided into four quarters for which the absentee rates of games and

nongames classes are plotted. The standard deviations for the nongames

group are also close to each other: .189 for the first term and .191

the second.

Teacher Y taught four seventh-grade classes and one eighth-grade class

each term — all games classes the first term and all nongames classes

the second. A total of 57 seventh-grade students were enrolled with Y

for both terms; 23 eighth-grade students were enrolled both terms. In

teacher Y's first-term games classes the seventh-grade mean absentee

rate was .076, with a standard deviation of .106. During the second

term, when Y's classes were in nongames mode, the mean absentee rate

for these same students rose to .130 (nearly double), with an increase

in the standard deviation to .140. Eighth-graders in games classes

the first term had a mean absentee rate of .057; this rate rose to .131

(more than double) in the nongames second term. The standard deviation

increased slightly, to .088.

Table 2 describes data for all students enrolled during the first term

in the classes of the two teachers, including those students who

transferred out of those classes the second term. Teacher X had 57

students in games classes and 42 students in nongames classes. The

141
Absentee Rates of Students

in Games (G) and Nongames (N) Classes

of Teacher X in First Term and Second Term

Quarters Quarters

Second Term First Term

Figure 1

142
mean absentee rates are comparable to those in Table 1: the rate is

.096 for seventh-grade students in the first term; it is .2A6 for

seventh-grade nongames students in the first term, v/ith standard

deviations of .105 and .234 respectively. Teacher Y taught only games

sections in the first term., with an enrollment of 88 seventh-graders

and 31 eighth-graders. The mean absentee rate for the seventh-graders

was .111, with a standard deviation of .166; the rate for the eighthgraders was .086, with a standard deviation of .168.

Table 3 presents the mean absentee rates of students enrolled in the

second term with Teachers X and Y. Some students had been in games

classes, some in nongames classes, during the previous term, and not

necessarily with the same teacher. The first column of descriptive

statistics is for those students in games sections throughout the first

and second terms (GG) . The second column describes students in gam.es

classes the first term and nongames classes the second (GN) . The third

column describes students in nongames classes the first term and games

classes the second term (NG) . The fourth column describes students in

nongames classes throughout the two terms (NN) . As in Tables 1 and 2,

the data are described by teacher and grade; the numbers of students,

the mean absentee rates, and the standard deviations are given.

Three general hypotheses about absentee rates in games and nongames

classes as indicators of differences in student attitudes are of interest

and can be tested by the data available in Tables 1-3. The first hypothesis is concerned with testing v/hether the mean absentee rates of the

games classes are less than those of nongames classes taught by the same

teacher. This hypothesis can be tested only with the data from the

classes of Teacher X, who was the only teacher to teach both kinds of

classes concurrently. The second hypothesis is concerned with testing

whether the low absentee rates experienced in gamies classes in the first

term deteriorate significantly when these students are shifted to a nongames class in the second term. A combination of findings — that

games classes have lower absentee rates than nongames classes and that

these lower rates tend to disappear when students are subsequently switched

to nongames classes — would constitute strong evidence for attributing

the lower absentee rates to the learning situation organized around games.

The second hypothesis can best be tested with data from the classes of

Teacher Y, who had all games classes in the first term and all nongames

classes in the second term, with many of the samiC students in both. The

third hypothesis is concerned with testing whether students who have

experienced lower absentee rates through participation in games classes

in the first term and are enrolled in nongames classes in the second

term (denoted GN) have a lower absentee rate in the second term than

students in nongames classes who did not participate in games classes

the previous term (denoted NN) . In other words, does participation in

games in the first term have a carry-over effect which produces lower

absenteeism in the second term than there otherwise would be? Data

from the second-term classes of both teachers can be related to this

question, since each teacher had some GN and NN students whose absentee

rates can be compared. These hypotheses are summarized in Figure 2.

143
Summary of Hypotheses -

Teacher First Term Second Term

X G N

Y G N

X,Y GN— NN

Figure 2

144
The first hypothesis can be tested (a) by comparing the absentee rates

of students in games and nongames classes of Teacher X for both terms

(Table 4); (b) by comparing the absentee rates of all students in games

classes and nongames classes of Teacher X in the first term (Table 5)

;

and (c) by comparing the absentee rates of students; in games and nongames

classes of Teacher X in the second term who had been in the same kind of

class the term before but not necessarily with the same teacher (Table 6).

In all instances, the null hypothesis is that there is no difference in

the absentee rates of students in games and nongames classes. Table 4's

statistics describe the students enrolled with Teacher X throughout both

terms (from Table 1) . The F ratio indicates that the variances of the

two groups are quite different. A Student T statistic, which assumes

equal variance, is inappropriate. Therefore, the Behrens-Fisher t*

statistic, which adjusts for differences in the N and the variances, is

used. The results indicate that the null hypothesis can be rejected at

a significance level of < .005.

The probability that the mean absentee rate for games classes is less

than the mean absentee rate for nongames classes is .9968 for the first

term and .9995 for the second term. This is a Bayesian posterior probability statement ba^ed on a flat prior probability distribution. It

takes into account unequal variances and unequal N's and is based on the Behren-Fisher distribution. An equivalent statement for the first

term is P(Meanj,^ <_ Meang | Sample) = 1 - .9968 = .0032. As the probability

approaches 1.00 (or 0.00, depending on how it is stated), the observer

can be more certain that the data indicate that one mean is larger than

the other. As the probability approaches .500, the observer becomes less

certain that one mean is larger than the other. The Bayesian posterior

probability is presented as an alternative way to view the data. It does

not test the null hypothesis, as the t statistic is designed to do. It

simply says that given this sample and no prior knowledge, there is a certain probability that one mean is greater than the other.

Because the number of students enrolled both terms with Teacher X in

the nongames group is so small compared to the number of students in the

games group in Table 4, it was decided that each term should be analyzed

separately. Table 5 contains the analysis for the first term; Table 6,

for the second term. Note that the F ratio again indicates a big difference in the variances of the games and nongames groups. Since the

games group absentee rate is so close to zero, it is understandable that

its variance is considerably less than that for the nongames group. The

t* analysis which adjusts for unequal variance and N's is consistent with

the former; that is, the null hypothesis can be rejected at a level of

i significance of < .0005. for both terms. The probability that the mean

absentee rate for games classes is less than the mean absentee rate for

nongames classes is .9998 the first term and 1.0000 the second term.

145
Turning to the second general hypothesis, the question is: l-Jhen students

are switched to nongames classes following a term with games, does the

low absentee rate achieved in the first term deteriorate (increase) in

the second term? Tables 7 and 8 present data for students who enrolled

for two terms with Teacher Y, in games classes the first term and in nongames classes the second. Table 7 describes seventh-graders; Table 8,

eighth-graders. The matched t analysis indicates a highly significant

difference between absentee rates for the first-term games and the secondterm nongames classes.

The null hypothesis that the absentee rates of students in games classes

the first term are not less than their absentee rates in nongames classes

in the second term must be rejected for both seventh and eighth graders:

the significance level of the t for matched groups in both cases is .0000.

The mean absentee rate for seventh graders in nongames classes v/as nearly

double that in games classes (.076 to .130), and that for eighth graders was more than double (.057 to .131).

The third, and final, hypothesis deals with the possibility of some carry-over effect from participation in games in the first term to lessen

a'senteeism in the second term. Absentee rates were compared for two

groups of students enrolled in nongames classes in the second term: one group of students had been in games classes in the previous term (GN)

one group had been in nongames classes in the previous term (NN)

The data are summarized in Tables 9-11. The null hypothesis is that the

second-term absentee rate of GN students is not less than that of NN

students

Table 9 summarizes the data for the seventh-grade students of Teacher X.

The second-term mean absentee rate was .193 for GN students compared to

.270 for NN students, a .077 difference. Since the F ratio indicates a difference in the variances at a .0222 level of significance, the BehrensFisher t* value was computed (t* = 1.272). This is not significant at

the .05 level (t* Q5 = 1.764 and t* = .694 by the Cochrane-Cox approximation); however, it is significant at < .10. The evidence for rejecting

the null hypothesis is marginal; it can only be rejected at the .10 level

of significance. An alternative way of characterizing the evidence is by

a Bayesian posterior probability statement: P(MeanQ^ < Mean^^ | Sample)

= .8980.

The data for Teacher Y's seventh- and eighth-grade classes, summarized

in Tables 10 and 11, support this marginal finding with respect to the

carry-over effect. The difference in mean absentee rates for the seventhgraders was .033 (.127 to .160) and .086 for the eighth-graders (.131 to

.217). These, too, were significant only at the < .10 level.. The respective Bayesian posterior probability values were .8330 and .7835.

In summary, the results indicate the following:

(1) The probability is .999+, given these samples, that the absentee

rate for students in games classes is less than that for students in non- games classes. The null hypothesis that the absentee rate for students in

146
games classes is not less than that for nongames classes can safely be

rejected. In these samples the mean absentee rate in nongames classes

was more than three times that in games classes.

(2) There is a statistically significant rise in the absentee rates

of students switched from games classes in the first term to nongames

classes in the second term. The rates just about double. The null

hypothesis that there is no increase in absentee rates when students

transfer from games to nongames classes can safely be rejected.

(3) The evidence for carry-over effects, however, is tenuous.

Although students from nongames classes in the second term enrolled the

previous term in games classes are more likely (about . 8) to have a lower

absentee rate than other nongames students enrolled the previous term in

nongames classes, the data is marginal for rejecting the null hypothesis

that there are no carry-over effects to lessen absenteeism in the second

term. The null hypothesis can be rejected only at the significance level

between .05 and .10.

Discussion

That there are profound effects upon absenteeism in the Detroit innercity

school where this study was conducted when an EQUATIONS instructional

tournament is introduced into the regular mathematics curriculum is

beyond reasonable doubt. The evidence is clear that absences drop

markedly. Interpreted as an indicator of students' attitudes toward

school and what is being done there, such lower absenteeism is perhaps

j one of the strongest and most pervasive gauges possible of the affective

influence of a procedure. To the extent that such gaming techniques jolt

this affective dimension, they undoubtedly set the stage for influencing

the cognitive dimension. It is hard to improve the way Russell said it

i in discussing the good life:

I Although both love and knowledge are necessary, love is in a sense more fundamental, since it will lead intelligent people

to seek knowledge in order to find out how to benefit those

whom they love.

With the games, it is clear, there can be success in creating the love.

{ The next question is obvious: Does it lead to the seeking and achievement

of knowledge? In intelligent hands, it should. On this dimension, we need to find out more.

ii

i: 147
REFERENCES

Allen, L. E. , Allen, R. W. & Miller, J. C. Programed Gaines and the

Learning of Problem-Solving Skills: The ITFF 'N PROOF Example , THE JOURNAL OF EDUCATIONAL RESEARCH, Vol. 60, No. 1, September

1966.

Allen, L. E., Allen, R. W. , and Ross, J. The Virtues of Nonsimulatlon

Games , SIMULATION AND GAMES, Vol. I, No. 3, September 1970, 319-326

Edwards, K. J., and DeVries, D. L. LEAl^NING GAMES AND STUDENT TEAMS:

THEIR EFFECTS ON STUDENT ATTITUDES AND ACHIEVEMENT, Center for

Social Organization of Schools, Johns Hopkins University, Report

No. 147, December 1972.

Edwards, K. J., DeVries, D. L. , and Snyder, J. P. Gajnes and Teams ; A Winning Combination , Vol. 3, No. 2, SIMULATION & GAMES,

September 1972.

Henry, K. M. THE EFFECT OF GAMES ON COGNITIVE ABILITIES AND ON

ATTITUDES TOWARD MATHEMATICS, Ph.D. Dissertation, Oregon State

University, 1973.

Jeff ryes, J. Let's Play WFF 'N PROOF , THE MATHEMATICS TEACHER, Vol. 62,

No. 2, February 1969.

Russell, Bertrand. WHAT I BELIEVE, Allen & Unwin, London, 1925.

Reprinted in WHY I AM NOT A CHRISTIAN, Simon & Schuster,

New York, 1957.

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CO o o 00

00o

in CN

\0 vO

r-- o O iH o O

CM

00 o c

to

CU CO o c

CO

cu

149
Table 2

Absentee Rates for Students Enrolled

in Games and Nongames Classes of

Teacher X and Teacher Y for the First Term Only

Teacher Grade First Term

Games (G) Nongames (N)

No.

Mean

S.D.

X 7 57

.096

.105

42

.246

.234

No.

Mean

S.D.

Y 7 88

.111

.166

No.

Mean

S.D.

Y 8

31

.086

.168
Table 3

Second Term Absentee Rates for Students Enrolled in the

Games and Nongames Classes of Teacher X and Teacher Y in

the Second Term, Some of Whom Were Enrolled with Other

Teachers Or in Different Kinds of Classes in the First Term

Teacher Grade Term Kind of Class

First

Second

Games

Games

(GG)

Games

Nongames

(GN)

Nongames

Games

(NG)

Nongames

Nongames

(NN)

No.

Me an

S.D.

X 7 46

.082

.092

10

.193

. 128

9

.107

. Ill

36

.270

. 244

No.

Mean

S.D.

Y 7 55

.127

.1A2

25

.160

.136

No.

Mean

S.D.

Y 8

23

.131

.088

10

.217

. 327

151
t*-Analyses of Absentee Rates In Games and Nongames Classes (Tables 4-6)

Null Hypothesis H^: Tlie absentee rates in games classes are not less tha

the absentee rates in nongames classes.

Table 4

Absentee Rates of Seventh-Grade Students Enrolled

in the Games and Nongames Classes of Teacher X for Two Terms

—- —— — - — First Term Second Term

Games (G) Nongames (N) Games (GG) Nongames (NN)

No.

Mean

S.D.

44

.084

.093

14

.252

.189

44

.078

.091

14

.295

.191

F

t

t* obs

t*.005

t*.0005

Value Significance

Level Value Significance

Level

4.1522

not

appropriate

3.20

2.99

4.17

.0002

> ,0005

< .005

4.4084

not

appropriate

4,11

2.99

4.17

.0001

> .0005

< .005

P (Mean^OIean^ | Sainple)= .9968 P (Meang^<Mean^^ ] Sample)=,9995

152
Table 5

Absentee Rates of Seventh-Grade Students Enrolled

in Games and Nongaines Classes of Teacher X in the First Term

First Term Games (G) Nongames (N)

No.

Mean

S.D.

57

.096

.105

42

.246

.234

F

tt* obs

t* .0005

Value Significance

Level

4.9814

not appropriate

3.88

3.54

.0000

< .0005

P(Mean < Mean | Sample) = .9998

153
Table 6

Absentee Rates of Seventh-Grade Students Enrolled

in Games and Nongames Classes of Teacher X in the Second Term

Second Term Games (G) Nongames (N)

No.

Mean

S.D.

46

.082

.092

36

.270

.244

F

t

t* obs

t* .0005

Value

Significance

Level

7.0626

not appropriate

A. 39

3.54

.0000

< .0005

P(Meang < Mean^ | Sample) = 1.0000

154
M

a

tched t-Analysis of Absentee RaLes of S t_u dents who Switched fror. Ganor^

to Nongames Classes (Tables 7-8)

The absentee rates of students in the first term

when they were enrolled in games classes are not less

than the absentee rates of those same students in the

second term when they were enrolled in nongames classes.

Table 7

Absentee Rates of Seventh-Grade Students Enrolled

in the Games and Nongames Classes of Teacher Y for

the First and Second Terms

First Term Second Term

Games (G) Nongames (GN)

No. 57 57

Mean .076 .130

S.D. .106 .140

Mean difference .054

S.D. .076

t 5.3301

Significance level .0000

Null Hypothesis H :

155
Table 8

Absentee Rates of Eighth-Grade Students

Enrolled in the Games and Nonganies Classes

of Teacher Y for the First and Second Terms

First Term

Games (G)

Second Term

Nongames (GN)

No. 23 23

Mean .057 .131

S.D. .071 .088

Mean difference

S.D.

tSignificance level

.073

.066

5.3091

.0000

156
t- and t*-Analyses of Absentee Rales in Gaines-Nongames and Nonganies-Xongames Classes (Tables 9-11)

Null Hypothesis : The absentee rates ot nongames students in the

second term who v:ere enrolled in games classes

the first term are not less than the absentee

rates of other nongames students in the second

term who were enrolled in nongames classes in the

first term.

Table 9

Absentee Rates in the Second Term of Seventh Grade Students Enrolled in

(1) Nongames Classes of Teacher X the Second Term and

(2) Games or Nongames the First Term (Not Necessarily

with Teacher Y the First Term)

Absentee Rate in Second Term

First Term

Second Term

Games

Nongames

(GN)

Nongames

Nongames

(NN)

No.

Mean

S.D.

10

.193

.128

36

.270

.244

Value Significance Level

F

tt* obs

t* .05

t* .10

3.6584

not appropriate

1.34

1.76

.69

.0222

> .05

< .10

PCMean^^ < Mean^ | Sample) = .8980

157
Table 10

Absentee Rates in the Second Torm of Seventh Grade Students Enroll

(1) Nongames Classes of Teacher Y the Second Term and

(2) Games or Nongames the First Term (Not Necessarily

with Teacher Y the First Term)

Absentee Rate in Second Term

First Term Games Nongames

Second Term Nongames Nongames

(GN) (NN)

No. 55 25

Mean .127 .160

S.D. .142 .136

Value Significance Level

F 1.808 .4299

t .9742

> .05

< .10

P(Mean^^ < Mean^ | Sample) = .8330

158
SIMULATION/GAMING: AN AUTOTELIC INQUIRY TECHNIQUE

By Ron S tadsklev

Assistant, Institute of Higher Education

Research and Services

The University of Alabama

Huntsville, Alabama 35807

Today the term simulation/game is used to cover a multitude of

activities and materials. It is a catchy term that has become fairly popular

in the educational field. If you want to sell something, don't call it role

playing, don't call it an instructional game, don't call it an autotelic

inquiry technique; call it a simulation game. Teachers' ears pick up when

they hear that tem. It seems to me that a more inclusive term could be used

to refer to these activities and materials. I offer for consideration the

term "autotelic inquiry techniques." It is apparent today that the "inquiry

approach" is the popular way to structure learning. However, I would contend

that most of the inquiry taking place today is not "autotelic", meaning

inquiry in which the activities of the student are self -directed toward a purposeful end. The normal pattern is something like this: "Class, we will

meet in the library for the next two days," says the teacher. "We will break

into seven committees, and I want each committee to study one of the seven

continents on our globe and find out what the chief characteristics of each

continent are. Now go inquire. Reports will be due in two days." Instead

of telling the students what she thinks they should know, she has them dis- cover it for themselves —she lays inquiry on them. It may be a form of

inquiry, but is it autotelic? Does the activity the student is engaged in

interest him enough to want to do it? Does it relate directly to some felt

need?

Five Techniques

To my way of thinking, a simulation game is just one of a group of

eiiperimental learning techniques that tend to elicit a large degree of

autotelic inquiry. The model illustrated in Figure 1 depicts five such

techniques: learning games, role playing, instructional games, social simulations, and simulation games. It seeks to show a building relationship

from simple to conplex, with simulation games being the most sophisticated.

At the bottom of the model is an area labeled "Mental Garage", which is

intended to represent the human mind. Two thoughts are housed in this garage,

one about educational philosophy and one about learning theory. They constitute the basic assumptions underlying the rationale for using these

techniques. As far as educational philosophy goes, we work from the assunption that says that experimental learning is where the real pay-off is.

Students do not learn by being taught . They learn by experiencing the con- sequences of their actions; in other words, by having to cope with their

environment. If you don't buy these two assumptions, you probably won't

relate to the techniques identified above, because they are built on these

as s imp t ions.

159
AUTQTELIC INQUIRY TECHNIQUES

Figure 1

160
From Mental Garage we move out in two directions, one called

Simulation Avenue (where we manipulate people) and the other called

Game Avenue (where we manipulate things) . The first step up either

avenue brings us to relatively simple and unsophisticated techniques.

On Game Avenue we come immediately to learning games. These are defined as simple game exercises which, if effectively analyzed, can

lead the participant to some learning about himself and about interpersonal relationships. It has one ingredient, namely game element.

You are all well aware, I am sure, of the constantly expanding usage

of the word "game" and the growing list of definitions. For the

purposes of this model I will use Clark Abt's definition, which states

that a game is a contest (play) among adversaries (players) operating

under constraints (rules) for an objective (winning). Examples of

learning games would be the T- Puzzle Game , the Wood Blocks Game , the

Bridge - Building Game , and many of the exercises designed by human

relations people such as Pfeiffer and Jones in their four-volume publication

entitled A Handbook of Structured Experiences for Human Relations

Training .

Going up Simulation Avenue, we move into role-playing technique.

In this technique, participants take roles and act them out in a simple

scenario. Here again we have simply one ingredient, role-taking. Role

playing is the practice or experience of "being someone else," or perhaps

being oneself in a new situation. Again, the human relations world makes

extensive use of this technique. Examples of pre-packaged materials

would be You , Actionalisis , or Can of Squirms .

As we continue up Simulation Avenue, we gradually move into

something a little more sophisticated, which may be called a social

simulation. This involves the use of role -taking during the operation

of a comparatively complex environmental model of an actual or hypothetical

social process. It will give a selective representation of realty,

containing only such elements of reality as the designer deems relevant

to his purposes.

This technique adds another ingredient to role playing, namely

"environmental model." I use this term to designate a set of interrelated

factors or variables which together comprise elements that are symbolic

of a social system. The variables utilized are limited to those needed

to ensure that the model will possess a degree of likeness to reality

(isomorphism) . Often it is hard to discern where the scenario used to

set up the role for the participants becomes an environmental model- -hence

the jagged line used to divide the two techniques. Examples of social

simulation would be Portsville , 1787 and The Lovable Church.

As we move up Game Avenue, we will discover an instructional game

which also has two ingredients : game (which has already been defined)

,

and drill (which is simply the process of practicing and repracticing)

.

Instructional games present knowledge or information in a gaming process,

and one must gain some cognitive understanding of this information in

order to function well in the game. Examples of this technique would be

161
System I, Propaganda , and Queries 'n Theories . Again, the jagged line is

used to indicate the difficulty of discerning the exact point at which

a learning game becomes an instructional game.

The next step on either avenue brings us into Simulation Game Plaza.

This is where we put it all together. Social simulations are nothing

new in educational settings, as anyone that has ever conducted a mock

trial or election knows. Instructional gaming is old as the hills; even

Daniel Webster had spelling bees. If there is anything new in the

world (and I am not sure there is) , it is the attempt to merge social

simulation with an instructional game and receive the benefits of both

techniques in trying to reach the participants and turn them on. If

the simulated experience doesn't hook them, then the game experience might.

A simulation game, then, is a sophisticated technique involving the use

of role -taking during the operation of a comparatively complex environmental

model of an actual or hypothetical social process instilled into game form.

It represents reality selectively containing only those elements that the

designer deems relevant to his purpose. Examples of simulation games would

be Ghetto , Starpower , and The Game of FarmingIt seems to me that a simulation game is much more of a cHallenge to the designer than any of

the other techniques. This is because of the inherent difficulty involved

in trying to build in entertaining and playable game elements without

producing great distortion in the isomorphism of the environmental model.

Many hours of trial and error will be necessary in order to come up with

just the right mix.

Analytical Scales

If simulation games are frustrating to design, it is even more

frustrating for users to attempt to get a handle on what games are and

how they operate. For this reason, I have been trying to develop a set of analytical scales that might provide quick but meaningful information

for the potential user.

Figure 2 illustrates an effort to measure each of the four components

of a simulation game. The scale used to measure the game component has, i on one end, the term "autonomous competition," and on the other,

"interacting competition." Autonomous competition is that in which one ] participant's actions do not directly affect the others. Each demonstrates t his best performance without any interference from the other and then . . compares results. An exainple of an A3 game element would be golf. Chess, ! on the other hand, would be an example of an 13 on the game scale, because j every move that one participant makes affects the other participant's

move in a variety of ways.

The drill component is built into a simulation game in either an " overt or covert fashion. Ghetto might be an example of a C2 or C3,

since students are certainly going to be practicing and repracticing

arithmetical procedures but will probably not perceive it as drill, while

in a game like Campaign all players quickly discover the need to become

162
(SI z

163
proficient in the rules of parliamentary procedure in order to function

well. The chairman may even go as far as to take time to drill openly

the rules with his workers so they can be more effective in the

parties' deliberations. Hence, this game weighs out on the overt' end of

the scale.

I think the scale we can use to measure the role -taking component

is "prescribed" and "non -prescribed." Culture Contact would be an example

of a P3 simulation game. In this game players are told such things as j what colors they like, what attitudes they hold, and even how they move

their body when they sepak. Prescribed role playing can be very difficult

to work with unless you have a good setting, with people with the right

kind of personalities. Non-prescribed role-playing is illustrated best

in a game called They Shoot Marbles , Don't They? Here one is asked only

to try to acquire marbles. One is given roles such as policeman, government

official, landowner, etc., but is completely free to fill that role in

any manner one desires.

The environmental model component, which I feel is the heart of a simulation game, is measured on a scale running from "closed" to "open."

In a closed model game like Ghetto, someone designs a very tightly

organized structure comprised of just the components they want the

participants to experience. The participants then interact with this

model, and their actions are usually highly predictable. The more closed

the model, the more predictable their actions are. In an open model game

like Starpower , one does not create a model of reality and then have

participants interact with it. On the contrary, in open-model gaming the

participants create the model. The game presents a goal for the participants

to seek, then provides a few broad parameters to control their actions.

When the participants begin to interact in order to achieve their goals,

they create a model of reality. Open-model gaming is very unpredictable

and requires the game director to deal with many unforeseeable situations.

The scale at the top of the model applies to the simulation game in

its entirety. Most simulation games tend to lean either towards a strong

simulation element but not much game flavor, as in the case of games like

Campaign and Tracts, or be very gamely but have a weak simulation element,

as in the game Blacks and Whites . As stated in the first part of this paper,

achieving a good balance between these two elements is probably the essence

of success in designing a simulation game.

164
DESIGN TASK GROUP

Developing Computer Based Simulations

Facilitator's Statement

ROY I. MILLER

Environmental Simulation Laboratory

School of Natural Resources

University of Michigan

Ann Arbor, Michigan USA 48104

Unless an overly narrow definition of computer-based simulation

is adopted by this sub-group (for example, one limiting consideration

to the large urban models) , all of the other topics discussed in

all other design' sub-groups are relevant to this one. After all,

the process of designing a computer-based simulation has all of the

problems associated with the design of any simulation -- plus one,

the ornery (and expensive) machine. As a self-protective measure,

this author opts not to impose such a narrowly construed definition

on a group so likely to be heterogenous as this one. Therefore, I will put forth a broad definition of computer-based simulation and

I will narrow the scope of the discussion by concentrating on those

issues that are particularly challenging for designers of computerbased simulations.

Three terms are too often used interchangeably to describe

"things'" generally included in the discussion of simulation: pure

simulation, game, and gaming-simulation. "Pure simulation" is an

attempt to reproduce a real world process (social, political,

economic, physical, etc.) in an abstract form without any direct

human participation in the reproduction. For convenience, we limit

the term "game" to encompass activities carried out by groups of

people according to some pre-set rules. Usually, though not

necessarily, the term implies that the results of the "game" do

not have real world implications beyond the learning experience

generated in the game environment. 'Gaming-simulation" is a combination (or in set-theoretic terms, the intersection) of the

two -- a reproduction of a real world process in an abstract form

in which human participation governed by a set of rules is an

integral part. Those simulations using the computer for accounting

purposes, for data retrieval, for decision making and/or to

recreate system behavior through pure simulation are computerbased.

As a starting point for discussion of issues associated with

developing computer-based simulations, it is useful to identify

three broad problem areas. The first is the design decision to

resort to a computer-based simulation. The second is the technical

decision concerning hardware and software. Finally, several

theoretical questions must be resolved separately for each computerbased simulation.

For many years, elaborate statements of the advantages of

the computer have been contrived to justify its use in simulation.

These include such arguments as: the machine allows you to view

systems dynamically, it lets you deal better with complexity,

it allows for reproducibility of experiments, it makes possible

165
sophisticated data manipualtion and analysis, etc. Although cases can be cited where the computer has made possible the realization

of these claims, too many cases are on record where it clearly has

not. To avoid further misuse of the computer, the decision to

develop a computer-based simulation must be made with some care. This sub-group might seek to identify some criteria for making

such a decision.

Once into the development of a computer-based simulation,

the designer is immediately faced with several technical problems.

He must select hardware and decide which computer language is

best suited for software development. These choices must be made

with such thoughts in mind as dissemination, future technological

changes in che computer field, and costs. He must also assemble

a team of computer specialists as well as experts in the subject

matter of the simulation. The value of many computer based

projects (including computer-based simulation work) has been

sorely limited due to poor choices on these matters. Lack of

transferability and dependence on one or two key programmers have

minimized iihe impact of many computer dependent projects. Again,

this sub-group might seek some criteria for dealing with these -

' technical issues.

Finally, and most interestingly, several theoretical questions

must be resolved by the designer of a computer-based simulation.

Each of these questions is relevant to non-computer simulations;

however, the power of the computer creates more options for the

designer of computer-based simulations and, therefore, ekch must

be considered with extraordinary care. These include such questions

as

What is the relationship between data gathering and theory

building (how do you allocate resources between the two and which

comes first)?

What is the appropriate level of abstraction for the simulation?

What is the appropriate level of aggregation of key variables in

the simulation?

How do you deal with the non-quantifiable?

How much human participation do you build in and, if you use any, how do you build the man-machine interface?

How do you narrow the topic to something workable, yet usable?

How do you validate the results of the model?

This sub-group might first expand this list of pertinent questions

and, then, attempt to get a feeling for how to answer them.

166
DESIGNING COMPUTER-BASED SIMULATIONS

FACILITATOR'S STATEMENT

MARSHALL H. WHITHED

Dept. of Political Science

Temple University

Philadelphia, Pa. 19122, U.S.A.

There are a variety of concerns to be faced, I think, in the design of

conputer based simulation-games. Some of these questions are briefly outlined in the paragraphs below, with no intention of their being ordered

into hierarchies or priorities.

1. Is computerization necessary? Really? It adds an appearance of

elegance and mysticism- -but also adds burdens of complexity of use (particularly in logistics, particularly for the smaller and less

well-equipped school), difficulties of understanding the hidden

models (see below) , etc. The canputer has uses, and sometimes

absolutely necessary ones --but scmetimes people are designing simulation-games with computer support because the product seems to

be more sophisticated.

2. Document at i on , Especially, of the models and submodels, both intended by the designer and perhaps also some unarticulated by the

designer and representing hidden biases, contained in the computer

programming. Without documentation, unless the reader/user can read the computer programming language, he is unable to ascertain

what intended and unintended models and biases may be involved.

2a. Given that adequate documentation is a good thing, how do we get it?

Bearing in mind that most of us work in less than ideal conditions

with reference to staff, financial support, our own time, facilities, etc. (And preparation of documentation doesn't help most of us at all in tenns of getting hired, promoted, tenure, etc. --one of

the only projects I know of which encourages and provides some payoff for documentation labors is Project Compute at Dartmouth-

v.'here people receive financial support to spend the summer at

Dartmouth preparing user's manuals and documentation)

.

3. Interfact between ccmputer programmer and simul-gajne designer.

Given that most of us are not expert computer programmers, this means we will have to work with a computer programmer professional.

How to coTimunicate adequately with him. Indeed, how to find him,

first of all (remember inadequate budgets, etc.) . And how to make

sure that he doesn't start adding his own substantive ideas to the

programming code (it has happened to me, and, I suspect, to others)

.

4' Interface between the computer facility (program, input-output

device whether printer, CRT, remote terminal, etc.) and the simulation-gaming participant. Our primary purpose is not to teach our students conputerize, but some substantive point or points

embodied in the substance of the simulation-game. So we want to

make the problem of interaction with the ccmputer as sinple

167
Facilitator Statement/Computer-based Sinulations/M. VvTiithed/ page 2

as possible, presumably???? Use of conversational mode time share

techniques versus batch mode interaction with the computer. Other

means --score sheets, porta-punch cards, etc- advantages, disadvantages.

5. Complexi ty and non- learning . Having a computer at hand sometimes may

invite the simulation-game designer to exercise a perchant for greater

complexity in model design. But after a certain point--may it some- times be that the resultant -game becones so complex that to the player

whom we are trying to educate, the simulation -game becomes just as much a hidden black box regarding the substantive materials involved

as the real -world subject --and if so, are we really furthering his

educational process.

6. Questions of who_ shall have access to computer-based simulationgaming. Assuming that perhaps seme of our efforts might be truly

useful- -the reliance on a conputer to operate does have the effect

that some social groips in our society, who could perhaps afford to

buy a book to find out about manual models and simulation-games, will

be excluded by virture of their inability to access the computer.

7. Fuller utilization of the computer's power of rapid feedback to meet

educational criteria of quickly reporting back to student learners on their work (a criterion we so seldcm meet in the academic world????).

8. The social re sp ons ib i 1 i ty question. Raised at the London 1973

Advanced Study Institute on Urban Simulation and Analysis, but not

answered. Ranging from who shall have access and political power

distribution to questions of professional certification (should we

have or not?), to possible misuse of our work by which agencies and

should one refuse to work on certain contracts

9. The role of the university and/or versus the private consulting firm

in this work, access, public documentation, and questions of public

policy

10. Designing conduits for distribution to other users of simulationgames. Project CONDUIT of NSF? The Clark Rogers/Declan Kennedy

computer-based information retrival concept. Some kind of international university -based clearinghouse/ center (Whithed and Sarly)

An archives open to scholars and govt, officials, is now being

established at Polytechnic of Central London. The Peter House/EPA/

regional university dessimination of RIVER BASIN. What else????

ERIC???? Financial support for it?????

Prepared for the 12th Annual Meeting

of the National Gaming Council and

the 4th Annual Symposium of the

International Simulation and Gaming

Association Sept. 17-19, 1973

168
FRAME GAMES : DESIGN AND REDESIGN

R.H.R. ARMSTRONG and Margaret HOBSON

Decision Simulation Unit

Institute of Local Government Studies

University of Bimingham

Birmingham, England

(Note: these notes are intended only as a possible starting point for

discussion)

.

1. The basic framework for any game or gaming -simulation exercise consists

of:

(a) Roles

(b) Scenario

(c) Accounting system

(d) Rules and procedures

2. Games can be categorized (on one dimension) according to the emphasis

accorded to each of these elements and (on another dimension) by the

extent to which the representation 1 (a) and (b) accord with "reality".

3. If it is accepted that games can be viewed in terms of their components

then any game can be regarded as merely one specific example of a "framework"

.

4. Thus redesign (adaptation) becomes a process of identifying the nature

of the particular framework and having approximately the same emphasis

(both in tems of balance between components and accord with "reality",

5. On the other hand design of a "framework" depends upon

(a) The manner in which the individual components are defined.

(b) The relationships established between the conponents. These points

are illustrated in Figure I.

6. Given the minimal classification provided by Figure I various types of

framework emerge dependant upon

(a) The degree to which the rules and procedures and the accounting

system are "structured"/"unstructured"

.

(b) The manner in which roles and scenario are defined.

169
7. 6 (b) above can best be described as providing a "style".

8. If this is so 6 (a) above provides the basis for development of "frame"

games. (See Figure II),

9. From the argument so far it appears that a basic approach to the design

of "frame" games involves two sets of considerations: \

(a) Development of structures to accommodate:

(i) conceptualisation of problems.

(ii) basis for development of analogies.

Abstract games provide a vital link in this process because they

provide a means of

(i) Generalizing from existing games and gam.ing -simulations

(ii) Providing a conceptual framework into which new concept can

be placed.

(b) Identification of participants and objectives

so that:

(i) the degree of "structuring" required can be determined.

(ii) the particular "style" to be adopted can be established.

170
ROLES

A, "Definitive" sijnulation

exercises

Rules/procedures : structured

or "unstructured".

Accounting system : accurate

data analysis - highly

structured.

Objectives

(a) study of "system"

behavior

.

(b) study of decision

options.

"realistic'

"realistic"

B, G aming - S imu lat ion

Rules/procedures: "structured"

or "unstructured"

Account ing sys t em : data

analysis secondary (order of

magnitude) - flexible/minimum

structure.

Qbj ectives : (a) identify data needs

(b) study relationships

Scenario

4-

'symbolic"

SCENARIO ^

C. ' 'Gaming - s imula t ion

Rules/pro cedures :

"unstructured"

Account ing Sys t em : capability

for accurate data analysis

but flexible/minimum structure

Objectives:

(a) " identify crucial

decision -making groups.

(b) study of decision

options

.

D. "abstract"^ games

Rules/procedures : "structured"

or ^'unstructured"

Accounting Systan : "structured"

Objectives:

(aj conceptualization of

problems

(b) development of "analogies"

'symbolic"

Figure I

171
Ru1 es /P ro ce dure s

'Structured"

A.

Participants : students

Obj ectives : teaching

"established" knowledge

Participants : (a) students

(b) Practitioners

(c) General public .

, •

Objectives :

(a) Investigation of problem

areas

(b) Comnunication about

problem areas

Accounting system

"Structured"

C.

Participants :

(a) Practitioners

(b) General public

Obj ectives :

(a) Investigation of problem

areas

(b) Communication about

problem areas (e.g.

public participation)

"Unstructured"

DParticipants :

(a) Practitioners

(b) Researchers

Obj ectives :

definition of problem areas

"Unstructured"

Figure II

172
FRAME GAMES: DESIGN AND REDESIGN

FACILITATOR'S STATEMENT: SOME PROPOSITIONS ABOUT THE

USE OF THE POLICY NEGOTIATIONS M3DEL IN THE COMMUNITY

CONTEXT. ^ By: Earl S. Mulley

Associate Director

The Center for Simulation Studies

Saint Louis, Missouri 63105

The Center for Simulation Studies has used the Policy Negotiations model

for more than four years in both academic and non-academic contexts.

Out of this experience we are willing to state certain propositions about

the model. The validity of the propositions for us is rooted in user

observations and reflections on the ejq^erience of the game play, immediately after the play itself and after some longer time period. It is on

the basis of such positive and contructive feedback that we have con- tinued to use the model, adapting and innovating when needed to fit the

needs of client groips.

Propositions: • .

'

The P.N. model is one that can be:

1. a tool to assist groups in analyzing and describing their situations both structurally and dynamically.

2. a tool for sharpening the definition of the presuppositions,

character, and objectives of key interest groips in a system's

decision making process. . -

3. an exercise in defining issue and policy alternatives, and

exploring their various systemic in^Diications

.

4. a means of surfacing role perceptions and feelings of members

of a group or organization.

5. a tool for testing the perceptions and data incoroorated in the

interest groups in the process of policy formation.

6. a device for making educated guesses about those forces outside

the system that affect it. .

-

7. a means of discovering and even experimenting with negotiating

and leadership skills and style.

8. a means of creating empathy for those in another life situation

by assuming their position and feeling the pressures exerted on that position by the system.

9. a tool for testing the perceptions and data incorporated in the

model against the strain or tension created in the model by the

game play itself. QVhere there is a fit, there is a learning;

and where there is not a fit, there is a learning.)

173
Two Caveats:

Since the people supply the context of the game out of their own experience,

the simulation becomes the opportunity to sharpen and clarify, in the interaction and exchange process during and following the play, the varied

perceptions of and feelings about the organization of which all the participants are a part. This process demands of the game director a broader range

of skills than simple knowledge of the model. It is the conviction of the

Center for Simulation Studies staff that the model is best used with a groip

as a part of a larger training or developmental program that has built into

it those processes and skills to lead the group beyond the new insights and

learnings evoked by the P.N. model.

The P.N. model should be used within its limits, i.e., not with extremely

complex organizations or with grotps that want to use it as an idealistic

"what if" exercise.

174
DECISION: FUTURES ^DDELING

By Dennis L. Little

Long Range AcJministration Planning Staff

Division of Administrative Appraisal and

P lanning

Office of Administration

Social Security Administration

Baltimore, Maryland 21235

FACILITATOR'S STATEMENT: Within our corporate, educational, and public

institutions, the enphasis on the future is increasing. The bibliography of

futures publications has now reached a reported 20,000 titles. In 1971-72

academic year, over 190 educational courses, centering on the future, were

offered in our institutions of higher learning. Over half of these courses were offered in education, business administration, sociology, and political

sciences. The Federal government has established an Ad Hoc Interagency

Committee on Futures Research. The rapid growth in federal expenditures for

the "Great Society" programs-- from $1.7 billion in FY 1963 to $35.7 billion

in FY 1973- - has contributed to the current federal interest in the future.

People are beginning to understand that the future is not singular, not a linear extrapolation of present trends. They are beginning to see there are

a multiplicity of alternative futures, some of whose occurrence we may con- trol or influence through our current decisions. The social scientists have

begun to experiment with potentially powerful new tools for probing the

future. These range from complex ways of extrapolating existing trends

(Delphi, envelope curves, etc.), relevance analysis, the preparation of

detailed speculative scenarios, and the construction of highly intricate

models, games, and simulations.

1 Intuitive analysis and trend extrapolation are inadequate representations of

I the complex reactions and interactions of the real world. Consequently many

futurists have taken to mathematical modeling, gaming simulations, and games.

The directions taken have been quite diverse. As facilitator of this para ticular sub-group meeting, I would propose, the following points for

discussion. First, why model the future. Second, a review of the state of

the art in modeling the future. This might be broken down further to the

I work in conputer simulations-- Jay Forrester's Urban Dynamics and his

protegee's work The Limits to Growth probably are the best examples; the work

in gaming simulations-- The' Institute for the Future's Connecticut Game,

STAPOL (State Policy) developed by the facilitator at the Institute for the

Future, and Project PLATO are reasonable examples; and games-- Olaf Helmer

I and Ted Gordon's Futures Game and Helmer 's Future State of the Union are exanples worthy of review. A more recent style of game, where the players

I design the model, should also be reviewed. In games like Peru 2000 and

I Squatter City 2000, players design communities for the future along the same

lines. Arthur Waskow, Institute for Policy Studies, has proposed "future

gaming" centers which could offer e:xperience in "living" alternative futures

to people who are fed up with the present but have no feel for a

175
workable or desirable society. Warren Ziegler, Syracuse University,

Educational Policy Research Center, has done extensive work in the area of inventive planning workshops.

Third, the success and problems in modeling the future; and fourth,

the future of futures modeling. On this final point, the group

might wish to discuss new concepts; work in progress, or perhaps

the more difficult question faced by each futurist as to whether

they should be following the more technocratic approach of Forrester,

Meadows, and others, or the more humanistic, "bottom-up" approach of

Waskow and Ziegler. One group accepts the idea of alternative futures

but proposes to maintain control of those futures through adaptive or preventive decisions. The other group, like the first, believes in

the innovativeness of man, but also that innovation is a method of

inventing the future--as opposed solely to preventing or adapting

to it.

In any event the future is ours. Bring your crystal balls, alternative agendas, and any papers or examples of work in this area to

the sub-group meeting--Futures Modeling--Tuesday afternoon.

176
DESIGNING INTERACTIVE SOCIAL SIMULATIONS

FACILITATOR'S STATEMENT

GEORGEANN WILCOXSON

The Program Agency

United Presbyterian Church, U.S.A.

^75 Riverside Drive, Room 1168

New York, New York 10027

SUGGESTED TASK: To identify and address the most significant present

issues related to designing interactive social simulations.

PROCEDURE:

Session i

A. Brainstorm and prioritize specific issues.

B. Divide into small work groups around each issue. Each

group to prepare a draft position paper on their issue.

Sess ion I I and 1 I 1

Presentation, discussion and consensus seeking on each issue.

The facititator will then attempt to pull together work of the

entire sub-group in time for sharing at "Full task group summary

meeting" on Wednesday.

SUGGESTED ISSUES (to be added to by group)

1. Values and assumptions implicit in each of the models

of the design process presented during Monday panel.

2. Models of the design process additional to those presented by panel

.

3. Specific techniques that help designers accomplish

different aspects of the design process.

A. Definition of "interactive social simulation."

NOTE: GROUP MEMBERS ARE REQUESTED TO BRING CASSETT RECORDERS IF POSSIBLE

177
Sub -Group: Selecting and Developing Media

In Simulation Design

Facilitator: Charles H. Adair

Professor of Social and

Environmental Studies

College of Education

Florida State University

Tallahassee, Florida 32306

If the crucial, functioning parts of a simulation are to effect

participant behavior as desired, the proper fom of media must be selected

or developed. At times the selection process is quite simple while at

other times it is most complex. Too often the task is approached with

neither a rational or a creative frame of mind, and games become merely

variations of monopoly or poker. The position of this facilitating note

is that the principle of alimetry is too often evident in games and

simulations. Biologists have observed that living forms constrain the

functions of those fomis. If a bumble bee were to become the size of a man, his respiratory system would have to take in and discharge air with

the force and volume of a jet engine. So too, when we choose to repre

sent newly born babies with poker chips, the functions of a game are restricted.

Just how functional need our media be? That depends on at least

three possibilities.

1 . How real ist ic niust be^ our media?

This depends on the model of reality the designed has in mind.

Fidelity in a simulation is not always important.

2 . How much can one afford to invest^ in media?

This depends on its utility which is determined by the marginal

performance of students and the anticipated use of the simulation.

A model helps here.

Low . Hjigh

Low Fidelity o± Simulation High
3. How can we be creative in generating media selection ideas?

This is aided by asking of ourselves, "Do I want cognitive clarity

in the main, or is rich-impressionistic experience to be

preferred?" Does this function rely most on cognitive, social

ego or visceral motivation?" "Will symbolic, ikonic or enactive

modes of participation be appropriate?"

179
STUDENT DESIGNED GAMES

FACILITATOR'S STATEMENT:

HARRIET TAMMINGA ' Department of Sociology

University of Denver

Denver, Colorado 80210

I*m sure that there a.re easier ways to teach than by having

students try to design a gamed simulation- giving a lecture

isn*t too hard if one is rea.sonably a.rticulate and this can

be further simplified by carefully filing old lecture notes

to be revived at the appropriate point in the following semester. Of course, a conscientious instructor might occasionally entertain a few doubts about the effectiveness of this

"teaching" method, particularly if he is actually concerned

with "learning". Instructors v/ho insist on making it more

difficult for themselves by using the teaching method of having students design games have-n't proved, however, that this

educational technique ensures more or better learning. But

those who have seen the heightened interest and apparent increased understanding of subject matter of the students who

have been involved in the game design process usually seem to

feel that the extra time and effort expended were justified.

(Perhaps this is a phenomena similar to that often reported

regarding simulation participants ) just think of the cognitive

dissonance if they ha.d to admit that their time and effort

had been wasted!)

It is difficult to make generalizations about what is learned

through the game design process since the educational goals

for various disciplines differ. In addition, the terms "game"

or "simulation" or some combination of these are applied to a

variety of things which different instructors may view as the

desireable end product of the design process. There are different levels of abstraction which can be represented by a

game: from a simplified replication of actual events or roleDlaying, somewhat akin to a. description of an occurence,

ranging to complex simulations of analytical models, which

are m.ore like explanations of some real world phenomena. In

teaching sociology, I've been concerned with having students

design gamed simulations which involve grasping the underlying

conceptual model. (c.f.. Barton or Twelker, who refer to the

relationship between the real world phenomena, the conceptual

model, and the simulation.) Although it is possible to use

an existing model, it is often necessary to help the students

develop an analytical model before they can visualize the gamed

representation of it. Students often find it hard to shift

levels of abstraction in order to identify patterns or relationships in events in terms of the conceptual model, instead

of focusing only on the level of the immediate referent situation or tangible erame elements. Not all students are ready or

willing to work to get this understanding, but game design offer

the possibility to those who are.

180
i "Computer-Based Gaming Models"

I Philip D. Patterson

Environmental Protection Agency

' Washington, D. C. 20015

The use of computers as part of the operation of games began early

with the military. Early use of the computer in non-military gaming

[ activities is also evidenced by the Internation Simulation (Harold Guetzkow,

1966), Carnegie Tech Management Game (Peter Winters, etc., 1964), International Operations Simulation (Thorelli and Graves, 1964).

' The rich history of both the design and use of manual and computer

j urban games provides a good backdrop for discussing 1) the reasons for

I designing and using a computer-based game, 2) the ways in which the comj puter is used by the designer and the player, and 3) the experiences

gained by both designers and users of computer-based urban games.

The following outline represents a possible starting point for a

j discussion of computer-based gaming models using urban games as the illustrative example. An indication is made as to which person (s) -designer

,

user (instructor or leader), and/or player benefits from the computer

\ assist.

Reasons for Using the Computer

Allow for Complexity (designer)

Communication (player, user)

Deal with Complexity (player, user)

Provide Discipline for Inputs (user)

Provide Accuracy for Outputs (user', player)

Ways Computer Is Used

Bookkeeping (user , player)

Quick Feedback (designer, user, player)

Simulation of Outside Forces (designer, user)

Simulation of Internal Market Operations (designer, user)

Flexible (location or time of day) Input from Teletypes (user, player)

Experiences with Computer-Based Urban Games

Cost of Design and Debug (designer, user)

Cost of Use (user, player)

Achievement of Realism (designer, user)

Dissemination

1. Computer compatibility

2. Language transfer

3. Facilities required

4. Documentation of Model

5. User's Guide

6. Player's Manual

181
Several examples of urban gaming models will illustrate why computers

have been spurned by some designers and used by others.

First it is clear that some urban gaming models would probably

lose their dynamics and thus be harmed by computerizing them. SIMSOC

and SITTE are two examples of this class. For example, SIMSOC allows for

a lot of horse trading among the players as they hire one another, travel

from one region to another, etc. Any need to rely upon a computer would

only hamper the actions of the players.

Second, there are some relatively simple games that can be played

manually, but ease of play (particularly if many cycles of play are contemplated) can be achieved if a computer version is used in which the

computer performs a bookkeeping function. Examples of this class are

the CLUG, METROPOLIS, and NEW TOWN games that are available in both

manual and computer versions. For example, CLUG is an easy game to play

manually during the first few rounds when one starts play with a blank

board. By the time twenty parcels of land or more are developed, however,

the annually payments made by the players for salaries , goods , and transportation become so burdensome that a computer provides welcomed bookkeeping assistance.

The computerized CLUG and METROPOLIS games were expanded, respectively

by the CITY series and the METRO-APEX gaming models. The CITY models

added computer simulations for urban functions such as migration, housing,

employment, transportation, and shopping. METRO-APEX added computer simulations for migration, housing, exogenous and most endogenous activity,

and voting. These models, along with GSPIA and several others, used the

computer for both bookkeeping and computer simulation.

A recent development in urban gaming models emphasizes the use of the

computer as a communication device and simplified bookkeeper more than

as a simulator. Examples of these games are TELECLUG, BUILD, and ACRES.

For example, ACRES as played at Dartmouth is run in such a fashion that

players may input decisions at any time prior to the time the instructor

has specified as the end of the round. This could be several hours or several days after the start of the round. Furthermore, the players may

use any of the many teletypes around the campus for making their inputs.

A recent and still small portion of urban games are those that have

grown out of mathematical simulations. Forrester's Urban Dynamics model

has served as such a starting point for an urban game and others are likely

to follow suit.

The game designer who is contemplating the design of a computer-based

game should realize that a synthesis of game design techniques and computermodeling techniques will probably be required. A hybrid technique is called

for, and one should not overlook the experiences that others have gained

in searching for this technique.

182
UNSTRUCTURED AND GAME-GENERATING GAMES

FACILITATOR'S STATEMENT:

'Unstructured, and game-generating games' are actually

structured, but they are mostly less pre-struc tured than

conventional simulation gameso Therefore I vould like to

suggest to substitute the term 'unstructured games' by:

- Minimal structured games

or - Non-specified games

or - Skeleton games

or - Heuristic games

or - Frame games (see: Sub-Group: Frame games: design

and redesign)

If - however - the concept of unstructured games is generally accepted, I vould argue in terms of information

theory that messages vhich do not shov any structure

(manner of organisation of elements) do not contain any

information. Accordingly an unstructured game is a nongame: Vhat is called an unstructured game does not mean

anything to any observer.... What do you think about it?

'Minimal structured and game-generating games' might be

defined as games vhich provide a framework within which

the game-participants specify the content of the game.

Emphasis of the players' activities is laid on designing

- not only on playing the game.

To clarify this let us arrange social and simulation

games on a continuum with the extremes 'rigidly structured

games' (rules determined) and 'unstructured games' (rules

not predictable). To give some examples: Chess and Metropolis (Duke) tend towards the extreme of rigidly structured games, GRIPS (Varshaw et.al.) and SCENARIO (Dette)

tend towards the extreme of unstructured games. Refering

to the last two approaches it can be said that both contain a set of rules i.e. a sort of structure - but, deviating from the first two approaches, their field of

application is not pre-defined and the direction of the

arguements in the game is neither predictable nor following any probability distribution.

The crucial question in the design of 'Minimal structured

and game-generating games' - actually concerning all

games - is the question of validity: "¥hat is a game of

this category good for?"

Vithout restriction I only would say that each assessment

of the validity of a game is a short-lived one: A game

which has been proved invalid to serve one defined purpose might be valid to serve another important purpose

not yet discovered - or - a game which seems to be valid

at one point of time becomes invalid the next one, when

it can be fully replaced by a 'better' game> or something

else.

183
So far as my practical experiences with 'Minimal structured and game-generating games' are concerned, they are

mainly based on the development and test of the SCENARIOGAME at English and German universities.

To give you a brief outline of this approach, let me quote

the comment from one of the game-participants:

"1) Each move in the game takes on a rituallike aspect. The purposes of these 'rituals'

appear to be to allow those involved to leave

behind normal responses and possibly - although

not necessarily - be open to new or unusual

responses,

2) The game is highly dependent on user

participation: you get what you put into it.

I would imagine that mental blockages against

fantasy become quite functional.

3) It offers some advantages of encounter

sessions without the raw exposition of personal

hang-ups. One's feelings are exposed through

one's attempt at abstract intelligence.

4) As with everything that allows for spontaneity, there seems to be no guarantee of success:

only the players can do that, with their attitude.

5) I can see the game being used as a means

of introducing new students ("oh yea, she was the

one who played the role of 'f ranch tickler' in

the game") with an exchange of goals, emphasis

and desires,"

Comments like these on a game are certainly encourageing

the game-designer to present the game again - and they may

stimulate potential players to play it. But, do they validate the approach according to scientific standards if

only the percentage is high enough?

The number of times a game is played and the number of kits

which have been sold do they validate a game, or are other

variables - perhaps image or influence of the game-designer

- responsible for the height of these numbers?

Or, are there generally accepted ways to measure the validity of games, where the human imagination and the potential

to design own thoughts are the main factors?

KLAUS F, DETTE

Lehrstuhl fuer Stadt- und Regionalplanung

Technische Universitaet Berlin

1 Berlin-¥est 12

Strasse des IT.Juni 135

GERMAN!

184
FORMAL PAPERS

A Process for Designing, Developing and

Evaluating Social Simulation

Charles H. Adair

Professor of Environmental and

Social Studies Education

Curriculum Design and Personnel

Development Program

College of Education

The Florida State University

Tallahassee, Florida

32306

A paper presented in the panel, "Models of the Gaming -Simulation Design

' Process" 12th Annual Symposium of the National Gaming Council and 4th

li Annual Conference of the International Simulation and Gaming Association.

185
Introduction

Simulation design, beyond all doubt, is a dynamic process. The ex- plication of the process model or system developed at Florida State University over the last five years was made possible by repeated experience in

applying it in a graduate course, "Simulation and the Social Studies - SOE 523," and the contributions of many students and colleagues.

Novice designers vary greatly in their knowledge of form and function,

the selecting of media and evaluating a prototype they have developed.

Crudely and haltingly the following structure has emerged as means for

shaping a first experience.

Figure I

General Introduction

Models and Theories

Pedogogical Models

Simulation Media

Prototype assembly i Developing an Evaluation Strategy

Observation

Field Testing f Analyzing Data j Improving the Simulation

- Getting The Designer Started

Most often, those who would develop a simulation have an idea or imag^

in mind. It may be characterized as a novel arrangement in which participants could learn about some general topic of interest. A wild life ecologist, for example, wishes to manipulate uninterested adults into a new

posture of great concern for selected endangered wild life species. To

develop a working vocabulary and to conceptualize the function of the con- dition to be simulated is a first necessity. The eager designer wants to move immediately to developing the form of prototype itself and some selected experience is necessary. The total design process, we have introduced

by means of an inhouse video tape recording. Some early discussion around

Hon Raser's Simulation and Society ,^ Sarone Boocock's and E.O. Childs'

S imulation Games and Learning ^ and the particular interests of the designerto-be are quite helpful. A few exercizes in which the concepts of congruence, abstraction, fidelity, utility, isomorphism and learning transfer are manipulated stand as operations of value depending on the background of the

beginner. Those who need it are taught to flow chart quite simple functions

Several piecemeal and skeletal simulations are played and analyzed, with

the concepts in mind.

Since the design process in viewed as a research and development activity a task of defining the problem always exists. Students are asked to

write a "position paper" in which they review an array of systematic explan186
ations of the problems they have defined. Essentially, they must arrive

at a precise definition of a current state of affairs and a preferred state

of affairs before selecting or developing a theoretical explanation of means

of getting from one to the other. The "means" is in itself an explanatory

system. In the case of a wild life ecologist it was crucial to determine

which species were to be included, the means of determining how they are valued and understood by the target population, generating an indexing procedure,

selecting a theoretical rationale for developing values and a means for

value clarification. This is a new, demanding learning experience which supj ports the Raser assertion that simulation design is in itself a unique theory

building activity.

Students and practitioners in the social science disciplines and applied fields, e.g. nursing, social welfare, law, education, etc., usually

I are poorly trained in theory. They have real difficulty in conceptualizing

due possibly to long experience in simply describing rather than explaining

social phenomena. They need considerable help, and it is worth it.

Once students have a clear idea of the components and the syntax of the

^ components to structure their simulation tlje matter of social and human

dynamics presents itself. I have found James S. Coleman's "Social Processes

I and Social Simulation Games" in the Boocock and Childs text to be most valuable reading. Each fledgeling designer presents "his model" and the whole

design group interacts around it by applying the Coleman ideas of a social

environment , procedural rules, mediation rules, behavior constraints, goals

land means of achievement, environmental response rules and police rules.

; See Figure Two (attached). This operation has the effect of forcing the

designer to specify the functional behavior of simulation participants and

the means for achieving it

.

Quite often the explication of a conceptual model as being dynamic is

I the real breakthrough in understanding social simulation. Symbolic words

jare no longer confused with real behavior. Also the number of rules and

I expected entry skills of participants is reduced considerably. Inbarr and

Stoll have presented many case studies of important designers that had to

I learn this the hard way.'^

Sophisticated student designers at this point are urged to read Herbert

{{Simon's, The Sciences of the Artificial .^ It may be noted also that adivanced students begin to view their efforts, at about this stage, as being

jthe stuff of a good doctoral dissertation study. When this is the case ^Hill and Kerber's excellent test on education research design and analysis

jjis suggested along with reading the later segments of the Guide For Simulation Design .

Building the Simulation Prototype

tOnce the theoretical model has been operationalized in a flow chart

ormat the tasks of media selection arises. Each function in the flow chart

|;j.s examined with the use of a Media Selection Model presented in another

Ijpaper at this meeting. (See Figure III) . The designer poses a series of

[questions for each function.

,\ 1 . Do I want clear, cognitive meaning or rich impressionistic experience in this function?

187
2. What is the best representative mode to employ: symbolic, Ikonic

or inactive?

3. What kind of motivation is appropriate here: congnitive, socioego or visceral?

4. How will learning take place in this function: verbally, vicarioi

ly through objects and inferences or by direct experience?

5. Given the answers to 1-4 what is the optimum medium: Printed Materials through Direct Real Experience?

This process again is a demanding intellectual exercize that helps bul

does not solve the problem of media selection or development. If two medii seem to be equally appropriate the one incurring the least development cosi

is suggested. In the case of absolute "hang ups" students are encouraged

to "mess around" with a wide variety of objects, colors, swells, surfaces,

shapes and sounds. What doesn't result analytically at once will be pro- ' duced intuitively in time.

An aspect of the media selection process is the basic development of

specialized materials. Case studies, critical incident series, special

purpose map projections, cartoons and other materials call for special deve

opment skills. When students possess them all is well; otherwise, they

must develop the skill or contract the services of others to help.

To put it all together, to assemble the prototype, like the actual

media development itself, is aided by the early efforts to conceptualize

clearly. The flow chart suggests the proper sequence and arrangements. j' A double purpose is satisfied by the development of a handbook for

instructors or others who would monitor the simulation. The designer must

view the prototype as consumers would see it. After the experiences described to this point the designer finds difficult the realization of how

much he is a part of the simulation. To work properly for others the simulation must be free of designer assistance during its operation. Of cours< this is discovered in field testing, but that is rather late in the game.

A participant's manual is prepared, usually rather poorly. Field tes^

ing seems to be the only way to cause designers to reduce the volume of

initial instructions and to include crucial information here-to-fore unanticipated .

Evaluating the Simulation

The very complex nature of social and human behavior found in simulate

activities has rarely been evaluated powerfully. We have been helped cons; erably by Michail Scriven's, "The Methodology of Evaluation"^ wherein he

views both products and processes. Conventional pre-post testing within

an experimental design has merit, yet more is needed by the designer; he

must observe the internal mechanisms in a formative way. 8 To facilitate

matters the designer is asked to study his flow chart and enter the media

selected for each function. He draws another flow chart to the same pro- | portions, omits the notation and has a "skelcLun' uj. jiiS.-^ he wxshes to o'>-! serve. Next he employs a "Schema For Analyzing Social Simulatiou^'' +<-

188
specify the diagnostic, formative and summatlve attributes which are essential to meet the general criteria of Isomorphism and "playablllty . " For

example the entry characteristics of participants, the needed skills, knowledge, attitudes and desposltions are specified. "Does one need to know the

range of a Florida crocadlle in salt and fresh water to comprehend a particular critical incident?" asks the wildlife ecologlst. In answering such

questions designers develop a Simulation Evaluation Strategy , The simulation has processes that aire crucial to overall success. Most evaluators attempt to observe these with testimonial-like questions of

participants after the action is completed. But this lacks varaclty and discreteness. We attempt to examine the Internal, functional and substantive

replications of the theorectical model. This is facilitated by raising the

question of the desirability of divergent or convergent learning behavior

and using those concepts of Raser and Coleman noted above. We have found

that this operation is most valuable in making the first data from "tryouts"

of the simulation truly Informative for the designer.

The more conventional aspects of evaluation are treated in two summatlve

dimensions: performance expectations and valuatlonal expectations. The first

are observable and measurable cognitive behaviors capable of being recorded

at the termination of the simulation activity. They may also be observed

during the operation of a simulation to render evidence which would logically explain some failure at the end. The establishment of preset, anticipated outcomes occurlng due to defined stimuli which pertain to specific

goals or sets of goals are recorded and can be compared experimentally,

Valuatlonal expectations are those ad hoc, indirectly measurable,

crudely observable factors of motivation that affect the participation in a simulation. The concept is used by Lawrence Halprin who described "creative

processes in the human environment."^ More specifically the heavily re- searched variables of Interest satisfaction, cognitive growth, achievement

motivation and coping are considered.

Since most of those who have gone through this experience have had

little or no training in observation some time is sf/ent on the subject

at this point. Reflecting on Durkhelm's The Rules of Sociological Method , John Madge's The Tools of the Social Sciences , Harold Larrabbee's Reliable

Knowledge , Simon and Bayer's Mirrors for Behavior and Carlo Lastruccl's,

The Scientific Approach is quite useful for serious students of observation.

Yet for most beginners a series of suggested activities are employed. From

this effort and a visceral "need to know" the designer carefully develops

a Field Tester's Guide . He "trys it out" to insure that all Important data

is Included and redundancy is avoided. This little tool to formulate the

feedback from others who test the simulation has not been very successful.

Probably the fatigue, personal cost and lack of adequate reward to the designer

is the cause.

Field Testing

To observe actual performance of subjects is a crucial matter in simulation design. Most often the simulation is "tried out" in dormatories

,

homes and local bistros. The gross operational weaknesses of the prototype

are revealed this way. Next "try outs" are arranged for the target popula189
tion and the designer must contact the appropriate source. Family planning

clinics, jails, school classes, garden clubs and graduate seminars are examples. The designer tests not only the prototype itself but also the data

collection procedures, the Student Manual, the Instructor's Manual and the

Field Tester's Guide. The preliminary results are given what may be called

a serious but general examination. The data is "eyeballed."

Field testing at the outset helps the deslgner-evaluator to generate

emperical hypothesis to be tested later as scientific hypothesis. For example it was found in testing nursing and social welfare undergrad majors

that the game Obstacle Course really didn't produce much in the way of cognitive gains regardless of the compliments of professors and student players

Yet the very same game produces significant cognitive gains among inservice public health nurses and social welfare professionals who are working

in family planning clinics. The first case conforms to the experimental

findings common to our literature, yet the second does not. A question

arises: If it is assumed that students in school are accustomed to learning

by convergent means and that practitioners in real vocational situations are accustomed to learning more divergently through their experience, is it not

best to simply have students study conventionally and practitioners learn

through experience in simulations? Obviously many theoretical insights can be brought to bear in setting up an experiment. The point of the illustration is that field testing has more than practical payoffs for serious students of simulation design.

Experience has suggested that early field tests should include a preliminary experience followed immediately by another experience in the simulation. The first effort by participants is awkward and usually familiarizes them with the goals, media, rules and restraints. The second allows

the designer to make fruitful observations.

After prototype modifications have been made due to early field test

results the well designed experiment is in order. This may be asserted because a proper theoretical foundation has been layed and the treatment re- liability is much less in question. The costly and demanding effort of

controlled evaluation through experimentation can take place legitimately.

\ Analyzing the Data

Efforts at Florida State University to date suggest the following guidelines

1. In comparative studies which test simulations, it is most often

true that one doesn't have matched samples, so some analysis of

covariance technique may be used to insure equivancy of groups.

2. If the simulation is run with the same students more than once, a carry-over effect exists, so one should compare post test results

after each trement rather than the differences between pre-post

test results.

3. It is very often true that one is interested in the comparison of

average performance but individual performance too, so a concern

for the distributions and correlations should be included in the

study.

190
4. Analysis of variance, covariance and other statistical techniques,

particularly if done on a computer, demand assumptions about the

population, sample, continuity of responses, format of data for

analysis, etc. , that suggests very careful and early planning.

5. Very often simulations, when used as treatments, allow us to make

observations of participant behavior in a (molecular) part of the

total set of simulated events. It is crucial to consider the

postdictive and predictive nature of events surrounding the event

to observe properly in such cases.

6. Since many games involve scores that may be used as success-failure

criteria one is confronted with the problem of using criterion ref- erence measures. Nonparametric comparative techniques are frequently the solution for analysis.

Modification and Improvement

All of us who test carefully our simulations find great moments of exihilaration and depression. The modification of a component, rule or condition that has been generated by hard work isn't accepted readily by a designer,

His intellect and creativity are challenged. Yet so it must be.

Quite often the tested protjrpe needs more sophisticated media to achieve

its designer's intents. And this is costly, another real problem, the solution of which usually wil have to come from funds supplied by government

programs or business firms that wish to use the simulation.

Summary

This review of a simulation design process has attempted to stipulate in

ia somewhat linear manner the components and sequence of operations which

have proven appropriate and useful at the Florida State University. In

fact, much that happens has a hueristic quality that makes this model

stochastic at best. So it is with most efforts to link theory and prac-

|tice in creative efforts.

191
References

1. Charles H. Adair and John T. Foster, Jr., A Guide For Simulation Design , Instructional Simulation Design, Inc., P.O. Box 3330, Leon Station, Tallahassee, Florida, 32303, 1972.

2. John R. Raser, Simulation and Society , Allyn and Bacon, Boston, 1969.

3. Sarane S. Boocock and E.G. Childs, Simulation Games and Learning , SAFE

Publications, Beverly Hills, California 1968.

4. Michael Inbar and Clarice Stoll, Simulation and Gaming In Social Science , The Free Press, New York, N.Y., 1972.

5. Herbert A. Simon, The Sciences of the Artificial , M.I.T. Press, Cambridge

Massachusetts, 1969.

6. Joseph E. Hill and August Verber, Models, Methods and Analytical Procedures in Educational Research , Wayne State University Press, Detroit,

Michigan, 1967.

7. Michael Scriven, "The Methodology of Evaluation," Publication No. 10,

Social Science Education Consortium, University of Colorado, Boulder,

Colorado

8. Gene V. Glass, "The Growth of Evaluation Methodology," Monograph No. 22,

Laboratory of Educational Research, University of Colorado, Boulder,

Colorado.

9. Lawrence Halprin, The RSVP Cycles: Creative Processes In the Human Environment, George Braziller, Inc., New York, N.Y. 1969.

192
START

Comprehend and apply

both substantive and pedagogical

materials.

B.Learn to structure knowledge with

a flow chart.

K.Write the necessary manuals and handbooks.

J.Choose attributes

for an instructor's handbook and a player's manual.

!. Select or prepare

appropriate media.

Define essential entry skills and

competencies

M.

Prepare a Simulation

Evaluation

Strategy.

N.Write crude

performance

objectives.

FINIS

V.

IVIake the necessary

revisions in your

simulation.

U.Analyze the

data.

Fiow Chart I

An Overview to Simulation Planning

and Building.

193
topic a.iQ a tneoret.Cd! txpianiLion

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•itate i'iow it could

be incorporited

within a simulation.

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Cnar'i of your

tentative Simulation.

Describe in wn iiag wnat, when, and how to OL/aerve

Collect and tabulate your field data.

FieiG Tester's Guide

naii'ieve rne

Field Tester 'i GuKie.

Q.

Identify and

contact potential

Field Testers

3ki

Duplicate and

distribute the simulation media

to the Field Testers.

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196
A MODEL FOR SELECTING OPTIMUM MEDIA AS. ?ART

OF THE SIMULATION DESIGN PROCESS -

Charles H. Adair

Professor of Environmental and

Social Studies Education

Curriculum Design and Personnel

Development Program

College of Education

The Florida State University

Tallahassee, Florida

32306

Introduction

To present a model for selecting media in simulation design requires a few

definitional notes, a general framework for the activity and some rather

specific descriptive constructs to reveal the model components, their interrelationships and the necessity for each. This paper will attempt to re- veal a process that has been employed over the last three years at the Florida

State University and has been included as part of a basic Guide For

Simulation Design .

Simulated learning activities possess the potential for being a major breakthrough in the teaching-learning process. Possessing the long sought quality

of bringing reality to learning encounters, they have the advantage of high

validity, independent of the typical problems of misuse in the classroom

such as we see with textbooks. As John Raser notes, "simulation is a djmamic

model" which contibutes to even more than participant learning - to theory development itself.

For those of us designing simulations and training designers the awful truth

of Abraham Kaplan's appraisal of models presents itself. He notes that by

their nature basic structures are revealed with strengths and weaknesses being apparent. Theories, like well written essays, tend to seduce the casual

j observer but in the case of models, the cards are on the table. Everything is

I exposed.

)

I Our products reveal themselves for brutal, penetrating criticism of

I isomorphic structure, effective behavioral determinants/modifiers and

I clear results in terms of specified operational objectives. To create a

j synthesis of all of these components requires the selection and development

I of media appropriate to each. This is a problem malaxation which is far

l|'from solved theoretically.

"^A paper presented in the Task Group on Design as part of the 1973

meeting of the National Gaming Council and the Fourth Annual Symposium

of the International Simulation and Gaming Association.

197
Some particularly superior thoughts on optimism media selection have been

advanced by Rand Corporation scholars, educational systems designers like

Professor Leslie Briggs and a host of specialists in educational technology

audio-visual education and communication. Yet the principles and generaliz

tions from these sources have not seemed to possess the practicality and im

mediate applicability needed by designers. Over many experiences, both fru

trating and rewarding, a crude system has emerged at FSU and the purpose of

this short paper is to describe and explain the Model for Selecting Optimvnn

Media in simulation design.

Observing the basic design dictum that form should follow function the crea

of a simulation must start with a model of the functions he wishes to repli

cate. I have found that the process of reducing general models to operatio

terms by flow charting has aided us in specifying the conceptual and syntac

structure of the simulation to be. Once this is accomplished the selection

of media appropriate to rather specific operations is facilitated.

Each of the functions of the simulation has its own media requirements depe

ing on the operation of participants at that point, the behavioral constrai

and rules prevailing throughout the simulation and particular inputs from

antecedent operations. With these elements ascertained and specified it

is possible to employ the model (Addendiim I) in selecting and developing

the instrumental materials.

This model suggests a process that may be described in schematic form (See

Addendum II) . By using terminal symbols (circles) , function symbols (rectangles) , and decision symbols (diamonds) the conceptual components are spe(

fied. The use of connecting arrows reveals the syntactical order of the coi

ponents and the need for feedback and feedforward (loops) relationships.

A form more familiar to many beginning designers is a description of the

model components, step by step, jxixtaposed by an explanation for the neces-|

sity for each step.

Steps In Selecting Media

step #1 Take the general model, which structures the knowledge components

for your simulation, and compare it with your flow chart. If you

have failed to include any of the parts of the model, ask yourself

"Is this omitted on purpose or by oversight?" Make any changes in

your flow chart that you deem necessary of these steps.

The matter of reliable knowledge is at stake in step #1 and one must insure adequate isomorphism between the knowledge

deemed essential and the structure (conceptual and syntactical

of the simulation. This step insures a special rechecking of

the epistological quality of the simulation and your judgement;

based on the criteria essential to the application of your modi

198
step #2 Now that your flow chart squares with your conceptual model and you

know what each part of the flow chart is to accomplish you may begin to apply the Media Selection Model. The first few times that

you do this should involve going through the steps that follow very

systematically. Yet, as you catch on to the system only the model

in front of you need be considered.

To comprehend a complex process one must develop an internalized logic in performing it. Once this internalized logic

exists in the simulator, speedy utilization is pemitted.

step #3 As you examine the flow chart function (box, diamond, or circle)

and reflect on what it is to accomplish, decide on the learning

characteristics implied. You will have to note:

Storage

Encounter Intake Control Motivation

Action Cafter Suchman)

a. What kinds of information does a target individual possess?

b. If he doesn't have it - how can you give it to him?

c. If he does have it - how can he retrieve it?

d. What type of motivation is best here?

e. What control must the simulation have over activities?

f . What action do you want to have as a result?

If you can answer these questions, choose between one of the three

representative modes:

Symbolic: Best for experienced, sophisticated participants. Most

efficient if not changing (Ex. : reality of values and

transferring simple ideas. Book)

Iconic: Usually valuable for all participants. Must be selected

with artful, skillful effort. (Ex.: good for quick

identification. Picture).

Enactive: Best for inexperienced, naive participants. Crucial for

teaching reality and for changing values. Critical

for decision making. (Ex. : Role Playing)

While it is generally helpful to distinguish between

Symbolic, Iconic, and Enactive modes of representation,

very little is accomplished without identifying the operational characteristics, in terms of the teaching learning tasks, of each mode. Suchman 's model (above) helps to determine whether the target population must gain new information or retrieve what is already known. What the

immediate motive will be is a function of the urgency

imposed by the simulation and the characteristics of the

199
subject. Action will result in terms of these factors

as well as the kind of controls, induced by the simulation, in processing the information. The simulator's

choice of one of the three is a somewhat heuristic process of selecting modes in terms of his means-ends desires.

step #4 Now that you have chosen a representative mode, consider the kinds j of media available for that mode. This will be found on the right 1 hand side of the Media Selection Model. !

a. Select a type of media.

b. If you are stuck with two or more equally good media - ask yourself which has the greatest liabilities in terms of cost, availability, convenience, etc.

As the simulator, committed to a representative mode, attempts

to choose from a nvmber of rather specific media types, his

concern is to pick one that will optimize the particular learning for a particular kind of subject. When faced with the task

of choosing between media equal in terms of validity, reality

or attitudinal conditions, the simulator can make his decisio

on the basis of negative considerations such as, cost, convenience, time, etc. This is, as in step #3, a heuristic meansends strategy that becomes easier with practice and experience.

step #5 Imagine the particular form that the type of medium selected should

take in your simulation. Write your decision into the (box, diamond, or circle) function in your flow chart.

Recording choices on the flow chart serves the practical need for

keeping track of decisions. Also, it once again causes a reflectioij on the priority system for selection based on the amount of validitj

reality, or awareness critical for participants performing the function.

step //6 Proceed to the next function in your flow chart and, by going throuj

the steps 2-5, decide on the medium.

This step is one of getting the next selection task accomplished

and reinforcing the system in the mind of the simulator. Depending on the aptitude of the simulator a point will be reached in

which he simply may look at the model and he will rapidly progress

through the system without tediously or consciously attending to

the steps.

step //7 When you have selected the media for all of the functions in your

flow chart:

a. Consider how often they repeat themselves. Does this suggest

anything to you?

b. Can you simplify the job of getting the media or developing it

yourself by making any adjustments in your decision? I

200
The writer upon completing the several discrete media selection

tasks in the simulation, must view the whole. As an aggregate

it must possess some continuity and parsimony or be much too

complicated to construct or utilize. This closure point is

critical for both efficiency and subsequent action.

step #8 Procure or develop the media now.

To do the actual procuring and developing is important at this

point as there are usually many loose ends and sometimes judgment

errors in the process of selection. Tactual learning, novelty

and awkwardness in action are all structural-functional considerations that come into play as the materials are selected, shaped,

and organized for the prototype simulation.

Conclusion

To present a systematic procedure for selecting media is not to select the

media itself. At times a knowledge of botany will simply not get a flower

to grow in a crannied wall. It is at that point designers are urged to use

all of their senses, intuitions, fleeting hunches and bits of creativity

to perform the task. After considerable smelling, feeling, tasting, staring,

listening and talking about the function in the simulation something can

happen. And with luck aided by reflective effort the decision is made.

For the designer the next encounter is one of trying out the operation and

later testing formally.

201
Bibliography

Charles H, Adair and John T, Foster, Jr., Guide for Simulation Design , Instructional Simulation Design, Inc» P.O. Box 3330, Leon Station, Tallahassee, Florida, 1973,

Rudy Brats, A Taxonomy of Communication Media , Rand Corporation, Santa

Monica, California, 1972.

Leslie J. Briggs, et.al., Instructional Media , American Institute for Research, 135 Worth Beliefield Avenue, Pittsburgh, Pa. 1967.

Abraham Kaplan, The Conduct of Inquiry , Chandler Publishing Co., San Fran

Cisco, Calif., 1964.

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'WHERE ALL ELSE FAILS' - an approach to defining the possible uses

of Gaming- simulation in the decision-making process .

R. H. R. ARMSTRONG and MARGARET HOBSON, Inst. University of Michigan,

Ann Arbor, Michigan 48104

Introduction

Gaming- simulation is concerned with decis ion-making. Whatever

the subject matter a gaming- simulation exercise provides an environment

within which aspects of the decis ion -making process can be simulated.

The environment provided is made up of a number of components which

combined provide points of reference for the participants in an exercise; these components^ are:

(a) Role definitions - statements describing the , . specific situations within which the various

decision-making bodies/groups/ individuals are placed at the start of an exercise, together

with some account of the type of activities

they may or may not undertake.

(b) Scenario - a description of the general situation " . . with which all the roles are confronted.

(c) An accounting system - some means of recording

decisions and their consequences in such a way

that both the scenario and the specific situations of the various roles can be amended. The

accounting system covers both the 'model' and

the means (e.g. a computer) used to process the

decisions.

(d) Roles and procedures - a structure for the

exercise providing a framework for the activities

of the participants.

204
Gaming-simulation exercises are distinguishable from other forms of

participative exercise by the fact that all four of these components are

present. The emphasis placed upon any one of the components and the

manner in which they are defined or presented may vary, as may the way in

which they are combined, to suit the objectives being pursued in a particular exercise. Ignoring for the moment the variations that can

be produced by differing emphases placed on particular components, the

manner in which anyone or all of the components are defined and presented can vary from the precise detailed definition to the 'open ended' presentation. The more precise the definition of any component the less

freedom there is for participants to experiment ^ in that area. Such

precise definition implies one of two approaches to the use of an exercise, either: , . , . . .

(a) it is being used as a teaching mechanism and the

lessons to be learnt are 'contained' in the

definition; 2 or t

•

(b) the definition is regarded as a 'first approximation'

, to be tested during the running of the exercise.

Given the short history of gaming- simulation to date (other than

by the military) part of the lack of acceptance of the approach by

those engaged in the practical business of dec is ion -making has been

due to a 'distrust' of the precise definitions built into gaming- simulation

exercises by the academic practitioners of the art. There has been an

! implicit assumption made by the academic practitioner to the effect

that what is appropriate for the 'traditional' undergraduate or graduate

student is also appropriate for those engaged in the process of

decision-making

.

By contrast the use of more 'open-ended', less precise definitions

provides an opportunity for the participants in an exercise to develop

and 'fill-in' the original definitions by revealing their own perceptions

,j of what is important. This can also be achieved when precise definitions

j are used if those definitions are regarded as a 'yardstick' and an

I opportunity is afforded the participants for their amendment.

The argument is that gaming- simulation can be of greatest assistance

in the decision-making process if it is viewed as a means of enabling

I those involved in that process to make their perceptions of a situation

I, explicit. This argument is based upon the assumption that what is

I important in the decision-making situation is not the nature of 'reality'

but rather the decision-maker ' s perception of 'reality' . If this is

I accepted then gaming- simulation exercises used in the decision-making

||! process become one means of eliciting, and exploring the implications of

the decision-maker's perceptions.

2U5
Such an approach does not imply that the decision-maker 's perceptions

are, or should be accepted as 'correct', but rather that until they are made explicit they cannot be subjected to challenge, neither are they

so amenable to change. Further, until the decision-maker's perceptions are made explicit the possibilities for communication with others involved

in or affected by the decision-making process are less than they otherwise would be.

Making explicit the perceptions of those engaged in the

decision-making process can be described in more detail by reference to

a number of processes, namely:

(a) Developing an appreciation of the nature of the

'system' with which they are involved in terms

of:

the elements that comprise the system and their

possible interrelationships

the role(s) of other decision-making groups

or agencies

- the sensitivity of the 'system' to their own and others' decisions

the nature of the problems with which they are confronted

(b) Identifying possible alternative decisions/courses

of action open to them.

(c) Identifying possible consequences attaching to

alternative decisions/lines of action.

(d) Establishing the relevance of data/ information

to the making of choices between the available

decisions/courses of action.

(e) Developing an understanding of the nature and

sources of uncertainty affecting the decisionmaking process.

(f) Establishing the extent to which there is a consensus (or lack of it) amongst those

engaged in the decision-making process on points

(a) to (e) above.

206
In what follows three approaches to using the components of

gaming- simulation to facilitate these processes will be described

briefly. All of them are frameworks each capable of adaptation

to specific situations, they are:

- ALEA

- NEXUS

- SIMULATION CONFERENCE

ALEA5

ALEA is a format that has served as the basis for the

construction of a number of gaming -simulation exercises directly

relevant to practical situations.^ The main objective of the

exercises has been to investigate the relationships that do, or might exist between the various decision-making agencies involved in a situation. An additional objective has been to identify the information

needs of the decision-making agencies. The general approach has been one

of defining all the components in minimal terms so as to allow for development

and change, not only from one exercise to the next, but also during

the course of any given exercise.

Initially this approach was developed in response to the

type of participant in the exercises being run, all of whom were senior

officials in local government with an average of 15 + years experience.

Given this situation it was felt to be inappropriate to construct a gaming- simulation exercise which required the participants to 'abandon'

their knowledge and experience in order for them to participate. Rather

it was decided to construct an exercise based upon the provision

of 'points of reference' which would serve as the basis for the participants to use their knowledge and experience to develop the content

in detail.

Role definitions are specified in terms of the activities the agency

represented is undertaking at the start of the exercise. This is

supplemented by information concerning the current (start of play) position of the agency. Objectives and attitudes of the agency are not

specified except insofar as they are relevant to the past history of

the role and therefore necessary to the description of how the current

position developed. In this way it is made possible for the role to

determine its own objectives, and to change them during the course of

the exercise. Pursuit of such objectives being by means of manipulating

the balance as well as expanding or contracting the range of activities

undertaken. Within this context restraints on the activities of roles

are provided by the extent to which any activity is acceptable to or negotiable with other roles represented in the exercise.

207
The scenario presented normally consists o£ three elements:

(a) A written description

(b) Statistical material ^

(c) A schematic map.

All of this material is designed to do no more than provide a set of indicators which will enable the participants to gain an appreciation of the type of situation with which they are confronted.

While it is not presented directly to the players the information

contained in the scenario is supplemented by having available more

detailed reports, statistical sources and maps relating to the situation.

The accounting system used consists of two parts: First, a NEXUS^ 'model' which records consequences of decisions in both quantitative

and qualitative terms; and second, a general base map on which decisions

having spatial consequences can be recorded.^ Both these elements of the

accounting system provide flexible frameworks for handling changing

situations during the course of an exercise.

The rules and procedures used are designed to provide a minimal

organizational framework for the conduct of the exercise, as well as to

ensure that minimum records are kept to enable a post-exercise analysis to

be conducted. The organizational framework is concerned with defining

the timing and sequence of activities in the exercise. Any round of

play is divided into three or four periods as follows:

I Three Phase

(a) Assessment - roles evaluate their current position.

(b) Information collection - roles request additional information

considered relevant to their situation.

(c) Decision period - roles contact each other where felt necessary

to exchange information or negotiate on various matters, and

make their decisions for the round.

II Four Phase

Where there are four phases this is occasioned by the fact that

that NEXUS 'models' are not programmed to provide team accounts for the

roles, and thus the fourth phase is an accounting period in which the

roles summarize, from their own point of view, the consequences of the

round. Such team accounting is confined to financial matters.

208
The record keeping during an exercise is undertaken by use of four

forms

(a) Decision Form - decisions are recorded together with any

resource implications for the role taking the decision.

(b) Request for Information Form - requests for information

additional to that contained in the initial scenario are made to the central team and the answers given recorded on

the form.

(c) Contact Record Form - all contacts made with other roles

are recorded together with brief details of information

exchanged and the outcome of any negotiations that took ^ place

.

(d) Team Account Form - all transactions and events affecting

resources available to the role are summarized by the

participants.

In addition to the information recorded by the participants on

the four forms there is a completed NEXUS card detailing the consequences

of every decision taken and each event introduced into the exercise.^

Using the information contained in the forms and on the NEXUS

cards it is possible to 'map' the progress of an exercise in a number

of ways, each of which is capable of revealing some aspect of the

participants' perceptions of the situation. In the simplest terms

it is possible to plot the frequencies of such things as contacts,

requests for information and decisions , either in total or round by

round, thus providing some indication of the level of activity during

an exercise.

More elaborate analyses can be undertaken involving:

(a) matching requests for information to

decisions taken

consequences of those decisions

contacts between the roles

accounts of the roles

(b) construction of sociograms or matrices indicating

- the pattern of contacts between roles

the flows of information between roles

the relationships between decisions taken by different roles

(c) matching any of the analyses from (a) and (b) above to the

'total' outcome of an exercise.

209
All of these forms of analysis can be undertaken for individual rounds

of an exercise, for a complete exercise or for individual roles.

Wliatever form of analysis is used its importance lies more in the

fact that it can be fed back to the participants than as a straight

forward historical record of what happened. By feeding back the

analyses the participants can begin to question their own perceptions

as revealed by the analyses. In the first place such questioning can

be in terms of whether the analyses are an accurate record of what

happened. If it is accepted as a accurate record the questioning can

be concerned with the extent to which it is congruent with the experience

of the "Darticipants. In this way 'first approximation' models can be

used 'yardsticks' against which to match the perceptions of those

engaged in the dec is ion- making process. The information gained can be used

also as a means of amending the models used, thus increasing their relevance

for the decision-making process.

NEXUS ^0

NEXUS was originally used solely as the accounting system in the

ALEA series of games. It was then realized that given that it could

be used in the context of a complex game there was no reason why it

shouldn't be used in equally or more complex practical situations. The

first example of its use in this way was in the City of Liverpool

for the purpose of examining some of the implications for management of the

adoption of a P.P.B.S. approach within the authority. A second

adaptation was to the problems of planning and resource allocation within

the Fire Brigade of West Sussex County Council. -^^ A number of other

practical use developments have been undertaken in the past two years

(1971-73). 13

In all the practical applications known to the authors NEXUS has

been used for one, or both, of two purposes:

(a) the evaluation of alternative courses of action

(b) creation of alternative scenarios of future situations.

Its use for these purposes has often indicated areas requiring further

research and investigation, thus serving as a complimentary approach a to problem appreciation. ' ?

} Essentially NEXUS serves as a basis for making explicit perceptions ; of a situation by requiring that discussion follows a set agenda. The / agenda is as follows: i

5 (a) Definition of the 'System' under consideration - this } stage requires users of the approach to list the elements/

factors/variables considered to be relevant to the 'system'

(situation) with which they are concerned. The elements/factors/

variables listed can be of many types, ranging from the

easily quantifiable to the completely (?) qualitative. This

list provides the basis for the construction of the centre

card of the NEXUS display layout.

210
(b) Identification of decisions and events affecting the 'system'

defined - in this stage the main objective is to list those

alternative decisions and (random?) events which may affect

the 'system' defined in (a) above.

(c) Evaluating/ indicating the consequences of decisions/events

affecting the system - four sub-stages are involved in the

use of the approach at this stage:

(i) identifying which of the elements/factors/

variables defining the system are affected

by the dec is ion/ event under consideration

(ii) determining the unit of measurement to be

used (if any) in calibrating the effects

identified, (i) above

(iii) determining the direction of the effects

identified in terms of the units of measurement determined, (ii) above. It should be

noted that direction of effect is interpreted

only in quantitative terms and does not carry

with it any connotations of 'better' or 'worse'

(iv) deciding the magnitude of the effects in quantitative terms.

It will not be possible to complete all of these sub- stages

in relation to every element/ factor/variable included in the original description of the 'system'. In respect of the 'qualitative' elements it may

only be possible to proceed as far as (i) above i.e. to count the

number of times they are affected. The object at this stage is to

proceed as far as is possible with the evaluation of effects. If the

process has to stop short in respect of any particular element/factor/

variable this will almost certainly be an indication of the need for

further research/ investigation.

In the process of using the agenda provided by NEXUS those

engaged in the decision-making process reveal their perceptions

of the situation with which they are confronted. Insofar as such

perceptions are 'programmed' onto NEXUS centre cards they provide the raw

1 material from which gaming -simulation exercises can be constructed - re- presenting not what the 'real' world is actually like but how those

engaged in administering it perceive it. While it is of value in their

I] own right as aids to decision-making such perceptions can serve as in-

! valuable training tools for those about to assume positions of respon-

^ sibility in the decision-making process, insofar as they reflect the

I attitudes and values of those who presently carry the responsibility for

I (advising on) decision-making.

I 211
Simulation Conference

The development of the Simulation Conference approach arose primarily

as a consequence of the inability, in many instances, to apply quantitative

measures to the effects of decisions/events upon the elements/ factors/

variables used to describe the system under consideration. In the absence

of 'hard' numbers various rating scales can be applied, but all of these

suffer from the defect that they implicitly assume on 'equality' amongst

the decisions/events being evaluated. The Simulation Conference methodology^ overcomes this problem by providing a means of developing an 'ImpactScore' for each decision/event, which while it is an arbitrary number

does reflect a given group's perception of the relative importance of a specific decis ion/ event.

The ' Impact- Score' is developed through the use of a DELPHI

approach supplemented by the use of CROSS- IMPACT ANALYSIS.!^ In the

DELPHI stages of the exercise participants are asked (given a specific

future date) to:

(a) Give their estimate of the probability of

implementation/occurrence of each dec is ion -event

by awarding a score out of 100

(b) Rate^'^ the desirability, from their own personal

viewpoint, of the implementation/occurrence of

each dec is ion/event

(c) Rate the significance for the system under

consideration of the implementat ion/occurrence

of each decision/event

(d) Rate their own expertise in relation to each ' decision/event.

The responses are fed back to the participants in the form

of histograms together with associated statistical measures e.g. mean, \.. mode, median and interquartile ranges (where appropriate). This

process of feeding back the complete analysis of responses is important

because the 'Impact Score' is calculated using selected measures,

To feed back all the results enables participants to judge the appropriatenes.

of the particular measures used.

212
Between the first and second rounds of DELPHI participants are asked to undertake a CROSS- IMPACT ANALYSIS. Only after the Cross- Impact

Analysis is the second round of DELPHI conducted . ^ The 'Impact Scores'

derived from the second round of DELPHI are then used as the basis for

assessing the 'impact' of the decision/ event upon the 'system' under

consideration. - .

The 'system' is defined in terms of the elements/factors/

variables displayed around the perimeter of a NEXUS card. (Participants

are provided with a 'check- list' defining the elements/factors/variables

together with the unit of measurement, if any, to be used with each). Participants are asked to proceed as follows

(a) Indicate those elements/factors/variables affected

by the decision/event being considered.

(b) Indicate the direction of the effect.

(c) Distribute the 'Impact Score' amongst the elements/

factors/variables shown as affected. The 'Impact Score' to

be distributed under the following conditions:

(i) Not all of the 'Impact Score' need be

distributed.

(ii) No more than the total score can be

distributed - ignoring signs indicating

the direction of the effect when totalling.

Individually the completed NEXUS cards provide an explicit

statement of perceptions concerning the relative 'impact' of a decision/event upon the 'systen'. Taken collectively, or in various

combinations, they enable the 'total' perceived 'impact' of a series or selection of events to be made explicit. By manipulation of

the set of completed NEXUS cards it becomes possible to generate

alternative scenarios of the future.

The final stage of evaluation by the participants consists of

them writing, in prose form, a scenario based upon the results of all

stages of the Simulation Conference. Equally, the completed NEXUS

cards can serve as the basis for the construction of a game, and

the game process used as the means of generating alternative scenarios.

To date the Simulation Conference has been used to generate scenarios

relevant to issues concerned with manpower planning in local government.

It is being developed, and adapted, to provide one means whereby

computer simulations can be built (or amended) to explore the implications

of the perceptions of different groups of planners and decision-makers.

There is also a growing demand for its use as an 'educational' device

in that it provides a disciplined framework within which those engaged

in the decision-making process can review their own attitudes to

changing situations.
CONCLUSION

In all three of the examples described gaming -simulation techniques

provide a framework for the investigation of practical problems. ALEA

emphasizes the relationships between decision-making agencies - the

roles involved - while NEXUS is concerned primarily with the use and

manipulation of an accounting system for evaluation of alternative courses

of action. The Simulation Conference provides a means of generating

scenarios. IVhat they all have in common is that they depend upon

inputs from the participants. None of them are designed to 'teach' a particular lesson. All three approaches have as a common aim the

creation of an environment in which those engaged in the decision-making

process may become more self- aware.

The development of self- awareness is not the whole of the decisionmaking process. Any contribution that gaming- simulation teclmiques can make in this area will serve only to compliment other approaches. One

lesson gaming- simulation teaches all its practitioners it that there

are no such things as final solutions to problems. The danger practitioners

of gaming- simulation must learn to avoid is that of thinking (pretending?)

that what they have to offer will solve the problem of decision-making.

214
NOTES

1. A fuller description of these components is contained in R.H.R.

Armstrong and Margaret Hobson "Introduction to Gaming-Simulation

Techniques' in ALEA LOCAL GOVERNrCNT GAPPING SIMULATION EXERCISE

(T241 LG). The Open University 1973.

2. While this is true in general terms experienced game operators are well

aware that participants can 'revolt' and change aspects of an exercise to suit their own purposes.

3. 'Contained' in the exercise in the sense that the lessons will

be made explicit by use of the definition during the course of

an exercise.

4. It is accepted that gaming -simulation can serve as a communications

'channel' and that this can proceed along-side the process described

in this paper. However, this particular aspect will not be dealt

with, except in passing, as it is felt to involve specialist topics

which would be inappropriate to the main theme.

5. ALEA is a generic Latin term covering games of chance, especially

those played with dice. Our choice of ALEA as the title for a series of gaming- simulation exercises we developed in the Institute

of Local Government Studies (University of Birmingham, England) was influenced by the fact that on crossing the Rubicon Caesar

reportedly said, "i am ALEA iacta est" ('now is the die cast'). We

felt that if gaming -simulation was to have relevance to the decisionmaking process a title emphasizing the association with the 'Rubicons'

encountered in decision-making would be appropriate.

6. The range of subjects covered in the ALEA series is as follows:

New town development

Impact of a new town development upon an older town undertaking a programme of urban renewal

Local government reorganization

Conservation of historic city centres

7. A description of the basic mechanics of NEXUS is contained in

R.H.R. Armstrong and Margaret Hobson, "The Use of Gaming-Simulation

Tecliniques in the Decision-Making Process', paper presented to the

United Nations Inter- regional Seminar on the Use of Modem Management

Techniques in the Public Administration of Developing Countries,

^ Washington, D.C. , October 1970.

8. The general base map is generally of the type used in C.L.U.G.

and W.ALRUS (Allen Feldt, University of Michigan, Ann Arbor) on which land uses and other spatial characteristics can be indicated

by the use of symbolic models.

Ill

ZI5
9, There are a numbe? of ways in which the NEXUS cards setting

out the consequences of decisions/events can be 'programmed' for

use in an exercise. Three main alternatives are available;

the cards may be ' programmed ' by : - - -

(a) the control team either prior to or during the exercise

(b) a team of 'umpires' during the exercise

(c) the participants themselves

It is also possible to use various combinations of these three

alternatives.

10. NEXUS is a Latin word meaning the point at which things come

together. The display format used in NEXUS was developed from the

game FUTURES devised by Olaf Uelmer for the Kaiser Aluminum

Foundation. Development of the NEXUS approach has been based on elaborating a methodology for use and adaptation of the display

mechanism.

11. R.H.R. Armstrong and Margaret Hobson, 'Program Planning Simulation

City of Liverpool', Institute of Local Government Studies, University of Birmingham (England) July 1970.

12. R. B. Blackburn, 'Interaction Evaluation by Simulation', FIRE

MAGAZINE, 1971.

13. Amongst examples of the use of NEXUS are the following:

Social Services (long-range planning)

- Management Services (productivity bargaining)

Transportation (road network planning)

- Structure Plan Evaluation

Crisis Management

14. R. H. R. Armstrong and Margaret Hobson, 'Simulation Conference - notes on procedures and methodology' , Institute of Local Government

Studies, University of Birmingham (England) 1973.

15. Olaf Helmer, 'Social Technology', Basic Books, New York, 1965.

16. S. Enzer, 'Delphi and Cross -Impact Techniques - an effective

combination for systematic futures analysis'. Institute for

the Future, Middletown, Connecticut, 1970.

17. The rating scale used in relation to desirability, significance

and expertise is graded 1, 2, 4, 8 (supplemented in the case of

desirability by + or - to indicate approval/disapproval) as it

has been suggested that people find it easier to distinguish

gradations when a ratio scale is used.

216
18. The 'Impact Score' is calculated using the mean of the

probability distribution and the modes of the significance

and expertise distributions. The formula used is:

I = P X S X E

m m

8

Expertise ratings are 'discounted' by the division by the

highest possible rating and thus the 'Impact Score'

reflects the group's perceived importance of the decision/

event taking into account its acknowledged level of expertise.

The process of division is not strictly necessary but it reduces the

'Impact Score' to a number of more manageable proportions. Given

this 'discounting' it is felt that use of the mean of the probability distribution, rather than the median is justifiable, though

where there is doubt concerning its 'validity' either the median

or mode can be substituted in the formula.

19. The CROSS- IMPACT ANALYSIS stage is introduced to provide a focus

for reconsideration of the dec is ions /events included in DELPHI.

Results from the CROSS- IMPACT ANALYSIS are not used for any specific

purpose in later stages of the exercise.

i 217
SIMULATED UNIVERSITIES

I

H.A. Becker

Department of Sociology

University of Utrecht

2 Heidelberg laan, Utrecht,

The Netherlands

1.0 INTRODUCTION

1.1 The Academic Revolution

By now the members of the academic community and the public

in general are willing to recognize the fact, that tjie university

system is experiencing a revolution. This process started with a period of dignified and almost dull structural change, lasting from i about 1950 until 1968. The number of students grew rapidly almost in I every country. This growth, plus a change of the contents of science

and educational technology, forced the system to reorganize itself.

From 1968 until about 1971 the scene changed dramatically. The

students revolts brought the discontent, difficulties and resistances

j to the attention of politicians and the general public. Since 1971

the revolution has entered a period of less tumultuous but still

fundamental and rapid change. (1) ] This revolution in the house of science has induced quite a number

of research institutes and individual scientists to apply the instruments

j of science to the reconstruction of their own house. For instance in

sociology we see quite a boom in the sociology of education, the sociology

of science and the study of the management of science and of higher i education. In the course of this development attention has been given j to the application of simulation techniques. Especially the field of " economics has contributed a number of valuable simulation models of

university systems.

j

J The application of simulation techniques to the field of university

systems is not without problems. Are these models adequate models?

Could we get rid of their deficiencies? What strategy could help us to get

better models and a better application of these models in policy making i etc . ?

1 —————. '—— . — 1 The author is engaged in a research project, in which a number of simulation:

models of university systems are developed. The project is financially

supported by the Netherlands Foundation for Educational Research. It is i carried out at the Department of Sociology, University of Utrecht, 2

Heidelberglaan, Utrecht, The Netherlands.

218
1.2 Background of this Chapter

This chapter is based on a pilot study of the models of university

I systems now available. In this project we conducted a survey of the

literature on university simulation, and we visited a number of specialized

; research institutes in the United States, England, France and Gemany.

i The project started in 1971, and in 1973 a report on the findings was

' published (2)

.

In the meantime based on the results of this pilot study three

j research-projects have been started. The first one is directed at the

i development and implementation of a number of simulation models, that take

! teaching, research and external services into account. The second project

[tries to elaborate on the system of research activities in the

I social sciences. The third project is going to build a faculty flow

model. The three projects are restricted to the situation in the

Netherlands

.

This chapter gives an inventory of the types of university

simulation models, and gives some examples in each category (paragraph 2).

It continues with an analysis of a number of problematic aspects in these

simulation models (paragraph 3) . It concludes with some remarks on

the strategy of developing this field (paragraph 4)

.

j We will not elaborate on the concept of simulation used in this

:F chapter, because this subject is dealth with in the chapter on "the data

behind simulation models."

2.0 UNIVERSITY SIMULATION: MODELS

1 2 . 1 Introduction

Numbers mean little, but as an illustration we should have liked

^to be able to mention the number of models of university systems now

;in use. Especially because of the sharp growth of the number of models

!in recent years such a survey cannot be given.

The agency which has documented these developments best, is

iiQECD in Paris. This organization has undertaken an inquiry in its

member- states in 1969 (1) . This inquiry had a bearing on models of

educational systems, so not only simulations are involved. We have

the impression that about 2/3 of the number of inventorized models

comes within the definition of simulation. This inquiry was not re- stricted to university systems. However, a rough separation can be made

j'between models which wholly or partly have a bearing on systems of

,"higher education", and models of other educational systems. In

-diagram 1, we have given a survey of the models. To what extent has this

^picture Become obsolete? We are under the impression that - the number

of models at least - has been doubled in the years since 1969. Since

,1969 the OECD documents the new models which come to their knowledge.

iHowever, this organization no longer pretends to be able to give a somewhat

icomplete picture.
The only comparable study o£ a great number of models is by

Weathersby and Weinstein, and dates from 1970 (2). This study gives a structural comparison of analytical models for university planning. Thirty

models are compared, of which 12 are regarded by the authors of the

study as simulation models. Of these 12 models only one to a certain

extent can be used in the field of training, change agency, etc. In the

next paragraph reference will be made to the findings of Weathersby and

Weinstein. i Per category we shall give some examples of models. The examples

claim to be able to be typical of the category and to be able to

illustrate the category. They make no pretence to give a representative

picture of the category, quantitatively speaking.

2.2 Allocation Models

In a Norwegian study of 1969 (3) an estimate is made for nine

university departments of the numbers of freshmen, the number of those

graduating, etc. On a number of alternative conditions the researchers

arrive at estimates for 1975. They have the impression, that the

results of their calculations have somewhat more influence on policy i' making than calculations on the basis of trend-extrapolations and the ; like. The OECD-paper, which gives a description of the model, contains

also an evaluation by the researcher themselves.

"The experience gained by constructing and solving the model, as : well as the awareness of the model -builders of almost all the weaknesses j of the model, is very encouraging for the necessary future improvements i of the model. We would like, however, to conclude our report with the

following general remarks which may prove helpful to the model -builders

in any future work on the post-mortem.

a. The lack of a workable theory of how the educational system

operates and of study patterns have forced the model -builders to make

unrealistic assumptions.

b. Behavioral elements should be introduced into the model either

directly, through behavioral equations, or indirectly by exogenous estimatio

of the various coefficients based on behavioral factors.

c. There is lack of simultaneity in the system of equations. This

means that there is no feedback mechanism in the model. That is, each

step is determined by the previous, which in turn determines the next

step. This, again, is an over-simplification of relationships.

d. There is no consideration of the size of the model and there is no justification for the choice of the level of aggregation. We know,

however, that the larger the size of the model, the larger is the error

resulting from "noise" generated by solving the system of equations. It

would be desirable, therefore, to check errors involved in disaggregating

the system into such great details.

220
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221
e. The results produced by the model should be compared with results produced by other more aggregated and/or naive models It had often been the case that more aggregate models have produced more acceptable results."

I I This minute example of self-criticism does not need to be

supplemented. But he fact does need to be stressed that these model

builders themselves also provide us with possibilities which may lead

to an improvement of their model.

Our next example is a product of the Netherlands. By a working

group under the chairmanship of Prof. Dr. D.A. De Vries, a report was published on "numerical consequences of the envisaged structural change

in university education" . (4)

This simulation, published in 1971, scans some consequences of

the bringing into effect of the proposals by Posthumus on the reduction

of the duration of the study course and of the enrollment at Dutch

universities and university colleges.

The working group De Vries also mentions the consequences regarding

the number of personnel, accommodation etc... These consequences,

however, are not intensively involved in the simulation model. That is

why we count this model among the allocation models and not among the

production models.

In this simulation, each time the passing through the educational

system of 100 freshmen is examined before the structural change - and

of 100 freshmen after the structural change. In the memorandum the

reservation subject to which the estimations are given is fully considered.

Roughly calculated the estimation boils down to a decrease of the number

of enrolled students by 30% and of the number of students passing through

the university by 20%.

Thirdly a simulation by Albinsky, Geurts and Schute, who examine

the consequences of a numerous fixus for a great number of faculties (5)

This simulation, dating from 1972, proceeds on the expected inflow of

students according to the data of the National Planning Agency (central

Plan Bureau in the Netherlands) and on the patterns known from inquiries

of first and second choices with regard to faculties. The assumptions of

the researchers were:

a. because the choices show that entering a university as such,

and certainly also studying at a university, are rather taken for granted,

freshmen who cannot pursue their first choice, will choose a universitystudy which come closest to the indices of their preference.

b. this has the result that a numerous fixus in a certain faculty

causes an overflow into the most closely related faculties. If that

happens to a large extend, the introduction of a numerous fixus in several

faculties might result in the fact, that other faculties, in their turn,

get capacity problems, which they have to get rid of. If for that problem

the solution of a numerous fixus is chosen too, this, in its turn, can bring still other faculties into trouble.

222
c. if we want to examine whether something of the kind is within

the range of possibilities, we shall have to have insight into the way

in which the students will divide if they cannot follow their first

choice due to a numerous fixus. In this project we have taken it for

granted that this happens according to the percentages of preference for

alternative studies...."

As a result of their calculations, the researchers assume that a numerous fixus, introduced in 1972, will not produce a great effect

until 1976. They assume, too, (as was already hypothesized

theoretically) , that the satisfactory effect for some faculties often goes

together with a dissatisfactory effect for other faculties. This report,

too, develops the analysis and the deductions with a gradation of

reservations

.

Remains to be recalled that the National Center for Higher Education

Management Systems (NCHEMS) in Boulder, Colorado, is developing a student

flow model, which permits a rather detailed "monitoring" of the study

course per student and per category of students. Of this model, so far,

only a preliminary description is available (6) . It may be clear that

such a model can only be used to good purposes, if the student administration

is reliable, detailed and up to date.

2.3 Production Models

We are now entering a domain which accommodates many dozens of wellknown models. The show-model is the one developed by the Systems Research

Group in Toronto (7). The first variant dates from 1965. At present

the eighth improved model is in use. CAMPUS, in full: "Comprehensive

Analytical Methods for Planning in Universities College Systems", is

attuned especially to "resources planning". The model draws into

consideration: flows of students, systems of teachers, need of other

personnel, consequences with regard to space and cost of student provisions.

It can be supplemented by a model for building activities, in which also

allowances have been made for the developments of the capital market,

inflation and the like.

The model can be supplied with a sub -model for the planning of

a medical faculty including clinical activities. It is now being applied

not only in the university sphere, but, (with adaptations), also for

higher vocational education and secondary education. Expansion to primary

education is in course of preparation. Per user can be determined which

degree of details works best. The user can change components of the model

by hand, owing to which it can also be used as an instrument for training

and as a planning tool.
A comparable design has the RRPM (Resource Requirements Prediction

Model) NCHEMS at WICHE, Boulder, Colorado (8). This simulation, too,

is tuned to determining long-term and medium term policy. It can especially

be used to calculate the consequences of decisions, which will have an effect over several years. On a limited scale the user can experiment 1' with this model, too, with variations on the master model. - '

Our next example is a German model. The Hochschul- Informations

System in Hannover has, for the faculty of English philosophy and literature,

conducted a research into the question, how many students the university

can admit. Some years ago this faculty abolished a numerous fixus. That

is why an exact estimation of the number of students that could be admitted

did not apply. It was especially a question of developing an instrument

for short- and medium- term planning. The result is a calculation model

on the level of a department or faculty, which enables, o.a. analyses

to be made of bottle necks in the allocation of teachers, and which shows

the optimal use of rooms for lectures and working groups. The data-basis,

required for these models, can be realized without too great an investment

of man-power (9)

From HIS we also derive our next example. A. Hage c.s. have developed

a model for the faculty of geology at the university of Freiburg. They

began with an inventory and analysis of the state of affairs, partly on

the basis of existing administrative data, partly on the basis of inquiries.

Based on these, a calculation of needs for the coming period was made.

Thirdly, an optimal "re -allotment" of the available supply of space was brought about, in preparation of an internal removal. Involved were

seven institutes and a secretariat of the dean. Besides educational

facilities, the model also goes into the pursuit of science and professional

perspectives for graduates.

Because of the latter components this model is an asset (10)

In the Netherlands, too, production models for parts of the university

system have been developed. Within the framework of a project of

international co-operation under the auspices of CERI/OECD a calculation

model has been designed and tried out by a team of the University of

Nijmegen (leader of the project: J.L.M. Goossens) , which is based mainly

on the standards of the Overbeek Committee. The model has for instance

been applied to the sub- faculty of psychology in Nijmegen. In view of the

design of the Overbeek method, not only education, but also for instance

te pursuit of science could be brought into the scope of the model. The

report by Goossens c.s. arrives at an extensive survey of the factors which

have been taken into account when applying a differentiated version of

the Overbeek method. In this report the reservations under which the findings

must be used, have been worked out with great care (11).

224
In this series of examples of production models we finally mention

the Total University Simulation System (TUSS) , which has been developed

by De Nie at Utrecht University. The model can draw students, scientific

staff, administrative staff, supply of space and financial data into the

analysis. The model is being prepared for a number of uses in several

rounds . (12)

2.4 Interaction Models

There are many rather sijjiple simulations of university systems

which enable a faculty etc. to' be simulated with a limited number of

rules and a limited quantity of game -material , and which are suited for

purposes of instruction. This category includes the "madingly Game",

written in 1969 by D.J. Warren Piper and J. Race in Cambridge. The

nature of this game can be summed up best by mentioning the parts which

have to be fulfilled:

a. principal of college

b. administration of college

c. academic staff

d. students

e. National Union of Students

f.

gLocal Educational Authority

Summerson Council (which grants scholarships)

h. the press

i. the public

Participants have to arrive at a College policy, including such

matters as drafting an educational program, appointing scientific staff

and admittance of students. After five years a deputation of Summerson

Council judges the quality of the activities of the College (13)

.

EDPLAN of Clark Abt Ltd. at Cambridge, Massachusetts is in the field

of the commercial games. This scenario relates to educational planning

on the level of secondary education and "colleges", but is in closely

enough related, to university simulation to be of interest for the present

inventory

.

Persons interested can acquire a complete set of game -material, with

which from 27 to 38 players can simulate a process of educational policy.

A team of participants has to prepare and submit a budget for a number of

schools, and another team must judge the budget. The designers of the

budget are from the category of head masters and school boards; those who

judge the budget belong to the category of town councillors. There are representatives of the professional organization of teachers, the student

association, etc. Each participant finds in the rules of the game a description of the number of votes he may cast during the procedures of

decision-making. The leader of the game does not need to have a special

225
training in managing such games. It requires little imagination to conceive

the working of such a simulation. This can, for instance be a very useful

aid to train members of a schoolboard quickly and efficiently. The expert

commercial approach guarantees that the scenario is tested sufficiently

to make good what it promises (14)

t By Abdul Khan and P. Levasseur of OECD, a simulation was introduced

in 1969, which has as its object a complete educational system. \ The GAME-model (Global Accounts for Manpower and Education) has three

teams of participants; an "educational planning team", a "manpower

planning team", and an "economic planning team". The purposes of the model

are as follows :

i

a. the presentation of a computable model which could be used by educational

and national planning authorities;

b. the exposition of certain basic concepts and quantitative techniques

in educational -manpower plan formulation;

c. the simulation of the process of interaction which takes place explicitly

or implicitly between different departments and functions of a national

adminis tration

To give it a concrete fom, data on the French educational system were

introduced. The comment upon the practical application states o.a. the

following:

'Designing a game forces one to take 'a systematic look at the entire

socio-economic system of a given country involving collection, standardizatior

and processing of information. ... It was during the operation phase that the

major benefits of having invested time and effort in the construction of '< the game were realized. These benefits multiple each time the game is repeate

for different players For real life decis ion-making these benefits of

the use of a single simulated environment for planners from many different

countries. It would be interesting to compare this experience with a game

based entirely on one country and using planners of that country to play out

their respective roles iwthin the simulated environment.'

This comment contains a good number of wise lessons for further model

building. Reference will be made to this point in the next chapter.

In "Outlines and Development of Two Games on University Planning",

a doctoral essay written at the State University of Michigan, Frank Zilm

evolves two scenarios, which in the Netherlands would be characterized as "critical gaming". The "Comprehensive Higher Academic Operations Simulation

(CHAOS) Game" addresses itself to those, who already know the (American)

educational system rather well. It brings quantities, such as the relative

status of the various faculties within the game. The "Vice Chairman" has four

"votes" in the decision-making, the students altogether two "votes", so the scenario cannot be blamed for having a romantic prejudice. No more

romantic is the following passage:

226
"ironically, amny important decisions pertaining to a higher educational

system, are made by persons in positions where only a part of the overall

operating situation is understandable".

The game-positions are:

a. policy-makers (president, vice-presidents)

b. deans o£ faculties

c. members of the scientific staff; and

d. students

The scenario offers a formula, in which the simulated needs of the

university affect the policy capacity of the simulated university. This policy

capacity becomes smaller, if little is done regarding that need of society.

Furthermore, the accomplishments of the simulated university are being compared

with data on another, comparable university.

The second game by Zilm is known as "The Dynamic Academic Resource

Theory Simulation (DARTS) Game". It is meant to offer beginners in the field

a possibility to work up to the subject. IT can be used as an introduction

to CHAOS (15).

Finally we mention the Gaming Simulation of Tertiary Education, that

has been developed by De Nie. This man-computer simulation has been

successfully played by freshmen in 1972. At stake is the mapping out of a policy for three universities, which are associated with one another.

The model takes into consideration education and the pursuit of

science. The quality-dimension is brought forward by passing a judgment,

a.o. by awarding a "Prix d' excellence" to the best scientific publication

in a given year. The background of the model is the enactment of the

W.U.B. (Law on Reforming the University) and the structure of university

planning. The development of this model is not yet finished (16)

.

2.5 Final Remarks

In this paragraph we wanted to typify the categories of simulations

of the university system which are available at present. In the cases where the drafters of the models themselves went into the restrictions

with regard to their pieces of work, we have made reference to this. In

the next paragraph we shall go more fully into the aspects of the university

simulation models, which on the one hand are the weak spots, but on the

other hand are open to improvement, and which partly already are the object

of attempts to improve them.

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3.0 UNIVERSITY SIMULATION: ASPECTS

3 . 1 Introduction

In the previous paragraph we have taken a walk through a store with

numerous models of university simulation. In this paragraph we shall

examine "the" model of university simulation more closely, and in

doing so, look for the aspects which, in the present connection, deserve

special notice.

We can get hold of "the" model of university simulation most simply

by looking at the stages which can be distinguished when constructing

and using a model. Obviously university simulation models have the same

aspects as simulation models in the social sciences in general.

The first group of actions needed to arrive at a simulation model

consists of answering a number of question, i.e.:

(a) with which object do I have to deal exactly?

(b) what is the purpose of the construction of my model? Is it a case

of theory-building research? Practical research? Instruction? etc.

(c) furthermore, in case of an analytical aim: What is the definition

of my problem or complex of problems?

(d) can my object indeed be pursued best from a system-approach?

(e) can my object indeed be realized best by an approach with a dynamic model?

Next, the second group of actions. We must compose a list of components

of our simulation model. Which quantities shall we take as constants, variables

and parameters? Which variables are instrument -variables,which target -variables

What is the scope of our system, and which variables are exogenous variables?

If we want to look at the system for its optimum, we should also know, by

which criteria this optimum (or sub-optimum) can be tested.

The third group of actions requires making explicit the parts of

theory, social philosophy etc. which we shall employ in the construction

and in the handling of our model. By theory we mean, very traditionally

a body of propositions on social reality, whereby the propositions must

have reached a high degree of abstraction and of verification. By social

philosophy we mean a complex of opinions on the nature of society and on

the characteristics of a good society.

With the fourth group we do not look up but down. Which empirical

basis can we give our model? Are the available data sufficient? Do

supplementary data need to be collected?

Among the fifth group of actions we reckon the actual designing, testing

and putting into operation of the model. Think of the artistic inventiveness

of designing an adequate, goal -wise complete, elegant and parsimonious model.

EE

W.

t

228
To this groiQ) o£ action also belongs the prograjnming of the model for

ji conputer, if necessary. Here, too, an artistic inventiveness is required

resides a technical precision.

I Finally the sixth group of actions. (This does not immediately follow

jthe previous groups, time-wise. Generally speaking the groups of actions

in question observe a more logical sequence than a sequence as to time) . The

Activities to be dealt with finally, include looking at the validity of the

Jiodel. This is true of both analytical and educational models, and the like,

pie essential question in this respect is: Is the "distortion" of reality

Ln the model optimal? Validity and usefulness are interrelated: the use of

phe model determines the desirable degree of validity. In the concrete:

fiho keeps raising the validity, is finally left not with a very valid model

bf a university, but ends up with a real university in all its actual

functioning.

I We choose three aspects to be dealt with more closely: criteria

t^group 2) , empirical basis (group 4) and the complex of validity and

usefulness (group 6) . Per aspect we shall consider what the present

^ituation is like, and what will have to be improved in the years to come.

In doing so we have explicity chosen the three aspects, which, in our

Opinion, are the most problematical.

).2 Criteria

< Until recently, universities have been run on the basis of a number

.bf traditions, stereotypes and rought- and-ready rules. That worked rather

!>iell, certainly as long as small, constant numbers of teachers students,

'scientific projects, patients and the like, were involved. Meanwhile,

jniversity education on a massive scale has become a fact, the pursuit of

iniversity science has become a part of "big science" gigantic university

:linics will be mass-produced etc. From "management by tradition" to "management

oy objectives" is rather a transition. Radical students, economizing ministers,

j'ritical administrators have asked the centipede after its purpose and

pechnique of walking. The first consequence is a continuous stumbling of our

::entipede. Let us hope that its walking in a few years' time will be smooth

i^gain, and moreover more efficient than at present.

'I We shall have to come to see the university and its faculties, subject

iroup etc. as service systems . Services are given, and these services can be

:ested by criteria of effectiveness, justice etc. Three types of services

ire involved. In diagram 2, positions and processes have been amalgamated

Lnto a graphic scheme.

I The first flow of services goes from the university as service system

^especially scientific and administrative staff) to students, projects

!p£ research and other pursuits of science, and projects of external services.

'Students, research projects and external services are sometimes called the

'target- system" of the university.

229
Diagram 2. The University and Its Client Systems

assisting ^-"^

University as a

^^^^ system rendering

subsystems ^s,^^ services

Students as intermediate

client systems

Society

asultimate

client

system

Research projects as intermediate

client sys tems

Activities of external

services as intermediate

client sys tems

230
The second flow of services goes from students, research projects

and external service to society. In this connection society is sometimes

called the "beneficiary system", as the ultimate beneficiary.

The third flow of services supports the first stream, and, indirectly,

also the second stream. Think of administrative activities, housing,

student provisions etc. Think, also, of every systematic advancement of

"motivation" of staff and students, although this stream in fact is still

quite modest.

The three interdependent service systems need means in order to be

able to function. System one and system three end in the second system,

and this ends in society . In other words : We are concerned with an input

,

throughput and output of the total system and of each of the three subsystem.s

,

A scientific library can be an illuminating example in this connection,

although this example is more complicated than one might think at the first

glance

.

Probably the input of means can be rather easily described and tested

by criteria. New books and periodicals cost money, and free copies can

be appreciated at their true value. The throughput includes the care

of the library-personnel, the books, the housing, the presentation of

the available books, to the visitors, to those who lend the books and bring

them back. The output is the benefit which those who use the library derive

from this service system. This can hardly be conceived in criteria. This

profit, then, must influence the input and the throughput. The policy of

buying has to support systematically the quality of the output.

Finding (a) categories for the description and (b) criteria of testing

is now a field of scientific research and of scientific inventiveness which

keeps many scientists and scientific institutions intensely busy, f.i.

in the United States, England, France and Germany (1). Especially the

University of California at Berkeley is working on a large scale at finding

solutions, with financial aid of the Ford Foundation.

Speaking about this project in Berkeley, it is no coincidence that

the same institution works with models of computer- simulation. The difficulties

around the computer- simulation is one of the reasons why the criteriaproject has been undertaken.

The survey-study by Weathersby and Weinstein dating from 1970 ends in the

lamentation: "Up to the present, most models have tended to be simulations

of educational systems, with outputs left dangling for haphazard evaluation

at the end. A step in the right direction could be to run simulations but

with some framework for evaluating the outputs" (2) . Looking at the report

on the conference on "outputs of Higher Education", also from 1970 (3), the

picture is nearly equally gloomy. Also other studies on criteria for determining

231
the results o£ the university system, £.i. by UNESCO (4), make clear,

that we certainly cannot stop looking for hard criteria yet. Conclusion: - Useful criteria are eagerly being looked for; the progress made is

considerable and encouraging, especially in the U.S.A..

3.3 Empirical Basis

It requires a lot of time but is still rather easy to make a "theoretica:

model of a faculty or a university. We do not mean to say that many really

good "theoretical" models are available, but it is still possible to review

the field, and this task can be accomplished successfully by one scientist

within a few months.

Designing and realizing a model with an empirical basis is immensely

more risky, lengthy, more expensive and more frustrating. At least if

the model has to be attuned to important problems in that university system.

What about the empirical basis of simulations with regard to the

university system and its components? This question can only be answered,

if we differentiate the models - and, therefore, also their empirical

basis, according to a number of levels .

The first level includes describing the situation and development of

the university system by means of, comparatively speaking, rough quantitative

indicators. This process of describing such dynamic systems is called

monitoring . With regard to flows of students, the annual educational matrix

of the Central Bureau of Statistics in the Netherlands may be regarded as a deserving commencement of monitoring. But, due to technical factors, the

^ description is not available quickly enough, to follow the system in its

development, concurrently with the actual events. In the United States a system has been developed for this purpose: at random a great many points

of information in the scientific system have been chosen. By telephone the

informants concerned are asked for a number of data at regular intervals.

According to the "refreshing procedure" in a panel survey, the informants

are replaced by others at regular intervals.

Especially in Canada the United States and Western Germany, the making

available of a system of continuous information on processes in faculties,

universities etc., is already being vigorously and successfully pursued (5).

The second level of empirical information is that of specialized

projects of practical research . Bring to mind the evaluation-research of

concrete educational processes, undertaken by order of the teacher or agency,

directly responsible for this education. Such projects of practical research

can provide a most useful empirical basis for simulation-models. In order

to provide more than an incidental insight, however, they should be designed

^ with sufficient compactness and detail. Certainly as soon as the results of

such a research have been put into a data-bank, secondary analysis can

create and preserve a most useful reservoir of empirical data.

232
Empirical research with a theory-building purpose makes up the third

level" A difficulty here is that, so far, sociology and other empirical

social sciences are far from being equipped for describing dynamic social

systems. One single inquiry, or a panel in three or four waves, are inadequate

approaches in this respect.

Participating observation has too limited a scope. Document analysis

has been little applied up to now. Elsewhere we have elaborated which

developments are needed with regard to observation- instruments (6)

If we want to arrive at an adequate simulation of the university system, we shall have to arrive at collecting data on all three levels , and

that well interrelated. On the first level "monitoring" on a number of

core -indicators is necessary, and that in such a fashion, that developments

in time can be reconstructed. On the second level it is important

that results are well tuned to each other (as to time, qua shape by

standardizing). Also a good central depositing of results is of importance.

The third level requires a carefully chosen number of mutually harmonized

projects of theory-building research and of development of instruments for

description, analysis and systematical change.

In fact these wishes to achieve a better empirical basis are directly

related to the desirability of a good research -policy to the study of the

university system.

3.4 Validity and Usefulness

So far rather little research has been done into the validity of models

i for simulating university systems. In a field where simulating has been

i done for some time already, i.e. the study of international relations, evaluationresearch has taken place on a large scale, and is still going on. In

the years to come, also regarding university simulating, the validity of models

will be taken into consideration.

An important aspect of this validity research is, whether the models

can make useful, . empirically justifiable predictions. Predictions are,

both from policy - and from a theory-building point of view, most

interesting. It would already be of importance, if the predictions could

reach the modest level of consequence -analyses.

This situation leads to the conclusion, that interesting results may be

expected from research, where consequence-analyses of university systems and

the changes therein are performed with the help of man-models and man- computer -models ; in a later stage also computer -models. Such consequence -analyses can be validated by reconstructing in simulation, the processes which actually

took place, but are unknown to the participants in the simulation. When the

degree of validity is known, we can proceed from there to consequence -analyses

with regard to new processes. Obviously these should be followed by

evaluation- research, i.e. control of the predictive capacity on the basis of

actual events v/hich meanwhile have become known.

i.

I

233
Hopkins has raised some important and plausible criticisms on the use of large simulation-models for university planning (7) . To begin with

he goes into the relation between the expenses of making and using the models

on the one hand, and the output of the models on the other hand.

"Thus, it can be concluded that the collection and processing of data

for a cost- simulation -model requires a major investment of time and money.

Just how large an investment is difficult to say, for this depends on many

factors that are unique to each institution. However, based on

the author's experience, the total costs of developing and inplementing a simpl

CSM is on the order of $75,000 spread over a period of two to three years.

Data-related tasks account for approximately two-third of this total. The

most sophisticated CSM's have many added software and analytical features that

make the orders of magnitude more expensive. For example, the CAMPUS models,

designed as interactive computing systems, have cost more than $1,000,000 to

develop and implement.

To the implementation cost of a CSM one must add an estimate of the

cost of using the model to perform analyses. For the simpler versions,

this probably amounts to approximately $15,000 per year in analyst,

programmer, and computer time, provided that the model is used year after

year with the same data basis. However, because the parameters of the model

are known to change from one year to the next, it has often been recommended

that the data base be updated annually. In this case, the annual operating

costs might well be doubled."

Next, Hopkins goes into the movements of the parameters. The desirable

proportion of teachers as against students turns out to vary per institution anj,

faculty as much as 200% from one year to the next. In such circumstances a large computer -model with few possibilities to change parameters etc. during

the run is not a very practical aid. Hopkins' final conclusion can also be

important for our argument. He states:

"...based on cost considerations alone, the author would argue that

the use of mathematical models for making resource projections at the

departmental level is simply not appropriate. The cost of new educational

programs can be predicted far more directly, inexpensively, and accurately

if we use the judgment of experienced educators to estimate the student

demand for courses, the numbers of faculty that will be required to teach

those courses, and the extra staff and supplies that will be needed to

support that faculty. Research efforts in university planning would be

better invested in attempting to understand the order -of-magnitude effects

of proposed policy changes on various indicators of system performance. For

example, the author has found simple models to be both useful and economical

for analysing the overall effects of drop-out rates, enrollment ceilings, and

other campus constraints on degree output rates ; and for describing the

relationship between the unit costs of outputs and such variables as student

attendance patterns and aggregate teacher -student ratios. In the author's

experience, a model with only 10 to 20 decision variables can be far more

instructive than the large-scale models discussed in this paper. Thus, by

234
embarking on less ambitious (but not less iinportant) studies, we stand

to learn a great deal more about the factors which influence the costs

of university operatins and how these may best be controlled."

So far we know nothing about the validity and usefulness of models

for education on university systems , for instruction with regard to these

systems, for heuristic , plan-making , and systematically changing tasks.

Evaluation-research is a must here. An endeavour at usefulness -analysis was made in the previous paragraph where, in connection with the OECD-model,

we put in a plea for developing a game specific of a given country, and for

playing the game with skilled planners. The former proposal is not very

spectacular, but the latter is of great importance. What do specialized

skilled educational planners make of university simulation, and what

remains intact of such models (8)? Generally we may assume, that the

usefulness of university simulation models will be about equivalent to the

usefulness of simulation in fields such as physical planning, administrative

service etc.

3.5 Final Remarks

We have reviewed three problematical aspects of developing a university

simulation. Of course there are other difficult aspects. Finally, in

order to avoid giving too optimistic an impression, it may be desirable to

mention briefly a few more bottlenecks.

The theory for the foundation of the models is far from perfect. We

do not mean to say that there is a lack of speculative pronouncements

on the functioning of the university or on a desirable future thereof.

On the contrary. The academic revolution has induced hundreds of universitycitizens to publish dissertations on past, present and future of this

institution. The hypothesis of equality, the democratic form of government,

the mass university education, the menace to the pursuit of science, to

each of these considerable attention has been paid by newspapers and

periodicals, professional journals, on T.V., and, orally, in discussions.

So there hardly is a lack of hypotheses, although not yet enough inventive

thinking has been done about better solutions. But there is a great lack

of clear-cut opinions, accurately confined to their range in time and space,

bearing a note on their empirical basis, and related to the theoretical statements

on the university in general.

The lack of useful theory will make itself more felt in the years to come. As soon as the empirical basis will have become stronger, and as soon

as simulation in the field of university decision-making will become more

generally adopted, the call for good theory will become louder.

Is the building of models and the data -processing by means of computers

a problem? There is an excess of models for the analytical application of

simulation which can serve as an example. In this case the computer liardly causes difficulties. There still is a lack of useful basis -models for

the educational, heuristic application of simulation for many possible tasks.

F.i. instructing participants in a game still is a technicall backward field.

235
4,0 CONCLUDING REMARKS

The processes of structural change, that affect the university

systems in most countries, make a number of large scale policy measures

necessary. These measures have to include the application of models

like analytical simulation and gaming, because the scope and impact of

the reorganization make traditional policy instruments inadequate.

A handicap for an optimal use of simulation in the university

system is, that the scale on which development and evaluation of such

models should take place, can only be used exemptionally. The progress made

in large, specialized institutions in the U.S. and in Western Germany,

working with teams of 30 to 60 specialists, illustrates the desirability of

an ample scheme of manpower, equipment and financial resources. Also

the availability of specialized researchers and designers contributes a bottleneck, as university department offering advanced training in these

fields are scarce.

Models have to be developed and evaluated, they have to be implemented

systematically to. In both the U.S. and Western Germany organizations have

been created, that provide departments etc., as to the application of models

to special problem areas. University simulation is dependent on a number of

other areas of scientific activities. Especially the development of

consequential analysis may be considered of crucial iinportance of the

development of anlaytical simulation. Gaming constitutes a second general

input area.

On the other hand the simulation of university systems might also

provide simulation in general with a number of new aspects. The development

of the university system especially in the last five years has been

documented in a very intensive way. This creates the possibility to use

techniques like post-diction to analyze and re-enact processes in this system.

236
The author is engaged in a research project, in which a number

o£ simulation models of university systems are developed. The project

is financially supported by the Netherlands Foundation for Educational

Research. It is carried out at the Department of Sociology, University

of Utrecht, 2 Heidelberglaan, Utrecht, The Netherlands.

NOTES PARAGRAPH 1

(1) a.o. Chr. Jencks and D. Riesman, The Academic Revolution , New

York 1968.

(2) "Simuleren van universitaire systemen" , Utrecht, April 1973,

Dutch version only.

NOTES PARAGRAPH 2 y ; / v.^ r^^^^^^^^ i^"'' ';-

(1) O.E.C.D., Directory of Current Educational I^dels in OECD Member Countries , Paris 1969. ., ,. .

(2) G.B. Weathersby en M.C. Weinstein, A Structural comparison of analytical models for university planning , Berkeley 1970.

(3) O.E.C.D., Study of one mathematical model of the education system , Paris 1969, also: lore Thonstad, A Mathematical model o£ the Norwegian

Education System, in O.E.C.D., Mathematical models in educational planning

Paris 1967. ~

(4) Werkgroep-De Vries, Numerieke gevolgen van de voorgestelde her - structurering van het wetenschappelijk onderwijs . Den Haag 1971.

(5) M. Albinski, J. Geurts en F. Schute, Studentens top: verschuiving

van problemen , Nijmegen 1972.

(6) R.S. Johnson, NCHEMS student flow model . Boulder 1972. .

jC7) Systems Research Group, Campus Planning Model , Toronto 1973.

(8) H.W. Frey, Untersuchung des Personal -und Raumbedarfs im Fach

Anglistik mit Hilfe eines Simulationsmodells auf EDV-Basis , . Weinheim 1972.

1(9) A. Hage e.a., Geofak, Untersuchung des Geowissenschaflichen . Fakultat des Universitat Freihurg, Hannover 1972.

'10) J.L.M. Gossens, Development of a model for some aspects of university

management , Paris 1971.

lai) J. A.M. de Nie, Total University Simulation System, Utrecht 1971. (mimeogr.)

t 237
(12) D.J. Warren Piper en J. Race, Maddingley Game , Cambridge 1969.

(13) Abdul Khan en P. Levasseur, The Use of 'gaming' as a technique

for training educational planners. The OECD Observer , No. 39

April 1969.

(14) Abt Associates Inc. Edplan , Cambridge, Mass. 1970.

(15) Frank Zilm, Outlines and development of two games of university

planning , Michigan 1971 (mimeogr.)

(16) J. A.M. de Nie, Simulatiespel tertiair onderwijs , Utrecht 1972

(mimeogr.)

NOTES PARAGRAPH 3

' -

•

(1) See f.i. B.S. Bloom, J. Th. Hastings and G. F. Madaus, Handbook

on formative and summative evaluation of student learning , New York 1971.

(2) See note 2, paragraph 2.

(3) B. Lawrence, G. Weathersby and V.W. Patterson (eds.). Outputs of

higher education, their identification, measurement and evaluation , Boulder 1970; also D.W. Breneman and G.B. Weathersby, Definition

and measurement of the activities and outputs of higher education , Berkeley 1970.

(4) H.W. Peters, System of indicators and criteria for measuring the

efficiency of planning and management , Paris 1972.

(5) See notes paragraph 2.

(6) H.A. Becker, Observation by informants in institutional research,

Quality and Quantity , Vol. VI, 1972, No. 1.

•

-

: \ (7) D.S.P. Hopkins, On the use of large-scale simulation models for

university planning. Review of Educational Research , Vol. 41,

1971-1972.

(8) Abdul Khan and P. Levasseur, o.c.

238
THE DATA BEHIND SIMULATION MODELS

1. lOTRODUCTION

H.A. Becker

Department of Sociology

University of Utrecht

2 Heidelberglaan, Utrecht

The Netherlands

The majority of those who are developing or using simulation models

are dissatisfied with these models. We find the reasons for this

dissatisfaction as soon as we try to predict with analytical simulation

models, or teach and instruct with gaming models. Each type of simulation has its weak spots. Quite a number of causes could be listed for

the inadequacy of most of our models.

In this chapter we shall look at the hypothesis, that the explanation

for the inadequacy of simulation models in the social sciences is to be

found primarily in the weakness of the data behind the models . We shall

consider in this chapter also, to what extent there are opportunities

to find a way out of this deadlock.

2. SIMULATION

In order to establish a basis for communication, we first shall

have to define a number of our terms. In social sciences we are interested

in social reality and especially in regularities in this reality. Sometimes these regularities take the shape of systems. A system is

characterized by two or more identifiable parts, by an interdependency

of these parts and by system boundaries. If we have just a number of

unrelated processes or only a number of social positions we do not

speak of a system. Social scientists are confronted as a rule with

dynamic systems. As systems are often quite complicated entities, we

necessarily begin by introducing various simplifying assumptions which

enable us to represent the real system by an abstract model which makes

description, manipulation, etc. easier.

The models may be static or dynamic. A static model, like a map

of a city, represents a situation, but not a process; in dynamic models the

element of time in included. These latter models depict developments,

e.g. by showing the phases of processes. We call dynamic models of

dynamic systems, showing a certain degree of complexity, simulations .

The term "simulation" is used to indicate a miscellaneous collection

of models. If we want to have an organized, discussion about these models, we

will have to start with a classification. For this purpose we need a multi-dimensional classification.

239
Our first dimension deals with the instrumentation of simulation

models. We distinguish between computer-models, man-models and man-pluscomputer models. In the case of a computer model an analyst orders a computer to process some information, an arithmetical problem for

instance. During the processing of the information man does not interfere i\rith the operation of the computer, and therefore this model is called

(quite inadequately) a computer model. In man-models the processing of

information is done by the participants in the model. In man-computersimulation the participants and the computer take turns in processing the

information. This dimension has almost no theoretical relevance, and there

fore it is inadequate as a prinicpal basis for the categorization of

simulation models.

The second dimension deals with the potential functions of simulation

models. They can be used for analytical purposes. In theory-building

research we are interested in an analysis that results in propositions that

have a high degree of verification plus a high degree of abstraction. In

practical research a high degree of verification is desirable also, but

now a low degree of abstraction is sufficient (statements about the

developments in a single organization for instance) . Simulation models can

be used also for education; training, etc. in schools, universities,

during in-service training in organizations etc.. We can use them to facili

tate the development of plans for future action. Still another potential

function is planned change of attitudes, perspectives, habits, etc. of

participants in a simulation (function of change agency)

The third dimension is closely related to the second one. Now we

look at the nature of the simulated processes . Allocation processes are adequately analyzed as flows of entities through "channels" during a certain time period. Production processes are flow models too, but now

we record change with regard to the entities themselves (production) during

the advancement of the entities through time. We use an interaction model,

if an adequate representation of the reference- system demands the

inclusion of interaction between entities. In general allocation and

production models are restricted to analytical simulation.

Our fourth dimension is teminology as it is used at present. This

terminology is quite confused, especially because it tries to take

different dimensions into account without distinguishing between them

(for instance heuristic simulation, simulation of heuristic processes,

heuristic gaming, heuristic gaming-simulation mean different things).

In our opinion the best strategy to arrive at a uniform and practical

terminology would be to get a careful description of the most important

terms now in use, and to develop a uniform mult i -dimensional classification!

to match the terminology. We distinguished four dimensions, but it may

be necessary of course to add more dimensions. >

240
We shall not enter the Babylon of terminology in simulation much further.

In diagram 1 we present a classification of simulation models by terminology,

instrumentation and potential functions. In diagram 2 we develop this

classification a bit further. Elsewhere we have given a detailed account

of the references, arguments etc. behind this classification (1).

3. THE BvlPIRICAL BASIS OF OUR MODELS

3.1 A model of model -building

When designing and using simulation-models the necessary steps are,

in an arbitrary time sequence:

1) What is my problem? IVhat is my target? Do I have to develop

a model at all?

2) What are the components of the model in construction?

3) What theoretical, philosophical etc. notions do I have to incorporate?

4) Which data do I need?

5) How do I develop my model, how do I test it? How do I implement

it?

The comparatively elaborate venture of developing and implementing

a simulation model is only necessary if the characteristics of the

system and the characteristics of the objective demand such an approach.

The main characteristics of the system that demand this approach are:

complexity, dynamic structure, institutionalization or combinations of

these characteristics.

The main characteristic of objectives that demands this approach

is the wish to make the model highly complex, highly dynamic, highly

valid as to institutionalization, etc.

3.2 Characteristics of social systems

As a rule social systems have a relatively low degree of regularity,

jand therefore they have a relatively low degree of predictability (2)

.

'Manipulations like policy measures may force a system to become a bit

iTiore regular or a bit more irregular, but the basic characteristics of

(llow regularity remain.

J Nevertheless we need predictability, because we want the advantages

pf a scientific approach in analysis, teaching, instruction, planning,

||)lanned change etc.

j If we want a valid model of a system, the model cannot contain

acre regularity than the system itself. It is possible, however, that

i new look at social systems might disclose new aspects of the phenomenon

;[>f regularity.

241
Our first opportunity for a new perspective lies in distinguishing

between periods with relatively high predictability and periods with

relatively low predictability.

Let us look at an example. Often during policy negotiations the

policy-maker has quite a number of alternatives at his free disposal.

In this period predictability of the system might be relatively low.

As soon as the policy-maker has made his decision and the effectuation

of the new course has started, we get a period of relatively high

predictability.

A second opportunity lies in the introduction of a concept of

alternative pasts . If periods of low predictability are characterized

by a number of alternatives, an analysis of the consequences of

certain developments could legitimately include a number of possible

courses in the past. The concept of alternative pasts could be useful

when we turn to post -diction.

Of course this list of opportunities does not pretend to be a complete

one.

3.3 Data-Collection

If we want models that describe a system in its complex, dynamic

and institutionalized aspects, we need data concerning that system that

permit such a description.

Sometimes we can use information that is already documented. Content

analysis of documents in international relations is able to provide a data basis that is superior to the basis normally available in the social

sciences.

As a rule we have to obtain new data. The traditional approaches

(survey, panel, participant observation) are inadequate at this point.

New approaches will have to be developed, that have a number of merits

of both survey and participant observation, but that lack a number of

their drawbacks. The new techniques of data collection should have

the following characteristics:

a) an over -time data gathering. The development of models of dynamic

systems requires registration over a period of a month to a few years.

' To give an example: a question in a survey as to what a respondent

remembers concerning the events of the past week will not produce

enough information.

I b) gathering data as

"unobtrusively" as possible. For example,

a single direct questioning would certainly yield unreliable data. P

242
c) a data collection which can be applied on a large scale ; in order to bring forward regularities of a somewhat general

character one must be able to compare, if necessary, hundreds

of cases.

Our first example of such kinds of intensive data collection

is the "eductive" simulation, developed by Rome and Rome, They

register the growth of an organization through decisionmaking.

The organization is simulated in a laboratory by means of a gamingsimulation (3). This approach could be used, we presume, as a technique

of intensive data collection as soon as its results could be evaluated,

for instance by means of postdiction.

A second example is the use of "informants". These informants

observe the system according to instructions provided by the

research team. The informant -observer will gather and pass on

to the investigator data about what takes places within his "scope".

This can be their own conduct, the conduct of persons in their immediate

surroundings or activities in bordering social systems (4)

.

As an example we take higher education as a dynamic macro- system.

A part of this system, that would be of a size to permit research,

could consist for instance of five faculties , some related researchinstitutes outside the university and the part of the government -department,

that is actively involved in the policymaking with regard to these

faculties etc. The functioning and the interaction of these organizations

could be registered by for instance five to ten informers per

organization, keeping a record during a period of for instance three to

five years. In combination with a.o. analysis of written documents such

a technique of data- gathering is capable of providing highly valid and

detailed information.

3 . 4 Intensive and Extensive Data-Collection

As a rule the scope of intensive data-collection is subject to

marked limitations, for instance that of financial character. However,

proceeding on intensive data-collection, a complementary extensive data

collection can be brought about. Data-collection on a number of levels

can result in a powerful combination.

4. VALIDATION AND APPLICATION

How do we make sure that the data

How do we make sure that they describe

regularity and predictability?

4.1 Post-Diction

have an optimal degree of validity?

the system in all its relative

The technique of post-diction has not been used much in the social

sciences yet. It is applied in economics, and in the analysis of

243
international relations (5) . Why has it been used to such a small

extent in the social sciences? Perhaps the reason lies in the

insufficiency of the available data. If this situation improves,

the problem of validation will become less severe. The results of

the post-diction can be evaluated if and when we use a differentiated

interpretation of regularity (see 3.3).

Today, a subject area that could be approached with the technique

of post-dictioi is higher education. The development of a university,

a faculty, or a department can be reconstructed to quite an extent on

the basis of written documents. The system of higher education shows

a certain degree of democratic control, and therefore a certain degree

of openness. We need additional data, but these can be obtained with no more difficulty than we are normally confronted with in social research.

4.2 Consequential Analysis

Consequential analysis may be considered as a prediction containing

many conditions. If consequential analysis is employed in a field in which

this type of prediction has been used and validated (e.g. by post-diction)

on a regular basis, its results may be extremely relevant, especially from

a practical point of view. ,. ,

•

4.3 Anlaytic, Educational and Heuristic Functions

Not only analytical models but educational and heuristic models,

too, should demonstrate a high degree of validity in order to be useful.

Educational models provide the student with an abstraction of a system

he will have to deal with later. If this model does not contain the main

characteristics of the social system it describes, the educational process

is bound to be less than optimal. Of course we "distort" reality in

educational models, for instance by changing the time -decision. But how

can we design an adequate educational model with an optimal "distortion"

of reality without knowing this social reality to an adequate degree of

detail and validity?

4.4 Theoretical and Operational Levels

In the empirical sciences (including social sciences like political

sciences or sociology) we distinguish between statements or propositions

on a theoretical level and on an operational or experimental level (6)

Propositions on a theoretical level have a relatively high degree

of abstraction. They cover a great number of phenomena, that may differ

with regard to time, location, etc.

Propositions on an operational level are restricted to phenomena

of a relatively low level of abstraction. They contain statements

that give information on a relatively high level of verification. To

meet this standard of verification they are confined as a rule to objects

that have quite narrow limits as to time and space.

244
Theoretical propositions cannot be confirmed empirically in a direct way. They have to be "translated" into operational statements

,

and their confrontation with social reality (attempts to falsification)

takes place on the operational level.

Analytical simulations that aim at a high degree of empirical

validity have a tendency to keep to a low level of abstraction. A

model in the field of international relations simulating the development

of one international conference on disarmament may be able to predict

(by post-diction for instance) some characteristics of the phases of this

conference. Maybe in the long run the level of abstraction of models like

this can be increased a bit. But a predictive model of "the" contemporary

international negotiation, or of the development of "the" middle-size

town in the United States or in Europe is an Utopia. General analytical

models are like theories: their "predictive" power is limited. We must

translate their general statements into operational statements , that can

be put to a test in experimental situations.

The difference between theoretical and operational models has

consequences also for the use of simulation in the field of education

and training. Education aims at a general preparation of the participants

(students etc.) for a great variety of activities. This implies, that

educational models cannot have a high degree of direct predictability.

Their validity is examined by testing operational statements that have

been derived from the general statements. Training has a different

perspective. It aims at preparing the participant for a restricted set

of activities. Simulation models developed for training purposes show

a low degree of abstraction. Therefore, their "validity" with regard

to their reference -system can be determined in a much more direct process

of verification.

The problem of the data behind simulation models is located at

the operational level of this model. But of course the theoretical

level is involved also, especially as soon as theoretical models have

to put their statements to an empirical test after they have been

"translated" into operational statements.

5. CONCLUDING REMARKS .J '

Our essay puts forward a number of hypotheses

a) in the development of simulation models the data constitute

the most serious drawback;

b) we have to reconsider the regularity and predictability of

social systems;

c) we have to develop and use new approaches in data collection

and in validating the obtained data; some new approaches are available;

245
d) better data will provide us with better conditions for postdiction and consequential analysis;

e) the empirical basis as a weak link in the development of

simulation models does not only affect analytical simulations

but educational and heuristic simulations also.

If the empirical basis does indeed constitute the weakest link

in the chain of model building, improvement of this basis should

receive high priority. This might comple the simulationists to

expeditions into fields which they at present leave mainly to others

246
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NOTES

1) This essay has been financially supported by the Netherlands

Foundation for Education Research as part of a research grant

for a project, in which a number of simulation models of

university systems are developed. The author is working at

the University of Utrecht, Department of Sociology, 2 Heidelberglaan,

Utrecht, The Netherlands.

2) References, arguments etc. in general introduction to H.A. Becker

and H.M. Goudappel (eds) , Developments in Simulation and Gaming , Meppel 1972, and H.A. Becker, Simuleren van universitaire systemen , Utrecht 1973.

3) Predictions ultimately have to include explanation (E. Nagel, The

Structure of Science , London 1968), not only extrapolation of trends.

Predictions may contain clauses (like a maxLmum and a minimum) . They

must be relevant in a theoretical or practical sense. (A prediction

with too wide a margin between a maximum and a minimum is irrelevant.)

4) B.K. Rome and S.C. Rome, Organizational Growth Through Decisionmaking , New York 1971.

5) References, arguments etc. in H.A. Becker, Observation by informants

in institutional research. Quality and Quantity , VI (1972), no. 1.

6) H. Guetzkow, Some correspondences between simulations and 'realities'

in international relations, in M.A. Kaplan (ed.), New Approaches

to International Relations , New York 1968. "Post -diction" means

starting in the past (five years ago for instance) and "predicting"

developments up to the present time. This developments are presumed

to be known. If post-diction proves to be possible, the model

has shown to have a (very limited) degree of validity. The model

can be used now a.o. to predict future events also, if a number of

conditions are made explicit.

7) See a.o. E. Nagel, o.c.

249
SIMULATING ALTERNATIVE FUTURES FOR AMERICAN EDUCATION

by Jerry Debenham

University of Utah

Cultural Foundations of Education

Salt Lake City, Utah 84112

This paper is a report on the development of a completely computerized

simulation-game of the future of American education called SAFE (an

acronym for Simulating Alternative Futures in Education) . The game

models the short- and long-range impact on society of decisions which

educational leaders might make with respect to possible social, educational and technological developments frcm 1975 to 2024 A.D.

Following an introduction to the gane, this paper states the game's

specific learning objectives, briefly reviews the related literature,

outlines the game procedures, suggests alternative preparation and

playing techniques, and gives tested application ranges and costs.

Finally, it provides a sample run of the game, a summary of developmental trial- runs and an outline of needed further research and

development.

INTRODUCTION

Imagine yourself in this situation. The year is 2005 A.D. . You're a public school district administrator. You have just implemented a program which makes advanced intelligence drugs available to all

citizens in the community. An unanticipated minority has become re- bellious as advanced reasoning and memory powers qualify numerous citizens for professional training and jobs which the society cannot provide. Lawsuits are initiated by conservative groi^Ds demanding the dis

continuation of usage of the drugs. The teacher's union has decided t

strike if intelligence drugs aren't prohibited in the schools. Radicals threaten a revolution if their free distribution is discontinued.

The federal government hesitantly promises to back you if you maintain the program.

This is just one aaong an infinite number of possible scenarios which

can occur in the simulation -game SAFE. The game is the product of

several year's effort at synthesizing the growing body of futurist

literature in education into a meaningful classroom learning experience for students of social change. It has been recently used in courses in Education, Educational Administration, Educational

Research, Sociology and Social Work at the University of Utah.

LEARNING OBJECTIVES

The simulation-game SAFE is designed to help participants reach the

following specific objectives:

250
* Participants will learn a wide range of future educational

alternatives which can be anticipated to some extent from

generally foreseeable developments in American society.

* Participants will learn new techniques and approaches now

emerging to facilitate meaningful long-range planning.

* Participants will learn a model for studying the interrelationships between schools and society and the consequent restraints

on the powers of educational decision makers.

* Participants will develop an increased sensitivity to the

values of various socio-political groups.

* Participants will deliberately examine a variety of viewpoints on controversial issues about the future with the

intention of establishing informed opinions about them,

* Participants will demonstrate faith in the power of reason

and in analytical methods to foresee and build a more viable

future . .

* Participants will weigh alternative educational policies

against the standards of long-range overall public welfare

rather than short-term or special interest groups.

* Participants will judge problems and issues in tems of

situations, purposes and consequences involved rather than

in terms of precepts or emotionally wishful thinking.

* Participants will seek to integrate the future perspective

into their personal philosophy of education.

* Participants will show increased confidence in their own and their society's ability to deal with a rapidly changing

world.

RELATED LITERATURE

The potential of simulation techniques for professional training in

education, despite rapid advancements in other fields, roiiains relatively

unexploited. Where it has been developed and used, such as the

UCEA's "Madison Township Schools," ^ the focus has been on administrative

in-basket programs and not the dynamics of school -society interrelation

j ships. 2 Only a very few attanpts have been made for using computers

in the simulations.-^ None have been used widely and most are prototype models of the in-basket manual games.

SAFE employs a model of the interrelationships between schools and

society based on the general Get zels -Cuba model of administration

251
as a social process and the general theory of the systems approach

to benefit-cost accountability decision making popularized in the PPBS

techniques of district budgeting now rapidly spreading in the

United States.^ The general theory of the interrelationships between

education and society, it is recognized, is "in the infancy stages,"

Most of the specific dynamic interrelationships in SAFE are postulated

strictly for the purpose of building the simulation. The game does not

attempt to^ predict real educational development s of the future nor

their "iinfracV oh so'ciety ,' but "undertakes only to" open the imagination ' to alternatives and the need for gathering extensive reliable social

statistics until truly sophisticated, accurate systems models of " predictive value can be constructed. [ The game's development was heavily influenced by three other simulations

relating to the future of society: "STAPOL," by Dennis L. Little, et.al.,^'

"Delphi," by Stuart Ltapleby and John Briggs,^ and "Future," by the Kaiser

Aluminum Corporation. ° The interrelationships and alternatives in the

game were developed through such futurist techniques as delphi, cross

impact matrices, scenarios, and future -history analysis.^

The general outline of economic, social and value trends over the fifty ! years is primarily based on the work of Kahn and Wiener, 10 and the . ! alternative educational viewpoints concerning how schools should be I operated was heavily influenced by the work of Pounds and Bryner.H The \. development of the sixty innovative programs presented in the game is

based on a review of the general education literature and specific delphis

j and futurist studies which have predicted technological, biological and i social changes over the next half century of significance to educators. 12

GAME PROCEDURE

In its mechanics, SAFE centers upon the interplay of five basic

elemented:

District Innovation Planning Committees develop operating

and" p"rahn"ing programs within the' cons traints of a designated

operating budget. Their objective is to maximize overall social

satisfaction with public schools.

Edyents are general proposals for change in the educational ...

^ system. Two new edvents occur during each two-year planning

period and their implementation by the district affects the

socievents and the indices of satisfaction.

Socieyents are general classes of social developments (such

a'sHa^P "growth, student riots, teacher strikes) of financial

importance to educators and which occur on a probability

basis that may be affected by the various edvents and in

turn, affect the indices of satisfaction.

252
Educat ional E valuators are socio-political interest groups which

actively represent alternative viewpoints ccncemin^^ the best

aims and methods of education. They determine the impact of

district decisions upon the indices of satisfaction.

Indices of Satisfaction are social indicators of the degree

of relative cliaiige in satisfaction with public education

by each of the seven educational evaluators.

Each participant in the game represents an important community leader

and is part of an innovation planning committee for a large metropolitan

district. There are one to ten other districts in the state called STATOS.

The committee task is to please the evaluators over the long-run more

adequately and consistently than any of the other districts. If it can

do this, it can win more satisfaction points than any of the others by

the year 2024 and becomes the winner.

FIGURE I FLOWCHART OF INTERACTIONS BET1\EEN THE

DISTRICT INNOVATION PLANNING COMMITTEE AND THE ^ADRLD

253
Every two years the committee receives 12 million STATOSDOLLARS in tax

revenues above normal operation and maintenance funds to use as it

pleases. If the district goes into debt, it is charged interest. If

it saves a surplus, it earns interest. If the debt goes beyond 30

million, tax revenues are increased, but satisfaction points are lost

and the probability of a conservative reaction goes up. If the surplus

exceeds 30 million, tax revenues are decreased and satisfaction points

are won.

The committee has three ways to affect its world, a role played by the

conputer; through edvents, edsurance and edvertising. Figure I is a flowchart showing these alternatives and the locus of their effects.

The main way is through the purchase of edvents. These are sixty major

proposals for educational reform in STATOS. Table III briefly summarizes

20 of them. Up to 18 of these edvents may be available as options from

which the conmittee may choose at any given time. The committee task is

to select that edvent among the options which will win it the most

satisfaction points for the present, have the least undesirable long-range

consequences, and is least expensive after dividing the benefits by the

costs

There are numerous conflicting points of view concerning the goals

of education in STATOS which may be summarized in seven general value

positions given in Table I. And there are corresponding socio-political

groups, called the educational evaluators, who control all major educational decisions. Every edvent has some evaluators who favor it and

others who oppose it. The evaluators, however, do not necessarily represent the public in the district. The difference between the percentage of

influence the evaluators wield over educational decisions, and the percentage of citizens who sipport these positions is called the Gap. If

the gap gets too large, a revolution may occur.

The nunber of points a ccmmittee may win by the implementation of an edvent is determined by summing the product of the influence levels

and the degree to which each evaluator favors or opposes the edvent

(on a scale from -3 to +3) . For example, if the Essentialists control

32% of the power and are rated moderately in favor of an edvent (+1 on

.the scale), then they offer the district 320 satisfaction points (320

xl) if it is inplemented. If the other evaluators, however, *are against

the edvent, all total the district may still lose points.

Whatever decision the ccmmittee makes, it will have definite far-ranging

consequences. When an edvent is implemented, in addition to the points

it may win or lose the district, it increases the influence levels of the

evaluators who supported it and decreases the influence of those who

opposed it; that is, if the edvent is a success. It changes the probability of occurrence of many if not all of the 12 socievents. It also

has cumulative long-range effects upon the values of the public.

Unfortunately, not all edvents are successes. The success or non-success

of an edvent is dependent upon the extent to which teachers, students,

V

2b4
parents and administrators will si^port its implementation and the degree

to which it was a good choice in teims of short- and long-range consequences. When an edvent fails, the influence changes anticipated with its success are reversed and only half the satisfaction points are earned.

There are many evaluators in STATOS who are threatened by most changes

which occur in education and generally speaking, are most pleased when

the only change that occurs is a reduction in taxes. The decision

to avoid all change is called the Null Option in SAFE . Though it costs

nothing to implement, it has far- ranging effects upon the influence levels

of the evaluators, values of the public, and the probability of occurrence

of the socievents.

TABLE I BRIEF DESCRIPTION OF THE EDUCATIONAL EVALUATORS

1. Neoperennial is ts : This groi^ believes in a fundamentally unchanging

universe. Schools are responsible to teach the essentials of the

protestant ethic. The trend toward the expansion of school responsibilities is to be reversed. Influence level: 8%

2. Essentialists : This group believes in a slowly evolving world.

Educators are to transmit only those cultural elements that have

become thoroughly established (support the status quo) and integrated

into the national heritage. Influence level: 321

3. Social Realists : This grotp believes it is the job of the school

tb'lceep^ up with social change and adjust to the needs of the society.

It believes in moderate expansion of the schools and opposes any

programs which might weaken the influence of public education.

Influence level: 25%

4. Experimenta1 i s t

: This group believes the purpose of education is

the development of critically -minded individuals capable of seeking

and finding creative answers to the problems they face in society.

It favors considerable student freedom. Influence level: 12%

5. Social Reconstruct ionists : This group believes the purpose of education

is' to develop individuals with the ability and desire to create a better social order along the lines dictated by current social knowledge. Influence level: 121

6. Human Potent ialists : This group believes the purpose of education is

the expansion of consciousness and the provision of experiences

which pranote individual self -actualization. It promotes almost un- limited student freedom. Influence level: 101

7. Biological Recons tructionists : This group believes the ultimate

purpose of education is the prcmotion of the biological transformation of man. It prcmotes all programs which help man control or transcend his primitive instincts or capabilities. Influence

level: 2%

255
Every decade has a general value trend toward degrees of conservatism

or liberalism which results frcm national and international developments. The most cornnon trend of a decade is toward moderate liberalism

(egalitarian, epicurian, meritocratic) which extends back in

STATOS history for 5 centuries. Although the districts have no control over the general long-term or specific short-term trends of the society,

they can affect the 12 major social events which might occur during

any two-year period. These 12 events are briefly described in Table II

below. During every two-year period the computer generates a random

number between 1 and 1000. If this number is greater than the probability;

of occurrence for a socievent, it does not occur. If it is equal to or less, it does occur. The occurrence of a socievent, like the implementation of an edvent, also has multiple far-ranging effects. First,

its occurrence may increase or decrease the probability of occurrence

of itself in the future and each of the other socievents. Second, it

may change the influence levels of the educational evaluators and the

values of the public. Third, it may radically affect the income of the

district both positively and negatively, .

Participants can partially control the occurrence of socievents through

edvent selection or the purchase of edsurance. Edsurance is the second

way the committee may affect its world and consists of a series of programs which may range frcm ccmmunity-school interaction groups to the

establishment of emergency funds. Its purchase reduces the probability

of occurrence of negative socievents (with the exception of nuclear

war or revolution) by two-thirds.

Revolution may occur in the district if the gap between evaluator

influence and public values gets too large. This means that district

leaders have been ignoring the needs and interests of significant

segments of society which now constitute a powerless, alientated

minority. If a revolution occurs, it may succeed or fail. But in either

case, like edvents and socievents, it has far-ranging effects upon the

society. 1^

TABLE II

BRIEF DESCRIPTION OF THE TWELVE SOCIEVENTS

Socievent Description Cost

1. National GNP growth results in a tax increase SD +2.225 M.

2. Greater efficiency in school administration SD +2.625 M.

3, Increase in community involvement and concern • SD + 8,625 M.

4. Greater national interest and funding SD +6.750 M.

5. Conservative reaction by politicians SD -4.250 M.

6. Parent boycotts and suits over changes in schools SD -3,500 M.

7. Teacher strikes and sabotoge SD -4.500 M.

8, Student riots, protests and vandalism SD -4.250 M.

9. Sudden increase in student population SD -3.500 M.

10, Accidental school disasters SD -5.000 M.

11. Redirection of resources from schools SD -6.250 M.

12, Limited nuclear or other social disaster SD -125.000 M.

256
Edvertising is the third way the committee may affect its world.

It consists of a series of techniques ranging from public advertising

and tight control over news releases to lobbying and catering

to influential leaders -- all in an effort to persuade the evaluators

that they should like the committee's choice much more than they sean

I to be inclined to like it . Edvertising is a powerful technique which

' can win the district more points, change the evaluator influence levels

to more democratically represent the public at large, or change

influence levels to correspond to the values of the district leaders.

Unfortunately, however, district funds are limited and edvertising is

expens ive

In summary, the district innovation planning conmittee has three ways of

changing its world: through edvent selection, edvertising and edsurance

The conputer has five ways of affecting the district: through socievents,

revolution, edvent failure, control over the banks, and the basic, longteim multifold trend. The players soon realize that the computer plays

a very powerful role and the committee a weak one. They never have quite

enought money and the conputer is always creating some unforeseen challenge

to their plans. The comnittee task is to anticipate the short- and

long-range consequences of its decisions and likely social developments

in such a way that it can generally control the computer, maximize its

points and outperform the other teams

PREPARATIONS AND PLANNING

The game is designed so that participants can set their oivn initial

values for the public, the influence levels of the evaluators, and the

probabilities of occurrence of the socievents. By this technique, teams

can represent districts catering to various social classes and students

can model them according to their own state districts. The game is also

designed so that the edvents can be rewritten and all interrelationships

reworked. The conputer asks the relevant questions and re-programs itself.

If insufficient tijne is available for students to redesign the game, the

conputer is prograjimed to automatically provide a set of hypothetical

values and interrelationships

The actual playing. of the game is divided into five ten-year planning

periods. When participants come to interact with the computer, it takes

them only ten years into the future. Then it automatically summarizes

everything that has happened -- all the points the district has earned,

socievents which occurred, the debts accumulated, interest charged, changes

in influence levels and public values, and probabilities of occurrence

of socievents and edvent failure -- and turns itself off. This information

is then used to prepare policies and make decisions for the next ten-year

period.

In the assignments, participants are taught to mathematically optimize

their decisions by the use o£ three forms of analysis: delphi for evaluator effects analysis, cross -impact matrices for socievent futurist

analysis, and cost-benefit for optimum selection of programs. Every

decision which is implemented is immediately evaluated by the computer

257
for each of these three forms of anaylysis. The choice is compared to

each of the other decision alternatives available and ranked. During

the course of the game the assignments are gradually increased in difficulty until by the end of the game, students have the necessary

skill and concepts to perform all three forms of analysis, and

generally speaking, consistently receive the highest praise from

the conputer for excellent decisions.

APPLICATION

SAFE is completely computerized on an APL direct -interaction timesharing system which requires only a single IBM workspace of 54,000

bytes. Participants may sit down at a portable computer terminal

anywhere in the nation and connect by 'telephone with the nearest

computer facilities. The students run the terminal themselves.

The game takes anywhere from 6 to 30 hours to play depending upon

how many years into the future the participants want to go and whether

they redesign the initial values and other variables. Approximately

15% of the game time is for running the computer, 45% for individual

preparations, 20% for small group discussions, and the remainder for

class discussions both before and after the game.

The number of people who can play the game at a, given time is dependent

L^on trained personnel and computer facilities available. However, only

10 teams can play on one terminal and one account. Optimum team sizes

vary from 1 to 9, though teams up to 20 have successfully played the

game. Average costs have been $3.00 for the 145 page game manual and

$3.25 per team per round of the game for the computer usage.

TAELE III

BRIEF DESCRIPTION OF TWENTY EDVENTS

Edvent Description Cost

1. Career Education : Proposes that educational institutions become much more career oriented through the

establishment of Career Education Centers and SD 11 M.

Greater Community Talent Banks.

4. Family Neighborhood Learning Centers : Proposes that

centers be publicly financed where both children and

sd 16 5 M

adults can be enticed into new educational experiences.

7. Televised Home Study : Proposes that distinguished

scholars prepare televised study units and that

students throughout the nation be allowed to receive SD 11 M.

credit in lieu of traditional classes

.

10. Experiential Learning Schools : Proposes that educators shift emphasis fron cognitive to confluent

or experiential learning with careful emphasis on SD 8 M.

training the emotions.

258
Table III continued

13. Education as an Occupation: Proposes that the required years of schooling be increased and that students SD 18 M.

receive significant incomes as they advance into

secondary education.

16. Family Health Center: Proposes that health education

be vastly broadened in concept and made available to

the whole conmunity through publicly supported health SD 13.5 M

centers

.

Youth ToMis : Proposes that educational parks be

built in slum areas and denocratically organized as total youth communities with their own government, SD 17 M.

shops and student teachers

.

22. Educational Experience Centers : Proposes that centers be established which simulate conditions of the SD 18.5 M

past, present or future and that each school have its

own farm and mountain retreats

.

25. Future -Shock Curricula : Proposes that schools focus

the curriculum on adjustment to change through the

establishment of Ideatrons, Schools of Unlearning,

and a Center for the Synthesis of Knowledge.

28. Marriage Training Schools : Proposes that secondary

schools provide organized trial marriage experiences

. ranging from monogamy to group marriages.

31. Incidental Education : Proposes that all education

beyond grade school be nonconpulsory and that sec- ondary students be provided edu-credit cards so they can live and study according to their wants.

34. Schools of Releaminjj: Proposes that troublesome

students be sent to special schools where they are conditioned to associate undesirable acts with

extreme nausea self- induced by organic implants set

in the back of the skull for five-year periods.

37. Computerized Schools : Proposes that totally automated

high schools and colleges be built where computers

do all teaching, exajnining, monitoring and counseling .

40. E ducat ion C ent ra 1 i zat ion : P ropo se s that all educational

services be nationalized, equalized and controlled

from a National Education Assembly with elected repre- SD 6 M.

sentatives from every state.

43, World Language Education : Proposes that the schools

require all students to learn a newly invented in- SD 4.5 M.

temational language being taught throughout the

world.

259

SD 16 M.

SD 9.5 M.

SD 14 M.

SD 11 M.

SD 15,5 M
46. Genetic Bn^ineerin^' Education : Proposes that stude'nts and parents be taught the value and methods

of human and animal genetic engineering.

49. Intelligent Robot Tutors : Proposes that each student

be provided with an intelligent robot and that

teachers take the role of monitors of the robots and

ideal human types

52. Advanced Personality Drugs : Proposes that drugs be

used on students to control sexual desire, fatigue,

moods, fantasies, aesthetic perceptions, sense of

pleasure, etc., if necessary, to enhance learning.

55. Instantaneous Education : Proposes that bio-computer

technology be used to impart knowledge to the human

brain or to erase it instantaneously,

56, Vvt)rld, Reconstructionist Education : Proposes that a world education assembly be established to distribut knowledge, educational skills, and resources

equally to all humans on earth.

SAMPLE RUN OF THE GAME

The simulation -game SAFE takes into consideration over 1400 variables

and millions of possible interrelationships. No two teams which play the

game ever end it with similar power structures, public values, socievent

probabilities or satisfaction points. Through use of the computer all

calculations are immediately handled and the game appears simple to the

unsuspecting participants. It usually takes the whole course of the game

to bring them to full awareness and comprehension of the complexities of

interrelationships which are constantly occurring as they play it.

Table IV contains a sample of the conputer printout for the first two-year

period of the game. It includes typical student responses and includes

the kinds of mistakes participants often make when first playing the game

on the conputer. To the left are explanations of the computer statonents.

Many aspects of the game are not sho^^fll in this sample run (such as revolution, closure of public schools, points lost due to debts, etc.) because

the initial conditions for their occurrence are not met.

TABLE IV

SAMPLE TWD-YEAR CO^PUTER PRINTOUT OF SAFE

Explanation Conputer Statement

Introduction

You are about to play the game "SAFE" -- A simulation of the

future of education from 1975 to 2024 A.D. You represent

District 1 and are now responsible for educational decisions

from 1975 to 1984.

SD 9.5 M.

SD 18.5 M.

SD 9.5 M.

SD 16 M.

SD 6.5 M.

I

260
Table IV continued

One of

four

possible

general

trends

.

This

list

may

contain

as many

as 20

options

,

Taxes

received

every two

years

,

First

Choice

Computer

Decision

Analysis.

It may

also fail.

Beginning: 1st Ten-Year Planning Period

General Societal and International Developments over this

decade will strengthen values in your district favoring

moderate conservatism.

You are now living in the year 1975. Your edvent options are:

1. Career Education

2. Vouchers

3. Accountability

4. Authoritarian Schools

5. Family Neighborhood Learning Centers

6. Community Nursery Centers

7. Televised Home Study Program

8. Education as Vocational Training

9. Community Guidence and Evaluation Centers

10. Experiential Learning Schools

11. Interactional Catv Schools

12. Individualized Learning Schools

Your account has just been credited with SD* 12 million from

tax revenues. Total deposits in your account now are SD 12

million.

Which edvent would you like to implanent this year? If none, Type 0,

You made one of the best possible choices for gaining iinmediate

public satisfaction. Caution: You did not make one of the best

long-range decisions when considering socievents. Analysis ranks

it 6.

A cost-benefit analysis suggests that you made an excellent overall

decision.

Your innovation is successfully implemented.

You have remaining in your account SD 1 million.

Is there another edvent you would like to implement during this

two-year planning period?

13

A mistake;

not avail- You may choose'^'^each edvent only one and it must be one of the

able until options stated above. Is there another edvent you would like to

next two- implement during this two-year planning period?

year

period.

Third

choice You made a^g^d, but not one of the best choices for gaining

immediate publit satisfaction.

Analysis ranks it 6.

Caution: You did not make one of the best long-range decisions

when considering socievents

.

* SD on the computer will mean SD (Statosdollars) .

261
TABLE IV continued - —4

Conputer Analysis ranks it 7. Decision You have made a reasonable cost -benefit choice, but others 'j Analysis. were better. Analysis ranks it 6. . 'l

Unfortunately, your innovation! is a failure, half of its * satisfaction points are lost.

Your district is now in debt SD 6.5 million. I Is there another edvent you would like to implement during

this two-year planning period?

The "1" 10 1 following Unfortunately, you will likely lose points by the implementayour tion of this edvent. Analysis ranks it 10,

choice Caution: You did not make one of the best long-range decisions

will give when considering socievent . Analysis ranks it 8,

you a You have made a reasonable cost -benefit choice, but others

printout were better. Analysis ranks it 10.

of all Your innovation is successfully implemented.

variables Influence changes: 1 -1-2 -133 2 Totals: 79 321

that change 254 108 122 101 21 Socievent changes: -1 -3 _ 2 _ 0 4 as a re- ^2 -1 0 2 0 -2 Totals 665 9Q ^221_ 254 64 93 114

suit. 121' 123 57 65 19

'

They are ^our district ' is now in debt SD ' 15 . 2 739 mi 1 lion

in order there another edvehf ~you~would like to implement during thisi as listed two-year planning period? | in the '^ manual.

"No" 0

Indicate below how you want to edsure to change socievent . You must probability levels:

put a 1 CON PAR TEA STU PRI ACC RED

or 0 under lollloo ^ each of During 1975 and 1976 the following socievents occurred:

them. 1 national GNP growth earns your district SD 2,225,000.

7 teacher strikes cost your district SD 4,500,000.

The following socievents would have occurred if you had not

implemented edsurance programs: 8 student riots cost your

district SD 4,250,000.

Indicate below how you want to edvertise to change influence

and satisfaction levels:

"12" under NEO ESS SOC EXP REC HUM BIO

BIO is a 5 2 2 2 1 0 12

mistake;

you must You may not change any perceptions by less than 0 nor more

put a num- than 10 points

ber between

1 and 10 Indicate below how you want to edvertise to change influence,

under each, value and satisfaction levels:

NEO ESS SOC EXP REC HUM BIO

262
TABLE IV continued

A single 1

"1" means Edvertising cost you SD 2.002 million during this two-year period,

one under For this you earned an additional 100.0 satisfaction points and

each of increased influence levels by 0 points

.

them.

In comparison to edvertising for earning points, your edvertising

is ranked 4.

You have been charged SD 606,596 interest for overdrawing your

account

.

This two-year planning period has now ended. You earned 669

satisfaction points. Total satisfaction points earned since 1975 are 669.

Your evaluators have become more conservative.

Your public has become more liberal.

NOTE: The probability of undesirable socievents occurring has

gone up by 30 points.

NOTE: The probability of edvent failure has gone up by 18 points.

NOTE: The gap now is: +30 +15 +5 +16 -23 -20 -12

TABLE V is a sample of the computer printout for the conclusion to the

first ten-year (five two-year) period. It includes a statement of funds

remaining in the account, points earned, new values for influence groins

and socievent probabilities, edvent failure probabilities, new edsurance

costs, and satisfaction points per million investment. To the left are explanations of the conputer statements. ;

TABLE V

SAMPLE TEN -YEAR CONCLUSION COMPUTER PRINTOUT FOR SAFE

Explanation Computer Statement

all^ro ^ds

Conclusions to the first ten-year planning period

The ten -year planning period has now ended. The status of your

account is SD -32.2469 million. Total satisfaction points

earned in the game so far are 3,467,

263
TABLE V continued

The statiis of evaluator influence and socievents is as follows:

NEW OLD CHANGE

NEO 19 80 -61

These abbre- ESS 313 320 -7

viations soc 371 250 121

stand for EXP 107 110 -3

each of the REC 130 120 -10

seven influ- HUM 78 100 -22 ence groups

BIO 2 20 -18

GKP 677 666 11

These abbre- GRE 54 90 -36

viations COM 207 220 -13

stand for NAT 257 250 7 each of the CON 92 65 27

12 soci- PAR 77 95 -18

events TEA 161 115 46

STU 149 125 24

PRI 130 120 10

ACC 58 55 3

RED 95 65 30

NUC 30 20 10

ED/F 482 400 82

The new edsurance costs are aj

CON 295500

These change PAR 134750

because of TEA 362250

new soci- STU 326624

event prob- PRI 227500

ability ACC 145000

levels. RED 296875

follows

Total costs now are SD 1.6785 million.

When This is a change of SD 229125

positive, it

means an increase. Total satisfaction points per million SD investment now

equals: 33.8267.

Cost

This line The cost of running this round of the game is 2.81 dollars,

gives the

cost of useing the

computer

264
DEVELOPIvlENT AND EVALUATION SUMMARY

i The simulation-game SAFE has gone through a process of development

I and testing extending over a full year from June 1972 to May 1973.

Three approaches for reaching the ten stated objectives for development

i of the game were tried: two board games, one small group manual simulaI tion exercise, and four conpletely conputerized simulation versions,

i The results of each approach were tested, but only the computerized

versions were found to satisfactorily reach all the original objectives.

The computerized version of the game went through four major stages of

evolution and has been tested with six classes from the University of

j Utah and one from Brigham Young University. Student ages ranged fran 18

to 56 with the average around 26 and the most common about 20.

! Educational backgrounds ranged from Freshman to Post -doctorate . Class

sizes varies from 7 to 54 with team sizes from 3 to 20. Average preparj ation time on the part of students was 7-8 hours with a range fran less

i than 1 to 40 hours. A total of 155 students participated in the game

and 105 evaluations (68%) were canpleted and returned. On the returns,

92% said they enjoyed the experience and 8% said they did not enjoy it.

A total of 90% said it was worthwhile for them in view of the time and

effort put into it, and 10% said it was not v;orthwhile when considering

the time involved.

I In view of the fact that there were numberous "bugs" in the computer

' program which required frequent terminations of the game, constant

changes in the game rules as the model was being developed, manuals

which were always obsolete because of new changes, teams which were

much too large for lack of additional staff and facilities, insufficient

' allocated time for participation, and assignments which were vague and

cumbersome until almost the last trial runs, we felt that the student

response on these developmental runs was extremely favorable,

[ In general, the most frequently mentioned enjoyable parts of the game in

I their order of occurrence were as follows:

j 1) working with the computer

j 2) immediate responses to decisions

i 3) seeing future possibilities for education

4) group participation

5) working out interrelationships and making choices

I The least enjoyable parts of the game in their order of occurrence were

as follows:

1) homework assignments

i 2) trying to read the manual and understand the game initially

3) having to work in large groups

4) rushing and waiting for the computer

I The most frequently mentioned things students learned from participation

in the game in order of occurrence were as follows:

265
1) educational ideas for the future

2) how to bargain and compramise to arrive at a consensus

3) difficulty in a district in choosing and ijiplonenting programs

4) the problons of trying to please the most powerful

5) the consideration of long and short-term effects necessary

in planning

6) the need to think in tems of many variables when planning

7) how to make good decisions and what to take into consideration

8) the many uses of ccmputers for education

9) the fact that actions and policies of today profoundly affect

the future

10) how values and power groips shift

The degree to which the ten original objectives for development of the

game were met on the average with the six groups which played it is

summarized in Table VI below:

TABLE \ri

SUMMARY OF EVALUATIONS RELATING TO THE TEN OBJECTIVES

Degree to which the

objectives were met Objectives *

Not at all Very much

0 1 2 3 4 5

2 3 25 49 26

1 3 10 34 46 12

1 . 11 28 37 27

5 33 , 38 28

3 10 32 41 19

2 13 36 34 14

1 10 39 36 16

4 4 25 46 26

1 1 15 31 42 14

2 7 19 38 30 9

6 22 100 321 399 191

c 2% 10% 31% 38% 18%

Range of educational alternatives

learned

New techniques for decision -making

Model for studying schools in society

Increased sensitivity to values in

society

Deliberate examination of various

issues

Faith in the power of reason to see the future

Emphasis on long-range public

welfare

Problems judged in terms of situations

Future perspective in personal

philosophy of education

Increased confidence to deal with

the world

TOTAL

PERCENTAGE OF TOTAL

* See page 2 for canplete statement of objectives

266
Table VI shows that 57% of all responses were in the two highest

categories, "Very Successful," and 87% were in the highest three,

"Successful." Only one-half of one percent of all responses suggested

that the game objectives were not met at all through participation in

the game.

The five objectives for the game which participants in general most

frequently agreed were reached through the game (in order of

occurrence) were as follows:

1) Objective a: Range of educational alternatives learned.

2) Objective d: Increased sensitivity to values in society.

3) Objective h: Problems judged in terms of situations.

4) Objective c: Model for studying schools and society.

5) Objective e: Deliberate examination of various issues.

The only objective which received a significantly lower rating than

the rest, although over 75% of the participants felt the game was reasonably successful at reaching it, was objective j), "Increased

confidence to deal with the world." Many of the participants found

the game itself a somewhat future -shocking experience which seriously

challenged many of their conventional beliefs and ways of looking at

the world and the future.

NEED FOR CONTINUING RESEARCH AND DEVELOPMENT

The newness and complexities of simulations for educational purposes

and specifically about the interrelationships between schools and

society are such that virtually any well-thought-out evaluative re- search will make a genuine contribution to our knowledge. Ten specific

areas of research and development which might lead from the simulationgame SAFE are as follows:

1) SAFE postulates a model of multiple interrelationships between

schools and society. Research is needed to specifically

determine these interrelationships so that more sophisticated

and accurate models can be designed.

2) SAFE is delimited to modeling the interrelationships between

schools and society. The model could be extended to include

the entire range of matters which educational leaders must

consider in educational decision making such as effects upon

the students ana the organization.

3) The model in SAFE is based upon a hypothetical district and

community power structure. Edvents, costs and effects have

been intuitively derived. Research is needed to base the

game on a real district and power structure, real educational

alternatives and likely effects as derived by groiq^s of

specialists using such techniques as the delphi and cross- impact matrix.

267
4) Only one optimization run has been made to deteimine what

the effects and maximum, number of points are under a given set

of policies. Multiple such optimization runs need to be made

to determine optimum strategies for playing the game and flaws

where the model needs to be improved.

5) The simulation-game SA.FE needs to be compared with other

techniques for reaching the same or similar objectives to establish whether this means of teaching is significantly superior

or inferior to others. Also different techniques for playing

the game need to be conpared to determine the best procedures

under various student and environmental conditions.

6) Research is needed to determine which aspects of the game

have what effects so that learning outcomes can be more precisely

determined and controlled.

7) It has been observed that students with different personalities,

values and abilities react quite differently to the game and learn

different things. Research is needed to determine exactly how the

game affects different kinds of students,

8) The game has been criticized by some for excessive complexity

and difficulty in playing and by others for over-simplification

.

It has been recommended that different games of graduated complexity

be developed around the theme of school -society interrelationships

and that students have a chance to advance from one form to another.

9) The game has been critized for its particular liberal bias.

It has been suggested that there are many ways to look at the

interrelationships between schools and society and the kinds

of alternatives the future holds. It was reccmmended that alternative versions of the game be developed which incorporate a variety of theories of man, the schools and the future from

the religious, conservative, liberal and communist perspectives.

10) The simulation-game SAFE incorporates a restricted form

of computer-participant interaction. It has been suggested

that the game could be made more responsive and educational

by developing techniques for more extensive interaction.

For example, the computer could turn on fiMs, slides and

tape recorders, control lighting and actually operate a model bank. The program could be designed so that students

could ask a wide variety of questions concerning why various

affects occurred and the computer wuuld sqpply appropriate ; answers. Visual display devices could graph the effects of every

decision and cunulative overall trends and totals. The decision

analysis could be extended to include a game strategy analysis

with comparisons to optimization runs. '

268
REFERENCES

^The persons most responsible for the early development and re- finement of the concept of simulation in educational administration

and its application to the training of educational administrators were

Daniel Griffiths, Richard Wynn, Dan Davies, and Harold NcNally at

Teachers College, Colunbia. The years 1957 through 60 constituted an exploratory period which tried to determine factors which accurately

described the behavior of principles involved in adminstrative behavior.

The first uses of these developmental efforts for instruction oc- curred in 1959 in the summer workshops chiefly for elementary principals.

The next year 232 elementary school principals from various parts of the

United States became principals in the simulated Whitman Elementary

School within the Jefferson Townships School System. The simulation

included 103 in-basket items, planned meetings, dated letters, filesi

etc. The simulation was later expanded in 1961 and 63 to include problen

for persons in roles of high school principal, director of instruction,

business manager and superintendent of schools. In 1966 it was revised

and updated by the UCEA and renamed Madison Township Schools sioiulation.

For a detailed history of the early evolution of simulation-games

in educational administration, see Dale L. Bolton, editor, The Use of

Simulation in Educational Administration (Coliambus, Ohio: Charles E.

Merrill Publishing Co., 1971). ~ . .

2The number of simulation-games which have emerged in educational

administration is very small. Most early simulations were e;q)loratory

exercises and not used widely. In addition to the UCEA games (See

Footnote 3), only four other games have been used to any extent,

John Horvat's "The Collective Negotiations Game" (John J. Horvat,

"Simulation of Collective Negotiations," in Bolton, mcit . , pp. 198-234),

Dale Bolton's "Simulating the Process of Selection of Teachers (in

Bolton, opcit . , pp. 88-148), and Kenneth Mclntyre's "Simulating the

Process of Selection of Administrators" and "Shady Acres Elementary

School" simulations (in Bolton, opci

t

, , pp. 149-170). None of these

games deals with the (fynamic interrelationships between schools and

society.

30nly a few attenpts have been made at developing ccrputer usage

for professional training by simulation in education. One of the first

to be built was the "University Administrators' Decision Laboratory -- 360 Version." It was a conputer based management game using a systans

model of a university. The model was restrictive, however, and has

been used only to demonstrate the potential of ccn^uter usage in the

field.

At the University of Texas at Austin a CAI approach has been de-

!' veloped for teaching administrative decision-making. It uses ccmputer-

: based feedback of the in-basket method used in simulations such as

j the Madison Township game

.

269
Cullinan and Ruoermaii developed a proto-type computer-based

simulation for the UCEA. Their purposed was to investigate the information processin;fc; and utilization patterns of administrators through

simulation of an administrative decision situation, but school

society interrelationships such as those in SAFE were not considered. - Still other computer simulations have been developed, but none

have been used widely and most are proto-type models of automated inbasket manual simulations. One exception to this are the specialized

research simulations beginning to emerge^ such as the McBride simulation

of selection policies of 28 junior college dean and presidents.

But they are not designed for instructional purposes. See Wailand

Bessent, "The Uses of Computers in Simulation," in Bolton, opcit.,

pp. 198-234.

The need for a computerized game dealing with the complex issues

of educational decision -making has been recognized by the UCEA, which

just recently received a grant from the Ford Foundation for developing

such a game

.

Although the educational objectives developed by the UCEA group

for their cimulation-game (which has not been developed yet) are very

similar, and in many instances identical to those the author has set

for SAFE, the games will likely differ considerably in their emphasis.

Vvhiereas the UCEA game will emphasize the intricacies of decisionmaking in the oaily running of the schools, SAFE almost totally ignores

this aspect of decision -making and focuses almost entirely on the interrelationships between schools and society and the probable long-range

social consequences of educational decisions and of social developments

on the educational establishment. Whereas the UCEA game will focus on "in-basket" problems, SAFE focuses on alternatives to the schools as they are today. See Walter I. Garms, et .al . , "Computer -Based Simulation

for Training Educational Decision -Makers," research proposal by the

University Council for Educational Administration, February, 1973,

p. 1. Non-published.

^For a description of this model, see L. W, Downey, "Who Shall Train

our Administrators," in D.E. Tope, ed., A Fo^a-rd Loojc: The Preparation

of School Administrators^^ ^^JP. (Eugene: Bureau df Educationar Research,

University of Regon,' 196'0) , p. 97.

The significance of this model is that it was one of the first to

suggest dimensions for analyzing educational functions for both persons

within an organization and schools within society. It suggests the

need to look for role and goal conflicts among individuals and

groups in schools and the need to analyze educational decisions in

terms not only of these internal needs, but in terms of the values,

ethos, resources, and power groups in the environment. It was a preconditional development for the implementation of systans

analysis to determine specific interrelationships and incorporate

them into a conceptual whole.

270
Unfortunately, the educational theorists have failed to advance

beyond the state which Getzels and Cuba reached 10 to-i20 years ago.

This early work showed the extreme importance of analyzing the educational

setting in terms of both structural and functional dimensions and in

tems of both the organization and the society. It suggests dynamic

interrelationships both within schools and between and society. But

empirical research to actually determine what these relationsips are

has been very slowly forthcoming.

^At present, the major approach to using systons analysis and

the drive behind the building of comprehensive models of school -society

interactions is the budgetary program called PPBS (Planning, Programming

Budgeting, Systems). Program budgeting, as it is often called, relates

the output -oriented programs or activities of an organization to specific

resources that are stated in terms of budget allotments, rather than the

traditional line -item basis of objectives, i.e., debt service, instructional costs, administrative costs, etc. By this technique of analyzing

the budget in terms of overall objectives of the program, it is possible

to assess the benefits of specific programs in terms of the costs involved. In view of this "revolutionary" accountability development,

Hartley says that PPBS "has resulted in better statements of school

accomplishments, more clearly designed program priorities, program

budgets, system-wide goals, learning objectives, evaluation criteria,

analysis of alternatives, information retrieval systems, and three to

five-year projections." See Harry J. Hartley, ''Educational Planning - Programmin^ -Budgeting: A Systems Approach (Englewobd Cliffs

, "J .J .V" Prentice Hall, 1968)

.

PPBS is a decision tool which is spreading rapidly in this

country. Between 800 and 1000 local schools were in the process of

implementing some form of PPBS in 1971-72. But a general lack of technical and financial support from state departments of education have

made its use primarily limited to a refocusing of the budget to program

objectives and a consequent neglect of explicit program evaluation,

generation of viable alternatives, and thorough long-range planning.

See Harry J, Hartley, "PPBS: A Status Report with Operational Suggestions,"

Educat iona 1 Technology , April, 1972, p. 19.

The critics of PPBS argue that it provides no technique for

evaluating the intangible results of education and it allows for no objective automated technique for reaching decisions which must include

hundreds of thousands of variables. One of the most interesting new

developments which is an outgrowth of PPBS to solve such problons is the

EPPBS (Educational -Planning -Prograjiming-Budgeting-System) recently

developed and tested by Sisson, Brewin, and Renshaw. EEPS is the product

of a three-year ESEA Title III study which began in 1967, completed in

1971, and since tested in six school districts and two county offices.

It is a significant improvement over PPBS by using new techniques for

planning and decision -making similar to those developed and used in SAFE.

See Robert L. Sisson, C. Edwin Brewin, and Benjamin H. Renshaw, "An

Introduction to Educational-Planning -Prograjiming -Budgeting System."

Educational Technology , February, 1972, pp. 54-60.

271
6 The simulation -game STAPOL is perhaps the most important work to

influence the genera? overall development of SAFE as well as both the

concepts and content'^of the edvents and socievents . Numerous weak- nesses were found in playing the game and simulation-game SAFE was

an attempt to correct some of them. See:

Dennis Little and Richard Feller, Stapol: A_ Simulation of the

Impact of Policy > ^i^.^H^s fflA fflA Societal Developments

upon the Quality of Life (Middletown, Conn: Institute for the

Future, 1970), Docunent #W -12.

Dennis L. Little, Richard Rochberg and Richard Feller, Stapol : Simulation -Game iManual (Middletown, Conn: Institute for the Future,

197 1) , Document #WP-13.

Dennis L. Little, Stapol: A.ppendix^ to^ the Simulation-Game Manual

(Middletown, Conn: Institute for the Future"," "1970)', Do"cument tfWP-lTT"

^DELPHI is another simulation-game on the future of society

which considerably influenced not only the edvents but also the

socievents and the general computer program in SAFE. It was this

simulation which showed how the ccmputer could be used to create

a game simulating the interrelationships between schools and society.

This game also suggested the concept of decision-making which changes

the probability of occurrence for social happenings. See Charles

E. Osgood and Stuart l&npleby, 'A Conputer -based System for Exploration

and Possible Futures for Mankind 2000," from Mankind 2000, edited by

Robert Jungk and Johan Galtung (London: Allen and Unwin, 1969), pp. 346

^Osgood and l&npleby based much of their work on the Kaiser

Alujiimun and Chemical Game called FUTURE (1966) . A copy of this

game was obtained by the author and played in several classes. The

game significantly influenced the development of SAFE through the

general developments it postulates and the concept of changing

probabilities of occurrence which are modifiable to some extent

by the kinds of decisions which are made today.

^hese futurist techniques were used extensively in the

development of the simulation-game SAFE. The edvents are scenarios

of possible future developments, their impact on society is the

result of future -history analysis and the use of cross -inpact

matrices, the impact on the evaluators resulted from a modified

delphi technique. For a description of these techniques, see Theodore J. Gordon, 'The Current Methods of Futures Research,"

in Alvin Toffler, editor, The Futurists (New York: Randan House,

1972) , pp. 164-189.

Herman Kahn and Anthony J. Wiener in their work, The Year 2000

(New York: The MacMillan Conpany, 1967) summarize the basic trends

of the western world into a "basic, long-term multifold trend" (p. 7)

toward an increasingly sensate, bourgeois, scientific, meritocaratic,

urbanized society, The simulation -game SAFE postulates that this

trend will continue, but recognizes that short -reversals of the

trend will also occur. The nature and concept of a "post -industrial"

society was also taken from Kahn and Wiener, p. 186.

272
An equivalent to this trend has been worked out for education

by Michael Marian at the Educational Policy Research Center at

Syracuse called "The Basic, Long-term Multifold Trend in Education,"

Marian suggests that the basis of contemporary and future tremds om education will be around the shift of the system from "closed teaching"

to"open learning" where the focus shifts from inputs to outputs, from

buildings to the community. The simulation-game SAFE directly postulates

the validity of this series of trends into the foreseeable future. Almost

every edvent in the game is an extension of its implications.

11 Six of the seven philsophical viewpoints postulated in the simulation-game SAFE were based on two works: Ralph L. Pounds and Jajnes R. Bryner,

The School in American Society (I^ew York: MacMillan Co . , 1967), pp. 486-487,

and Theodore Brameld, Cultural Foundations^ of Education (New York: Harper,

1957), first chapter. Brameld divides public value orientations into four

groups: Perennialism, Essentialism, Experimentalism, and Reconstruct ionism,

with the first two being conservative groups and the latter two liberal

ones. Pounds and Bryner accept these four groups but add two more which

they felt were active value positions not included in the other four: Social

Realism and Laissez-Faire . These various philosophies were reconstituted

somewhat for the simulation-game SAFE according to modern trends reported in

the literature. A seventh group. Biological Re constructionism, was added in

anticipation of emerging value trends which will result from the biological

revolution to come.

12 Each of the sixty edvents is based on literature which either

describes current innovative programs, reccmmends new ones, or predicts

developments which could be the basis of nevi programs in the future. Some

edvents have been primarily taken from single authors (though many others

suggest similar ideas) such as Christopher Jencks and his proposal for

voucher programs presented in Edvent 2 (See Education Vouchee's » A fiepp_^^_^o^

Finan£ijig__ElQ^

Center for "the Study of PubTic Policy, Cambridge,' Mass . OEO Grant #CG 8542) . Four eavents were based on ideas in Jolm Henry Martin and Charles H,

Harrison's work. Free t_o_ Learn: Unlocking and Ungrading American Education

(Englewood Cliffs: P rent ice -Hall , Inc., 1972), Other examples of significant influence of single authors are Ivan Illich and the Incidental

Education Proposal, Paul A. Miller and the Youth Town proposal, Sidney M.

Jourard and the Marriage Training School proposal, and Raphael Patai and

the Charter Myth School proposal.

Three studies incorporating technological and social forecasts were

extranely important in developing a majority of the sixty edvents in SAFE,

especially the last 30 which are highly controversial and predicted to occur in the distant future. The first two works, The Year^ j 0 00 by Herman

Kahn and Anthony J. Wiener (opcit , ,) and W. 0. Evans and N. S, Kline,

Psychotropic Drug s in the Year 2000 (Springfield, 111., Charles C. Thomas

Plblisher, 1971), are the products of American think-tanks which sponsered

conventions on the future of society. The last work. Sane Potential

Societal and Technological Developments 1970-2000 by Paul de Brigard and

273
Olaf Helmer (Middletown, Conn., Institute for the Future, 1970) is a delphi which incorporated a large number of professionals in recommending

its conclusions

.

Three aelphis which focused specifically on the future of American

education were very influential in the development of edvents in SAFE.

The first is a non-published delphi performed by Billy Rojas and obtained

by the author through Michael Marian at the Educational Policy Research

Center at Syracuse University (1971). The second was conducted for the

New 5^ork State Education Department and performed by Delayne R. Hudspeth

in 1970 entitled "A Long-range Planning Tool for Education: Focus Delphi"

(Bureau of Two-Year College Programs, June, 1970) . The third delphi was conducted by Marvin Anderson at the Institute of Government and Public

Affairs at UCLA under sponsership of the Charles F. Kettering Foundations

entitled "The Education Innovation Study,

American Behavioral Scientist , March, 1967, pp. 8--27.

Other works which significantly influenced the development of the

edvents are Dennis Gabor, Innovations : Sc ientific , Techno log ical and

Social (New York: Oxford University Press, 1970). Author Clarke,

Prophiles of the Future (New York: Haiper and Row, 1958), and Charles M.

Darling, Perspectives f_o_^, the 7 0

' s and. 80 's (An experimental forecast

conducted by the' NatTonaT Industrial Conference Board and the Opinion

Research Corporation, 1969)

.

^^ The concept of "revolution" in the game is not to suggest a violent overthrow of civil government, but rather the radical change of

influence levels of the educational evaluators over public education in

the community, A district educational revolution may result from rapid

change in state or national government organization, new legislation,

violent acts of students or special interest groins, or the new involvement of previously unconcerned power groups. It is assumed that with

"revolution" the entire district administrative staff is fired and

replaced.

274
A GUIDE FOR

SIMULATION DESIGN

Charles H. Adair

Professor of Social Studies Education

The Florida State University

Tallahassee, Flgr^da 32306

John T. Foster, Jr. Instructor of Anthropology

Florida A & M University

Tallahassee, Florida 32307

275
TABLE OF CONTENTS

Rationale and General Objectives

A Pictorial View of a Segnrient

General Bibliography

Segment I Segment II Segment 1 1

1

Segment IV

Segment V

Segment VI

Segment VII Segment VIII Segment IX

Appendix

An Introduction

Models and Theories

Pedagogical Models

Simulation Media

Assembling the Prototype

Developing Your Simulation

Evaluation Strategy

Observation

Field Testing

Evaluating and Improving

Your Simulation

A Complete Simulation

Obstacle Course

tit
FLOW CHARTS

Significant tasks related to the production of a simulation have been incorporated in a series of

flow charts. You may wish to consult these diagrams as you proceed through the guide.

Flow Chart Number Title Page

I An Overview To Simulation - Planning and Building '

; -

II How To Do A Flow Chart

III Building A Position Paper ' . *

. ;

IV Media Selection For Your

Simulation ,

'

V Putting Your Simulation - Together . ,

VI Preparing To Evaluate

Your Simulation

VII How To Make Observations

VIII Field Testing Your Simulation

IX Evaluating and Improving Your

Simulation

277
THE RELEVANCE OF SSMULATION

So often we hear instructors say that students aren't turned on by their studies. And they are right.

Students are increasingly anti-intellectual in their behavior which suggests that they are simply

revealing themselves more truly than their parents did. Kids want to do their thing. And is that a bad

thing? John Dewey said that "Education is knowledge put to use." When students are forced to read and discuss human events and social problems without enactive involvement, the teacher is depending too much on cognitive motivation. When students gain no experience in making

decisions, talcing predictable chances and acting on specific value choices they find their studies to be biand and unsatisfying. The claim for relevancy by simulators is one based on the dynamic

involvement of students in ways they enjoy toward serious academic objectives.

The mission of this "how to do it" guide is to further change in the social and applied sciences.

Hopefully it will accomplish this by refining the talents of potential designers of simulations and

yielding finished products. Such objectives are rather lofty since individual simulators are faced with

the structuring of knowledge, the application of learning theory and the appraisal of the utility of

media. Going beyond these, they are also asked to test their social inventions. Stepping through

this work is in effect a trip along the boundaries or research and development.

Applied theory is a concern in that a simulation is a dynamic mode! of reality. It is characterized

by form and function manifested in specified behavior deemed desirable by the simulator.

Simulations reproduce more expeditiously, with less possible danger and obsen^able results, what

happens in comparable situations in the real world— marital relations, economic bargaining, political

persuading, communicating, etc. Whatever its substance the simulation always involves cause and

effect processes at work. When these processes are competitive and result in some participant(s)

winning or succeeding over others, a game exists. In a game one has conflict but not destruction,

because the objective is to outwit the opponent.

To realize the intent of this guide, students are asked to inform themselves and test their theoretical

ideas and predispositions in a continuously adjusted sequence of laboratory experiences. These

activities include reading into several books, playing games, and writing position papers leading to the

systematic development and the appraisal of simulation prototypes. Of course, such an enterprise

demands considerable initiative, industry, and interaction with others.

The repeated experience of the authors using the guide in a university course, reveals the roles of

students and instructor to be similar in that a common interest and productivity is expected. Everyone

evaluates the performance and products of everyone else, formally and informally. The role of the

instructor, it is assumed, is that of a consultant and fellow investigator.

General Objectives for A Guide for Simulation Design

1. To provide experience in designing short simulations.

2. To relate theory to practice in matching conceptual models to content and learning behavior.

3. To become familiar with the literature and products of simulation as a part of the study of social and natural phenomena.

4. To experience in a laboratory oriented environment designed by students and faculty a new

teaching learning relationship.

278
The Reoccurring Structure of Thh Guide

Segment Learning is the general knowledge and ability to be achieved. ^

" Performance Objectives are those specific products and processes to be completed by students.

*

Laboratory Activities are those procedures which lead to achieving the performance objectives.

Enablers are those reading materials, films, games and teaching-learning aids to be used in the

laboratory activities and personal study. .

TO THE PERSON WHO IS WORKING ALONE

Many individuals wish to produce simulations for their own specific needs and have no opportunity

to develop skills in a formal situation. This guide is sufficiently structured so as to permit one to consider only the most crucial elements of design as he builds his own simulation, even if the

theoretical details are of small interest. Those who are doing this should read the Introduction and

Objectives to each segment and ask themselves "How important is this to me?" When an objective is crucial the related readings, laboratory activities and segment materials would be of high priority.

Should an objective be only of slight interest then the readings, lab activities and segment materials

may be given short shrift. A problem arises however in confusing what is crucial with what is easy. And the beginning designer

is well advised to take great pains to insure that his design possesses the essential elements of a good

simulation. The principle of "garbage in, garbage out" which applies to computer operations is equally

applicable here.

279
GENERAL BIBLIOGRAPHY

1. John R. Raser, Simulation and Society: An Explanation of Scientific Gaming, Allyn and Bacon,

Boston, 1969, 180 p. (paperback) (Good bibliography).

2. Sarane S. Boocock and E. 0. Childs, Simulation Games and Learning, SAGE Publications, Beverly

Hills, Calif., 1968

3. Clark C. Abt, Serious Games, The Viking Press, N. Y., 1970, 176 p.

4. Ronald G. Kietsch, An Introduction to Learning Games and Instructional Simulations,

Instructional Simulations and Co., 1969.

5. Michael Inbar (editor-in-chief), Simulation and Games, An International Journal of Theory,

Design and Research, SAGE Publications, 275 South Beverly Drive, Beverly Hills, California,

90212, $10.00/yr.

6. Clarice S. Stoll and Michael Inbar, "Social Simulations," The American Behavioral Scientist,

special issue, July 1969 published by SAGE Publications, Inc. 275 South Beverly Drive, Beverly

Hills, California 90212 (good bibliography).

7. P. J. Tassey and Dereck Unwin, Simulation in Gaming in Education, Training and Business: A

Bibliography, The Education Centre, New University of Ulster, Coleraine, Northern Ireland, July,

1969.

8. Paul Twelker, "Simulation: An Overview," mimeographed paper, Teaching Research, Monmouth,

Oregon, 1968, 48 p.

9. Paul Twelker Instructional Simulation System, A Continuing Book Oregon State University,

Printing Department, Corvallis, Oregon, 1969, 286 p.

10. Carl M. White, Sources of Information In the Social Sciences, Bedminister Press, Vreeland Ave.,

Totorva, New Jersey, 1964

11. "Instructional Methods and Techniques—An Annotated

Bibliography," Training Methodology Part III (ED 024 880).

12. Michael Inbar and C. S. Stoll, Social Science Simulations, Free Press, N. Y. 1971

13. Herbert A. Simon, The Sciences of the Artificial, The M.l.T. Press, Cambridge, Massachusetts,

1969, 118 p.

14. Western Behavioral Sciences Institute, 1150 Silverado, La Jolla, Calif., 92037. This group

publishes various bulletins and position papers on game use, research, and design theory, in addition to publishing a variety of simulation materials.

15. Simulation/Gaming/News, Box 8899, Stanford University, Stanford, Calif., 94305. A

newspaper-size publication dealing with both practical and theoretical considerations.

Particularly valuable for those in public school work.

16. A Guide to Simulation Games for Education and Training, David W. Zuckerman and Robert E. Horn, Western Publishing Co., New York, 1970. The most complete catalog containing

hundreds of game materials in a number of instructional areas; $15.00.

280
Introduction

I To most people simulation is a familiar process. It is the essence of planning ahead and

reconstructing the past as well as describing the present. When a class must leave the school building

during a fire drill, or a crew must practice its "abandon ship" routine, simulation is taking place.

* Recently the distinguished newsman, Eric Severied, "interviewed" Lord North about the British

I policies toward the American colonies (CBS, April 7, 1971, The American Revolution). This was done

,| very much in the same manner as previous interviews on television with President Nixon.

i| In this segment it is important to learn the special meanings of some basic terms to be found in the objectives. As you read they will become apparent. Yet it is important for you to begin to take

systematic notes pertaining to the segment objectives and the laboratory exercises. You should enjoy

the game and the debriefing, yet keep your guide in mind at all times as you observe what you do.

281
Segment I INTRODUCTION-Objectives

1. Simulators will be able to distinguish between simulation and other learning activities b\

accurately applying the concepts of game, simulation game and simulation in asking an(

answering questions.

2. Simulators will be able to answer correctly at least ten of the fifteen questions relating tc Simulation and Society in the quiz at the end of Segment I.

3. Simulators will be able to demonstrate effectively their knowledge of the relationship betweer

abstraction and congruence (detail and accuracy) by explaining to the satisfaction of anothei

student how one is contingent on the other in a 2 x 2 table.

4. Simulators will comprehend and apply the concepts of learning transfer, simulation fidelity

simulator cost and utility to appraise a simple and a complex simulation game.

5. Simulators will be able to justify the use of simulations by employing references to economy

visibility, reproducibility, and safety in discourse.

READINGS:

1. John R. Raser, Chapters I and II

2. Meredith P. Crawford, "Dimensions of Simulations," American Psychologist, Vo. XXI, #8, Auc

19, 788-796.

3. Meredith P. Crawford, "Simulations in Training and Education," paper presented at the NAT(

symposium on "The Simulation of Human Behavior," Paris, France, July 1967, 15 p.

4. E. J. McCormick, "Simulation," Human Factors Engineering (2 ed.), McGraw-Hill, New York

1964, 14 pp.

5. Andrew Scott, et al., "The Procedures and Uses of Simulation," Simulation and Nations

Development, John Wiley and Sons, New York, 1966, pp. 159-170.

6. Edward C. Stewart, "The Simulation of Cultural Differences," The Journal of Communication

Vol. XVI, «4, Dec. 1966, pp. 291-304.

i (

282
LABORATORY ACTIVITIES:

Preparatory tasks:

1. Read chapters I and II in Raser. Note the Glossary in this segment.

Laboratory Tasks:

1. Discuss the guide by oven/iewing the segments.

a. Note that reading is important to each part, but that individuals have different needs so they

may read different material.

b. It is the general obligation of participants to:

(1) Achieve the objectives using personal initiative. (2) Demonstrate curiosity and, be prepared, when one makes a personal commitment ahead

of time.

(3) Complete laboratory activities. (4) Meet performance deadlines as a matter of courtesy to other participants in a class.

2. Play a simple game or simulation: Seal Hunting, Manchester, Consumer, and Ghetto. The sources

of these games are listed in this segment. Note: Should the games Seal Hunting and SIMSOC not

be available, substitutions may be made by selecting a game producing rich experience in a simple

format and a game characterized by a complex, theoretically sound structure (in that order) for use in the laboratory activities.

a. Is it a simulation or a game?

b. Which type is it in terms of isomorphic characteristics?

Congruence is the degree of accuracy with which a simulation reproduces a total field. Abstraction is the degree of detail, or lack of it, a simulation includes in the reproduction.

Abstraction

(Detail)

High

Low

Congruence (Accuracy)

High Low

Type 1 Type III

Type II Type IV

c. How would you evaluate this activity in terms of:

(1) Economy

(2) Visibility

(3) Reproducibility

(4) Safety

Discuss the simulation game SIMSOC with the help of the manuals (Instructor's and

Participant's). A visual construct for SIMSOC is available in this segment.

Compare Seal Hunting or the game you have played with SIMSOC in terms of the following

model.

9W Low Fidelity of Simulation High High

Criteria SEAL HUNT SIMSOC

Learning 7 7 Transfer

Simulation

7 Fidelity

?

Utility ?

7

283
Be sure to read the flow chart ("An Overview to Simulation Planning and Building") before goir on to Segment II. It provides the conceptual pattern essential to the development of a goc

simulation.

Flow charting is a useful task, and people who are not familiar with it should try several of the own. Flow Chart #2, "How to do a Flow Chart" will be of aid. Upon completion of activities 1-5 and the readings in Raser's book, take the Quiz in this segmen|

See if you can get 10 of the 15 questions correct. You may use the glossary of terms to help yc during the quiz.

GAMES:

1. Consumer, Western Publishing Company, Inc. School and Library Department, 850 Third Avenu

New York, New York.

2. Ghetto, Western Publishing Company, Inc. School and Library Department, 850 Third Avenu

New York, New York.

3. Manchester, Abt Associates, Inc. 55 Wheeler Street, Cambridge Massachusetts.

4. Seal Hunting, Educational Services, Inc. 15 Mifflin Place, Cambridge, Massachusetts.

5. SIMSOC, Free Press. 866 Third Avenue, New York, New York.

284
GLOSSARY

Terms Commonly Used in Simulation Design

Abstraction

Congruence

Economy

Isomorphism

Learning Transfer

Piecemeal Simulation

Reproducibility

Safety

Simulation Fidelity

Simulator Cost

Skeletal Simulation

Visibility

Utility

The degree of accurate replication of details of (molecular) functions or

attributes of reality in a simulation

The degree of accurate replication of major (moler) functions or attributes of

reality in a simulation

The characteristic of saved effort and time that accrues to the user of the

simulation

A combination of congruence and abstraction to meet the objectives of the

simulation designer

A process of gaining a skill or a concept through a predetermined operation

A simulation of an important part of a larger function or condition, the part

being crucial in every detail The attribute of being accurately replicated over time and in different places

The absence of the dangers that would accompany a condition or experience in real life The degree of accurate replication of real attributes and conditions characteristic of that which is being simulated

The total of time, effort, money and materials invested in the development of a simulation by the designer

A simulation of a total set or system of parts wherein no single part is as crucial

as the whole

The characteristic of easy to difficult revelation of significant performance of

subjects using the simulation

The difference between learning transfer benefits and cost to the designer

285
Components

Personal Goals Power

Wealth

Popularity

Basic Groups

Basin Innovin Masmed

Empin

SOE Independents

POP

Judco

Public Programs

Research and

Conservation

Welfare Service

4 Regions

Red

Green

Blue Yellow

SIMSOC MODEL

(This may clarify some of the information in the discussion

or the manuals.)

Constraints

["Rules of Game"

[Natural I employment

simbucks

travel—subsistence death arrests

absenteeism

private— public

investment

NATIONAL

INDICATORS

LEVEL

(food—energy

supply)

(standard of

living) (social cohesion)

(public commitment]

Simbucks

Investment OUTCOM

TravelSubsistence

Death

Conflict Level T

SUBJECTIVE CONTROLS

Income level Degree of scarcity

Concentration of Power

Regional differences superimposition

cross-cutting

Prepared by Steve Wollard

286
Comprehend and apply

both substantive and pedagogical

materials.

B.Learn to structure knowledge with

a flow chart.

K.Write the necessary manuals and handbooks.

J.Choose attributes

for an instructor's handbook and a player's manual.

I. Select or prepare appropriate media.

Define essential entry skills and

competencies

M.

Prepare a Simulation

Evaluation

Strategy.

N.Write crude performance

objectives.

FINIS

V.Make the necessary

revisions in your

simulation.

U.Analyze the

data.

Flow Chart I

An Overview to Simulation Planning and Building.

287
c. u.

Select a substantive Describe in writing

topic and a > both the topic, or ^

ineoreiicai problem, and the explanation. position taken.

H.Make a gross diagnosis of student competency.

0.Describe in writing

what, when, and

how to observe.

T.Collect and tabulate your field data.

G.

Identify a target population.

P.Organize a Field Tester's Guide.

S.Retrieve the

Field Tester's Guide.

E.Draw a model of

the explanation and

state how it could

be incorporated

within a simulation.

n1/

Develop a Flow

Chart of your

tentative simulation.

Q.

Identify and

contact potential

Field Testers

\1/ R.Duplicate and

distribute the simulation media

to the Field Testers.

288
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289
SEGMENT I

QUIZ: Select the best response (10 of 15 is a satisfactory score)

1. A simulation is

4.

a. a special form of model emphasizing mostly fixed structural relationships.

b. a general type of model including most of their different forms.

c. a general type of model including mostly fixed structural forms.

d. a special form of model stressing the functional, operating processes.

e. a special form of model that exactly reproduces a theory.

Simulations have an advantage as a research tool in that they can develop the same situation on numerous occasions. This concept is included in which of the ideas?

a. reproducibility

b. visibility

c. economy

d. safety

e. evaluation

Theories and Models

a. are the same phenomena and interchangeable terms.

b. are different in that the models define the subject matter.

c. are different in that the theory states a structure but does not display it. d. are similar in that both define the subject matter and both display or exhibit its structure.

e. are different in that a theory may show a static phenomena, but a model may not. A high degree of isomorphism in a simulation implies

a. that it reflects, to a large degree, the situation being duplicated in the number of elements.

that there are many items in the referent system that appear as single units in the simulation,

that the model behind the simulation has an iconic form,

that the model behind the simulation has a mathematical form,

that the model behind the simulation has a verbal form.

5. Input Variables Output Variables

^ Result A

> Result B

The model above

a. would be appropriate for many laws in the natural sciences.

b. would not be a system at all since the relationship between 1 and 2 is not exact.

c. would be appropriate to show the complexity with which a social scientist is confronted.

d. would be appropriate to show a low degree of entrophy.

e. would be appropriate as a referent model.

6. Which of the following is a fitting description for the social science theories?

a. non-systematic

b. probabilistic

c. explicit relational

d. totally entropic

e. non-self-fulfilling

f. non-self-denying.

290
7. A piecemeal simulation

a. stresses a large portion of behavior but not intensively.

b. has problems in that all things are never equal and laboratory consequences do not reflect real

life.

c. has high validity in that field observations correlate well with them.

d. are not attempted in limited confines and "sterile conditions."

e. can't be combined with other small segments usefully.

8. A skeletal simulation

a. has a problem in that some significant variables may be left out for convenience or over-looked.

b. has a problem in that policy recommendations from it are ignored.

c. has a problem in that the situation being simulated may be overly simplified.

d. has a problem in that they are often attempted in the laboratory.

e. has many problems that are identical with those of a piecemeal simulation.

9. A game and a simulation

a. are distinct and separate "entities."

b. are different in that the former permit a manipulation of "units and relationships" for

competitive purposes.

c. are different in that the former has more procedures and constraints that are rigorously

defined than the latter. d. are similar in that they have the same degree of flexibility.

e. are freely interchangeable terms.

10. A theory may be expressed

a. in a verbal form.

b. in a mathematical expression.

c. in a model

d. in A and C, but not B

e. in A, B, and C.

11. Abstraction

a. harms the goal of complete replication during a simulation.

b. is the process in which data is selected for construction of a theory.

c. is the process in model building in which non-essential details of a theory are neglected.

d. is the process which helps lead to the goal of complete replication.

e. is a process that does not raise a question of adequacy or validity.

12. (A< >B)

The model above

a. implies a relationship expressed in probabilistic terms.

b. contains high entropy.

c. implies a relationship between variables that is typical of some social science laws.

d. is an ideal never obtained in natural science.

e. expresses a relationship found in primitive laws.

13. Visibility includes

a. the idea of reproducibility.

b. the idea that a theory makes meaning more accessible.

c. the belief that a simulation can make the phenomena more physically viewable.

d. the belief that a simulation's static model is easily definable.

291
14. Freud's theory rests on an unsound tenet because

a. he failed to express it in the form of an iconic model.

b. he failed to consider the zoo laboratory as an item of contamination.

c. he expressed his theories in a literary form.

d. he asked an incomplete skeletal simulation.

e. he used an inductive approach to theory construction.

15. Social science laboratory research and simulation _

a. have the same degree of reproducibility and reliability.

b. are different in that the former has a higher degree of reproducibility and reliability.

c. are different in that the latter has a higher degree of reproducibility and reliability. d. are different in that the former demands a greater degree of involvement.

e. are similar that they both are more effective than natural science research approaches.

J,,!,;

V

1

292
MODELS AND THEORIES

The task of simulating involves a first consideration—what do you wish to simulate? If you can

report what it is to another person you have achieved a big step. Most often neophites attempt to grapple with an idea that is too big or one that is not completely understood. Toward the goal of

specifying what one wishes to simulate the use of models can make a contribution. Once you know

more of models you can report what others have described and/or explained. These three processes are

difficult in themselves, and it is hoped that the laboratory activities help you in the matter. This whole enterprise, as a first step in simulating, is to get at the problem of structuring knowledge.

A variety of models, representing conceptual structure are included in segment II. The equally

important concern for syntactical structure is illustrated in the flow charting you have witnessed and

done. Syntax refers to the order in which things are sequenced and attempts to get at "what causes what to happen?"

When a game or learning activity is based on a conceptual model it is easier to make a claim of

validity. At least it is easier for independent critics to judge validity. If the conceptual components are

clear and ordered it is easier to conceive the simulation itself. Also there is good reason to believe that

the conceptual components will be easier to learn and retained longer by student participants in your

simulation after you build it and are putting it to use. There is an old saying that "you can't teach what you don't know." This is certainly the case in designing a simulation.

II

293
Segment 1

1

MODELS AND THEORIES-Objectives

1. Simulators will be able to illustrate the (Baser) concepts of abstraction, simplification, and

substitution through analogy to physical, semantic, and formal models.

2. Simulators will be able to identify correctly specific types of models employed in the film, "Model

Man" (Econ 12).

3. Simulators will be able to distinguish correctly among examples of reporting, describing, and

explaining.

4. Simulators will recognize the conceptual and syntactical characteristics of structured knowledge

in a position paper written by a simulator.

5. Simulators will be able to demonstrate their correct recall of a model by drawing it on the

chalkboard and defining its components and component relationships.

6. Simulators will be able to apply the Coleman Model of Social Simulation by applying it properly to a hypothetical social situation.

7. Simulators will recognize strengths and weaknesses in using specific interpretive models.

Readings:

1. John R. Raser, Chapters II, IV (Important)

Sarene S. Boocock, pages 13-104 (Valuable)

Edmund C. Berkeley, Computer Assisted Explanation, paperback, Information International,

Cambridge, Mass., 1967, 271 p.

2. Richard J. Chorley and Peter Haggett, Socio-Economic Models In Geography, University

Paperbacks, Barnes and Noble, 1968, 468 p.

3. James S. Coleman, "Games as Vehicles for Social Theory," Mimeographed paper, Johns Hopkins

University, Baltimore, Md., 1968, 20 p.

4. Joseph J. Schwab, "The Concept of Structure of A Discipline," The Social Studies: Structure,

Models, and Strategies, Martin Feldman and Eli Seifman (eds), reprinted from Educational

Record, Vol. XLIII, #3, July, 1962, pp. 197-205.

5. Ira S. Lowry, "A Short Course in Model Design," Journal of American Institute of Planners, Vol.

XXXI, No. 2, March, 1965.

294
LABORATORY ACTIVITIES

Preparatory tasks:

1. Read Chapter IV in Raser.

2. Study and take notes as you read "Specialized Considerations Pertaining to Theories and Models

in the Social Sciences." This is to help you ask questions whenever you need to do so.

a. Are the types well defined in terms of their properties, and value? Can you think of better

illustrations?

b. Are the sources comprehensible?

Laboratory tasks: .

1. Take notes during Model Man (a film produced in Econ 12) and then complete the form:

Note: The Econ 12 Course and Materials are to be distributed and sold by Addison and

Wesley Publishing Co.

Identifying Specific Models and Their Properties

Model

Type

Modeling Processes Name Abstraction Simplification Substitution

Physical

Semantic

Formal

2. Read the position paper in the Appendix. Be able to go to a chalkboard and do the following:

a. Draw a diagram that identifies the factors and relationships between the factors.

b. Describe the conceptual and the syntactical structures of the paper.

3. Examine the position paper carefully and search for examples of reporting (What?), describing

(How?), and explaining (Why?). We will compare them in Lab #2.

4. After examining the Coleman Model in this segment:

a. What type is it? b. Can you apply the model to help explain

(1) A graduate student's situation in being graded in a typical course.

(2) The forces at work on the president of a university.

(3) The position of a student accused of cheating by a teacher as he faces an administrator.

(4) The dilemma of a new prisoner who attempts to gain favor with his guards and the other

prisoners at the same time.

(5) The problem of a juvenile court judge who wishes to provide complete "due process" of

law to an offender, yet protect him from public view.

5. What is to be claimed for the Coleman model in aiding one to report, describe, and explain any of

the situations in #4 above?

6. Do you know of a substantive or methodological topic that has a puzzling or difficult dimension

that makes it hard to teach in conventional ways? If not, think hard and discover one. Then try to apply what you have learned about simulations and models so far to describe a possible

simulation. In the next segment you will be expected to put this into a written form. To

accomplish this you should start collecting pertinent references to your topic.

295
Specialized Considerations Pertaining to Theories

and Models in the Social Sciences

Most students of the social and natural sciences are comfortable with several styles of thinking and

the use of theory for purposes of description and explanation. Those who specialize in the latter, are most often teachers who must describe and explain with clarity if they are to be successful. As the

general nature of theory and model identification is revealed here, the next segment includes rather

specialized considerations which curriculum developers should consider.*

Cognitive Sources of Models

Instructors, like most laymen, have found history at its descriptive best to be interesting, at times

fascinating. Most often these materials, and those employed to teach social phenomena, are in a

literary style. Explanation in this mode is couched in the desires and goals of particular personalities,

their political organizations, and their interaction with the cultural environment. For the purpose of

theory identification and model building, the literary style provides slight help, as it tends to be bound

by specific details of time and place. A description of the start of the Great Depression, by

dwelling upon the activities which occurred in a banker's conference on October 28, 1929, cannot

be easily reapplied in a different setting and era. You need to know how it started. More abstract and general than the literary style, with a verbal attempt to be precise, is the

academic style. In this form or mode, tentative generalizations or "great" principles are'expressed and

supported by numerous examples. The particular instances of the doctrine act mainly to clarify it. Prominent examples of the academic style may be located in political philosophy, institutional

economics, and intellectual history. Being more precise, glance at Toynbee's/4 Study of History if you

have not done so recently. The utility of models drawn from this style is questionable since many of

the theories are not operational or testable. It is difficult to base a simulation upon someone's

sophisticated hunch.

The eristic style, possessing a strong concern for "proof," more responsibility observes the scientific method, logical comparisons, and information analysis. Most popular with behavioral scientists, this style is evidenced by the work of Pareto, Keynes and Pavlov. David Riesman and John B. Coleman are scholars who have employed it in more recent time. Examples of eristic reporting dominate the social science journals today and provide a great reservoir for those seeking theories with potential as pedagogical models.

Along with the eristic style, the symbolic style is possibly the best place to search for theories for our purpose. With a concern for careful measurement and precise logic, symbolic language is frequently employed. This permits mathematical comparisons and transformations valuable in meeting

Bruner's concern for the "wide, powerful applicability" of profound ideas. Many teaching techniques,

socio-drama, debating, game playing, and economic problem solving, are derived from this style.

Following the idea of adopting with less rigor, the contributions of psychometrics, sociometrics,

econometrics, etc., designers will find many theoretical explanations which may be their models for structuring substantive ideas. - Two other styles, postulational and formal, are too elegent for use in social simulation. Indeed they

are seldom outside of philosophy, psysics and mathematics.'

Kaplan notes:

. . . these various cognitive styles do not correspond to any classification of sciences

according to subject matter. The situation here is rather like that in the arts; the substance

of a work of art, what is actually in the work, is indeed shaped by and perhaps even

constituted by the style, but not the subject matter, the point of departure for the artist's creation. A romanticist poem or expressionist painting may be more likely to have one

subject matter than another, but that some subject-matter can also be treated in quite other

styles. More important, the cognitive styles presented above are by no means listed in order

"The authors are heavily in debt to Abraham Kaplan, to a lesser degree John Madge and Richard S. Rudner, for the substantive considerations in this chapter. Should the reader wish to read in depth the volumes by these three scholars, they are highly recommended and are listed in the bibliography.

296
as scientific merit, unless this merit is tacitly defined by just such a stylistic requirement.

From the standpoint of their contribution to the progress on inquiry these are good and bad

specimens of each of the styles . . . What might ... be said is that the list is in rough

chronological order of development in any particular discipline.^

Indeed, the problem of maintaining precision of thought and clear communications has vexed

instructor and researcher alike in the social and natural sciences. Theories have all too seldom been

accepted by instructors as course "content" due to the abstractness of their expression. Yet theories in model form, when brought forward, answer the question "put up or shut up" to all who are concerned

i with inquiry. Models have the characteristic of "testing" the theory from which they are constructed.

If the theory is "ill-defined, vague and uncertain", the matter cannot be easily missed by those who

would use it in the laboratory or classroom.

The model and its referent theory, must be complementary in that each possess the same outer

limits and factors within those boundaries. To the degree that this is the case, the model is isomorphic,

j This is the essential difficulty in drawing models from the literary and, perhaps less so, the academic

cognitive styles. The scope and factors are not clearly delineated. Even in the eristic and symbolic

styles, the problem is apparent; the teacher should take the warning suggested in Kaplan's concern for

sources:

... certain propositions may command assent, not because of the overwhelming weight of

evidence supporting them, but because of the usage of the terms in which they are formulated.

When this tendency is overlooked, we risk losing the substance of knowledge by grasping at its shadow. A mixture of tautologies and what have been called "fourinsic slogans" is mistaken

for genuine theory, and a program is accepted as its own fulfillment.^

Types of Models

j Models may be casually considered as being of two general kinds, those which explain the structure

I of a major idea and those which predict a result with the use of a major idea. The former may be best

suited to help students test their own understanding of a situation while the latter helps to do this and

more, to predict the outcome of the situation.

These two categories of models will suffice for many teaching considerations; yet, for those who

would be serious parties to curriculum design a more sophisticated definition is in order.

297
The Physical Model

This popular and commonly employed model demands isomorphic similarity only as an analogue; as a physical object it may function quite differently. Buddha as a god and as an idol are quite different

in functional reality. A railroad network and the analagous control system have the same scope and

structure except they are vastly different in size, material construction and function. The teacher's

globe and the earth, the baby and the baby doll, and an almost infinite number of other physical

models are easily identified. Models of decision making and game-playing components are not so obvious examples; yet, they are theoretical replications of real situations capable of projecting subjects

into the same decision as those in a football game, a business transaction or a legislative compromise.

The Physical Model

The Earth

Leadership

Roles In A Group

The leader in terms of some

criteria responded to by each member of the group (note

that each member has 2

choices and that an "A" was

selected by more than 2 members.

Mind or Organism Organism Person

Three Stages

Of Psychological

Development'*

Active Reactive Interactive > >

Development Development Development

298
The Semantic Model

As a symbolic or conceptual system possessing a clearly specified structure the semantic model

characteristically substitutes the reality of data, established measures of fact and opinion, for easier-to-manipulate symbols. Logical comparisons of various theoretical explanations are facilitated and the fallacies of apparently "good" explanations are highlighted. Also, it is possible to visualize

additional rational approaches to the solution of problems by using semantic models, because the

structure of a theory that "fits" a situation is exaggerated and simplified, one may bring forth the

recollection of similar (isomorphs) factors in a similar arrangement.

One example, of the use of a semantic model is the reconstruction of a changing economy in the

early stage of the Industrial Revolution in England. This was essential to the popular game,

Manchester, to allow students to learn basic economic principles at work in a historical setting.

Integration of knowledge is demanded as the student player develops both "a sense of history" and

reliable knowledge of given laws at work.

Perhaps an even more important quality of this type of model is the creation of a relative easy

framework within which to view the relationships of various factors or variables. As it focuses

attention and demands more precision than physical or literary similarities, one must be involved in what Donald Oliver has referred to as "tough-minded impericism."' The analogies presented by a teacher to a class must square with the condition under analysis; vague metaphors will not suffice.

The Semantic Model

Ecological Zones in City Growth^

Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 Zone 6

Business District Wholesale-Light Manufacturing

Workingmen's Houses

Residential Houses

Residential Houses

Suburban-Residential

299
The Formal Model

In the tradition of deductive thinking so important to economic analysis, a formal model provides a rigorous explanation leading to a logical conclusion of alternatives. The Malthusian theory of

population growth to a point of marginal subsistence, is one example. Social scientists wishing to simplify a complete problem and shed light on certain conditioners of human behavior are willing to sacrifice reality in large amounts by making such unreal assumptions, i.e., "all men act rationally

in their own behalf". As a result, it is possible to single out the most relevant conditioners and

processes of behavior such as in the cases of political decision-making or the investment of surplus i profit by economic firms.

I When establishing generalizations within a formal model, "all things being equal", satisfies more [ than a general desire to be precise. It solves the Second Canon of Logic posed by John Stuart Mill. j'

If an instance in which the phenomenon under investigation occurs and an instant in which

it does not occur, have every circumstance in common save one, that one occuring only in ! the former; the circumstance in which alone the two instances differ is the effect, or the

cause, or an indispensable part of the cause, or the phenomenon.''

The Formal Model

Population Growth Leads to Poverty ^

Assumption: Population increases geometrically while the means of subsistence increases

arithmetically.

Productivity reaches a point of diminishing returns as arable land is limited.

-X—Maximum level of subsistence (all a population can consume)

Y—Minimum level of subsistence (the level of poverty and starvation)

N— Initial Size of Population

N'—Size of population at minimum subsistence level a—Productivity per population N

b-a—Population increase

c-b—Production increase as population increased from a to b

h—A point of total productivity/Total population at minimum subsistence

300
The Interpretive Model

Frequently, In the process of reasoning about a social problem, one exhausts the rational

possibilities of explanation. Quite often the search for explanation gravitates towards a more general

explanation that has served in analogous situations involving quite different phenomena. When one can

isolate a different independent variable in an old theory and adapt the theory, an interpretive model is the result. Kaplan notes that "... its greatest merit is that is allows us to use what we know of one

subject-matter structurally similar to the first. A rather dramatic account of such activity is revealed

in the constant development of theory in psychotherapy.' ° An example, is that of the gatekeeper theory developed by Kurt Lewin.' ' The original purpose of

the field theory was to appraise the forces determining food procurement habits of American families

during World War II. Yet, the main use of the theory, suitably modified, has been to explain the power

of political gatekeepers, those individuals who open and close the channels of power and priviledge in government and politics. The original theory helped to determine O.P.A. regulations during the War,

and its model, to help appraise political action.

An Interpretive Model

The Gatekeeper Concept

Food At

Grocery

Seed At

Store

33o

< m

X

a

Buying Planting

Growing

o

>m

Storing Harvesting

On Table

301
FOOTNOTES

1 . For those interested, Kaplan's description will probably be the best source. Abraham Kaplan, The Conduct of Inquiry, Chandler

Publishing Co., San Francisco, 1964, p. 261

.

2 Ibid., p. 262.

3. Ibid., p. 273.

4. Biggs and Hunt, Psychological Foundations of Education, Harper and Row, 1962.

5. Donald W. Oliver, "The Selection of Content in the Social Studies," Harvard Educational Review, Vol. 28, No, 1, Winter and

reprinted in Edwin Fenton, Teaching in the New Social Studies, Holt, Rinehart and Winston, New York, 1966, pp. 98-1 13.

6. Ernest W. Burgess and Robert E, Park, The City, The University of Chicago Press, Chicago, Illinois, 1925.

7. John Stuart Mill, A System of Logic, p. 256 as quoted in John Madge, The Topic of the Social Sciences, Anchor Books,

Doubleday and Company, Garden City, New York, 1965, p. 53.

8. Thomas Malthus, An Essay on the Principles of Population, Reprinted in John Beatty and Oliver Johnson, Heritage of Western

Civilization, Prentice Hall, New Jersey, 1958.

9. Kaplan, loc. cit., p. 275.

10. Gordner, Lindsey (ed.). Handbook of Social Psychology, Vol 1 , AddisonWesley Publishing Co., Reading, Mass., 1954, pps. 82-95. n. Kurt Lewin, "Forces Behind Food Habits and Methods of Change," Bulletin of the National Research Council, Vol. 108, 1943,

pps. 35-6S.

302
APPLICATIONS TASK GROUP

FACILITATOR'S STATEMENTS

Applications: Research

Richard L. Dukes

Department of Sociology

University of Colorado

at Colorado Springs

Colorado Springs, Colo., USA 80907

Many of the most widely used simulation games have been designed primarily

as learning tools through which players come to understand more clearly something

about the referent system which the game mirrors. As learning tools, games have

many worthwhile advantages including, 1) they can be designed so that they

abstract only the most inportant aspects of the social systems which they model;

2) the simulated social systems which the games generate can be replicated many

times; 3) they allow players to actively participate in the simulated social

system; 4) they can allow for the expansion or compression of time, and 5) they

permit the players to experience potentially dangerous or costly social situations under conditions in which such risks are greatly minimized. These same characteristics of games which are advantageous for learning are also highly

desirable attributes of vehicles for social research. However, if social

research is to begin to take advantage of the strong points of simulation gaming

by tapping the wealth of the hundreds of simulation games currently available,

then procedures must be developed for converting existing games into products

which allow the gathering of data for testing social theories while still preserving the playability of the games. The use of games in social research does

not necessarily preclude their use as learning tools, as revised games probably

can serve both learning and social research purposes adequately.

In order to successfully use simulation games as vehicles for social

research, the social scientist must answer (at least implicitly) questions for

which working guidelines are needed. These questions include, 1) how does one decide whether a game is worth the work necessary to convert it from a learning

tool into a vehicle for social research, and how can the social scientist choose

between two games which seem to mirror the same phenomena? 2) how can the optimum

tradeoff be gained between preserving the original rules of a game (to allow com- parability between studies involving the same game) versus the modification of

the game rules (to better fit theoretical and methodological considerations of a current study? 3) since research procedures have the potential to destroy playability, how can the optimum tradeoff be gained between play-ability and adequate

research procedures? 4) is reliability a necessary condition for the games themselves as well as for instruments for measuring play of the games? 5) how does

one decide is a simulation game is valid enough to be used in social research?

303
MEDICINE AND SOCIAL WELFARE

FACILITATOR'S STATEMENT

JOHN T. FOSTER, Jr.

Department of Sociology, Anthropology and

Human Services

Florida A. and M. University

Tallahassee, Florida 32307

A description of the "state of the art" in medicine and social welfare should

always be a crude guess. This belief is warranted when many professionals are finding novel ways to employ published simulations while others are working on designs for new ones. Shouldn't this be encouraged?'.

Either situation, innovative utilization or writing, requires creativity. The

following categories are offered as starting points which could lead to

different perspectives and thoughts-- inputs for acts of originality.

STARTING POINT 1. The overs imple example . (Distort reality and drive others

to search for a more real state of affairs.)

a. This notion combined with a published simulation.

In teaching some aspect of medicine or social

welfare, select a simulation based i^on some poor

explanation of the phenomena. Play the simulation as intended by its author, and afterwards

have the group of learners chop it in

discussion.

b. In a new simulation.

STARTING POINT 2,

STARTING POINT 3,

The reversed subj ect . (Talk about heaven by first showing

hell.)

a. This notion combined with ? published game.

Instruction about "progressive" social welfare centers

might be started with a simulation which portrays the

worst state employment agency. Face the learner with

an outrageous but valid example.

b. In a new simulation.

The unexpected participant ,

a. With a published game.

Interesting things can result in using people in a simulation for whom the activity was not intended.

Patients in an outer office might kill time with a very simplified game originally intended for the

staff.

b. In a new simulation.

304
STARTING POINT 4. The crafty administrator . (A good watcher may learn)

a. With a published game.

Select a controversial, stress producing simulation

and have potential employees interact within it.

(Ignore the game's cognitive goals.) Observe how

these individuals respond both facially and vocally.

Valuable clues to attitudes and values can be

exposed.

b. In a new simulation.

STARTING POINT 5. The sudden stop . (Interesting comments can be generated when a tire blows out.)

a. With a published game.

Play a simulation long enough to expose a set of

circumstances. End it in the middle where several

alternative conclusions could be projected. Pemit

the learners to argue over rational answers to the

quandary.

b. In a new situation.

Questions, 1. Can you think of specific examples which would fit into

each category?

2, Are there other categories to be added to this list?

305
TEACHING -TRAINING: URBAN PLANNING

David E . LaHart

Environmental Studies Group " Florida State UniversityTallahassee, Florida 32306

The urban environment is a complex, ever changing system of interacting

forces. Economic, political, social and environmental constraint provide

a core of interrelated, interconnected and interdependent systems. At the

center of these systems are human decision -makers, acting individually and

in formal and not so formal groupings.

By examining the urban environment in sinrple planning conponents, it can be

understood despite this complexity. Rules and ethics well defined by culture,

underlie these systems. As systems tend toward balance, generalizations and

patterns become discernable. These provide frameworks for simulations.

Working models of urban systems for education and planning purposes can be

made to conform with real world patterns. The problem comes in designing

models and simulations that provide insights into functioning of the urban

system. And understanding the functioning of urban systems is needed for

sound urban planning education.

Several urban planning simulations are currently on the market. The earliest

of these are the METRO and METROPOLIS series designed to simulate a medium

sized urban area. These simulations emphasize the short range decision-making

in a framework of a capital improvements program, tax structure and elections.

Participants role play politicians, administrators, educators and businessmen

as part of the simulation. The Cornell Land Use Game (CLUG) investigates land

development, speculation and land use control by permitting large areas of

land to be developed while using available resources.

These early simulations spawned a whole generation of new ones. The computerassisted REGION and CITY games are based on a hypothetical urban area with a population of 300,000 and attempts to simulate the economic and political

forces at work. Todays educator finds an elaborate collection of urban planning

simulations ranging from NEW TOWN to Hubbard's elaborate URBAN SYSTEMS.

Today we must address ourselves to these questions:

1. To what extent is function simulated in existing games?

2. What are the major functions of urban systems?

3. How can these functions best be simulated?

4. Are piece meal or skeltal simulations most useful in testing urban

functions?

5. Values of simulation in discovering future problems before they occur?

306
TEACHING -TRAINING: -ELEMENTARY -SECONDARY EDUCATION

Facilitator: Harriet Elizabeth Arnold

Master's candidate in Social Studies Education

Florida State University

Tallahassee, Florida 32306

If we assume that the principle function of a teacher is to teach

some subject matter, attitude, or appreciation to someone or to some

group; then we should be spending more time studying the best methods

for teaching any particular subject matter, attitude, or appreciation.

If the method is effective it will change the behavior of the student

or the beliefs held by the student. The use of simulation games is one

of these possible methods. However, to justify the time and effort

spent in making a simulation game and the money spent by the school on

them, they must do the job of teaching certain material, attitudes, or appreciations better than any other feasible method.

The position of the facilitator is that any interaction between

people, or between the environment and people can be simulated with

enough congruence that it could be useful in the classroom. When teaching the interactions of persons with each other or persons with their

environment the least effective method is talking about that interaction.

Using films and demonstrations the students can see the interaction,

but the best method is participation in the interaction by the students

themselves. They don't watch it. They do it. It is not possible for

the students to make actual city planning decisions, or to interact with

another culture. They cannot go back in time and fight a revolution.

They can do these things in a simulation game. In the Promise of Land

the students migrate westward. They make the decisions on where to go

and the best route for getting there. In Seal Htoit the students hunt

for seal with other eskimos

The simulation game is not just to put the students through a useful experience. It must be based on a viable theory and should teach

some useful concepts. The game should be structured so that the student

must put these concepts into practice during the play of the game. We

expect change to take place in the behavior of the student as he plays.

The teacher will be able to observe easily this change without interferring with it. In Seal Hunt the students must learn the concept of cooperation and apply it in their play or die of starvation. In the Promise

of land the students must judge the plausibility of runors and stories

from other settlers. If they judge incorrectly they might settle in an area which yields only a subsistence level of crops.

An actual experience of a phenomenon is the best teacher, but the

simulation game can put the student through the same or close to the same circumstances in the safety of the classroom and with little cost

to the school , The teacher must choose carefully among the many games

available since seme are developed like commercial games with no proof

of validity.

307
COMMUNITY AND PUBLIC POLICY APPLICATIONS

OF GAMING-SIMULATION

Facilitator's Statement:

J. Robert Hanson, Manager

Educational Systems Division

Scientific Management Associates

Gloucester, New Jersey, U.S.A. 08030

Our subgroup, under the rubric of "Applications", is asked to consider

some of the uses to be made of games and simulations for community

and public policy determinations.

As members of spaceship Earth, we desperately need opportunity to

learn new roles -- as parents, as citizens (world/ country/state/county/

municipal) as educators, as human beings, as futurists -- perhaps as historians, and certainly as spokesmen for the "gentler virtues".

Public policy (a "white propaganda" term) is often neither of nor for

the public, but it is certainly policy. Perhaps games and simulations

are among the vehicles an awakened citizenry should choose to become

involved in policy research and decision-making. The process of involve

ment may contribute to a better future while it simultaneously teaches

us better applications for old roles needing resuscitation.

Issues for discussion might include:

. the utilization, through gaming, of non-elitist decision-making

structures in traditionally hierarchically directed institutions —

public and private (e.g., a school system or a church), and the

resultant conflict over authority sources

. the impact of community participation in identifying needs and v setting goals, e.g., municipal government, state educational

goal setting, relative to futures-planning, etc.

. the impact of gaming/simulation as a by-product in teaching

certain types of research techniques and systems approaches to

planning, e.g., the conduct of a needs analysis, etc.

• conveying values (e.g., participatory democracy, town meeting

revisited, educational activities/goals in light of costs —

referendums, etc.) otherwise lost, overlooked or rejected by our impersonal i zed and under-informed society

• the impact of simulations as a way of testing acceptable futures

and as a way to accelerate public policy decisions in critical

areas, e.g., humanizing the learning process, conserving resources,

developing an economic basis for peace, etc.

. the identification of critical social issues as a result of broad

coramunity participation in a planning/needs assessment procedure.

308
COMMUNITY AND PUBLIC POLICY APPLICATIONS

FACILITATOR'S STATEMENT

GEORGE M. McFARLAND

Co-Editor of Simulation Sharing Service

News I etter

221 Wi Mey Street

Morgantown, West Virginia 26505

It would seem to be a given fact that this task group should pool

its collective knowledge to at least list and annotate the simulations

that are now being used to either assist In the process of formulating

public policy or interpret that policy. My experience has shown that

simulations are being used in both areas.

My experience has been exclusively in the area of using simulations

to assist people in their understanding of the nature of their community

as well as the processes that are used for formulating public policy.

I am aware that simulations are also being used to aid decision makers

in their task of formulating their community and/or public policy

decisions.

There is indeed an overlap between these two defined areas that I believe is most important to keep in mind. It has been demonstrated

that as people become aware of how decisions are made and learn who

the decision makers are, they can become part of the process. This

indicates that one might introduce and adm.inister a simulation to

inform participants about a particular problem in the community and

later discover that the simulation has become part of a subsequent

decision making process. By the way of i I I ust rat i on, I et me use Metro-Apex. It could be used to inform citizens of the complexity

and problems of maintaining good air quality in an urban area only

to become the source of a speculative and corrupt real estate

operation.

In summary, I would see the task of this group being to identify

simulations presently being used to explain or assist in formulation

of public policy. After i dent i f i cat i on, a brief statement of their

nature and then a tentative listing of possible outcomes of their

useage. It would also be helpful to identify groups or individuals

who have been successful in their application of simulations to this

area.

309
ISSUES IN GAME USE: WHAT VALUES ARE CONVEYED

BY GAME DESIGNERS AND USERS?

PANEL MEMBERS STATEMENT

GEORGE M. McFARLAND

Co-Editor of Simulation Sharing Service

News I etter

221 Wi Mey Street

Morgantown, West Virginia 26505

To generalize about the values conveyed by game designers and users through the media of simulations one must first admit to all sorts of

exceptions to the general statements. Regardless of the exceptions and

special concerns, there do seem to be several statements that can be

made about values promoted by simulation games.

Being a theologican by vocation I shall make my observations

through a statement of faith that seems to emerge in some degree in all

s i mu I at i ons

.

Simulation Game Designers' Creed

If one can discover a system that explains or predicts certain

events or decisions there is a framework for a simulation game. When

the game is complete a participant may experience the simulation and

thereby gain valuable experience for dealing with the subject in the

future. Why? Because they will have a system for analysis and/or

act i on

.

People enjoy competition both in simulations and real life.

Games make no sense unless or until one can discover the "pay off"

and how to maximize the rewards. People want to know who or what

won

.

Time is a critical factor. People who waste time or have trouble

utilizing time will become losers and/or victims. Those who are sensitive to time and use it wisely have an advantage.

The imagination is an invaluable analytical tool. Much can be

learned if a person's imagination is stimulated and alternatives are explored. Simulation games reward imagination and encourage participants to experiment with different strategies.

The advantage goes to those who examine the past in order to

consider the present and plan for the future. Simulation participants learn that great satisfaction can be gained by future planning

and anticipating future alternatives.

310
Simulations encourage people to pay attention. Those wf^o listen

to and/or read instructions carefully are to be rewarded. Simulations

definitely develop the participant's awareness of the importance of

keeping an open mind, at least long enough to understand the situation.

These then are the values that I see simulations consistently

transmitting to participants.

311
FORMAL PAPERS

SIMULATIONS AMD GAMES AS GROWTH GROUP EXPERIENCES

Judith Foster Karshmer - University o£ Massachusetts

School of Health Sciences

Division o£ Nursing

Boston, Massachusetts 02116

Recent sociological literature addresses itself to the use of

simulations and games as educational teaching tools (Boocock and Schild

1968, Greenblatt, 1971) and as vehicles for systems based research.

(Guetzkow 1966) . Very little has been written regarding the use of

simulations and games as a potential means for providing personal growth

experiences for participants. The little that has been published (Jones

and Pfeiffer 1970), (Krupar 1973) more easily falls into the "Role Playing"

category and is limited, in that, the emphasis is on individual roles

rather than on interacting systems, the essence of the simulation model.

At the University of Massachusetts Division of Nursing an attempt is being

made to utilize, in its true sense, the simulation game model for personal

growth group experiences.

Historically types of collective experiences likely to be used as personal growth groups included, T-Groups, Sensitivity Training, value

clarification groups, consciousness raising groups and educational self

groups.

It is the hypothesis of this paper that simulations and games may well

provide an even more fruitful growth experience due to the inherent dynamic

interaction that occurs within a simulation.

The unique usefulness of games and simulations as growth group

experiences does not lie in the increased cognitive learning a student

may gain from participation or in a grasp of referrents for concept

learning. This may indeed occur but is secondary to the purposes and

priorities of this utilization.

Then what is a simulation game to offer participants? If the game

is to maximize an individual's developing an awareness of himself and

facilitate his sense of existential being, how is this to be done?

The experience uses as the most powerful portion of the simulation

game the debriefing following the playing of the game itself. After having

played the game a large portion of the time is devoted to discussion and a group session.

What kinds of things will be discussed if not the content and

principles of the game?

312
1. Who were you in the game? How did that feel? What facilitated such a feeling? What hampered such a feeling? How come you did what you did?

2. Who were the other people in the game? How did you view them? What

thought did you have of them? How did you feel towards them? What

was that feeling based on?

3. How does your perception of another participant affect that other

individual?

4. In the game, was there a difference in your thoughts and feelings of

yourself and others? How?

5. What did you do differently in the game than you might do on the

"outside?" How come? How did it feel? What made it easy/hard?

What changes would you make with the design to allow you to act

differently?

6. Who did you feel close to? Who did you feel far from? How come?

7. What did you learn about yourself? How does it feel?

8. What does this experience have to do with anything?

REASONS THAT A SIMULATION GAME IS SO WELL SUITED TO SUCH A PURPOSE.

1. Simulation Games vs. Role Playing

As mentioned before such a use of games and simulations is beyond

ii that of only role-playing. Role-playing requires an individual to take

I on a short, "one shot" situation with one other person. There is no chance

to try several ways in a particular situation, or to see others reactions

to various modes.

j It is often difficult to become involved in role-playing as one may

i not be able to make the connection between the oneself. In a game a structure provides a system in which one must interact. Although a role

may have been assigned, the manner in which one continually relates to

the structure, provides data to make connections and clearly see personal

! styles within the role.

II. Safety

A sense of "safety" exists within a simulation game due to the inherent

constraints placed upon participants. Such "safety" is often lacking in

other less structured group experiences. Participants always have the

option to see involvement as representative of personal styles or to interpret

it as a result of the simulation.

313
"Safety" is also apparent from the point of view that a competent,

experienced, growth group leader is available to facilitate personal

growth and circumvent destructive interactions. She is also concerned

with using the anxiety generated in a constructive way and providing a "closure" to the end of each session. In fact, such a case of games and ;. simulations ought not be attempted by the novice.

III. Life Planning 7,

Simulations and games provide the opportunity for students to function

within a system not yet familiar to them. This not only allows the student

to "fantasize" as to how things might be in the future, but also see the

consequences of certain behavior or values. (Example - marriage, childbirth, family/professional commitments.)

IV. Dynamic Feedback

The student participating in a growth group simulations and games is

offered the opportunity to experience the dynamic force of their own behavior.

Immediate feedback is provided. She may try out new behavior at will.

V. Fun

Often growth group experiences are seen as painful and anxiety producing,

Simulations and games lend credence to the philosophy that learning can

indeed be fun and that looking at one's own behavior is an enjoyable experience

VI. Relationships with Authority Figures

Participation in simulations and games will encourage the student to

investigate her own attitudes in regard to authority, and authority figures.

The consequences of such values will be discussed and evaluated. It is

hoped that a student will become more realistic and aware of her relationships with not only authority figures (i.e. teacher, parent) but also

authority in sense of rules/obligations.

VII. Group Dynamics (System Integration)

By virture of its definition, simulations and games set forth an operating

model, a dynamic system. This provides participants not only a chance for

individual growth and development, but a wealth of potential for learning

about the basics and essentials of group functioning. Not only how the ; group "works", but the consequences of such arrangements can be studied and

reviewed. Group effectiveness can be considered - a possibility most difficuH

to identify in more traditional growth groups.

As can be seen, the emphasis for simulations and games as a growth group

is on the individual learning about herself. The game itself, its content,

the situation it simulates is secondary to the goal of providing students

with a vehicle for personal growth.

314
Simulations and games will add a much needed alternative to more

traditional growth models. This proposed application is the first step

in unleashing the personal growth potential that exists in such a tool.

As more work is done and data accumulated the stronger will be the

contention: Simulations and games may prove a viable part of the techniques

used in not only teaching, but counseling and psychotherapy.

DEFINITIONS

Simulation: "An operating model of central features or elements of a real or proposed system, process, or environment." (C. Greenblatt,

"Simulations, Games and the Sociologist," The American Sociologist , 1971).

Game: "Any contest among adversaries operating under constraints for an

objective (a victory, win, or pay-off)" (Abt, "Games for Learning",

Simulations Games for Learning , 1968)

Growth Groups: "Experimentially based situations concerned with

reactions, responses, thoughts and feelings in experiencing the self and

others. The purpose being to provide the learner with more understanding

of herself and how to use herself in a deliberative way."

315
THE DISORGMIZED HEALTH CLINIC AS A SIMULATION

John T. Foster, Jr.

Florida A. And M. University

Tallahassee, Florida 3230?

Introduction :

This paper is a brief journey from the presentation of a problem and a model(

which explains it to a glimpse at a teaching sim-ulation. Through such a venture the applicability of simulation in the health area will be further

demonstrated. Should it provoke thoughts upon other topics for new simulations in teaching, the author will feel it served a useful purpose.

The Problem :

Individuals who have lived in or upon the fringes of medicine can always

cite accounts of patient ineptness and of patient bugling. Perhaps none

can be more devastating than when he has prescribed something for himself

as treatment. The spectrum runs from a migrant laborer's wife who con- I sumed "lead" pellets to induce an abortion to the yo\ing mother who fre- j quently inserted a tampax thinking it has some value as a contraceptive. I On a less startling scale, women—particularly among the poor and badly

educated—desire having families with several children, and end up with

considerably more offspring. (Children for whom little familiar resources

often exist.

)

The failure to abstain knowledge and methods of preventing conception is

found even in a setting where a state offers free counseling, information,

pills and I.U.D.'s to a target population of 266,632 childbearing age

women. (H.R.S. 19T3) The system of distributing family planning materials

through county health clinics (at least one in 6? different political units)' covers the entire peninsula. While this is the situation, of the 68,0^3

women who took advantage of the aid about will stop returning.

(H.R.S. 1973)

Data supports the .notion that many women wish to limit family size

(Chilman 1968), appear at clinics for service in the family planning area,

attend several times and then stop coming back. (H.R.S. 1973) Why. does

this happen?

Numerous explanations can be offered. Too few clinics, inadequate funding

for those in operation, personality and- social problems of the clients

are all possibilities. A portion of an answer lies in the structure,

organization if you prefer, of the delivery centers. To elaborate upon

this point requires examining a position taken by Robert Merton in the

field of social disorganization.

"Social disorganization refers to the inadequacies in a social

system of interrelated statuses and rol(=^^ qi.^t- <- ^ collective

purposes and individual objectives of its members are less fully

316
realized than they could he in an alternative workable system."

(Merton 196l:T20) "The sources of these deficiencies include such

topics as inadequate socialization of the members of the structure

implying a lack of necessary values, data, skills and the organization's failure to adapt to the social enviroment. Compounding these problems is likely to be a breakdown in communications

such that individuals do not understand the messages sent within

the system or fail to receive the correct ones. As this happens,

the situation is further complicated by divergent values and concerns among various groups within the structure. The structure

below is more disorganized than the one on the lower portion of

this page." (See Figure l)

functions

Figure I (Adair 1972: U)

These models are of help in explaining the current state of many health

clinics which provide free family planning information and contraceptives.

The following generalizations can be supported by statements that lend

themselves to an interpretation very congenial to Merton' s.

!l. ) Nurses and Doctors do not often undergo adequate socialization,

j Data, Statements, etc.

a. "One serious problem seems to loom above all others. . . it is

the lack of prepared nurses, knowledgeable in methods of con- traception and experienced in teaching and counseling patients

on human reproduction and birth control." (Edmands 1970 :l62)

b. "Nurses, along with others, harbor stereotyped thinking regarding

the poor, for example, that they have babies in order to receive

higher welfare payments, that they are uncaring about bearing

babies out-of-wedlock, or that they prefer large families. These

istereotypes , in turn, are linked to the low esteem some hold for

certain social, ethnic, or cultural groups." (Edmands 1970 :l6o)

3,17
c. "The social distance between the professional and the public can

be great enough to create problems. Sometimes it is difficult

to initiate and maintain a feeling of m.utual confidence, gain

rapport, or convey concern and respect." (Edraands 1970:105)

2. ) CoiTununi cat ions may break down between the professionals and the

target population.

a. "Program and clinic personnel should be wary of handing the

young mother literature and expecting it to meet all her needs;

because many women come from depressed school situations; they

often read and comprehend on a 3rd grade level. (A recent sur- vey of maternal health literature revealed that it is primarily

geared to a 10th grade reading level. )" (Parenthood in Adolescence 1970 :Ut)

b. "Professionals frequently discuss planning concepts that are unfamiliar to patients. Phraseology, sentence structure and

length, and word usage may also create problems in communications

Technical terms familiar to professionals may have no meaning

for the average person. Even simple words have different meanings among various populations." (Edmands 1970:105)

3. ) The clinics can also be viewed as being ill-adapted to the social

environment

.

a. The target population may be limited-excluding teenagers, the

non-pregnant, or the non-mothers. "About one-third of all teaching hospital obstetric departments and nursing schools approved

giving family planning services to unaccompanied and xmreferred

teenagers in 1966-67." (Edmands 1970:llii)

b. Many clinics are poorly located to the vast areas they are supposed to serve with deleterious effects. "One study found

that if girls had to travel very far to reach the program, they

dropped out." (Parenthood in Adolescence 1970:39) ....

c. Enough clinics operate during the same periods of the day as many governmental agencies that one concerned individual was willing to ask the following in a national nursing conference.

"Why are clinic sessions like banking hours, from nine to three

and closed on holidays? If we want to provide service for all

patients, especially the working mother, evening or Saturday

sessions are absolutely essential." (Edmands 1970:165)

Admittedly many agencies have been able to rise above some of these problems yet others have not. In any case, it seems appropriate to collect

all the difficulties mentioned in a single model which reflects a "disorganized" clinic. (Adair 1972: U)

318
Doctors Inadequate socialization.

Nurses Communications break.

Location & time of day cut off patients.

/ Regulations excluding teenagers, non-poor.

PATIENTS EFFECTIVELY SERVED Child bearing age women.

(Adair 1972:5)

Figtire II

The patient faced with interacting in this structure confronts a maize of

Iproblems (i.e. regulations, instructions which don't communicate, nurses

jvith curt remarks, and so forth). The obstacles in the way of patients

jand their typical reactions to them are important things to know if the

"national goal of every child heing planned" is to occur; frustrated

individuals go away.

'The Simulation

It seemed logical to design a simulation which would project a disorgan-

'ized health clinic displaying client quandries that delay or impede service, a group of verbal responses from "clients" to a chain of difficulties,

and a set of consequences for leaving the health care system. Several uses

for one are apparent. By having young college students (in social welfare

and nursing) behave as clients within such perimeters, insight can be

generated into why those who need and want aid avoid the system. A re- cognition of system impediments is started before the student begins work

as a professional. Hopefully this will help him to appraise actual

clinics more perceptively and from a different perspective (namely the

clients), to identify situations which can be subjected to change (appointment hours and etc.), and to understand with more empathy patient re- actions .

Media developed took the form of a game board with tlie following components or sub-portions. First, obstacles were presented as a series of

barriers between the health center and a starting point. (See Figure III)

319
start

Return to

Start

can not

go

Go Back 2

Spaces

You can not

ride a bus to the

clinic

Return to

Start

you have

no car to

go to the

clinic

.

Figure III

FREE

PARKING Clin:

(Adair 1972:21

Each of the ouandries, whether it is the area of transportation or comimonications, stops the client—a plastic object moved by a die and returns

hid to start. Mathematically the board was designed so that only a portion (one quarter) of the players make it to the clinic with any speed,

while about another quarter tend not to arrive at all.

As the client lands on certain difficulties, instructions listed in a player's manual and on the game board force the client to draw reaction

cards which express how they should feel (frustrated, angered, tired,

determined and so on) and what to say out loud. One states, "These people

pretend to provide services." The player reads this to himself and the

oral response to the group. " A paper shuffling idiot is behind this. . . " In other words a static set of obstacles is made more dynaunic.

Having often been delayed in reaching the clinic, forced into negative

comments, and "hasseled" by the role of one of the players—a "judge"

exists to torment participants as the social environment does somewhat

the client arrives at his destination. Being at the clinic does not promise the fulfillment of family planning goals. Here a second "obstacle

field" begins. "You need an appointment." "Sorry the doctor is busy."

"Your schediiled visit had to be canceled." (See Figure IV).

Clinic

Return to

the clinic

Ran out of

pills

.

Return to

the clinic

You did

not understand the

nurse'

s

directions

,

Figure IV

Go Back 3

Spaces

Doctor

made you

mad on the

2nd visit.

Health and

Planning Goals

(Adair 1972:22)

320
Having reduced its liabilities (i.e. redoing the player's manual three

times) and reproduced media, a larger, more rigorous test vas held in a local health clinic (Polk County Florida on September 25, 1972). Data

was collected both on a questionnaire created especially to measure the

simulation's summative objectives and an evaluation schedule previously

developed and standardized by the F.S.U. computer center (C.A.I.). Results obtained from a sample of h6 adults—25 Public Health Nurses, 11

Social Welfare Workers, and 10 others (paraprofessionals , midwives and

medical librarians) supported tvo themes. The simulation yields cognitive

achievement, as measured on a field testing instrument, and it produces

positive dispositions in social workers and nurses. Six members of this

combined group on an openended question expressrd reactions which could

be interpreted as being negative ("boring," "awful" and etc.) While 23

were favorable. (For more explicit details see "Obstacle Course: A Field

Test Report" by Charles H. Adair-Adair 1973)

From the Polk County data, yet another list of modifications was generated

and acted upon. The number of cards was doubled with those indicating a trip to "Dropout Road" being color coded; and a rule was revised. These

changes permitted a conclusion by the author, after further tests in Jacksonville and Gainesville, Florida, that nor design innovations are needed

in its present form.

Comments

"Obstacle Course" is a finished simulation which can be applied in a setting where a person wishes to instruct others about "disorganized"

clinics. All that it presently lacks is the collection of more empirical

data to further indicate the degree to which the simulation achieves its

summative objectives.

As a creation, the game's novelty probably lies only in its perspective.

Obstacle Course inverts a situation for young nurses and social workers

by having them behave in situations like their own future clients. It is

hoped that others will consider similar approaches where individuals act

out complementary roles rather than highly different ones. (For useful

purposes, interns could appear as orderlies, health educators as niirsing

students, and so forth.)

It strikes the writer that more consideration is needed for simulations

where lieutenants become privates rather than generals. Many great military commanders in history knew very intimately the state of their infantry. To fail to raises the specter of mutiny and "fragging". So too

if significant goals are going to be achieved.

321
Bibliography

Adair, Charles H. and John T. Foster, Jr.

1972 A Guide For Simulation Design. Tallahassee: Instructional

Simulation Design.

Adair, Charles H. 1973 "Obstacle Course: A Field Test Report," an Unpublished

paper which may be obtained by "writing to I.S.D. , Inc. , Box 3330 Leon Station, Tallahassee, Florida 32303

Chilman, C. S.

1968 "Fertility and Poverty in the United States: Some Implications

for Family Planning Programs, Evaluation, and Research."

Journal of Marriage and the Family. May 207-225

Edmands , E. M.

1970 A Report on the First National Family Planning Conference for

Nurse ' s Education .

H.R.S. (state of Florida Dept. of Health and Rehabilitative Services.)

1973 "Number of Indigent Woman of Childbearing Age in Each County

of Florida, and the N-umber and Percent Admitted for Child

Spacing Services by Method of Contraceptive From Monthly

Report of Activities of Florida's County Health Dept. Calendar

Year 1972." Memorandiim of the Bureau of Maternal and Child

Health.

Merton, R.

1961 Contemporary Social Problems. , ,

National Invitational Conference

1970 Parenthood in Adolescence. New Haven: Yale University Press

322
Real women at various points drop out of the state's program and so it is

in the game. A portion of the reaction cards tell the client to give up.

The player than transfers his "client" to yet a third set of trying situations; those things which might happen as a result of not "sticking it

out." (See Figure V)

Rest

Go Back 1

Space

Go Back 3

Spaces

Dropout

Road

Try Grand- Try lead

mother '

contraceptive

advice.

pellets to cause an abortion.

Get sick.

Drop out of

night school

because of

children.

_Rocky Life

Figure V

(Adair 1972:22)

Field Testing

Both a problem and a teaching simulation ("Obstacle Course") have been

briefly described. At this point, it seems logical to wonder". . . did

the simulation work?" To this over simple question the author could re- spond in similar vague manner, "No," "A little," "Somewhat," "Yes I" "Obstacle Course" has been field tested on six different occasions with

college students (undergraduate and graduate) and professionals in local

health centers. The first four tests were held at Florida State University

during the summer of 1972 in the Department of Social Welfare. These

early plays of the prototype were informal sessions composed of interested

students most of whom were working on master's degrees. (The assumption

being that advanced students would be harsher critics than the undergraduate target population. ) The students would convene in a classroom, read

the manuals, and play the simulation. While this occurred the author

simply recorded the errors and mistakes made and the questions which arose. After completing the game, the designer explained its intent and requested

their criticisms and comments (writing these as fast as possible).

Numerous difficulties happened in the first field test session: the

playing cards were too complex—slowing down the action, rules needed to

be added (situations happened for which there were none), and several instructions required rewording. As a consequence, the simulations objectives were not achieved due to the undertainty in the procedures and the

cumbers omenes s of the media.

The simulation was then modified between the first and second play based

upon observation and intuition. Likewise, changes were built in between

the second and third, and so forth.

323
SIMULATION AND GAMING AS AIDS IN REGIONAL AND

INTER- COMMUNITY PROBLEM SOLVING*

Herman Sievering and James Sinopoli

College of Environmental and Applied Sciences

Governors State University

Park Forest South, Illinois 60466

ABSTRACT

Simulation/games (hereafter S/G) have been in classroom use for some time

and are viewed by many as an effective teaching medium. Only rarely has

any attempt been made to use S/G as an aid in decis ion -making (Duke, 1973;

Feldt, 1973; Schran, 1972). In addition, the increased interest in citizen

participation in the decision-making process makes it necessary that S/G

be evaluated as a structure for involving citizens in the decision process.

The purpose of this paper is to (1) investigate the use of S/G as an implementable structure for involving citizens in community and regional

decision-making and (2) describe an ongoing attempt to evaluate S/G as an aid

in the regional planning and decision-making process.

INTRODUCTION

The basis for the theory and application described in this paper stems

from a societal need for both communication and a communicator of totalities.

Society exists as many different, overlapping, and multilevel communities in

need of a communicator of the interfaces between those subsystems as well as the subsystems themselves. In addition, the need for broader base decisionmaking originates and is perpetuated by a similar value structure. Within

that value structure is a striving for uniqueness, specialization, individualisi^ and independence.

*This paper has been submitted for publication in Simulation and Games .

324
The effect of that structure upon our mental processes is fragmentation,

I compartmentalization, and a complete lack of overview or comprehension of

a totality. For a community (people gathered together in a common locale,

or with common interests, or under common law, or with common privileges)

this value structure breeds narrower policy decision-making, disengagement,

competition, ignorance of interdependency , exaggeration of individualism,

, and generally "The Pursuit of Loneliness" (Slater, 1970).

Decision-making in communities is hindered at two crucial points:

(1) the framing and definition of problems (our failure to perceive or communicate totalities) , and (2) narrow decis ion-making processes (our lack

i of participation and cooperation) . Solutions to problems are limited by

: the definition and orientation of that problem. Simple solutions implemented

' to solve problems devined "out of context" actually complicate the problem.

They eventually are the cause for the epitomy of bad management, i.e., severe and unexpected repercussions. The lack of a comprehensive problem

i definition is reflected in most community decisions being reactionary rather

j than anticipatory. Citizen disengagement in the community decision -making

I process is also responsible for narrow decisions. To expose that process

I and to encourage citizen participation in that process, a public forum for

the education and involvement of citizens is needed. The environment

for the necessary public forum should be conducive to the articulation of

values and needs, exchange of ideas, amplification of differences, and the

building of tolerating relationships.

S/G can be used to fill the void left by both these needs. Simulation

j is a tool to be used in avoiding fragmented decis ion-making because its

replication of reality is more holistic. Viewing problems in a different

i| context, i.e., in a larger perspective, generates different and usually better

II problem definitions. Of equal importance to this characteristic of

i communicating totalities is the use of the gaming environment as a public

I forum for citizen participation. With proper instruction and guidance,

ij gaming participants can be made aware of alternative (and possibly more

optimal) decisions reached through broad base decision-making. Their involvement

; in a social laboratory tests cooperation, engagement, and a sense of community

ij as a means to produce broad base decis ion -making.

CITIZEN PARTICIPATION

Many governmental agencies and programs, social institutions, and

{i academic research projects are committed to the general principle of citizen

I' participation and involvement. EPA Director Russell Train in the keynote

address to the National Conference on Managing the Environment said,

i "Turning now to citizen participation, I will state may absolute conviction

that this is the single most important ingredient in the environmental

management process. The environment is just too important to be left to

I us bureaucrats". The demand for citizen participation in policy formulation

325
is on the upswing and many federal programs have specified the need for

its inclusion. A basic assumption of the American system of government

is that the best means for achieving long-term public support with minimum

coercion is to involve the public in the decision -making process (IMpleby,

1972). These same programs are, however, so constrained by specific

priorities and program guidelines that the result is an inhibition of

participation by citizens. The final users or consumers - the citizenry - can never really criticize, evaluate, and direct the development and

implementation of a product or process, so that it is of maximum

applicability to their needs . Without constant feedback from potential

users, any policy applications risk their relevance, accountability, and

credibility.

The dichotomy between the structure of an existing project, plan, or program and citizen determination and input into that structure exists

because of the ambiguity concerning citizen participation. Strategies

of citizen participation have failed mainly because the involved project

directors have: (1) no precise meaning of citizen participation, (2) no implementation structure as to how to involve citizens, (3) either lack

the resources or lack knowledge of what resources should be used to organize

and involve citizens, and (4) have not determined the extent to which

citizens will have a voice in decisions. It is the last point that strikes

at the dilemma in citizen participation; the demand for both participatory

democracy and expertise in dec is ion -making. In American society, symptoms

of such a dilemma can be seen in the alienation of citizens to their

government; students to their teachers, and consumers to industry.

What is needed from the inception of any program, plan, project, or institution is a continuing forum in which the expert directors and the

potentially affected decision-makers, community leaders, and general citizenry

can discuss and exchange ideas on the development and implications of the

final product, technique, or process. Such a forum permits effective and

fair reconciliation of diverse political and administrative interests.

It can also provide for local or subcommunity differentiation while giving

top priority to regional or community goals.

It is only through conflict generation, concrete discussions, and

argumentation that effective solutions to social problems and needs can

be explored. It is a characteristic of social needs and interests that they

cannot be articulated by isolated individuals who are exposed to collective

communication and direct confrontation with the situation which is under

discussion. The normal case is that the isolated interview can only

articulate his needs roughly and vaguely (Offe, 1969). A forum for

conflict generation and resolution is then needed for proper definition

of objectives and awareness of needs and values.

People know that effective participation and worthwhile involvement

can, happen only within guaranteed coherent, long-range, and well -coordinated

community programs which the participants and people concerned can easily

control by themselves, economically, politically, and administratively, so that the experts play a secondary role (Kuenzlen, 1972). A community forum

326
must be an ongoing autonomous activity. S/G offers participants an opportunity

to view the urban setting as people gathered together for mutual advantage

rather than a conglomeration of competitive and fragmented activities.

REGIONAL APPROACHES AND REGIONAL PLANNING

The gaming environment of S/G can be used as a community political and

administrative planning device. Within that environment, participants can

set objectives, decide on a means of attaining those objectives under the

imposed constraints, and if the forum is ongoing, actually evaluate the

results of their participation. The socio-political planning tool is

interfaced with a technical planning tool: simulation. Technical regional

planning involves assimilation of great quantities of abstract and technical

data, exploration of viable solutions, and an implementation and operation

phase. These technical planning phases must feed into and have feedback from

the complementary political planning phases. Technical planning usually

sinks under the weight of informative overload, and the inability to

interrelate that information. Modeling and simulation are tools to be

used in dealing with problem definition, informative overload, complex

interrelationships, and the regional planner's never ending search for

comprehensiveness

The characteristics of technical regional planning invite a systems

approach, systems analysis, and eventually modeling and simulation. Regional

planning is concerned with the order of activities and channels in space

and time. It is hardly ever concerned with the same space and the same

time; thus the specific need for regional designation within a time frame.

This gives rise to its features (and advantages) of being open and subsystematic, along with the methods and tools of the profession, modeling and

simulation among them.

SIMULATION

Large scale urban modeling has come under recent attack even

though its development is in an embryonic state. Lee suggests that,

"Contrary to what has often been claimed, what was learned has almost

nothing to do with urban spatial structure; the knowledge that increased

was our understanding of model building and its relationship to policy

analysis (Lee, 1973). Modeling must be viewed in terms of its assumptions

and Imitations, and in comparison to other communications and planning

tools. Model structure limits response of the system and solutions

to problems and disturbances of that system. By assembling a model with

real world data on the operational scale of the relevant system, one can begin to derive simulation of that model: (1) the relationships that appear

to govern the interactions and, (2) the areas within the modeled totality

where further research is necessary for comprehension (Commoner, 1973).

327
Urban simulation interfaced with gaming environments need not be

"hypercomprehensive," predictive, or on a macroscale (Lee, 1973). They

should be simple, descriptive, and aggregative, and be built with extensive

quality control. Simulation's contribution to gaming is the re -establishment

of an operational decision-making environment. A gaming environment offers

the context in which individuals can begin to communicate with each other

and learn how to interact with a "total" structure. Under today's conditions

where elaborate systems govern outcomes, the individual must either devote

considerable energy to establishing a context which permits assimilation of

torrents of information, or failing this, be deprived of full participation

in his environment. Without proper context he can neither comprehend his

environment individually nor enter into dialogue about it (Duke, 1972). ^

S/G AND A REGIONAL APPROACH

The thrust of the argument on the use of S/G for regional approaches

is that individual decisions in the gaming environment effect aggregate

behavior within the simulation and, in turn, it is the description and

attributes of simulated aggregates that are part of the informational basis

for the individual game decisions. Gaming participants intuit in the

context of a simulated totality. Any unexpected repercussions or "counterintuitive" results of the simulation are caused by the gaming

participant's lack of properly communicating with the holistic environment.

There are no "counterintuitive" results in a dialogue between an individual

and a system if the individual comprehends the total system. The regional

decision-making process (the feedback loop of individual decisions and

aggregated behavior) is well replicated in S/G.

Besides the exposure of the regional decision-making process, such

S/G reveals that good regional planning is dependent on the understanding

of aggregate location factors. Although location theory is couched in the

compu-er simulation, gaming participants are concerned with the relative

advantages of location dealing with the growth and form of their region. In

order to increase the probabilities of development in a desired location,

participants must clarify their objectives, weigh the attractiveness and

advantage of different locations, and design a means to influence behavior

towards that location.

The direct involvement by gaming participants in the crux of regional

planning (location advantages) plus their exposure to regional decision-making

is complemented by gaming 's ability to communicate the analytical technique

of simulation directly to the user audience. Gaming has the capability to

educate and motivate decision-makers to understand and use an interfaced

simulation in assessing alternative solutions to urban problems. In the

use of technology for regional problem analysis, the gap has proven too

large between the groups that quantitatively analyze urban problems and the

citizenry affected by these analyses (Thibodeau, 1973) . S/G can begin

to "teach" technology and its proper application. It is a vehicle for human

communication as well as communicating systematic thinking. j

328
APPLICATIONS

At Governors State University we are in the early stages of an. S/G

project which addresses both broad base community decisions and the avoidance

o£ fragmented decisions. Our efforts are aimed at (1) establishment of an ongoing forum for the education and involvement of citizenry in

community decision -making and the analytical tool of simulation and, (2)

avoiding fragmented growth through a gaming forum that promotes a regional

view of growth issues by being interfaced with a local region simulation.

Our concern over inter -community relations and fragmented growth arises

from our locale. The University is a new state university in the federally

insured new community of Park Forest South, Illinois. Both the University

and the community are in an embryonic state, with the population of Park

Forest South being only 4000-5000 and the University not even into permanent

facilities. There will be tremendously rapid urban growth in the area until

a saturation level is reached in 25-30 years. The new town is situated

in the south suburbs of Chicago which is - governmentally - one of the

most fragmented in the entire nation. Within a 20 mile radius of Park

Forest South exist 40 governments. With such a fragmented governmental

structure comes the concomitnat inefficient use of natural and human

resources. Couched in these terms it is obvious that good regional planning

is an important immediate need. The project goals are to promote regional

planning and to avoid fragmented growth.

I BIRTH OF A FORUM

Our first effort to establish a public forum in this community to

j promote regional planning, to avoid fragmented growth, to introduce

j community decision-makers to simulation, and to generally gain a community

i base, came at a series of workshops entitled Environmental Planning Workshops

j for Community Leaders (supported by OEE Grant 316-40-11) . Two series of

workshops were held with each series consisting of four workshops lasting 6

; hours and having approximately 50 participants in each. Participants were

j leaders in local government, business, labor, community action groups,

human service agencies, and legal agents.

Each workshop day consisted of two major portions: involvement in

Richard Duke's METRO-APEX in the morning, with the afternoon spent in

discussion of solutions to transportation, land use, and water problems

and the integration of such solutions. Although APEX and the discussions

were by themselves useful, it was the continuity between the two that was of importance. The discussion led to problem- solving approaches which

I could be tested in the APEX environment with the results from the game/

simulation fed into the discussion of alternative solutions (See Figure

1: "Workshop Logic Flow Diagram").

329
The first workshop was initiated with the challenge that the next

five years are the most critical to the future of Chicago's south suburbs.

The simulation activity was then introduced as the best way to look at - alternative futures by projecting ourselves through five years of our test ' community - APEX County. After an half-hour introduction to tlie simulation/ ^ game APEX and approximately an hour for introduction to their respective ! roles, participants completed the first of four cycles of APEX decision- ^ making that being 1973 decisions. i

Upon entering into the second cycle (decisions for 1974) participants' | understanding of their roles in APEX and an appreciation of the need to ^ allocate human resources efficiently was clear. However, coordination to

arrive at cooperative decisions was still not emphasized. By the conclusion

of this second cycle the mood was ripe to point out the need for clear ^ cut guidelines to foster cooperative decisions. Thus, the functional

' discussions following this second cycle of APEX focused on essential elements ^ of policy planning. It was at this point that the continuity between the

functional area discussion and simulation first was fully recognized by

some of the participants, for only at this point was the simulation appreciateas a true testing ground for policy planning. ^'

Upon entering into the third cycle (decisions for 1975) , simulation ' as a tool to test strategies, to test implementation of regional planning ij policies, and to look at alternative futures was appreciated. Having [ in hand guidelines for regional planning in the respective functional areas

of transportation, water, and land use - each participant began to develop

strategies for implementation from the perspective of his own role.

Two salient facts became evident at this point. First, the cooperation

across roles was essential to any implementation program. Second, that ' planning by functional areas was not sufficient. The focus for functional ' area discussion then became: |i

1. What is the state-of-the-art in the planning for each functional area'

2. How can functional area plans be integrated? and

3. How do we plan in a more holistic fashion? J

The fourth and last cycle (decisions for 1976) became an attempt

to implement integrated or systems planning with a follow-up discussion

focusing on implementation strategies for the regional planning guidelines

developed in the previous discussion. Tliis last discussion brought forth

the need to use simulation on a continuing basis as a tool in promoting

the regional planning guidelines. The presentation of the need for an interpretive scheme for regional data further supported this point.

The results of the workshops were: (1) the introduction of a public

forum and simulation to the community; and (2) the development of planning

guidelines for the south suburbs of Chicago.

330
(The Workshop series with concurrent APEX runs also offered a normal and < experimental audience to conduct research. We took advantage of this

opportunity by conducting an experiment involving the use of the gaming

environment as a social laboratory to test a representation structure as a means for better communication, articulation of values, cooperation, and

more optimal decision-making. With only one of the two concurrent runs

of APEX having this representation structure, both gaming decisions, and

participants' interests and demands wer monitored and compared. Evaluation

of this comparison between the two runs indicated truth in both hypothesis

and theory; a representative structure breeds cooperation and better

decision-making, and the gaming environment is a useful social laboratory).

After evaluation of the spring workshop, efforts have shifted

to three fronts in preparation for the next series of workshops. These involve:

(1) a local region simulation, (2) modification of the gaming environment,

and (3) further community involvement.

In process now is the conversion and recalibration of the APEX data

base and computer simulation. APEX is particularly well suited to a simulation of Will County (the County just south of Chicago's Cook County)

' since it has a population centrally located in the county (the city of

j Joliet with a population of 80,000) and a total population of approximately

j one -quarter million. Thus, APEX's central city becomes Joliet and the

i city/county political structure of APEX overlaps well that of Joliet/Will

I

County.

It is considered essential that Will County citizens and decisionj makers be integrally involved in this converison process. Unless this

[ happens the finished simulation will have been developed in isolation with

no community people aware of the simualtion model assumptions and limitations.

This can only lead to failure in the long run for inappropriate

I questions (i.e., questions not recognizing the assumptions and limitations)

v\^ill then be addressed to the overall simulation/game when community decisionmakers are later exposed to it.

I At Governors State University we are now holding a sequence of courses

to: (1) complete the data base collection, (2) continue the process of

! involvement of community people, and (3) validate and verify the resultant

Will County APEX. In the first of these courses a mix of students (2/3)

and community people (1/3) will change the gaming data base and

familiarize themselves with the simulation models. In the

second course, more community people will be involved with several students

observing the responses of Will County residents to their roles in the

I changed simulation/game. Follow-up courses will be aimed completed

at community people.

I Validation of data for sub -model internal consistency will occur

during the first of the sequence of courses. A two-level verification

program is intended. The major simulation model - the Lowry urban growth

model - is being evaluated through an independent simulation program on

the city of Joliet and its immediate surrounding environment (which accounts

for most of Will County) . The second and larger level of verification will

begin in the second of the sequence of courses with observation of the response

of Will County residents, observation of the fit of the overall data base to

331
Will County itself, and, most important, examination and evaluation

of the fit of a five year projection (1970 to 1975) to the real county

environment. For the simulation to contribute to the decision process

it need only be operational and have macroscale accuracy.

It is considered important that the second of three fronts - modification of the gaming environment - be dealt with. Hardly any :r computer or manual simulation has yet allowed for the necessary depth

of interaction with the data base to succeed in the involvement of

community people to allow S/G to be functional and practical aid in decisionmaking. A computer game like APEX needs much more visual aid to

complement the large amount of numerical data available to the gamer.

The use of visual aids as found in the manual games C.L.U.G. or W.A.L.R.U.S.

are very helpful but may still not be sufficient for the job (Feldt, 1973).

We are soliciting the aid of our instructional communication and support

staff to develop films, graphic arts, and other visual aids to complement

the lego block visual of manual games. In the future we hope to use

P.L.A.T.O. terminals (Umpleby, 1972) to move the gaming environment into

the homes of Will County decision-makers.

Of course, these efforts will be of no real value unless people from

the region being simulation and gamed take an interest in this project.

The spring '73 workshops were a first step in this direction, the

sequence of courses is the second step. By the end of this course series it

is anticipated that twenty to thirty Will County residents and decisionmakers will be actively involved. It will be at this point in time that a second workshop series is planned. Invitations to general citizenry but

particularly to city and municipality managers, township supervisors,

planning and environmental protection office staffs, and business/industry

as well as land developer/realty representatives will be appropriate.

Projection beyond this stage is difficult, but it is hoped that the

Will County APEX will have "taken root" and become an accepted aid in

regional and environmental decision-making. In particular, an effort to involve

the Will County Regional Planning Commission will be made. Achieving a broad base of involvement would then be important, with highest priority

being placed on general citizenry use - thus addressing the felt need for

a public forum.

CONCLUSION

A rationale for S/G as an aid in public policy decision-making on

regional and environmental issues has been given with the suggestion that

S/G can best serve as a public forum for the generation, discussion,

and resolution of these problems - particularly considering the increased

interest in citizen participation in the public decision-making process.

The description of an attempt to achieve this task in Chicago's south

suburbs has focused on the process of community involvement. Successful

integration of S/G into community decision-making will depend upon the

depth of involvement of the user at inception, during, and in the terminal

phases of such an endeavor.

332
REFERENCES

CCMONER, B. (1973), "Alternative Approaches to the Environmental Crisis",

Journal of the American Institute of Planners , May, 1973: 147-162.

DUKE, R. (1972), "Gaming/Simulation - A New Communication", Paper at the

Third International Conference on Gaming/Simulation, Birmingham,

England, July, 1972.

DUKE, R. (1973), Personal communication on the use of APEX in Hawaii,

March, 1973.

FELDT, A. (1973), Personal communication on the use of W.A.L.R.U.S. in

Traverse City, Michigan, March, 1973.

KUENZLEN, M. (1972), Playing Urban Games , I Press, Inc., Boston.

LEE, D. (1973), "Requiem for Large Scale Models", Journal of the American

Institute of Planners , May, 1973: 163-178.

OFFE, C. (1969), "Sachzwang und Entscheidungspielraum" , Bauwelt, September,

1969: 476-489.

SCHRAN, H. (1972), "Urban Systems Gaming - Development in Germany",

Simulation and Games 3: 309-328.

SLATER, P. (1970) The Pursuit of Loneliness , Beacon Press, Boston.

THIBODEAU, R. (1973), "Who Reads the Output", Modem Data , January, 1973:

48-51.

UMPLEBY, S. (1972) , "Is Greater Citizen Participation in Planning Possible

and Desirable?", Technological Forecasting and Social Change , 4: 61-76.

333
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334
PAYING THE PIPi:!:ii or PAY US AGAIN, SAM!

Stuart Cipinko

Uni'^'ersity of Redlands

246 Fourth Street

Redlands, California 92373

"Metanoia, Man makes himself not in his own ima.c^e , but

in what he understands to be his best imaq;e . Simulation

f?;ames can provide fresh imap^es by which people can live.

This will call for a . . . tranf ormat ion of the whole

simulation milieu... a new level of consciousness for a

theoloo:y of liberation." (Wilcoxson Washburn, 1972)

Phis quote appears in the second issue of Simulation/Gamingr/News , the house orphan of the gamine; community. It sets out very clearly

the normative paradiffjm in which many of us who use simulations

labor--g:ames are an accent of, and a vehicle for, radical social

chane!;e. i'hey are not neutral models of reality, but crucibles

in which new, and hopefully better realities, mie^ht be forged.

Implied in the statement is a philosophical commitment which

transcends the merely instrumental use of simulations as tools,

a metaphysic which places praxis above practice, metamorphosis

before technos . Appropriately, the article in which these

sentiments appear is entitled " I'oward a L'heology of Simulation/

Gaming.

If this ultimate concern with values were a dominant theme on

the current gaming scene, this paper would have no purpose.

But unfortunately, and I think tragically, it is not. Since

May, 1972, not a single article in S/G/N has examined the value

implications of simulations; moreover, an examination of

Simulation and Games reveals that in the three year history of

that .journal, no serious consideration of the ethics of gaming

has been manifested by any of the contributors. If these

.iournals are at all an indication of the present state of mind

in the field, then its practitioners have suffered what is, at

worst, a loss of nerve (in its most pejorative existential

sense), or at best, a disturbing dissolution of critical selfconsciousness . This paper, analytical in its form, but frankly

polemical in its intent, is an attempt to call back the good

in us from our immersion in a dangerous and insidious evil.

No human enterprise is conducted in a vacuum. Every human

activity takes place in a social milieu which gives form to

and imposes constraints on the exercise of creativity. There

are three aspects of our current milieu which have especial

importance for that form of activity called science, of which

simulation and "-aming are a special case: consensus, success,

and history.

It is by now a commonplace that the conduct of normal science

transpires within, a conceptual paradigm about which there is

335
minimal debate; the fact that soience is done at all is proof

that a consensus exists rec^ardinp: the basic features of the

world to which scientists turn their attention. Jut the rcround

of bhat paradi-;m is not. contrary to the canons of science,

empirical; it is rather, metaphys ical--a shared under standinp;

about what "reality" is essentially like, and about the proper

methods one must use to correctly understani that reality.

Smpii^ical evidence, then, is nob so much a support of the

paradip:m as a result of it. (Kuhn, 19'^?)

It is not difficult to discern a parallel situation in the field

of simulations. rhe literature on simulations and c^amin?^ concentrates overwhelminpcly (I am tempted to say totally) on tv/o

thinc!;s--the creation of nev/ forms (the hardware, if not the

currency, of the discipline), and the evaluation of the insbrumental efficacy of those form.s, e.-^. how does it chan^^e the

behavior of those involved, ho^^^ much (only in a very limited

sense what) is learned, what is its value for future research?

Phese, of course, are not unimportant considerations, but these

questions could not even be asked if there were not a prior

(perhaps a priori) understanding^ that simulations are supposed

to be usejful, that thev are, in fact, means to a s-reater end.

And it is in this conception of simulations as means that the

heart of the paradip-m lies.

A means-end relationship is not merely (or even primarily) a

lop:ical imperative; it is, rather a technical necessity. the

notion that means and ends are separate cognitive cater':ories

is the product of what Jacques Ellul has called "technique

consciousness," which develops in "a world once criven over

to the pragmatic approach and now beine- taken over by method"

(Ellul, p. 15). i-'echnique is, in Ellul's words, "the m.ind of

the machine;" it is "the translation into action of man's

concern to master things by means of reason. . .make quantitative

what is qualitative ... take hold of chaos and put order into

it." (Ellul, p. 43) In this process of rational mastery of

chaos, all value questions are reduced to a single consideration:

does it work? If the answer is affirmative, all other questions

become irrelevant.

If the literature on simulations is an accurate reflection of I the sentiments of those who practice them, then it is clear

that we have become prisoners of technique. We are purveyors

of a new technology, and the form of that technoloc^-y (the

very fact that it is technology) compels us to adopt the world

view in which all things are measured by their efficiency, all

worth determined by a narrowly defined "usefulness." And so

we concentrate on improving our delivery systems and perfecting

our feedback mechanisms, with efficiency as our guide, and a

naive understanding of productivity as our goal.

336
All of this would be of little moment if the subiects of our

efforts were non-reactive entities like molecules, or unfeeling;

forces like ener""v and inertia for which the tools of a technoloQ-ical society were expressly desi,n:ned. Fiut our subjects

are people; our techniques are employed on those whom, when

we are not acting; as professionals, we normally treat as worthy,

self -respect in^r individuals. As professionals, however, caus^ht

up in the heady power which sophisticated techniques ^ive us,

these Deople become ob.iects to be manipulated. Ho matter how

open the ^ame form, no matter how non-authoritarian the facilitator, the unequal distribution of knowledge in a framing- situation places the ^ame director in a potentially manipulative

position. It is in the debriefinp;, where the learninp; should

take place, that the manipulation is most subtle and most damap;-

in£r, as the facilitator tries to draw the participants into an

understandinp- of their experience that reflects his or her own

interpretation of what happened. I'he most henifr^n motives in

the world do not chane^e the fact of differential power, and I

wonder if even the most saintly araons; us has the right to force

people to be free.

Ch/s manipulative capacity, and the technical consciousness which

impels it, would not be so danp:erous if the lar,?:er society in

which it operates were inimical to its exercise. If we were

forced to fi,o:ht for our rip:ht to manipulate, we mio^ht be more

inclined to think seriously about what we were doinp-. But

exactly the opposite is the case. It is no accident that simulations and p-aminp" are now the callin=;-card of "innovative"

education; it is no accident that "radical" educators are employ

I ins: shames as teaching': tools almost As fast as they can be turned

' out; it is no accident that the a?-ents of corporate capitalism

I are incorporating: simulations into mana?^er training programs;

and it is certainly no accident that substantial government fund

ing is ?-oing to those who produce and refine the tools of the

I trade

The coming of age of simulation research dovetails nicely with

the coming of ap-:e of behavioral psychology. Both are presented

as a radical departure from traditional methods of learning and

knowing; both emphasize heavily the technical innovations which

make the new approach possible; both insist that the burden of

change be shifted to the subject from the expert; and both talk

about behavioral modification as if that label described an

i unmitigated good akin to divine revelation. And both work--if

one goes through the right steps, follows the guidelines, uses

the proper iarcron, one gets results. Call it insight, call it

learning, call in conditioned response--one gets change , and

that's what counts.

I But chancre is not necessarily either radical or good. Change

337
supported by those very institutions most dedicated to preserving the status quo should be immediatelv suspect; only a

political naif can really believe that the master institutions

of a society would work deliberately to undermine their own

existence. Simulation research is supported because it creates

a kind of chano'e peculiarly resonant with the ideolo-^y of a

liberal, technolop:ical state--quant itat ive chani=!:e rather than

qualitative, chanR:e an sich rather than chan^^e fur sich .

The only thinp; more damanring to the morality of an enterprise

than ab.ieot failure is success. Success is the most obvious

kind of positive reinforcement; it tells us in the only terms

our society allows to understand, that what we do is good.

And since this validation reinforces our own self -percept ion

(no one wants to think that what she or he does is bad) , we

continue to do that for which we are rewarded, we accept other's

definitions of the good, and we cease to question our own

activity. We are, effectively, bought off.

None of this shou.ld really be surprising if one considers the

historical background from which the present state of the art

arose. It is a notable fact that developing sciences tend very

quickly to forget their origins. In their preoccupation with

the present, the practitioners of a new science search frantically for respectabilitv , and rewrite their histories to more

closely correspond with the enlightened understanding- to which

they aspire. So physics and chemistry do not dwell on their

beginnings in alchemy and magic ; economics downplays the importance of its early philosophers to concentrate on the newest

developments in stochastic analysis; sociology forgets its

genesis as the reactionary response to the French Revolution.

And simulation/gaming does not confront its derivation from the

attempts of the military to improve its capabilities for making

war.

It is richly ironic that the radical and liberating possibilities

which so many see in simulations should derive in large part

from that sector of society most consistently dedicated to

conservatism and repression. One can say, of course, that the

present work in the field has transcended its ori^^ins, but such

a statement strikes me as both short-sighted and inaccurate. | The military, whatever its reactionary tendencies in other areas

j

has always been a champion of technological innovation and

efficient management, I'he proliferation of arms, each one bifcger and better than its predecessor, is almost a m.odel of technical consciousness prone mad. The nearly obsessive desire to

find new and less wasteful ways to kill people is an example of

the efficiency ethic with a veneeance. And the military is the

pillar of what Alvin Gouldner has called the Welfare-Warfare

State, the institution most closely allied with the state both

financially and philosophically. !

338
I do not mean to suff:e;est a parallel between simulators and bhe

military. The former are considerably less numerous, and infinitely less powerful. But there seems to be, to some extent,

a shared consciousness —one that exalts technique over meanin?^,

innovation over insiecht, rhetoric over reality. There is a

J serious dan^^er here--technical consciousness creates the world

' in its own image, replacing; human values with machine values,

so that it becomes difficult to tell why we are doinp; something

j as long as we continue doing it. It is in this kind of conI sciousness that war can become peace, and manipulation freedom.

If we are to escape the trap into which this technological

preoccupation would lead us, we must reclaim human values as

j an explicit and crucial aspect of any simulation experience.

We must recognize that simulations are not, and cannot be, value-

[ neutral tools, that they imply a construction of reality for

vjhich we, as facilitators or directors, are responsible, and

1 to which, by our very presence, we lend credibility. And this

I! burden demands that we become ethically sensitive as well as

technically expert.

We are not philosopher-kings, and we should not pretend to be.

We are not ob,iective observers, detached from a world we help

create, and we should not pretend to be. And, since no one

completely escapes the onus of the past, we cannot be radical

I innovators unless we work at it self -consciously--and this we

can strive to do.

339
Reference s

Ellul, Jacques. The i''echno lop:ical oociety , /intap-e .jooks

(hew York, 196^)

.

Kuhn, Thomas S. T he Structure of Scientific Revolutions . Phoeni

Books (Chica5;o, 19^^).

Wilcoxson, ueoro:eann and Washburn, John. " Poward a theoloTy of

simulation/o;aminp;. " Simulat ion/ Jaminfr/News . Vol.t, No. 2, iMay

340
PUBLIC POLICY APPLICATIONS

George McFarland

Simulation Sharing Service

Morgantown, West Virginia 26505

I Simulations are useful tools for training citizens in the complexity

: governmental administration and decision making. They have also demons tra-

:d usefulness in the areas of assisting citizens to examine viable alternatives

b self-centered interests, developing strategies for responsible and

ifective involvement in governmental decision making, in raising the

pnsciousness level of community people to local, state, national issues and

foblems. To our knowledge there are at least 15 groups (centers) in the U.S.

hat are using simulations to educate and/or sensitize citizens to community

jssues/ involvement . There may be others. The particular target groups of

jiese centers are: unions, clubs, special interest groups (eg. W.R.O.,

mool Bond Issues, Housing, Church, League of Women Voters), continuing

tucation, neighborhood coalitions and home extension.

I Continued involvement with these groups is anticipated for the fore-

;eable future because a number of citizens are becoming increasingly interested

1 learning how to have an impact on their local government. Public media,

lurch programming, union publications, revenue sharing and personal

,[iconvenience or suffering related to public policy are all contributing factors

) citizen interest in the process of public policy formulation. The

Imulations listed below are intended to begin a list of the kinds of simulations

(lat have demonstrated some usefulness in the overall process of developing

i larger group of informed, sensitive and active citizens in government (primarily

'^cal) . We know that these simulations contribute to the above category of

.tizens. Our use of these simulations indicates our belief that our country

3eds this kind of citizen.

1. Whipp - simple look at causes underlying housing problems.

2. Welfare Week - experience of being on welfare. *GSI

3. Power Play - understanding the dynamics of power.

] 4. Urban Dynamics - basic structures of interlocking systems in

' growth and development of urban areas. *C/G

j 5. Policy Plan - develops community involvement about a particular

' concern (Frame Game)

6. P.U.D. Exercise - demonstrates need for comprehensive land

planning. '^B.S.

7. Ghetto - sensitizes middle class to some ghetto problems relating

to quality of personal lives. *C/G

I 8. New Town - introduction to the relationships between politics and

I economy of urban areas. *C/G

j 9. The Poverty Game - deals with welfare myths.

10. Much Ado ABout Marbles - difficulty of effective government,

communications, cooperation and trust (Frame Game). '^GSI

11. The Pollution Game - basic introduction to land use and

environmental quality. *C/G

341
12. Serfdom - explores power systems based on straight line

management policy (Frame Game). *S/S/S

13. Metro-Apex - aid to citizen participation in governmental

process. *C/G

14. Community Interaction Game - development of political strategies

and tactics. *C/G

15. Richland U.S.A. *St.L.

16. Starpower *C/G

17. CLUG - urban and regional economic, politics and sociology

(Frame Game) . *C/G

18. Yes, But Not Here - basic model of community organization

(Frame Game). *C/G

19. Polls *C/G

20. Policy Negotiation Model - analysis of political situation

(Frame Game). *C/G

21. Compacts - urban social service system-community organization

(Frame Game) . *GSI

Let me emphasize that this list of simulations is not a suggested list

of materials that might be useful in recruiting (training-developing)

informed citizens. This list could easily be used for classroom teaching

(and many often are used this way) . The games on the list have been used

successfully by some groups . This means that others may also find these

simulations successful. In other words, they are field tested. If you

are finding it difficult to develop informed, responsible citizens' groups

in your community, you might want to consider employing some of these

simulations. If you wish help in learning how to use some (all) of

them, then that sort of training can probably be provided by many (or all)

of the 10-15 active training centers. Larry Coppard has the most current

list of the centers that we know of today. His address is: P.O. Box 134,

Park Forest South, Illinois 60466.

*Description contained in:

GSI - Gamed Simulations, Inc., Brochure

C/G - Contemporary Games

B.S. - Barbara Steinwachs

S/S/S - Simulation Sharing Service, October/November Issue, 1972

St.L. - Saint Louis Simulation Games Center

342
MASSIVE MANAGEMENT GAMING

Richard F. Barton

College of Business Administration

Texas Tech University

Lubbock, Texas 79409

Management gaming to educate college students for business careers has been

with us for 15 years. Management games have emerged in many varieties and

for many applications. One type of application that is slowly emerging

involves very large numbers of students. To reach thousands of students

with management gaming, what changes must be made? What is lost? What is

gained?

Management games come in two general types: general and functional. Functional management games train participants to make decisions in separate

specialized functions such as marketing, production, and finance. General

management games reveal to players, through decision experience in managing

a simulated company, the interactions among the separate specialized functions. Most general management games emphasize the "totality" or wholeness

of business organizations. Players also learn by very real experience the

difficulties of keeping small groups of persons on track toward objectives.

Usual Organization of Management Gaming

The structure of most management games is two or more companies interacting

competitively in a single industry. Each company is managed by a team of

players who try to interact coordinately to reach team decisions. The decisions of each team affect the outcomes of all teams. Most management games

are now computerized. The computer model receives decisions from teams and

computes interactions and consequences that are fed back to participants in

the form of financial and environmental reports. These reports plus instructions from the game administrator and rules of the game from a player's

manual are the basis for the next round of decisions. Play progresses until

some desired number of periods has been simulated, usually representing

several years of operations of the firms in the industry. Figure 1 shows a blank decision sheet. See Figures 2 and 3 for illustrative company and

industry reports. In some applications, special team activities such as written reports or oral presentations are required of players to support

team decisions. Also, the internal structure and organization of teams can be manipulated as desired for behavioral learning purposes

The number of firms per industry may range from one to nine, depending on

the game selected. Of course, one firm per Industry is a monopoly and

there is no competitive interaction among firms—the "solitaire" of management gaming. Any number of players may make up a team. Most authors

recommend from three to five members per team for games of moderate com- plexity. Plays of management games may last a few days in executive development programs or entire quarters or semesters in college courses. Management games have found popularity in junior and senior business courses with class enrollments limited to 20 to 50 students. A class of 20 students

can be accommodated in a single play of a management game by 4 interacting

343
IriL IMAGINIT MANAGEMENT GAME

Year

Firm DECISION SHEET

Quarter

Company Name: Month

Market A Market B

Product Names: A-1 A-2 B-1

Prices $ $ $

Materials inputs per unit $ $ $

Salesmen $ $ $

Advertising $ $ $

Product research and

development

$ $ $

Materials to be ordered $ $ $

Units to be produced

Employee fringe benefits

per hour

$

• Draw a wavy line through

product columns not used.

Dividends per share to be paid

$ If assigned, write decision

rationale on reverse side.

'

Operations research $ Decision deadline

Short-term Borrow

loans (Repay)

$ Team members sign names and

Bonds Issue

(Redeem)

$

titles below.

Shares of stock to be

offered

Decision recorder

Factory Purchase $

capacity (Sell) Rationale recorder (if any)

Figure 1. Player's Decision Sheet

344
j The Imaginit Management Game Year 1 uuarter 0 Month 0

BA. 120 First Practice Decision for A- 1 Detergent Only 10:30 Class

Company Report for Finn 84 A-1 A-2 B -1 Totals

Income Statanent

Shipments in Units of Product 3180153. 0. 0. Net Sales Revenue 21109949. 0. 0. 21109949.

Cost of Goods Sold

1 Direct Labor ($) 3850000. 0. 0. 3999012.

Direct Materials 7166667. 0. 0. 7166667.

Storage 446590.

Factory Depreciation 500000.

'other Factory Overhead 850000,

j Cost to Manufacture 12962269.

Change in Finished Goods on Hand ($) -523954. 0. 0. -523954.

j Cost of Goods Sold 12438315.

' Gross Profit on Sales 8671634.

1 Salesmen ($) 1350000. 0. 0. 1350000.

|Advertising 2100000. 0. 0. 2100000,

j Research and Development 0, 0, 0. 0. Employee Fringe Benefits 385000, 0. 0. 383267,

! Operations Research 0.

j Administrative Overhead 834842.

j Interest 120000,

Profit Before Income Tax 3883525.

Ij Inccme Tax 1864092.

1 Net Earnings 2019433.

f Dividends per Share 3.00 Total Payout 900000.

] Shares Sold 0. Proceeds 0.

I Change in Stockholders Equity 1119433.

il Balance Sheet

[Cash 3760372. Accounts Payable 1685020.

1 Accounts Receivable 1897615. Short-Term Loans 0. .iiMaterials 1133333. Bonds 2000000.

j Finished Goods 1892154. • Paid-in Capital 14000000.

1 Net Plant 12600000. Retained Earnings 3598455.

j Total Assets 21283475. Total Equities 21283475.

' Common Shares 300000. Book Value 58,66

! Market i^ote 83.97

Current Policy and Environment

Average Industry Prices this Period

Current Total Market Demand (Units)

Share of Market this Period

Potential Shipments next Period

Prices

Materials inputs per unit ($)

Materials on Hand ($)

Materials on Order ($)

Months until Materials arrive

Production levels (Units)

Number of Finished Units on Hand

Distribution Channel Inventories

-A ..--B---

6.70 0.0

15754025. 0.

--A-1-- --A-2-- --B-1--

0.210 0.0 0.0

3441473. 0. 0. 6,65 0.0 0.0

2.15 0.0 0,0

1133333. 0. 0. 0. 0. 0. 0.0 0.0 0.0

3333333. 0. 0. 553181. 0. 0. 121044. 0. 0.

1133333.

Figure 2. Company Report for Each Team

345
Figure 2. Company Report for Each Team

Purchase or Sale of Factory Capacity

Loans Made or Repaid 0.

(Quarters Dividends too Low 0,

Firm Labor Rate 3.50

Fringe Benefits per Hour 0.35

Current Number of Labor Shifts 2,

600000.

Bonds Issued or Redeemed 0. Total Dividends to Date 900000,

Actual Labor Hours 1095050.

Probability of a Strike 0.03

Persons Available per Shift 252.

346
The Imaginit Management Game Year 1 Quarter 0 Month 0

'End-0£-Period Industry Report

BA 120 First Practice Decision for A-1 Detergent Only 10:30 Class

CoiTpany Report for Firm 81 A-1 A-2 B-1 Totals

Share of Market this Period

Prices

Materials Inputs Per Unit ($)

Advertising

Salemen ($)

Quarters Dividends Too Low 4. Common Shares 300000.

Market Quote

0.198 0.0

6.65 0.0

2.10 0.0

2000000. 0.

1350000.

Total Dividends to Date

Book Value

60.26

0.0

0.0

0.0

0.

Company Report for Firm 82 A-1 A-2

2000000.

1350000.

0. 60.78

Totals

Share of Market this Period 0.212

Prices 6.70

Materials Inputs Per Unit ($) 2.00

Advertising 2300000.

Salesmen ($) 1300000.

Quarters Dividends too Low 4.

Common Shares 300000.

Market Quote

0.0 0.0

0.0 0,0

0.0 0.0

0. 0, 0. 0. Total Dividends to Date

Book Value

64.33

Company Report for Firm 83 A-1 A-2 B-1

Share of Market this Period 0.176

Prices 6.60

Materials inputs Per Unit ($) 2.05

Advertising 1800000.

Salesmen ($) 1300000.

Quarters Dividends too Low 0.

Common Shares 300000.

Market Quote

0.0 0.0

0.0 0.0

0.0 0.0

0. 0, 0, 0, Total Dividends to Date

Book Value

85.10

Canpany Report for Firm 84

Share of Market this Period

Prices

Materials inputs Per Unit ($)

Advertising

Salesmen ($)

Quarters Dividends too Low 0.

Common Shares 300000.

Market Quote

A-1 A-2

0.210

6.65

2.15

2100000.

1350000.

0.0

0.0

0.0

0.

0,

B-1

0.0

0,0

0.0

0,0. Total Dividends to Date

Book Value

83.97

2300000.

1300000.

0.

62.35

Totals

1800000.

1300000.

900000.

58.87

Totals

2100000.

1350000.

900000.

58.66

Figure 3. Industry Report for All Teams

347
Figure 3. Industry Report for All Teams

Conpany Report for Firm 85

Share of Market this Period

Prices

Materials Inputs per Unit ($)

Advertising

Salesmen ($)

Quarters Dividends too Low 4.

Common Shares 300000.

Market Quote

A-1 A-2 B-1 Totals

0.204 0.0 0.0

6.90 0.0 0.0

2,10 0.0 0.0

2250000, 0. 0. 2250000.

1300000. 0. 0. 1300000.

Total Dividends to Date

Book Value

63.39

0. 61.99

348
Instructions for within team structures or for presentations and reports by

i teams are possible only if made uniform for all teams. Because so many

j teams can only be treated uniformly, the same "industry" must be simulated

'in all parallel plays within the auditorium. Absenteeism on decision days

and enrollment changes by students dropping and adding the course after

j- teams are organized require rules for handling missed decisions and for

adapting within teams to absentee role players. Surveillance by the teacher

j of individual team activity is practically impossible. Yet, simultaneous

exposure of thousands of students of business to actual decision making with

• irrevocable (though simulated) consequences has been done.

Large course sections usually appear at freshman and sophomore levels. Thus

massive management gaming may be desired or needed only for introductory

courses while the usual organization described earlier is more suitable to

advanced courses. The principal purposes of a general management game are

! to integrate and to put together previously learned knowledge—to let the

ij student experience how all parts of a company fit together in interaction

jj to produce ultimate profit and other consequences. So how can beginning

students be expected to play a management game before they have learned anything about business? The answer is quite literally "jump in and swim."

Extra practice decisions and a good player's manual are called for. Here

is a situation where simulation-gaming can really prove its merits. When

beginning students make decisions for such elements as product quality and

|| prices, stock issues and bond offerings, salesmen and advertising, puri chasing and producing, dividends and plant investment, they learn the lan-

! guage of business. When they see consequences in the form of income statehiments, balance sheets, and flows of funds that look like the annual reports

sent by corporations to their mothers and fathers, they learn how business

decisions affect business results. When these results are tied to simulated

|i] stock market quotations, to shipments of their products, to shares of their

markets, to probabilities of strikes, they learn the responsibilities managers must carry. These things students can learn without ever having a

' first course in accounting, marketing, finance, or production.

An Illustrative Implementation

'At Texas Tech University during the fall semester of 1972, THE IMAGINIT

\ MANAGEMENT GAME was implemented with 900 students divided into two sections

j of an introductory course called Business Enterprise. No laboratory sections were available. The course carried two pass/fail credits so grade

I motivation for game participation was absent. The two sections of the class

I met in an auditorium seating about 450 students. The course consisted of

j lectures by the dean and by guests and the management game. For the game,

i students were organized into 45 industries of 20 students each. There were

I 4 members per team and 5 teams per industry. Students had assigned seats

' and were assigned to teams on a side-by-side basis from left to right for

the first row, then continuing right to left for the second row, left to

j right for the third row and so on. This way team members sat close

! together during class time. Decisions were required once a week. Four

complete class sessions were devoted to explaining the game. During

349
teams of 5 players or by 5 teams of 4 players. A class of 45 students can be accommodated by a single play of 9 teams of 5 players. A class of 50

students can be served by two parallel plays of 5 teams of 5 players. Several classes of 20 to 50 students each using parallel plays can provide

gaming experience for a single course for one or two hundred students per

quarter or semester. This organization provides a sizable exposure of

business students to management gaming. Let us examine the resources

required.

First, computer service and an assistant to handle the decision input and

computer printout may be necessary. However, since the instructor for each

class may be supervising at most ten teams, he may perform his own computer

chores. He can be helped if players keypunch their own decision cards. j Helpful in this circumstance is having the computer program cataloged in

the computer library so that only the data carried over from the last deci-^

sions and a very few computer control cards must be handled by the

instructor.

A desirable administrative characteristic of a computer game model is provision for different team numbers for each parallel play so computer output is not mixed up. Another desirable feature is simulation of different

industries, both during a semester and from semester to semester. This way

players cannot claim to learn and tell secrets of the game (even though the

may be wrong about the secrets). If possible, consequences should come out

of the computer in a way that minimizes hand sorting of computer paper.

Management gaming teams may meet in corners of the classroom, in separate

rooms during the class hour, or privately outside of scheduled hours.

Usually, the teacher tries to be available to answer questions before decision deadlines

.

Changes to Accommodate Massive Numbers of Students ..

Consider now reaching over a thousand students per course through management gaming. How much of the usual organization described above can be

retained? What adjustments must be made to accoiranodate these large numbers

of students? What is lost? What is gained?

Course enrollments of a thousand or more frequently mean giant lecture sec- tions given in classrooms or auditoriums seating 200 to 1000 students. One

approach to management gaming for numbers this large is breaking the course

into laboratory sections with few enough students to implement the usual

organization of management gaming just described. This multiplies the

administrative burden per teaching assistant because teaching assistants

usually handle more laboratory sections than teachers handle course section

Another possibility, where laboratory sections are not available or desired

is massive management gaming in the auditorium itself. Parallel plays of

the game become a necessity to accommodate all the students. Separate firm

numbers for each team help avoid mixing up the computer paper. An assistan

to perform computer courier and paper handling chores is needed. Special

350
this time three practice decisions were made. After official play started

6 years of official decisions were simulated.

To handle the logistics of massive management gaming in an auditorium a "captain of industry" was appointed for each industry (a group of 20 students) . This "captain" was responsible for receiving the computer output

for his industry and distributing it to teams. Each team distributed com- puter pages to its own members. Therefore, to distribute computer output

the game administrator was dealing with only 45 persons. Computer runs were made on multiple-copy paper. Paper separating tasks required about

one hour a week. Key punching required one to two hours a week. Reruns

due to keypunching errors required another hour a week on the average, Dis

tribution of computer output was accomplished by placing the computer pages

for each industry in an envelope. During class, "captains of industry"

were asked to come forward and remove their computer outputs from the en- velopes and leave the envelopes with the game administrator.

Written reports were required of each team during the semester. These were

an initial and final team organization report and an initial and final over

all policy and strategy statement. Also required were "decision rationales

written on the reverse sides of decision sheets. To avoid one or two players on a team from dominating the others, leadership roles for each of

these assignments were rotated so each player was the team leader at least

twice. (To further spread participation, the role of "decision recorder"

was also rotated within teams) . A reading of the written reports and decision rationales revealed that these beginning students were indeed learning

sophisticated concepts related to business and industry without explicit

"course" instruction in these concepts beyond the management game player's

manual

Teams were scored on the basis of simulated stock market quotations within

an industry. Team and industry standings were reported periodically during

the semester. A reward in the form of a certificate of excellence was given to each player on each winning team. Since there were 5 teams per

industry, 20 percent of the students were winners. The questionnaire at

the end of the course elected the management game as the most outstanding

feature of the course.

In the spring semester, a similar implementation was made with 300 students

in a single section (this being primarily a fall course) . In this instance

3 teams per industry were used resulting in one third winners.

References

Barton, Richard F. THE IMAGINIT MANAGEMENT GAME . Lubbock, Texas: Active

Learning, P. 0. Box 16382, 1973.

"What's Wrong with the Introduction to Business Course?" Computing News - letter for Schools of Business , Vol. Ill, No. 7 (March, 1970), School

of Business Administration, University of Colorado —Colorado Springs,

pp. 1-3.

331
SIMULATING SEXISM: UNINTENTIONAL (?) REPLICATION OF REALITY

Nancy D, Glandon

University of Redlands : - Redlands, California 92373

During the session "Evaluating Simulations and Games" at last year's symposium I raised a question about the sex of the participants in various

roles in one high school simulation of local government. Both the answer

by the speaker and the reaction of the audience to my questions have

caused me to ask the same underlying question again: do simulations-^and

our debriefings of them perpetuate real world sexual discrimination? And,

if so, how do they do it, and what are we, as game users and designers,

doing about it? The response of the speaker last year was something like

"well, yes, boys tended to be in the higher status, decision -making

positions and girls seemed to be concentrated by choice in supportive,

lower-status roles, often functioning as secretaries." The reaction of

the audience was amusement -- with some raucus laughter -- that the

question was even posed, and seemingly one of "well of course" when the

answer was given. At no time was it suggested that this particular parallel with 'real' reality was shared with the high school participants. My

purpose here is not to accuse those particular simulation directors of

chauvinism - either intended or inadvertent - but to examine the possibilities of sexism in simulations and in their use in more general terms. And

perhaps, in so doing, accuse us all.

While simulations and games have been variously defined, a common element

to all definitions seems to be that they are partial reconstructions of

reality, designed to illuminate in miniature the processes of behavior,

attitude formation, and dec i- ion -making. There are probably as many

definitions of sexism as there are of simulations -- but generally sexism

refers to attitudes, behaviors, and structures which limit, deny, or prescribe certain attitudes, behaviors, or statuses to men or women. Assuming

these definitions to be accurate, there is only one other assunption

necessary (which is at least as valid as the fomer) : there is sexism in our society, and therefore there is sexism in the realities oFlsociety

which simulations attempt to reproduce. So, to the extent that simulations are accurate reconstructions of society, we can conclude that they are accurate reconstructions of sexism as well. And, to the extent that

simulation designers, directors, and participants are products of an admittedly sexist society, they can be expected to exhibit sexist behavior

and attitudes in their simulation experiences - in their decision-making,

and in their perceptions of decision makers.

^This paper is primarily concerned with simulations used in teaching

and community insight, rather than with simulations used for research

purposes, although similar comments would be appropriate there, too.

352
-exism in' simulations can, I believe, take two forms: first, a recon- struction direct from society --or what could be called 'simulation' of

sexism J second, an introduction into the simulation itself either through

the particular structural components of the game or through the attitudes

and behavior of the director and/or participants during the playing of the

game and/or during the debriefing -- or what we can call an 'acting of sexism

within the simulation. Obviously these categories are not mutually exclusive

and behavior and attitudes called sexist are likely to occur in both realms

simultaneously

The interrelationship of these two realms becomes clear when we try to look

at particular simulations and spot overt and covert sexism. I would like

to examine the existence of sexism in game structure, the possibilities of

alerting structures of games to deal head-on with sexism, and the process of

debriefing as a means of exploring sexism, either in the simulation structure

or within the acting out of the game.

Sexism is built Ante the structure of games in a number of ways:^

in role descriptions which become stereotypes of male/female attitudes;

in role assignments where the director suggests or assigns certain

positions based on her or his perceptions of 'predictable' responses

of males or females.

One recent example, "Remote Island," reported in the May 1973 issue of

S imu lat ion/Gamin^/News (Cohen), contains five role titles and descriptions:

I four' are male , one female . Three of the four males are given both first and

last names; all four are given attitudes which favor or oppose the issue at

hand. All four have a predictable econonic interest in the decision.

The one role for a woman reads: "Mrs. Homington. Your name is Mrs.

Hcmington and you are a housewife and mother . You represent a group of

housewives who are interested in the processing plant and whether it comes to

the island. You listen to the arguments and ask questions, because you want

to decide whether to support or oppose its ccming." (p. 11, italics added)

This last role (given last in the article too) is the only role where a vested interest for a certain side is not given; it is the only role where

marital status is mentioned; it is the only role which suggests to its players that the appropriate strategy is to listen and wait - to be essentially

passive. I am not suggesting that housewives should not be included in the

roles used in simulations; I am concerned however that this is too often the

only role which is viewed as 'appropriate' for women. And if in certain

cases the game designer would view the simulation as 'less real' if the

active powerful roles were neuter or female, then it seems to me that it is

incumbent Lpon both the designer and the director to point out that fact of

reality, and discuss its implications with the participants, I caution

though that such a decision may be a cop -out, letting both the designer and

the director slip comforably into a world they prefer and find easier to

game

353
in directions given or suggestions made which affect either the sex of

the role occupant or the behavior required for such a role;

and in the labeling of the role titles themselves.

Many popular simulations contain role titles such as congressman, chairman,

councilman; most descriptions use he, him, his exclusively. While we tell

ourselves that such usages refer to 'man' in the generic sense, research

on college students suggests that for students at least 'man' is interpreted as meaning 'male' rather than 'people' or 'all human beings.'

Studies by Schneider and Hacker (1973) indicate that' Use of a generic label

"may serve to 'filter out' women, largely by suggesting imagery appropriate

only or prijnarily to men." (p. 12) Both theory and research in fields

such as sociology and linguistics have maintained that social reality is

defined and constructed through the use of symbols, and that language, as a specific system of such symbols, is linked to the creation and perpetuation

of a particular perception of reality. It is time for game designers to

examine their own perceptions of the sexual reality they present through

their simulations.

Certain simulations such as the "High School Game," the "Marriage Game,"

and "Ghetto have built into them constraints which differentially limit the !" options available to females and males. All three of these games contain

incredible possibilities for discussions of differential life chances faced

by women and men. I wonder how often we as game directors turn the debriefing of these and other games to such issues.

It is also possible to take other existing games and make the sexism

obvious, and of central concern. One such attempt on my part is described

in detail in an article "Sexism: Rigging SIMSOC to Make the Point" (1973)

.

Using Gamson's basic model of inequality, differential access to resources,

and limited comnunication, I increased the realism by introducing sexism

into the game structure: all heads of groups and all travel and subsistence

agencies were assigned to males; all members of the ghetto region were women. The participants respond with typically social class -based reactions to the

situation of women, and are unable to deal with it except through tokenism.

Throughout the simulation a certain amount of sexual consciousness-raising

occurs: some men become aware of their own' liberalism' in 'permitting'

women to participate; some women become aware of their own willingness to

acceed to the wishes of men; and most students seem to have a hightened

awareness of the supposed randomness of status in our society, and the

ineffective position of those without power.

The exploration of sexism, as well as the more traditional issues which

Gamson's model raises, is of course discussed in the debriefing immediately

after SiMSOC and in later class meetings. And it is in the debriefing where

these issues are confronted directly.

One of the few things which is agreed upon by most simulators is the importance of the post game discussion as the place where learning occurs. And

it is during the debriefing that the facts of sexism are most frequently

overlooked. Do we ask: what roles and attitudes did the males have? Did

they differ from the roles and attitudes of the females? Did women or men

have the power - or the authority? Were women or men leaders? And most

354
crucial: Why was it this way? Who is talking most now? Who is really

listened to? Why?

Research conducted by Coleman, McElroy, and Whitehurst (1973) on small

group problem-solving indicates that participants' perceptions of leadership differ in single-sex and mixed-sex groups, and more importantly, that

perceptions of leadership differ from objective observations of leadership.

"Men were chosen as leader, both by themselves and by others, far more

often than women were chosen as leader." (p. 8) However, "in single-sex

groups, not only are women able to see themselves and other women as being

leaders when there are no men present, but women actually tended to choose

themselves or be chosen by other women at a slightly higher rate than men

chose themselves or were chosen when there were no women present." (p. 9)

Further, "perception of leadership in small mixed groups appears to be subjective in that leaders are apparently chosen not on task- related ability

but largely on the basis of perceived status. In conditions where there

are clear status differences (e.g. in mixed groips) , reliance on such

ascribed criteria as 'maleness' appears to occur, while in situations of no clear status differentiation (e.g. in single-sex groups) objective criteria

such as quality and quantity of interaction may assume more importance,"

(p. 9)

When the researchers compared perceptions of leadership with the objective

criteria for leadership (nunber, duration, and quality of interactions)

they found a statistically significant difference: wcmen were objectively

leaders in 60% of the cases; yet were perceived as leaders in only 71 of

the cases, (p. 11)

Is this phenomenon of perceiving leadership through sex-colored glasses

happening in the simulations and the debrief ings we direct? Are our own perceptions as 'detached, interested' observers filtered through our con- ceptions of 'appropriateness'? Who are the decision -makers in our games?

I would suggest that we carefully watch the processes by which decisions

are made - perhaps extend our use of videotapes - and seriously attempt to

confront the links between sex and leadership.

Boocock suggests that "games may affect attitudes, in particular the individual's attitude toward his sense of control of environment," (p. 316)

If she is correct, and I believe she is, then it seems to me that we must

deal with the attitudes of all our simulation participants -- male and

female -- toward control of their environments. We must share with than

our understandings of the sexual structures of our games, our perceptions

of sexist acting in the game setting, and explore with them all the facits

of the issues of life chances, leadership, decision-processes which our

games reflect.

In my three plus years of gaming I have found little interest, rare discussion, and no research on these issues I have raised, Wiy not? UTiat

does this lack of concern say about game designers and directors? It is

time to look at ourselves, our biases, our views - to see if we, through

our simulation experiences - are limiting the options and perceptions of

those who play - so trustingly - our games.

355
If there is any moral obligation on the designer or director of a simu

lation (and sometimes I wonder if we acknowledge any) it must be the

obligation of pointing out the realities illustrated by the simulation

and their impact on the participants' views of the social world. It seems to me that a part of this obligation must be the obligation to

deal with the sexism illuminated through the simulation - consciously,

frequently, and seriously.

356
Bibliography

Boocock, Sarane S. An Introduction to the Sociology of Learning . Boston:

Houghton Mifflin, 1972

Cohen, Richard B. "A Remote Island, for You," Simulation/Gaming/News

(May, 1973), pp. 9-11.

Coleman, Marietta, David McElroy and Carol A. Whitehurst. "Sex Differences

in the Perception of Leadership in Small Groups," paper presented to

the Pacific Sociological Association, May, 1973.

Glandon, Nancy D. "Sexism: Rigging SIMSOC to Make the Point" Simulation/

Gaming/News , Vol. 1. No, 8 (September, 1973), pp. 1, 5.

Schneider, Joseph W. and Sally L. Hacker. "Sex Role Imagery and Use of

the Generic 'Man' in Introductory Texts: A Case in the Sociology of

Sociology," The American Sociologist , Vol. 8 No. 1 (February, 1973),

pp. 12-18.

Simulations

Ghetto, Western Publishing Company, New York, 1969.

High School Game , developed at Johns Hopkins, was demonstrated by Constance

SeicSier at the National Gaming Council Symposium, 1972.

Marriage Game : A Simulation of Marital Decision Making , Cathy Greenblat,

Peter Stein, and Norman Washbume, Random House, 1971.

SijnSoc: Simulated Society , William Gamson. New York: The Free Press,

1972 (second edition)

357
ADVOCACY - A COMMUNITY PLANNING GAME FOR THE RANKING OF

SCHOOL SYSTEM GOALS AND TRAINING NEEDS

J. Robert Hanson, Manager

Educational Systems Division

Scientific Management Associates

R150 Nicholson Road

Gloucester, N. J. 08030 •:

I. Introduction

The "Advocacy" planning game is one more step in a growing trend to

include the public in decision-making areas formerly ruled by

specialists. Recent examples of the public's entry into social

policy decision-making includes consumer protection (the meat boycott),

public safety (Nader's Raiders, et al) and legislative issues

("Common Cause", taxpayers associations, etc.).

"Advocacy" also represents a fundamental shift in public policy determination in that the total communi ty--taxpayers , parents, staff and

students--are involved in assessing both the needs of young people and

determining the goals the schools are to service.

But why a planning game? There are three reasons:

1. there must be an agreed upon mechanism for determining school

system priorities since resources do not allow all concerns

to be treated at the same time;

2. there must be a way to include in the decision-making process

all the people affected by the educational system—particularly

students and the community that finances the schools;

3. there needs to be a way to include in the school system's thinking

the educational goals identified by the State Department of

Education, and approved by the State Board.

The result of playing "Advocacy", or nearly any type of educational

planning game, is that 1) the school system will have prioritized

goals and 2) an agreed upon procedure for using its resources in a way that a) focuses on the clisnt--the student, and b) represents

the involvement of the total educational community: parents, teachers,

school administrators, students and the larger community.

II . A planning game

"Advocacy" is an interaction game. Unlike board games ("Monopoly",

chess, etc.) or simulation games (computer or data bank-assisted),

"Advocacy" is built around people interacting with one another

and then recording their actions on a board, rather than having

358
the board (via die, spinners, etc.) determine their actions for

them.

The name of the game comes from the fact that participants are asked to consider the students' needs from a position other than,

possibly, the one they may be most familiar with. The game is

not, however, to be confused with role-playing. In role-playing

participants are asked to demonstrate pre-determined behaviors,

often purposely hidden from the other participants, for purposes

generally resulting in a conflict situation which can then be

resolved. In "Advocacy" the assumption is made that conflict

already exists since there are no community-approved goals or procedures for the operation of most school systems, and that the

acknowledged lack of such approved procedures results in conflict

through the public's non-involvement or misunderstanding.

"Conflict" is a constant in all human relationships, and when

addressed constructively can be seized as an opportunity for

resolution and progress. Therefore, the game assumes disagreement

even to the point of agreeing to disagree, but disagreeing within

the rules of the game, i.e., that the democratically achieved final

ranking of needs and goals will be personally "owned" by the game's

participants.

Participants are assigned to constituency tables advocating

educational needs resulting from the community-wide needs assessment process. For example, tables would be identified as "teachers",

"administrators", "students", "Board members", etc. Those assigned

to each table, however, would constitute a mix of representatives

from all the various constituencies in order that a balanced

representation of personnel would be present at each table. This

mixed representation is critical if the community's participation

is to be taken seriously in policy-making, and more particularly

if the school system is to become student or client-centered.

The mixing of constituency representatives, therefore, provides

for: 1) increased interaction between members of the educational

process, 2) a method for resolving conflict, and 3) possibly a more objective analysis of training needs for particular

constituency groups.

"Advocacy" is an educational as well as a planning game. The

game's several purposes also include educating the community toward

more pertinent solutions to young people's needs, and away from

some of the authoritarian attitudes their own education may have

fostered in them.

Game Organization

As gamers arrive they register, receive a name tag, and are assigned

to a constituency table. There are five constituencies in most

school systems: 1) students; 2) Board members; 3) teachers and

359
and support staff; 4} administrative staff (including clerical and

custodial support personnel); and 5) the community.

Constituencies represent both the groups from which educational /

needs have been solicited and those who will generally desire

additional training in light of the new or revised educational /

priorities resulting from the planning game.

A central factor in "Advocacy" is the recognition that "new

occasions teach new duties", or more specifically that with the

clarification of school system priorities the roles of all

personnel change. These approved changes then inevitably require

the development of new skills, and thus the total educational

community-- the five consti tuencies--act in concert to determine

what training priorities need attention in order to implement

those agreed upon changes. For example, if a high ranked goal was "...to more effectively prepare senior high school students

for the selection of a career..." then it would probably be

necessary to train guidance counsellors, teachers and selected

community representatives in effective methods of re-orienting

the curriculum, finding out-of-school opportunities for site

visitations, and bringing guidance personnel up-to-date on the

entry requirements for many different types of jobs. Or, if the

game results in a high ranked need to "...individualize instruction

for each student..." then teachers, administrative staff and Board

members would need training in curriculum design, new patterns for

supervision, and the introduction of programmed budgeting, etc.

In short, it is unrealistic to expect prioritized needs responsive

to vastly accelerated social change to be effectively implemented

without taking seriously the need for assisting all levels of

personnel in obtaining new skills and attitudes.

Playing the Game

The game is divided into an introduction and three rounds.

The introduction consists of a rapid overview of the needs

collection process, and often there is some type of audio-visual

presentation to explain the rules of the game.

Round I Ranking of Product Needs/Goals (white cards)

The game facilitator at each table introduces the goals resulting

from the community-wide needs collection process. These are goals

which are focused on student achievement and are the "outcomes"

or "products" of the school system. These product needs have been

converted to cards with one need or goal on each card. Each goal

also has a number weighting, and, of course, the name of the constituency for which outcomes-products are being recommended.

360
The group then begins a discussion process resulting in the

ranking of each individual goal. This ranking is accomplished

by:

1) the facilitator presenting the goal and answering questions

2) the group discussing and ranking the goal by placing it on

a numbered mat (mats are numbered from +5 to -5 -- "extremely

Important" is a +5, "moderately important" is a +3, etc.)

The group may change its collective mind as often as it wishes

during the allotted time period. The facilitator will be responsible for keeping his group on schedule in order that all product

needs will be "matted" by the end of the round.

At the end of Round I, the matted needs are collected by messengers

and are delivered to the game manager's table. Here the needs are

tabulated and are immediately fed back to the tables by closed

circuit TV monitors. Additionally, the totals are posted on a chal kboard.

During the first intermission, gamers will be able to compare how

their high ranked goals fared in comparison with the other tables.

Round II Process Meeds/Goals (yellow cards)

The second round follows a similar process with the cards being

matted after explanation and discussion. In the second round,

however, the group will be prioritizing proposed training

procedures for the outcome goals that ranked highest in Round I.

It is the facilitator's responsibility to see that only those

process goals are ranked that are responsive to goals that

survived Round I.

Again, at the conclusion of Round II, the matted cards are collected, tabulated and fed back to the tables on the TV monitors.

Round III Final Ranking of Product and Process G oals

In the last round the product and process goals surviving the first

two rounds will be re-ordered. In some instances there may be

high-ranked product goals without correspondent process goals. The

lack of a process counterpart does not reduce the product goal's

val ue.

361
The facilitator will introduce both cards in a set (one product-white,

and one process-yellow) for matting at the same time.

At three points during Round III {every 15 minutes) the game manager

will announce the changing scores for the sets surviving Round II. - In this way each table may be kept abreast of what is happening at

all the other tables.

At any time during the game, participants may send messages via

"runners" to other tables requesting support for particular goals.

The responding table will then "negotiate" some form of exchange

or trade for their particular favorites, i.e., advocating the

approval of certain outcomes and their counterpart training

components.

Additionally, new goals may be introduced by a table (a constituency)

and proposed before the entire group via the public address system.

Also, a goal rejected in Round I may be recalled, or rewritten, and

proposed for reconsideration through the public address system and/or

via group to group negotiation.

Any gamer may go to the microphone at any time to speak for 90 seconds

advocating a particular product or process goal.

Spaces are reserved in the room for small groups to caucus during each

round, and between rounds. It is important, however, that not more

than two group members be absent from their respective tables at a given time. The absence of more than two members effectively restricts

the remaining players from matting the remaining goals.

At the end of Round III the matched sets of ranked products/processes

are submitted to the game manager, are tabulated, and as a result of

a total number of points secured for each product goal are placed in

a ranked order from highest to lowest.

This listing then becomes the school system's developmental blueprint

for the following year. Needs ending up in a position too low for

inclusion in Year I may then be scheduled for Year II, and so on.

School systems are encouraged to replay the game at two year intervals

in order to sustain community interest and support and to assist the

district in keeping current on student needs.

At no point does the ordered ranking of goals foreclose administrative

responses to crises. Hopefully, a well-planned and executed planning

procedure will reduce the number of emergencies that arise.

362
VI. Decoding the Advocacy Cards

Reading the cards is easy. The cards have been coded with the layman

in mind.

In the upper left-hand corner -is an Arabic number which indicates

the importance the constituency which submitted the card placed on the goal. The Roman numeral is the number of the submitting

constituency; hence, in our sample shown below this is the second

highest need submitted by Constituency Seven. In the upper right

hand corner is a letter which indicates how important the need was interpreted to be by all the constituencies submitting needs in

the assessment process. This sample card's needs were in Category

"A" representing the highest level of need, i.e., it occurred the

most often among needs submitted by all the constitutuencies.

The number appearing next to the letter indicates the need's correspondence with the State's product and process goals. For example,

if a 10 point value appears there is a complete correspondence

(5—partial and 3 or less a minimal correspondence) between the

need and the State's approved goal structure.

The lower left-hand corner contains either an "N" or a "T". This means the goal is new to the operation of the school system, or that the program now exists (T) but is in need of upgrading.

2:VII A-10

Training of all school personnel in loving their

neighbor, protecting their environment, expanding

consciousness and cooperating with one another.

$10/person per instructional hour

for 100 people for 10 hours

for a total of $10,000

June 1973

363
The costs of training needs are estimates based on current expenses.

The time designation is an estimate of when the need might be

implemented if approved. The card also specifies how many need

to be trained, and approximately how long the training will last

for a total dollar amount.

General Notes

The figures for costs and numbers of people involved can be

Increased or decreased based upon the group's assessment of the

goal's importance.

Groups will not be given the names of the constituencies submitting

particular needs in order that each goal be examined and discussed

on its own merit.

The number and letter coding is for the gamer's guidance only.

Gamers are to make up their own minds about the importance of

each need.

364
LEARNING TOOLS TO RESEARCH INSTRUMENTS:

A RESEARCH PACKAGE FOR STARPOWER

Richard L. Dukes

University of Colorado at Colorado Springs

Colorado Springs, Colorado 80907

Introduction

Many of the most widely used simulation games have been designed

primarily as learning tools. If social research is to take

advantage of the strong points of these simulation games for

testing social theories, then procedures must be developed for

converting simulation games into products which allow the gathering of data for testing theories while still preserving the

playability of the games. The use of games in social research

does not necessarily preclude their use as learning tools, as in

many cases revised games can serve both learning and social

research purposes adequately.

This paper will present modifications for the simulation game,

Starpower ^ (Shirts, 1969). The modifications are intended to

provide examples of how simulation games may be modified for use

in social research. The entire "package" of modifications presented here allows the gathering of data on approximately 80

variables which can be used to test social theory.^ The revisions

reported in this paper have been used in over forty plays of

S tarpower and do not seem to significantly alter the playability

of the game. Revisions should be taken only as suggestions which

should be modified freely in order to fit particular combinations

of research and learning needs.

Game Materials

All game materials can be carried in a small case. Description

of the case and its contents provides a convenient way of

describing game materials and revisions of the game.

1 It is assumed that the reader has at least some familiarity

with the original version of the game. If this is not the

case, the reader should see the "Directors Instructions" for

S tarpower . 2 Variables from the package have been used to test a theoretical

model derived from Ralf Dahrendorf 's Class and Class Conflict

in Industrial Society (1959) . Results of the test may be

found in Dukes (1973)

365
Game rules and standardized instructions to players can be

written on the inside of the lid of the case for reference

during administration of the game. The use of standardized

instructions to players helps to, increase comparability between

plays of the game and is highly recommended. It is also recommended that the game rules be written where players can see them.

Not only do written rules seem to help the players comprehend

the game more clearly, but during the rule change portion of

S tarpower . the upper class members can be required to formally

state any rule changes by erasing the original rules and writing

new ones. In this way, rule changes can be recorded accurately

by observers. The most convenient place on which to write the

rules seems to be the same chalkboard on which players' scores

are tallied.

Distribution of Game Materials to Players

When random assignment of players to the social classes of the

game is dictated by the research design, a quick method of

assignment of players to classes and distribution of game materials is necessary. The use of business envelopes of various

sizes to hold playing chips, identification tags, and Players

Logs can provide such a method. Business envelopes come in a series of sizes. The 9^ inch size can be used for the upper

class, and the 9 inch size can be used for the lower class and

so on. While players do not seem to notice the differences in

the sizes of these envelopes, game administrators can tell at a glance which type of distribution of playing chips is contained

in any envelope. The envelopes then can be placed in the case

in a random sequence. Since S tarpower is usually played with

the same number of players in each social class, the envelopes

can be sequenced in groups of twelve, for example, with dividers

between groups „ Within each group of twelve envelopes there

would be the same number of envelopes for each social class.

Envelopes can be passed out of the case (in order) to players in

blocks of twelve and still insure random assignment as well as quick distribution. When there are only players left unassigned

who form a block of less than twelve, equal numbers of envelopes

for each social class can be selected from the next block of

twelve envelopes in the case. This small number of envelopes

can be quickly shuffled into random order and distributed to the

remaining players. In classroom situations, frequently players

arrive just after assignment of players to groups has taken place

Quick identification of the contents of an envelope from the

outside allows assignment of individual players to one of the

groups without unbalancing the sizes of the groups.

366
Identification Tags

In order to ease observation of play of the game, the square,

circular, or triangular-shaped group identification tags can

be provided with unique symbols, so that the observers can

identify individuals during the game and record their behavior.

Circle tags can be assigned letters of the alphabet, square

tags can be assigned numbers and so forth. Partially removing

players' anonymities in this way may lessen tendencies toward

collective behavior, however the impact of uniquely identifying

players is probably small, particularly in situations where

j players may already know each other anyway. This procedure also

simplifies the game due to the fact that game administrators do

not need to know the initials of the players, and there is no

confusion due to two players having the same initials. When

there is inter-group mobility players exchange these tags as in

the original version of the game.

Players 'Logs

A system of gathering information about play of the game during

trading rounds is presented below. In this system, players keep

track of the identification numbers or letters of the players

with whom they trade as well as the colors of the chips which

] were exchanged.^ In this way the researcher can keep a sequential

account of players' chips, scores, trading patterns, bonus points

and inter-group mobility. Players fill in the information as they

trade. This procedure does not seem to interfere with the normal

tempo of the game. One scoring page is kept for each trading

round of the game. These scoring pages are alternated with pages

of questionnaire and rating scale items which the players fill out

between rounds of the game while the administrators are preparing

for the next round of play. The items are designed to measure

players' attitudes towards other players as well as their observations of play. Questions are presented in an increasing number

after each round. Most of the questions are asked more than once

so that changes in attitudes or ratings of play can be measured.

Questions which might suggest strategies to players are asked

only after the game is over. Coefficients of reliability using

the test-retest method range from .82 to .98 for these items.

3 During pre-testing of the revisions, another scoring system

was tested. Chips were assigned unique identities. Players

recorded the identities of their chips after each trade.

This procedure proved to be too tedious for players and was

replaced with the present system.

367
Group Bonus Procedures

The distribution of group bonus chips to each social class in

small boxes is a procedure which avoids the bias of giving

these chips directly to a particular member of each grouping.

The boxes containing the three group bonus chips can be placed

in the center of each group. Players then take it upon themselves to pick-up and distribute the chips. If the chips are

given to a player by the game administrator, this player is

placed in a position of authority by the administrator and

usually receives at least one of these chips. The use of the

boxes also allows observers to record the identification number

or letter of the person who subsequently picks up the chips.

Players are told that the bonus chips are not considered to have

been allocated until the chips have been given physically to the

receiving players. When the bonus round is over, the game administrator picks up the boxes whether there are any unallocated

chips in them or not.

Timed Rounds

The use of a timer with an audible alarm can be used to accurately

limit the time of each trading round and bonus round in the game.

The timer insures comparability in the length of the rounds, and

it provides a non-arbitrary decision maker for ending each round.

When the alarm sounds, the round is over.

Preparing for Another Round of the Game

After scores have been computed and players have exchanged identification tags and seats (but not scoresheets or chips) , the game

administrator may choose to collect and redistribute all the chips

as directed in the S tarpower Instructor ^ s Manual , or he may let

the players continue to play with the chips they have. While this

latter procedure may tend to lessen the impetus to trade in subsequent rounds, if bonuses for the number of trades are used, (see

below) this tendency rarely becomes a problem. The procedure

offers quicker progression of the game, especially with large

numbers of players.

Checking for Errors and Filling-in Missing Information

At the end of the game, chips, identification tags, and Players ^ Logs are put back into the envelopes and returned to the game

368
administrators. This procedure allows later checking of actual

chips against reported score as well as the checking of tag

identification numbers or letters against the reported group

affiliation. As envelopes are unpacked, the colors of the chips

in the envelope can be written at the bottom of the last score

sheet for later coding and checking. Once the game materials

are readied for another play, missing data in the log is sometimes

impossible to replace, so careful unpacking and checking of the

envelopes after each play is advantageous. Sometimes information

about play which is missing from one log can be found by checking

the scoresheets of other players in the game, as the information

concerning trading of chips or tags between two players is recorded

by each. During the design phases of scoresheet construction, such

comparisons can provide information on the accuracy with which

players can use the scoresheets. College-age players used the

scoresheets with a 98% accuracy rate during pre-testing of this

instrument.

Tape Recording Play of the Game

A small cassette tape recorder can easily be carried with the

other game materials. A high-quality machine with an internal

microphone can record inter-group conversation in a rather large

room without ever being taken from the case containing the other

game materials. Tape recording seems to be most useful during

the portion of the game when the rules are changed. The benefits

of recording the entire game should be weighed against the time

consuming task of listening to hours of tape. For use with

ij S tarpower . tape recorders seem to work best during bonus and rule

change portions of the game as back-up devices which are used in

! conjunction with observer category systems and long-hand notes.

I, The usual cautions concerning unobtrusive tape recording and player

i privacy should be observed.

;' Observer Rating

I Several methods of observer rating have been combined to provide

I a flexible method of rating game interaction. Many different

ij types of systems were tried, but the method which seemed to work

1 the best is presented here. Also, rather than rating complete

i games, the rating of group bonus rounds (intragroup interaction)

'l and portions of the game in which the rules are changed (interI group interaction) seemed to provide the most important information

l!

369
on interaction without hurting the playability of the game.

During the bonus rounds, one observer (usually game administrators can do these observations) sits in or near each group and

records the tag identification number or letter of players who

interact during the three-minute session. These observations

are very easy to rate and yield the amount of interaction

initiated by each player. If it is important to know to whom

the interaction was directed or the type of interaction during

this portion of the game, then the simplified Bales (1950/1970)

method of scoring (described below) can be used at this time as well as during later portions of the game. During the portion of

the game in which the rules are changed, an observer sitting in

each of the groups notes the tag number and classifies the interaction of each player in the group which is directed to players

in the other groups. The coding scheme is a condensed version of

the Bales technique. There are four codes: "v^" (smile) for positive reactions; (period) for statements or attempted answers;

(question mark) for questions; 'W (frown) for negative

reactions. The coding scheme preserves much of the original

system, but since each code has a high intuitive meaning, it is

simpler to use. Observers can remember the four simple codes, so an ordinary stenographer's notebook can be used rather than the

printed forms commonly used with the Bales technique. The notebook

format provides a very flexible procedure for mixing codes with

long hand notes on any collective behavior which may occur during

this part of the game„ Using one code or note per horizontal line

of the notebook keeps the entries in proper time order. Long-hand

note taking begins when a player leaves his seat; the observer for

the group in which the player was seated writes down the activity

of that player. If the player changes a rule on the chalkboard,

the observer copies ver batim what the player writes on the board.

After the game, observers code all rule changes onto a standardized

code sheet, which when completed for a number of plays, allows

comparison of rule changes across the game plays.

Different Numbers of Social Classes

The game rules for use with the present version of this package

create only two social classes instead of the original three.

The middle class has been eliminated. The number of classes was

reduced since the theory to be tested in the research for which

this package was designed, was conceptualized in terms of two

social classes. Added advantages of using only two social classes

include 1) the necessity of having only two observers and 2) decreasin;

the number of relationships between groups. For groups A, B the only

inter-relationship is A-B, but for groups A,B,C there are three interrelationships: A-B, A-C, and B-C.

370
The elimination of the middle class may not have much overall

affect on the amount of conflict in the game over many plays

,

since sometimes a middle class acts as a buffer between the

upper and lower class, thus lessening the conflict. However,

in other cases the middle class may form a coalition with one

of the other classes (usually the lower class) resulting in

increased conflict. The question concerning the amount of conflict, of course, can be answered more accurately in future

research. At this time, however, no specific number of classes

seems to be sacred, and decisions regarding the number of classes

to incorporate into game rules should be based upon theoretical

and methodological considerations.

Creating Different Types of Simulated Social Systems

One of the advantages of using simulation games for testing

social theories is that these games can be modified easily to

create social systems which are different from each other only

along specified dimensions. Researchers can then use the "type

of social system" as a treatment of an experimental design to

which players or groups of players can be randomly assigned.

Below are described the changes in the original rules of Starpower

which can be used to create an open (or class type) social system

and a closed (or caste-type) social system. Since the original

version of the game is primarily a closed social system, the rule

changes focus on the opening up of class lines through the use of

bonuses for trading. In the open social system plays, a bonus of

25 points is given to each player each time a trade is consummated.

In the closed social system plays a bonus of one point is given to

each player each time a trade is completed.

In the closed system resources have more of a fixed value which

does not increase when resources are exchanged. In the open

system resources are more interactive in that they increase in

value when they are traded. Exchange in the closed system is

more zero-sum, since except for the bonuses for attaining chips

of the same color (which is quickly used up when the chips are

not redistributed after each round) one player must win in each

trade, and one must lose. In the open social system, exchange is

less zero-sum, as the 25 point bonus per player for each trade

serves to offset the point differences between the chips of unlike

colors which must be traded by the players. It should also be

noted that points concentrated in chip values can always be

lost in subsequent trades, while points concentrated primarily in

"trade bonuses" cannot be so easily lost. In this way, exchange

371
is more risky in the closed system than in the open system.

Perhaps the most important difference between the two systems

is the basis of status and mobility . In each system the distribution of playing chips is the same, however in the closed

system the point spread of 25-50 points between the classes is

almost impossible to overcome through trading unless an upper

class member makes a blunder. Therefore, as in the original

version of the game, the social system is essentially a caste

system in which unchanging status is ascribed before the first

round of play begins. In the open class system the point spread

between the classes can be overcome by lower class members who

are able to make approximately two more trades during a round

than any member of the upper class. Since upper class status

in the open system is more achieved , there is a greater chance

for lower class members to become upwardly mobile through their

own trading activity. In the third round of the game, the upper

class members are given the authority by the game director to

change the rules of the game. In the closed system this authority

is more likely to be concentrated in an ascribed, monolithic

group due to the characteristics of resources, exchange, status/

mobility discussed above. In the open social system authority is

more likely to be concentrated in a group in which players have

gained or maintained their status through achievement. In fact,

quite a few of these players are likely to have experienced

several group memberships during play.

Adequate Samples

Since S tarpower may produce many different outcomes such as revolution, equilibrium, apathy, etc., the sample should include

a number of game plays which is high enough that there may be

confidence that the range of outcomes in the sample represents

the distribution of the outcomes which the game can generate with

a given population of players. Especially if the researcher is

attempting to analyze individual behavior, there may be a temptation on his part to stop sampling when enough individuals have

played the game to enable him to undertake statistical analysis.

If this sample is based on just a few plays of the game, results

may be heavily biased.

Conclusion

Revisions presented in this package should be taken only as suggestions , not dictums . The original instructor's manual for

372
Starpower was written in a manner which invited manipulation

of the game rules and procedures. It is hoped that this package

will invite further manipulation of the game and improvements in

the package.

REFERENCES

Bales, R.

(1970) Personality and Interpersonal Behavior. New York:

Hoult, Rinehart, and Winston,

Bales, R,

(1950) Interaction Process Analysis. Cambridge, Massachusetts:

Addis on-Wes ley.

Dahrendorf, R.

(1959) Class and Class Conflict in Industrial Society. Stanford,

California: Stanford University Press.

Dukes, R.

(1973) "Organization, Conflict, and Change: A Test of a Multivariate Model Within Two Types of Simulated Social

Systems." Unpublished Doctoral Dissertation, Department of

Sociology, University of Southern California.

Shirts, R.

(1969) Starpower . La Jolla, California: Simile II.

I

I'

I

373
A PEDAGOGIC;^JL SCHEMA FOR THE DEVELOPMENT AND USE OF COMl^UTER SIMULATION TSCHNOL

Dana B. Main, Robert Stout, D. W. Rajecki, Hovjard Eichcnbaum and Trudy Villar

Department of Psychology, University of Michigan

Ann Arbor, Michigan 48104

m

St

m

si

For the past three years we have been developing and using computer data-ge

erating models in teaching the undergraduate psychology elementary researcbj

design course. At the Dartmouth Conference, Main and Head reported on the

first year's experience with this type of computer technology and described

the general features of the first version of the experiment simulator (Main

and Head, 1971). At that conference, Johnson argued for a pedagogy utilizi

a com.puter simulation approach for teaching research design strategy (Johns

1971) . He compared it to the traditional instructional laboratories and to

the use of computer data banks. Since that time. Main has reported on diff

ent pedagogical (Main, 1972a, Main, 1972b) and evaluational (Main, 1971) de

velopments. Rajecki, et al, wrote a report detailing some of our original'

models (Rajecki, et al, 1972). '

In meetings such as this one, in workshops, in informal faculty meetings, a; in conversation, we have been asked a variety of questions ranging from en-! quiries about the programming to skepticism about the value of teaching stu

dents about research without generating "real" data. Some persons have bee'

concerned that the models generating the data may be "wrong" and, therefore

may misinform the student; some fear they reflect the literature too closel

and may stifle a student's questioning mind» There has been doubt that an ' undergraduate can really appreciate the intellectual complexity of the proc

and there has been skepticism that the process is too simpleminded. There

a sense in which each concern is justified if only a part of what we have c and envision doing is examined.

The purpose of this paper is to present the total schema which is guiding c development. Within such a structure we can point to the parts which we ar' others have accomplished and with which we have had considerable experience

to the parts with which we have had only recent experience, and, most impoi

tant, to the parts which we believe need to be developed in the near future

Not only does this put our work into perspective , it may also inspire you t participate in this very exciting innovative development.

We will describe a sequence of four pedagogical modes that can engage stu- \ dents and be utilized by faculty who have no knowledge of computer programrf

This sequence can originate as eairly as the second semester of the freshmar

year, (We strongly suspect that it could begin in high school, but we have'

had no such experience. Johnson has informed us of some use of this pedagd'

in high school [Johnson, 1972]. We believe that all modes can be designed''

engage undergraduates, although more complex versions are certainly appropr

ate for graduate students and professionals. A student may entSr the firstmode and work through all four throughout his undergraduate career. The tl

spent on any particular mode or sub-sequence is dictated by the sophisticati'

of the student and the goals of the course utilizing this form of pedagogy.

We are not committed to any particular subject area in the behavioral sciei^ or to any specific theoretical framework. The system v/e have initiated carj

374

fi
deal with any subject matter content in the behavioral sciences.

We will describe these modes in terms of the student experience. We do this

in order to emphasize the very real possibility that excellent performance

by students in later modes can generate instructional materials for other

students in earlier modes . We do not mean to imply that the only resources

^developed for the earlier modes should arise from the work of advanced under-

;igraduates. It is reasonable and desirable that contributions be made by projfessional persons and graduate students. It is simply that this pedagogical

Jschema has some interactional exchanges that are unique when compared to most

educational processes.

Mode 1

|ln the first mode, the student receives a description of a particular problem

jarea in the behavioral sciences. This description may be very brief and may

jjinclude references to the real literature. It may be more or less extensive

'|in supplying students with informational detail. It usually describes con-

||flicting theories. It is meant to set the stage.

'The student also receives a complete list of all possible manipulable variables

.and their allowable values defined by the data-generating model. In the

.simplest case, he is informed of a single dependent variable and its values.

[iThere may be more than one dependent variable described. He is further informed of the value of each manipulable variable that is defaulted if he

^chooses to ignore it. The default value is constant—that is, a particular

jvalue of the variable. It may be selected from the set of possible values by

[jlsorae random process.

|iln this mode a student designs an experiment by specifying: (1) the number of

g experimental groups in his design, (2) for each group the values of the manip-

^ulable variables and the names of the dependent variables in the case of more

than one dependent variable, and (3) the number of subjects [within a specified range] for each group.

This information is submitted to the computer and serves as commands to a datagenerating model. The student's output are values of the specified dependent

variable(s) which can be plausibly interpreted as raw data. All of our datagenerating models have been probabilistic; therefore, the very same design

^ generates different values of the dependent variable.

Depending on his research goal the student generates hypotheses-, designs ex- periments, summarizes results, and explores relationships between manipulable

variables as well as functional relationships among different dependent variables. He is encouraged to report his findings in terms of support or disconf inflation of possible theories. He gets into problems of scaling and is

r motivated to acquire some statistical skills in order to make inferences

about the underlying; model generating the data.

_

' : \ 375
Our first three models are .n this mode. They have been utilized in the elementary psychology laboratory course each term for the past three years. This course is taken by second semester freshmen and sophomores who usually plan

to major in psychology and is taught in small sections by graduate student

teaching f ellov7s . Some or all of our models have been used in undergraduate

and graduate psychology statistics courses, in a course in research design for

psychiatry residents, in an elementary sociology laboratory course, and in an undergraduate motivation course. The models, developed by graduate students,

involve subject areas of the etiology of schizophrenia (Malin) , imprinting

(Rajecki) and motivation (Mueller)

.

Mode 2 1 In the second mode, the student again receives a description of a problem j area. But this time he is informed of only a subset of the manipulable var- | iables and of all, some, or none of their possible values. He may also be in-i

formed of only a subset of possible dependent variables utilized by the data- [ generating model. He is made aware, either initially or later, of one or j more X-variables which may be contributing effect to his results. The con- | cept of X-variables in instructional simulations was first suggested to us by |: Richard Johnson (Johnson, 1972) and was developed for classroom use by Cromer \ and Thurmond at the University of Louisville (Cromer and Thurmond, 1972). In \ Cromer and Thurmond's instructional models, the student is provided with a f complete set of variables less one: the X-variable. Information gained from • rvns on the other variables may or may not lead the student to infer the X- ' variable. If he does, the instructor provides him v;ith a computer command

that causes the X-variable to contribute to the values in the data in subsequent runs. If the student has not correctly inferred the appropriate variable, but some other implausible or impossible alternative, the instructor J may give him a command that makes no systematic contributions to subsequent

data values . i

Two new data-generating models developed by three of the authors of this papeij are being implemented at this writing. j

E The Social Facilitation (SOC FAC) model developed by Rajecki involves the foli

lowing problem. The performance of a task is generally enhanced by the presence of another person, but the learning of a task is usually impeded by the

presence of a co-actor or observer. These effects have been found in species [: as divergent as insects and humans. In the initial stages of the simulation i, the student learns how these effects are obtained via Mode 1. 'He next learns < that the effects of the presence of another are similar to the effects of gen--

eralized drive (D^ in the Hull-Spence form.ulation) . The question is, then, ' why does the presence of another have such generalized drive consequences?

At this point the problem description addressed to the student ends, period. ' It is his obligation to specify all of the variables for the balance of the

simulation. But additionally he is confronted v/ith the task of inferring the

376
why of the phenomenon. UTiy should (or v7ould) the mere presence of another

member of one's species have these effects? Is it because the task implies

evaluation of performance? Does it have to do with the subjects' personality

or social history? These and other questions have been raised by social psychologists whose work has appeared in the literature. Based on this literature,

a large number of X-variables (a la Cromer and Thurmond) have been programmed

and are available to the instructor by code name. These include (omitting

details) variations of independent, dependent, and subject variables. If the

student's inference matches one of the alternatives available, he will be provided with the appropriate code and can then evaluate his hypothesis. If his

inference is judged to be inadequate or specious, he can be given a code name with no effect, or he can be "counselled" by the instructor.

Eichenbaura and Villars, graduate students in psychobiology , have developed a model entitled Drug Observations: Program for Experim.cnts (DOPE). The model

deals with the question of behavioral m.echanisms of drug action. Four commonly

known drugs may be examined in three strains of rats, in training and retention tests, and three different laboratory learning situations. All manipulable and dependent variables are given to the student, but the values of the

dosage levels, time of injection, amount of reinforcement, and degree of

training are infinite. The student runs the risk of drug overdose, ceiling

training effects and contradictory data between different tasks, strain, and

dosage levels. DOPE provides an option for additional challenge to the student. Once the "universe" of drugs has been behaviorally classified, an X-Drug

may be assigned to the student. These X-Drugs include drugs similar to those

four already in the model and to saline. It would be the student's task to

classify the X-Drug.

In Mode 2 the student must do everything he did in Mode 1, but in addition he

must operationalize concepts and particularize values of variables. He must

generate hypotheses on how mechanisms work and must articulate manipulable

variables. He must select from the set of possible values of the variable

those he wants to explore and must justify his selection or particularization

through logical argument supported by results from his simulated experiments.

These last two data-generating models encourage a stepwise systematic strategy.

They both have more than one dependent variable. SOC FAG encourages the operationalizing of concepts across species. DOPE has som.e interesting inverted

U-shaped functions that will encourage multivalent versus bivalent designs.

We have had extensive experience with Mode 1 and some limited experience with

Mode 2. Before describing the next two modes yet to be developed for general

use by undergraduates, we would like to describe the Michigan Experimental

Simulation Supervisor program developed by Robert Stout, who stoutly and selfji confidently uses the acronym MESS while Main, doggedly and perhaps too selfconsciously, calls it EXPER SIM.

1 From this description we hope to convey the large set of possible data-generiating models that can be constructed with this software for Modes 1 and 2 and

577
its potential use in later modes.

Supervisor Program

Tlie primary function of the simulation supervisor is to serve as an interface

between students and m.odels of behavior; it serves as an indirect channel of

communication between the creator of a simulation model and those who explore

that model. In order for it to perform its job in the most effective manner

possible, the supervisor has been designed to be maxir.ip.lly unobtrusive; it

requires little special knowledge and skill from either the student or the simulation designer, although, of course, the student's task is by far the easier.

Though simple to use, it is a flexible, powerful system; it is possible for a student to specify an experiment involving a five-way factorial design with

only five lines of input to EXPER SIM. Students can design factorial experiments involving com.plete or incomplete, balanced or unbalanced designs, or even split-plot (v;ithin-sub jects) designs or covariance designs. There is no general type of experimental design it is not possible to ao

,

From the point of view of the simulation designer there are also few restrictions on x-jhat can be done. Although the system is primarily oriented toward

models which produce a numeric output, it would be possible to implement a model whose output was, say, English sentences. Models may be static or dynamic

univariate or multivariate. The current software, which can easily be modified , to fit different size requirements ,~ can handle up to thirty-six independent

variables and six dependent or concomitant variables. Implementing a model

involves writing a FORTRAN subroutine which embodies the model, and preparing

for the supervisor program a data deck which specifies the names of the simulation variables and their allowable abbreviations, legal values, default values;

and other program parameters. The amount of programming necessary to produce

a model is not usually large; the model subroutines for the currently available simulations are between one hundred and two hundred FORTRAN statements

long, including extensive comments. There is- a subroutine library containing

random number generators for a variety of univariate and multivariate distributions, as well as numerical integration routines.

Although all the models implemented to date generate data de^ novo each time they are called, this situation is primarily a matter of convenience; it would be a simple matter to write a "model" subroutine which would sample from a bank of,

say, survey or personality data, instead of using an algorithm to generate ar- tificial data. It makes no difference, of course, what content area is being

simulated; it is as easy to simulate experiments in ecor-omics or .pharmacology

as in psychology.

IThile EXPER SIM makes the programming part of creating a simulation relatively

easy, it should not be supposed that bringing a good simulation into being is a trivial task. If a model is to be realistic it must include all of the quirks

interactions, and variability of real data, and devising a simulation containing

378
any reasonable number of variables is a task that can strain any scientist's

knowledge and imagination.

Mode 3

In the third mode, we envision undergraduates modifying algorithms of models

they have been extensively exploring during the first two modes, developing

algorithms of data-generating models in different subject areas, and developing models that generate conflicting data or different models that generate

similar data. We would like to design the instructional environment and the

computer technology such that undergraduates could engage in an educational

experience of the- kind the graduate students who worked on our past models

have experienced. As in Mode 2, the student would have to operationalize

variables and select or particularize values of these variables. But rather

than exploring relationships and fitting simulated data to hypothetical

theories, the student must specify these relationships, generate the algorithm,

and explore via Mode 1 the consequences of his modelling decisions. He may

add or modify variables as in Mode 2. But the important component of this

mode is that the student learns how a behavioral mechanism may work by attempting to build a mechanism that generates data similar to what is known

about that mechanism. It is our hunch that some students could begin to ex- plore Mode 3 even at the end of our elementary research design course. Certainly this is an activity in which many advanced undergraduates could engage.

If the student has programming skills, excellent models can be developed for

instructional purposes —such as PAVCO-Pavlovian Conditioning that Richard

Nussloch developed as an undergraduate at MacAlister College (Mink and Nussloch

1971)

'I At the present time, however, the vast majority of undergraduates in the behavioral sciences do not program. Although they could be challenged to generate

at least first approximations of their models, they cannot place them onto

the computer for exploratory and modification purposes without the assistance

of a programmer. With the large number of undergraduates at the University of

Michigan, the bottleneck created by the necessity of a programmer has been too

great for us to attempt to develop Mode 3 on any large scale. What is needed

is an interactive program with sufficient flexibility that enables undergraduates without programming knowledge to place their models onto the general

program for purposes of their own exploration and possibly for exploration by

other students participating in earlier modes.

I Mode 4

The final mode is one that links the students' simulation activities with the

"real world". Those of us enthusiastic about computer simulation pedagogy

often fail to convey that the purpose of all of this is to help students develop strategies for understanding the "world outside" (whatever that might be

379
interpreted to be) . We envision laboratory courses in which a student having

explored his own model in Mode 3 or that of someone else's in Modes 1 and 2,

compares simulated data to that which he has collected in real laboratory exr- periments. The real data that he and his classmates collect could be stored

in a data bank and compared to that generated by a model. - -

At the University of Michigan, Flint, Raphelson (Raphelson, 1971) teaches his

motivation course using a data bank v/ith data generated by his students over several terms and by our Mode 1 motivation simulation. Cromer and Thurmond

have used laboratory data generated by students in conjunction with data-generating models (Cromer and Thurmond, 1972). Rajecki has piloted this mode

with the SOC FAC model and student generated data this past term.

The Mode 4 is limited by the kinds of data a student can feasibly collect or by the kind that can be collected in data banks, but it is in this mode that

he can develop descriptive and predictative skills in terms of real world phenomena.

In summary, we have presented four pedagogical modes that utilize computer simulation techniques. We have described where we have been, where we are now,

and where we hope to be. It is an exciting adventure. VThy not join us?

380
REFERENCES

Cromer, A. 0., and Thurmond, J. B. Toward the optimal use of computer simulations in teaching scientific research strategy. Proceedings of the 1972

I Conference on Computers in Undergraduate Curricula, June 1972.

' Johnson, R. DATACALL. A computer-based simulation game for teaching strate

' in scientific research. Proceedings of the Second Annual Conference on Computers in the Undergraduate Curricula, June 1971.

Johnson, R. Personal communication, 1972.

Main, D. B. and Head, S. Computer simulations in the elementary psychology

laboratory. Proceedings of Second Conference on Computers in the Undergraduate Curricula, Dartmouth College, June 1971.

•Main, D. B. A computer simulation approach for teaching experimental design

'presented to the American Psychological Association, Washington, D. C, Sep127, 1972a, 245-248.

r Main, D. B. The laboratory class as a simulated scientific community. Presented to the National Gaming Council, Baltimore, Maryland, October, 1972.

Mink, W. and Nussloch, R. PAVCO: A computer simulation on Pavlovian con1 ditioning. Presented to the American Psychological Association, Washington,

!|d. C, September 1971.

I Rajecki, D. W. , Malin, D., and Mueller, S. EXPER SIM: Computer simulations

I for teaching elementary research design in psychology. Report' from Center f

j Research on Learning and Teaching, University of Michigan, February 1972.

!

I Raphelson, A. C. Personal communication, 1972.

I teinber 1971.

Toward a future-oriented curriculum. American Psychologist ,

381
EDUCATION AKD TRAIimTG FOR COrTTEMPORARY UPJiMJ FLAMING SYSTEMS ;

THE H4PACT OF INIERACTIVE SBTUL/iTION .

MAY 1975

"by:

ROBERT M. SARLY, B. Arch. ,M. Sc .Arch. &T.P.,

Executive Director, R. A.D.I. U. S. - Research Analysis and Design

in Urban Systems.

Lectiu:er, Department of Social and Environmental Planning,

Polytechnic of Central London.

Research Fellow, School of Environmental Studies, University

College London.

ABSTRACT

Current planning education and training prograimnes lack a full sense of realism. They are deficient in providing the planner

with enough preparation in areas of applied decision-making

under conditions of uncertainty, conflict and continual change.

Interactive simulation methods can help in infusing realism by

means of participation, role-playing, representational and performance

methods. Three alternative programmes are proposed to extend the

scope of current planning education and training, and to improve

the linkage to current practice: An Introductory Linkage, A

Continuing Linkage, and A Service Linkage. The objectives and

potentialities of these progranmes are described. Ifeny of the

required methods already exist, and many others are being

developed to fill ciirrent programme needs. The interactive

simulation programme at the Polytechnic of Central London is one of a growing number of successful application of this approach.

382
EDUCATION AM TRAIITIHG FOR CQI^EMPORARY UKBM FLAMING SYSTEI4S:

THE D'TPACT OF I1JTEEACTI7E SIMULATION.

1, Introduction to the Present Dilemma .

1.1 Ilrtan planning systems pervading all aspects of contemporary

urban life are not just becoming more complex in themselves,

but rather they are accommodating a more sophisticated

understanding of the processes and inter-relationships that

comprise these systems. To the student or apprentice planner

preparing to take up a position of responsibility in these

systems, the critical problem is to be able to clarify and

conceptualise a mass of information in r elatively short time

as a basis for realistic judgement and decision. This problem

is often not one of insufficient data but of over-abundant data

of variable quality. The "data glut" is compounded in practice

by a growing dependence on the evaluative judgement, understanding

and experience of fev/ over-burdened and under qualified decisionmakers. Systems of urban development, plannijig, management, analysis,

and control each require a range of skills that are in short

supply in planning practice, partially because many of our present

planning education and training programmes are failing to

provide them. Traditional methods and modes of instmiction

comprising current academic programmes no longer relate very

well to the changing complex requirements of contemporai^y urban

planning systems . ^"^ ^

1.2 IVkintaining a gap between planning education and planning practice

must be costly both for the individ\ial and for society, its effects

could be widespread: social and economic productivity may be

retarded, individual motivation may be stifled, and effective

professional judgement may be impaired, resulting in part from

the inadequacies of the preparation which is given the students

and trainees in the planning field. A major aspect of these

inadequacies is in the sense of realism conveyed in contemporary

education and training programmes. Planning skills, techniques

and theories are often presented in the broadest terms but with

383
scant regard for the crucial demands of their performance in

application to the real problems of contemporary urhan planning

systems. Programmes for preparing planners in ways and means

of analysis need to have a firm grounding in the practical

constraints that performance places on the evaluation and

(2) implementation of academically generated planning systems.

1.5 The representation of planning systems in a realistically

generated context for demonstrating the potentialities of planning

in application to real problems is taken in this paper to be

the model for that planning system. The behaviour of the model

over time is shown by means of a simulation, and when the

simulation is a function of the interaction of two or more

independent decision-makers, their performance is examined

(3) in terms of some form of interactive simulation model.

2. The Case for Interactive Simulation.

2.1 The gap between academic representations of urban planning

systems and the so-called "real world" itself serves some

im.portant functions, including providing the possibilities of

controlled analysis and experimentation. However, it also

serves to devalue the relevance of much of this analysis.

Little opportunity exists in the planning laboratory for the

direct application of formal educational knowledge or formal

training experience to the informal problems of the real world.

Yet to consider these practical problems merely on the basis of

their informality, lack of intellectual rigour, difficulty of

measurement, or controversiality is surely counterproductive to

the basic aims of preparing planners to perform most effectively

in a changing profession and under conditions of uncertainty

and conflict.

2.2 There are certain practical problems that are currently left

almost entirely to the fortunes of chance, whim and intuition.

In the framework of urban systems these problems often cover

important ax-eas of knowledge, to name a few, such as: the processes;

of developmental change and social succession in urban regions;
the mechanisms of community interaction and commimication;

the management of competing and conflicting planning interests

In iir'ban space; and the nature of government intervention in

the private sector over time. These problems also cover

important training areas such as: the operation of bargaining

mechanisms in the property and job markets; the co-ordination

of policies within and between local authorities and social

groups, the effectuation of citizen rights, (e.g. landlordtenant, employer-worker etc.) and political opportunities.

(5) There are many more . '

Not that all these problems areas are totally ignored in

current education and training programmes; on the contrary

many of them are analysed dispassionately in the objective

atmosphere of formal lectures and discussions. This is a classical approach but it may leave the student with rather

little with which to discern the relevance or realism of

complex urban planning systems should he be confronted with

liaving to make a responsible decision. On balance, some of

the most important aspects of current programmes include:

clear and objective analyses, formal and dispassionate

discussion, exemplification and generalisation, and description

of general conceptuiil forms and structures. Some of the most

deficient aspects include processes of plan synthesis, both

concept'oal or operational synthesis; the dynamics of human

interaction and value formation, the time processes (e.g.

development, grovrth and decay), planning uncertainty, (e.g.

the inadeq_uacy of data, the ambiguity of judgement, and the

difficulty of measuring effects), and analyses of self-interest

(i.e. the legitimate motivation of different people and groups

based upon their perceived objectives, priorities and values).

Overall there is a basic need for reinforcing the generalist

perceptions required of the planner in co-ordinating the

(6) specialists with v/hqm he must work. ^ ' It is suggested here

that if this is done, the approaches used would be likely to

amount to some form of interactive simulation.

385
3' The Essence of Interactive Simulation.

5.1 There is no single t.^^^e 01" interactive simulation any more than

there is a single type of lectirre, or Job; but there are certain

basic characteristics commonly identified v;ith those instru-ctional

methods relating to interactive simulation. In terms of these ' basic characteristics, the application of interactive simulation ! methods may vary from the highly str-u.ctuxed approach to the

loosely structured. Some examples are discussed below.

5.2 A primary characteristic of interactive simulation is participation,! The participant initiates puri^oseful activity in response to a set

of given conditions of which he is a part. One example of a highly

structured participation simulation exercise is the programmed

teaching machine. The participant responds to a given question

and proceeds according to the success of his responses. A common ji example of the loosely strxictured participation simulation is an

| architectural design studio, in which the student/apprentice

must actively simulate real build.ings by djjawing pictures of

them and by responding to the conditions of the brief and

the judgement of the design instructor.^

3.3 A second characteristic is role-playi.ng. Several students

participate in relation to one another's roles, as well as to

their o\m. The theatre is a popular form of highly structured

role-playing simulation and "good theatre" may be quite a good

source for understanding the complejd.ties of human nature. Most

professional actors take roles that are fairly veil defined,

leaving the scenario of role interactions with little uncertainty

except to the audience as to the final outcome. In other [ circumstances such determinacy is unrealistic and role interaction | simulations ,ay be more loosely structured, as in the many

role-interaction games used to train business managers, personnel

directors, industrial relations representatives, and government

planners. In fact, role-playing iaiteractive simulations are relevant to any bureaucratic position where the "understanding | (8) ' of human relations is of prime importance.

386
5.4 -A third characteristic is representativenes s . A simulation

is a replication of change; it is a model that represents a process of change that occurs in reality by selecting those

aspects of the process that are relevant to the objectives

of the study at hand, and by simplifying the rest. Highly

structured representative simulations may take the form of

computer-operated or computer-assisted models of reality,

since these can be readily sho\m to represent certain parts

of real urban aystems. The representation takes place as a

result of both a machine-manipulated set of procedures and a

man-manipula.ted set of objectives. These methods are most

applicable for projecting current conditions or for studying

current patterns of behaviour. Loosely structured representative

simulations may be used to illustrate the general principles

of urban systems and behaviour such as the population explosion

(9) or the evolution of slum areas. ^

3.5 A fourth characteristic is performance , the course of activity

follovving the simulation is mea,sured or moiiitored in terms of

the activity of each individual participant and the consequences

of his interaction with the simulated urban system. The highly

structured performance simulations are used to pursue such

questions as the efficiency of a man at a desk doing a given job

in a bureaucratic context; or the cash flows of a new town

development programme with criteria for evaluation economic

viability. On the other hand a loosely structured performance

simulation might look more at the behaviour of the participant

while engaged in the simulation, such as in the examination of

informal information requirements by local authority coimcillors

many programme policies for the next ^-yeax period. ^"^'^^

5.6 In short, the essence of interactive simulation is that it

instructs in areas of knowledge and e3cperience that bridge theory

and practice in urban systems at a level less formal than the

prepared seminar or programmed lecture and more formal than a

chance, whim or intuition. In a highly inter-connected urban

society the social cost of sub-optimal planniiig decisions can

387
be enormous, but it v/o"u2d be a needless waste if it could be

reduced even slightly by improving the quality of those

planning decisions by more realistic preparation of planners

for their real professional roles.

A Pract ical Programme for Interactive Simulation.

4.1 The primiary objectives of a practical programme of interactive

simulation which supplements an existing course in urban planning

systems should be closely related to fulfilling practical

requirements of the programme. These objectives can be used to

measure the utility and the effectiveness of the interaction

simulation programme.

4.2 As mentioned above, three deficiencies in current education

and training programmes particularly amenable to methods of

interactive simulation are:

4.2.1 Assessing the effects of time on the processes of

development, growth and decay.

4.2.2 Monitoring aspects of uncertainty v/ith respect to

data, value judgements, and consequent effects.

4.2.5 Accommodating the legitimacy of differing self-interest s and the motivational behaviour of different urban groups.

4.3 -An instruction programme in the field of urban systems that could

be improved in any of the aspects above might well consider some of the methods of interactive simulation. This could take several

alternative forms.

Alternative 1: INITIATING LINKAGE

I Course7Training Unit

Alternative 2: CONTINinNG LINKAGE

Coircse/Training Unit II

388
Alternative J: SERVICING LINKAGE

Course/Trainin/^ Unit

III

4'3«1 The Initiating Linkage .

At the very beginning of a course of instruction an

intensive block of interactive simulation activity

would serve the following purposes:

A. It presents a broad brush preview of the entire

course showing how the pieces fit together and

the order in which they are to be taken.

B. It confronts the participant v/ith the problems

he is expected to be able to solve upon completion

of the course.

C. It puts the subject of the course into the broader

context relating to other areas of knowledge and

experience the participant may wish to draw upon

in the course.

D. It helps to break d.o\m the natural inhibitions of

the participant to his colleagues and to build a

sense of group identity which serves to reinforce

leaiTning.

E. It helps to break dov/n the polarisation between

participant and instructor and helps to encourage

learning at various levels simultaneously.

F. It stimuJates interest and enthusiasm for the

subject and provides insight into the natiu?e of

responsible decision making in the course area.

4.5*2 The continuing linkage .

To place the block of interactive simulation activity

at the end of the course xmit would shift the emphasis

of the programme toward aspects of evaluation and

implementation with the following purposes:

A. It re-integrates the more difficult aspects in

the course showing their relevance and application.

B. It demonstrates the application of course-taught

materials to sitiiations in which the effectiveness

of those materials can be seen and evaluated,

C. It tests the general ideas developed in the course by implementation in given situations.

389
D. It helps to differentiate the function of analysis

in the co"Lrr.''se from that of judgement ajid it elucidates

the relevant processes of decision-making.

E. It gives preliminary experience in dealing with the

course matter in a context of reality, and it allows

the participant to practice his nev.'ly acquired skills

and rehearse his broadened understajiding of the urhan

system ajid to monitor his performance.

4 . 5 • 5 The servicing; linkage.

Alternatively interactive simulation activity may be

spread throughout a course unit so that, at each staging

point within the formal course, reference could be made to

its counterparts in reality by means of the simulation

activity. Co-ordination is paramount in this kind of

linl-cage, one variation of which is the interactive

simulation coujse unit, in which the subject of the

course is the interactive simulation method itself, with

the following purposes:

A. To demonstrate the relevance of interactive simulation

methods for urban systems analysis.

B. To attune the participant to the mechanism of interactive

simulation and to its potentialities for ada,ptation to

different types of application.

C. To provide the opportutiity to devise and test

interactive simulation models and exercises with

respect to a given set of instructional objectives.

D. To strengthen the interactive aspect of urban,

systems ajid to provide the opportunity to exercise

the course materials in the process of their

development

.

5 • Two Exajnples of Int eractive Simulation Exercises .

5.1 The M.A.R .R.I.A.G.E. Game.

5.1.1 Marriage and Related Roles in a Gaming Exercise (Paul &

Ann Noble I97I ) was designed and tested with the help of

two post-graduate planning students at the Polytechnic of

Central London in a course unit on decision-simulation

390
model making. It is a role-playing interaction exercise,

described briefly as follows.

5.1.2 The primary object in the Marriage Game is that two

people, boy (b) and girl (g) , are to be married. Before

the marriag'e can take place they have to make a number of

decisions. The purpose of the game is for them to make

these decisions. Four other people are concerned in this

process, his father (F-^), his mother (M^), her father (F )

jj Jj G

and her mother (M^) . Each role player has a number of

goals which he wants to achieve and when all the decisions

have been made the achievement or non-achievement of these

goals is scored.

5.1.5 In the Marriage Game the persons playing M_,, F , M_^, F^, G G -b B

B and G are each given a role profile and some goals. Each

person can reveal as much or as little of his profile to

any of the others as he wishes, (remembering that revealing

some parts of their profile may detract from the lilclihood

of achieving their goals), and if anyone wants to add more

goals to his list he can do so as long as they do not

conflict vdth his role profile. These ranked goal sheets

are handed in to a "friend".

5.1.4 The B and G have a decision sheet v/hich says what decisions

they must make before they can get married, and v/hen the

decisions are finally made they are recorded on this decision

sheet. In arriving at their decisions, the B, G, F.^, I-lg,

F„,. M-,, all negotiate verbally with each other to decide the

G G

preconditions for m.arriage. The parents can negotiate with

each other if they wish. Negotiations can be private or

public. Then, after all the pre-marriage decisions have been

made, the record sheet is taken to the "Friends" who decide

whether the decisions are both viable and compatible. If they

are accepted then the "Friends" record the decisions on the

display board. Note ; Everyone can win or everyone can lose,

and in the event of a failure to negotiate all the pre-conditions

for marriage, the marriage is called off. This fact is

recorded on the display board and the goal cards are distributed

and scored as before.

391 .
5.1.5 Each player collects another copy of his goal set, mimhers

thera again in the order of importance that he now ascribes

to them. (This may or may not be the same as before). If

he has acquired extra goals in the course of play then

these may be added to the list and ranked. Each player

then marks his own list of goals as achieved or not

achieved in relation to the displayed decisions. He then

records at the bottom of the sheet v;hether he thinks he

has achieved more than he has lost/lost more than he has

achieved or that his achievements and non achievements

balance out. Finally, score cards are then made public,

and a general discussion ensues. The total time it takes

to run the Marriage Game is about 1-2 hours including

discussion. It is an excellent prototype model of decisionmaking under conditions of conflicting objectives.

P.L.U.G. The Polytechnic Land Use Game.

.2.1 The Polytechnic Land Use Garne has been adapted from the

Community Land Use Game (by Professor Alan Peldt) for use

in a variety of courses dealing with subject matters relating

to urban design, architecture, town planning and urban

development. Considerable care has been taken to maintain

the game in the simplest possible framework of operation

in order to facilitate its ready adoption into a wide

variety of teaching contexts.

f

.2.2 The game attempts to reduce the broad range of variables

affecting urban land use decisions to a small number of ! basic attributes of towns and their surrounding countrysides j which appear to make up the more universal and important

components of urban systems affecting the development of

particular forms of land use in particular locations,

including the highway network, the points of access,

property taxation, various community services and a

1 particular range of land uses.

392
5.2.5 Play begins with each player In possession of a fixed

amount of capital (usually £55? 000 ) with which he may

seek to buy land; construct commercial or residential

properties in locations of his choice; and seek to make

a profit on his investments through the buying and

selling of land, through gaining employment for his

residential properties, through putting his industries

into operation by hiring employees, or by gaining

customers for his service establishments from among the

residential units located in the community by other

players. Given the initial parameters imposed upon a particular play of the game in the form of transportation

networks, taxation policies, the location of the Ports,

and the kinds of land uses allowed, most land use decisions

are then based upon the degree of accessibility desired

betv/een particular forms of land use already developed

during play or anticipated land use developments which

seem likely to occur in future rounds of the game.

5.2.4 Capital enters the community from the outside world through

payments from the bank to industries and is then disseminated

through the other sectors of the commimity by means of

payrolls to employees and payments by residences to persons

operating localized or centraJized shopping centres for

the routinized purchases of the necessities of life.

Capital leaves the community primarily in the form of

payments made to cover transportation costs, throiogh tax

payments made to support community services and capital

improvements, and through the loss of building value due

to the regular depreciation of buildings during each round

of play. Careful planning and management on the part of

of the players allows them to minimize monetary losses to

themselves and to the comm-unity 1. through mini mi zing

the distances between particular forms of land use which

interact frequently, 2. through prudent management of a

393
commianity capital improvement programme v/hich will provide

enough corvices to fulfill the needs of a growing community

but which will not be wasted on unoccupied land, and J, through

careful handling of their renovation and construction costs on

buildings already in operation. With careful management

of their investaient choices end v/ise decisions as to

the location of their investments pla;yers are usually

able to realize a return on their investments in

excess of 7% pe^r ro'orid.

5.2.5 The ending of the game is not defined at this point

and it could conceivably continue indefinitely. Most

plays, however, tend to terminate after the community

has attained a population of several hundred thousand

which occurs in 15-20 roimds for moderately prudent

players. Playing time is the major limiting factor

in the game ajid most plays of the game require ten

hours of play for an adequate introduction to the

game itself and the growth of a community of some degree of maturity.

394
Concluding v/ith a Successful Start .

6.1 Dirring the past three years at the Polytechnic of Central London,

this author has worked together with colleagues in the Department

of ib?chitecture, Surveying and Estate Management, Business I'lanagement

and Social and Environmental Planning and also with associates at

SAGSET (The Society for Academic Gaming in Education and Training)

in generating a number of varied programmes of interactive

simulation methods along lines described in this paper.

6.2 The inter-disciplinary interest in these programmes has exceeded

that normally encountered in such activities and the enthusiasm

that has been generated in the programmes has helped weld together

certain aspects of a loosely connected environmental studies

programme at the PCL,

6.5 According to plan the present programme of interactive simulation

activities scheduled for next year will expand to include: a pre-term role-playing exercise, to a,ssist in the selection of

applications; an introductoiy week of participation and interaction

simulation to create course-group identity and measure individual

interests and skills at the start of -the course; a simulation

exercise to service each of the course units on (l) new towns,

(2) planning procedures and the organisation of planning, and

(5) decision theoiy; a 3-day mid-course intensive seminar on interactive simulation methods; and a complete 6-week course unit on the design and application of interactive simulation

models in urban planning systems.

6.4 This is the position in April 1975; "the next stage is to develop

a fuller range of simulation exercises to service all the course units in the programme; to integrate interactive simulation

methods with the final evaluation processes at the end of course;

and to strengthen the links between the course and on-going urban

systems simulation work being applied in the field.

395
REFERENCES

:

Cynthia Cockbum, Provisions for Planning Education, CES, London, 1972.

George Odiome, Training by Obje ctives, An Economic Approach to

Management Training , I*Iacmillan, New York, 1970

John Taylor and Rex Walford, Simulation in the Classroom , Peng-uin,

London, 1972.

Robert Goodman, AJter the Planners , Pelican, London 1972 - especially the "Introduction" by John Palmer.

ibid.

Dale Beach, Personnel: The Management of People at Work . Macmillan,

New York, I967.

Josephine Klein, Working with Groups , Hutchinson University Press,

London, 1963«

Alan Elms, Role Playing, Reward and Attitude Change , Van Nostrand

Reinhold, New York, I969.

Robert Sarly, MIKEGASIMO; The Milton Keynes Gaming Simulation Model ; Its Use in Teaching, Training and Research , PCL, London,

Stanley Seashore and Robert McNeill, Eds., Management of the Urban

Crisis, The Free Press, New York, 1971*

ACKNOWLEDGEMENTS

:

The author would like to thank Professor Thorn Blair, Arthur Edwards,

Basil Brenchley, John Palmer and Judith Allen, without whose support

throughout the past two and one half years this paper could not have

been written. Others too numerous to mention have provided much valuable guidance and help. Nonetheless, the views expressed herein

remain those of the author.

396
THE PUBLICATION AND DISTRIBUTION OP SIMULATION GAMES

By Irving B. Naiburg, Jr.

18 East 6Hh Street

New York, N. Y. 10021

I Perhaps because I have been priviledged to be responsible in part for

i the successful conmercial publication of two important simulation games,

SIMSOC by William A. Gamson, and CLUG by Allan G. Peldt, I am aware of the

economics of publishing such games for the college market. The basic

criterion for successful commercial publication of a simulation game through

a large publisher is that the developer of the game has secured wide market

testing and acceptance before it can even be seriously considered for

commercial publication.

This is because of the very high overheads of large commercial publishers.

They are geared to high volume sales of high priced goods such as a basic

textbook selling for $9 or $10. Salesmen's commissions are based on dollar

volume and they will spend time on such high priced items as textbooks and

'( tend to neglect a relatively low priced item with a less certain market

such as a simulation game, even if it sells for as much as $4 or $5-

Thus in my opinion the future of publication of simulation games

i through the large commercial publishers is not bright. Economic constraints

due to declining enrollments at the college level have forced large college

; publishers to cut back most publishing except for basic hardcover textbooks.

-I Thus even publishers such as The Free Press, where as sociology editor I

i|. acquired both SIMSOC and CLUG, are no longer seeking to publish simulation

games. They have acquired none since I left The Free Press in 1972.

The situation with the smaller publishing houses is fluid as to their

ii interest or lack of interest in simulation games. It would not be practical

I for me to name such houses here for that reason. Also, there are new

i publishers that start up and some of them are interested in simulations.

'1 I would like, in my private capacity as one interested in seeing more

I simulation games on the market, to offer my help as a resource person to

[those developers of games who seek advice on how to go about getting a game . published or publishing it themselves. Since each game is so different this

, solution seems more practical than attempting to give general guidelines

in this paper. If I can not solve a particular problem, I may be able to

direct you to someone who can. Just write me at: I8 East 64th Street,

New York, New York 10021. Please let me know how to reach you by telephone

[because I may have questions regarding your problem.

i The one general suggestion that I can make here is that you try to put

I together an inexpensively reproduced preliminary version of your game and

; let people know that it is available for a few dollars through announcements

in the various newsletters and other media that serve both those interested

'in simulation and those interested in the subject area of the game. After

you have received feedback from users, you may then be able to have it

published successfully by a commercial publisher.

jj You could try to get support for such a version if you need it through

;your imiversity or through a foundation interested in the subject of your

f simulation. If you have developed a game and you are seeking suggestions as to how it can be put in a format to make it available inexpensively, I would

be glad to give suggestions on. that as well.

I hope that the future of publication and distribution of simulation

hgames can be advanced by the "home grown" methods I suggest.

397
TASK GROUP SUMMARIES

Design Sub Group Summary:

Canputer -Based Gaming Simulations

by Philip D. Patterson

' Inst. EPA

Washington, D. C. 20015

The Design Sub-Group focusing on computer-based gaming simulations

met on three separate occasions during the 1973 National Gaming Council

Symposium. The attendees at each successive session diminished in

number (from 18 to 11 to 7) and the continuity of attendees was not

maintained; that is, only two people attended all three sessions.

In spite of these circumstances, a healthy exchange of ideas,

experiences, and recommendations emerged from each session. Since the

discussions in each session were so different and so independent, this

report will summarize the three sessions and then draw a few general

conclusions from the overall sub-group activity.

One might expect that at least half of the diversity that characterizes gamers would be absent when a group of gamers who use computers

got together. Such was not the case at this three-session meeting.

Approximately 25 different people attended one or all of the three sessions

and their gaming interests spanned as wide a spectrum as exists in the

entire gaming community.

Ccmputerized gaming models are used in a wide variety of disciplines.

The two most widespread uses - military and business - were not represented adequately during the three sessions. Military games were mentioned only briefly in the last session, whereas the sole business gamer

was at all three sessions and brought up the subject during the last

two sessions.

398
Harold Guetzkow attended the second session and was the sole voice

for the international gaming simulations which are almost exclusively

computerized. The use of computer simulation in the field of medicine

for diagnosis was discussed in the third session. Gaming as related to

Computer Assisted Instruction (CAI) or Learning (CAL) was discussed in

the last two sessions.

Prior to the subgroups first meeting, facilitator statements (these

are contained in Appendex A) were prepared by three individuals and dupli

cated for symposium participants. These statements were not received by

all of the participants. As it turned out, only about half of the sub

group attendees had seen these facilitator statements.

399
Session 1 - Monday Afternoon

Session 1 was the only one in which the three facilitators were

present. Since a number of the attendees and two of the facilitators

had not seen the statements ahead of time and no one suggested a reading

of the statements, the statements did not really provide any focus or

background for the discussion.

The fact that the facilitators all had experience in computerized

urban gaming simulations lent a bias to the first session's discussion.

400
S ess'ion 2 - Tuesday Morning

This session was the only one in which every person attending the

session was asked to describe their past and future uses of computerized

gaming simulations. The first person was interested in having school

officials learn to work with computerized data information systems

as well as use the data to plan the future of their academic institui tions. This person was interested in the software issues of relating

I computerized data files to user oriented training and gaming tools.

I One of the facilitators thought the linkage was a relatively minor

issue when compared with the selection of which data was to be used and

for what training purpose.

A second person from the Internal Revenue Service National Training

Center described the use of manual gaming tools used in the past and

future plans to tie some computerized training games to the PLATO

j system developed at the University of Illinois. In Session 3 a PLATO

I

j user was able to describe some practical experiences that he had with

|| the PLATO system.

The third person discussed the development and experiences associ-

; ated with WALRUS II. Here the impact of uncertain developmental budget

levels were highlighted. Experiences with METRO-APEX were also mentioned,

and this led to the next person who is utilizing the APEX model and

I calibrating it for the rapidly growing suburban county south of Chicago.

401
It is a rare instance when the planned use of a gaming simulation by

community people is first to learn about the intricacies of their growing

county and then secondly to work together to shape the future of their

county. This serious use of gaming for more than educational purposes

dominated all three sessions, but at this point and on several other

ocassions one person raised the issue of the half-hour computer gaming

model used for learning specific material.

The computer-based games that are of short duration, have interactive capability via teletype operation, can be built and used with

limited funds, and can be used by a single person are a definite segment of the computer gaming spectrum. Some computer games are designed

solely for educational purposes and aimed at the average highschool

or college student. They may be integrated into the course and used to

reinforce some portion of the course content.

The next participant discussed the use of management games for

military personnel. There are presently eight computer-assisted managemenlj'

games, four of which are quick-hit tools (i.e., they can be used in less

than an hour) . The most complex simulates 48 months of military management and takes five days to play.

The next participant discussed four of the most significant developments in Internation Simulation: an all computer version, an interactive version that can be used with or without human input, the further

evolutions within the Joint Chiefs of Staff, and a big 60 plus player

version. The modular approach for data banks and theory banks used in

international simulations was stressed.

402
Session 3 - Tuesday Afternoon

This session got new information inputs from gamers in the military

and medical fields. The medical game in most simple terms is to "make

the patient's money go furthest". This means the doctor tests the patient

in some systematic way rather than test his own hypotheses of what might

be wrong with the patient.

This session attempted to come up with some recommendations for

persons interested in designing computer gaming simulations. Some

commonly shared ones were:

1. Don't use the computer unless time, manpower and money are

more than adequate.

2. Multiply all time estimates from programmers by a factor of

two to four.

3. Allow plenty of time for debugging. Testing and debugging will

I take two to three times the amount of time required for design

and programming. \

4. Build the team around a key programmer who will be available

for the duration of the project. Have a design person who can

j communicate with and provide a check on the key programmer.

' 5. A commitment that money cannot buy is required from the entire

team.

6. An expertise of computer simulation, game design, and synthesis

i

! of these two skills is required or must be developed en route

to the design of most computer-based gaming simulations.

403
The topic of evaluation arose during this session, and all agreed

that the funder (usually not the developer) must be convinced that some

thing cost-effective is being built. Sometimes the complexity of the

computer games stands in the way of their being tested and demonstrated

effective or ineffective.

404
UKBM PLANNING SUB-GROUP: SUMMARY PAPER

David E. LaHart

Environmental Studies Group

College of Education

The Florida State University

Tallahassee, Florida 32306

The urban environment is a complex, ever changing system of interacting

forces. Economic, political, social and environmental constraints provide a core of interrelated, interconnected and interdependent systems.

At the center of these systems are human decision-makers, acting individually and in formal and not so formal groupings. Despite this com- plexity, the urban environment can be understood if the simple planning

components are examined critically. Rules and ethics, well defined by

culture, underlie these systems. As systems tend toward balance, generalizations and patterns become discernable. These provide frameworks

for simulations.

The Urban Planning sub-group considered two types of urban simulations;

those with research functions and those with primarily educational functions. While these types are not mutually exclusive, this grouping provides a realistic way of examining the profusion of iirban simulations.

Allen Feldt was q^uick to point out that simulations , as planning or training tools , have a relatively low utility because of the uniq_ueness

of each urban area and limitless possibilities for development. Planning simulations should concentrate on situations that are highly generalizable and transferable.

I For example, W.A.R.D. (What a Revolting Development) is specifically

designed to train people to understand the maze of government agencies

involved in neighborhood redevelopment. This particular simulation

gives intense training in manipulating biireaucrats and the bxireaucracy on many levels of government. Because the theoretical models behind

the simulation are highly transferable, this simulation has a relatively

high utility and can be modified to fit almost any neighborhood.

I Simulations designed to generate policy based on a private technical

I data base necessarily have a low utility. They are used to examine

alternatives to decisions and many such simulations can examine the

effects of a wide array of alternative decisions. These so called

"predictive powers" of simulations can make significant contributions

as research tools and have been used as instruments for community

education. For example, a Florida utility company used a simulationI game that enabled customers to "predict" their utility bill based on

j their present one if current trends in power use and production continue.

I Simulation participants were allowed a wide number of alternatives but

I the "best" choices were the ones the power company officials had advocated for several years. The simulation proved a more powerful public

\ education tool than previous mass media campaigns and the utility

il company was allowed to proceed with its expansion plans. Decision

405
making exercises can bring local situations into sharp focus with very

little effort. As more people become trained in simulation design,

this method will grow in popularity.

Many sub-group participants felt that future sim\ilat ion-games will not

be predictive necessarily but will emphasize "pre-experiencing" . These

future simulations will be based on easily modified models developed by

the participants. The starting point will be identifying an issue or problem that interests the participants and the simulation will develop

from that point.

406
TEACHING AND TRAINING SUB-GROUP: BUSINESS

SUMMARY STATE OF THE ART PAPER

Myron Uretsky, Department of Computer Applications

and Information Systems

New York University 10453

Richard F. Barton, College of Business Administration

Texas Tech University 79409

I. Prospects for the future that have portents in the present state

of the art of management and business simulation gaming:

A. The management of companies will be inextricably involved in

on-going simulations and games.

B. The education of businessmen will be a large scale effort in

simulation and gaming methodology.

II. Present and future resources and technologies supportive of

management by simulation and gaming:

A. Identifiable trends:

1. An increasing amount of business data processing is

handled on the computer.

2. Data processing brings together in one place data from

multiple areas within the firm.

3. There will be computer capacity for the implementation

of large simulations.

4. Increasing amounts of decisions are being implemented on

the computer.

5. The technology of man-computer interactions via terminals

will facilitate gaming simulations of complex business

problems.

B. Logical extensions:

More attention will be directed towards more accurately

estimating future trends, competitors actions, and other

uncontrollable variables.

Since less time will be needed for data processing and

routine decision-making, more managerial time will be

available for complex decision analysis.

More accuracy will be required in decision-making because

the cost of errors will be higher.

1.

2.

3.

407
4. More manc^erial time will be spent in building models and

simulating the outcomes of possible decisions.

III. Conclusions:

A. It will be technically and operationally feasible to develop

a business curriculum based on simulation and gaming

methodology.

B. New tools and new experiences need to be designed for this

environment

.

C. The implications of such an approach are a changed structure

for the economics of education.

D. New evaluative criteria will be needed for use in this

learning environment and to evaluate the administration

of such an educational program.

E. Similar issues will concurrently arise in business enterprises

as gaming simulations play more significant roles in assisting

real business decisions.

Final report prepared by: Richard F. Barton

Texas Tech University

Myron Uretsky

New York University

408
RESEARCH APPLICATIONS OF SIMULATION GAMES: SUMMARY PAPER*

Richard L. Dukes

University o£ Colorado

Colorado Springs 80907

Social science research involving the use of simulation games

encompasses the widest imaginable perspective. First, gaming crosses

many disciplinary boundaries, and therefore embraces many different

types of research problems. Second, there is no clear, agreed upon

methodology for use with games , as opposed to the more traditional

survey or experimental methodologies which are quite well developed.

In the absence of any as yet well developed methodology unique to social

science research involving gaming, the most intelligent course of action

for developing a methodology for use with games, seems to be to borrow

elements from existing methodologies and adapt them for use with games.

Suggestions presented below should be taken only as first steps toward

a methodology for use with simulation games.

Research Designs

Experimental designs provide the most direct road to causal inferences

from independent (manipulated) variables to dependent (measured) variables.

Experimental designs are not used more often in most social science research

I primarily because more often in most social science research primarily because

1) Subjects cannot easily be brought into the laboratory and/or 2) The

variables to be studied involve possible danger to the subjects (ex. the

study of revolutions) . Since gaming research must bring players together

to play, the application of experimental treatments as different forms of

the same game or as different games becomes straightforward. Since most

j simulation games have the ability to model potentially dangerous phenomena

in relatively safe fashion, games can often avoid the problems encountered

in more traditional applications of experimental designs. Since games often

provide more complete social situations than the scenarios provided in small

: group research, games have the potential to avoid some of the artificiality

problems of many social -psychological experimental studies. Experimental

research involving simulation games also has the advantages of not requiring

cover stories to create social situations and operating on autotelic (selfmotivated behavior engaged in for its own sake) behavior which does not

require the paying or other corecion of players. Simulation gaming research,

if intelligently applied, has the potential to avoid many of the ethical

problems encountered in much experimental research, as well as to provide

j strong causal inferences from independent to dependent variables.

i Questionnaire and interview techniques have the advantage of the

ability to gather larger amounts of data on a large number of individuals

in relatively short periods of time. Rather than gathering samples of

individuals from a population as is commonly done, data may be easily gathered

409
on individuals who have played a particular game. If the researcher

is also conducting the game, of course, data on every individual can

be gathered. While many survey research studies attribute groiq) membership

from certain background variables such as social class, true grotq)

membership (where individuals actually interact with each other) can be

accomplished in simulation games. True group membership in simulation

games may lead to stronger relationships between variables which

counterbalance the usual short-term nature of simulation game research

(this relation should be true of most small group research) . Many items

and scales with demonstrated reliability which have been constructed for

questionnaire type research, represent a wealth of untapped resources for

gaming research. Often, little or no re-wording is required for such items

or scales for use with simulation games. Time-outs or pauses between

rounds of games offer logical places for using questionnaire type items

which may not interfere with the tempo of game play. While game scores

are often "noisy" variables, scoresheets can provide information on the

process of game play. Post-game questionnaires, of course, provide informatioit

about game play which cannot influence game play and are a way of asking

reactive questions. In short, games provide a setting in which over- time

data on the process of game play may be gathered without interfering with

play. Questionnaires for use with simulation games may have to be tested

for reliability with players who have played the game, if the questions

contain wording which pertains to the game.

Observer category rating systems such as the Bales method may be

quite useful in observing play of simulation games. Observers are usually

not unnatural parts of most gaming situations. Usually, observers

may roam about the gaming room quite freely without distrubing players too

much. Often observers can be built into games in the form of newspaper

reporters, etc., but it should be cautioned that such roles may be subject

to biased information and "managed news" in ways which an observer as an

observer would not. Game administrators as observers may be the most

natural way to observe game play, particularly if the administrator does not

take sides with particular players or groups of players.

Independent variables commonly used in simulation game research

include different types of players, different games, or different versions

of the same game, or play of a single game. Dependent variables often

include game play, learning, attitude change, change in the structure

of the game through re-design, different qualities of communication among

players or between players and others.

A common pitfall of sampling procedures often employed in simulation

game research involves the inappropriate specification of the sampling

unit. Nhach of the research to date really deals with how groups of players

behave, and yet often, the analysis is based on non-aggregated individualVariables

Sampling

410
level data. To solve this problem, researchers will have to properly

specify the sampling imits, and where groups are the units, play the

game a greater number of times. The statistical determination of sample size

depends on the variability of outcomes on the measured variables which

the game can produce, given a particular sample of players. This topic

will be discussed below under "reliability," but it will suffice to say that even given the confidence level and the tolerable error, the statistical

formula for determining the sanple size requires some estimate of the

variation on each variable to be measured. Game research where individuals

are the sairq^ling units, but where the number of plays of the game is small

enough to be considered probably not representative of the distribution

of play outcomes which the game can generate, should be avoided. Game

research has rarely included random samples of any specified population.

Most game research (or more properly, as Goodman terns it, research on plays

of games) has utilized availability samples. Where availability samples

are used, some sort of randomization procedure where individuals, or even groups, are randomly assigned to experimental treatments, is preferable

to single treatment methods.

Reliability

Reliability has traditionally been regarded as a property of measuring

instruments, and for simulation gaming research, reliability should be

demonstrated for instruments to be used. It also might be useful to consider

reliability to be a property of simulation games themselves. We have

anticipated this concept of reliability as a property of games, above. For

games with a specified number of outcomes, determination of the distribution

of these outcomes with regard to a particular variable becomes a much easier

task than when the game outcomes have a highly emergent quality, and

therefore an almost limitless number of outcomes with regard to a particular

variable. What seems to be needed is a large number of plays of a game

and reliable measurement (determined in the usual way) of the play and/or

outcomes of the game in order to approximate a distribution of possible

outcomes. There seems to be no reason that this task cannot be acconplished

within the framework of traditional -type game research.

Validity

Validity of simulation games has proven to be difficult to assess

beyond establishment of face validity. Part of this problem may stem

from reliability problems concerning games, as reliability is considered

by most researchers to be a necessary condition for validity. Perhaps

more gratifying studies of validity have to wait for more adequate studies

concerning the determination of reliability. However, until that time,

perhaps a workable definition of face validity can be presented. A game

may be said to have face validity for a certain population of players

if questions used to measure variables which are asked of players are

reliable and similar to those which might be asked concerning the referent

system which the game models.

411
*The research applications of simulation games task group consisted

of many persons who participated both formally and informally during the

course of the meetings. The task group was a floating body of people

and ideas. The group can be considered to have met any time a number of

people began to talk about simulation games in social science research,

and this was a frequent occurrence. Formal and informal participants

included Sarane Boocock, Fred Goodman, Gail Fennessey, James Fennessey,

Steve Kidder, David Sarly, Constance Seidner, and at least a half-dozen

others whose names I cannot remember, but whose ideas I do. These

participants are not responsible for any errors which occur above, as they are mine alone.

412
i GAME DEMONSTRATION DESCRIPTIONS

SCENARIO - GAME

A Psycho - Heuristic Game for Random

Invention of Problems and Solutions.

KLAUS DETTE

Technische Universitat Berlin

Lehrstuhl fur Stadt- und Regionalplanung

Professor Dipl.-Ingo Friedrich Gunkel

ADVANCED STUDY INSTITUTE

URBAN SYSTEMS SIMULATION

AND ANALYSIS CONFERENCE

Polytechnic of Central London

July 16-27, 1973

London NV1

The purpose of the selected activities, performed by the participants of the SCENARIO - GAME, is to help the players to create

original ideas in a selected complex decision-field and to use

the offered principles of 'creative thinking' elsewhere.

As all game-participants - they are human beeings - are original

thinkers themselves, the SCENARIO - GAME only provides a rough

framework which is supposed to initiate the emergence of original

ideas. The actual source of ideas are the participants themselves

- they are asked to use their imagination as a means of production.

In the SCENARIO - GAME the process of 'idea-evaluation' is separated from the 'idea-getting' process: The final assessment of the

quality of the ideas, generated in the SCENARIO - GAME, takes place

outside the game. This separation is made, because immediate ideaevaluation inhibits the emergence of new ideas.

The purpose of the SCENARIO - GAME is not to examine specific previously acquired knowledge ( reproduction ) , knowledge as an expected

response to an accepted stimulus - but to encourage creative thin-r

^ing ( production ) , thinking which gives the thinker the impression

that after the thinking process he knows more than before.

413
Unfortunately, the penalties for other than 'expected' responses

to stimuli provided during education, professional training and

exercise have led to a certain reluctance towards 'non-expected'

responses. To moderate this reluctance towards non-expected or

original responses, in the SCENARIO - GAME the players who come

up with the most original ideas are rewarded by taking up their

ideas for further investigation.

To sum up, the SCENARIO - GAME is a method which is supposed to

encourage participants, at first, to use their imagination as a I: means of production in order to experience imagination as a j powerful! tool to recognize and to solve human problems in an

alternative way, and at second, to use this experience in relevant practical decision-making situations.

SCENARIO combines the two complementary activities of

constructing the game and employing ito This has proved to be highly instrumental in motivating the game

participants to develop new ideas and to communicate

effectively with one another,,

Sofar the context of the scenario-writing method is

concerned, SCENARIO similarly aims at the development

of strategic concepts or missions outside the menu of

conventional responses, that is: Standard approaches

to problem-formulation and problem-solving are arbitrarily excludedo The often systemic approach of

scenario-writing is, however, reduced to a less broad

sequence of problem-formulations and solution-formulations. In morphological terms: The end of a SCENArio-session is, to create a path through the (deci—

sion-field-specific ) Problem/Solution/Time - Space,

where problems and solutions are 'discovered' which

are ( hopefully ) new to most game-participants.

2o Furthermore SCENARIO, if applied in the design of

socio-technological-economical systems - might be seen

in the context of the ' divergence ' -phase , which is

according to 'Design Methods' the first step in any

design activityo In the divergence-phase the designsituation is supposed to be explored by: — ¥idening the area of consideration

— Removing pre-conceptions

— De—programming the human mind

— Exploring the problem-fabric

o

As well as defining the 'divergence' phase, the above

four statements also define the purposes of SCENARIO;

and the attempt is being made to prove that SCENARIO

is a useful tool for e.g. decision-making groups in

local authorities during divergence-phases.

414
3o In order to attain the above purposes of SCENARIO, that

is in other vords, to counteract "carry-over" thinking,

and to stimulate game-participants to look at cases

other than the straightforward surprise-free problems

and solutions, a specific technique is introduced into

the SCENARIO-GAME:

In the first place, participants are asked to step out

of the 'real world' and to look at a decision from unusual points of view. In the second place they are encouraged to look at the in this way generated ' phantastic consequences' from ordinary points of view.

in the following, most attention in this paper is given to

the description of the first version of a planned series of

SCENARIO-GAMEs.

In the first place this version is supposed to be a selfcontained game. In the second place it should be seen as an

introductory game for interested game-users without previous

game-experiences and people who want to design their own

games.

It is assumed that this game has some potential to show how

"the game-designer's pre-conceptions influence the gamedesign in general and this SCENARIO-GAME-version in particular.

415
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416
GAMIWG-SIMULATION RECORD SHEET *

TITLE The "Promise of Land

Designer: Harriet Elizabeth Arnold

Date of Construction: November, 1972

Subject Matter: Migration in the United States IT^O-lSOO

Purpose: To teach migration patterns in the United States, 1T^0-1800,

to American History students.

Intended Use: Supplement for eleventh grade history.

Related Games: Ancestors or descendants

PRAGMATICS

Availability : Unpublished

Cost

Source:

Space and Paraphernalia : Space requirements: Regular size classroom

Computer requirements: None

Other media required (not provided in kit): 1 map of U.S. (topographic),

6 pencils, Scotch tape

ICLt paraphernalia:

Materials and quantities needed: ' 1 game board, 6 tokens, numbered and

lettered cards, rumor cards, six score

sheets, 6 participants manuals, 6 small

game boards, 1 game board key, 1 instruc

or's manual, 6 station cards

Standard/ Custom-made

Documentation: Kniffen, Fred, "Folk Housing: Key to Diffusion,"

Wolpert , Julian, "Behavioral Aspects of the Decision to

Migrate," Wolpert, Julian, "Migration as an Adjustment

to Environmental Stress,"

Personnel Requirements : Number of operators needed: 1 adult supervisor and two students

Operator roles and skills: Supervising adult: introduce materials and

collect materials at end of play, supervise

play, supervise play; student 1: hand-out

numbered and lettered cards student 2 : mark

score sheets

Player Characteristics ; Number of players : twenty to thirty-six

Age range: seventh through twelfth grades

Prior knowledge or sophistication required or recommended: Must read at

seventh grade

level

Desired degree of player homogeneity: not applicable

417
Time parameters : Preparation time:

Operator training: none required

Player preparation: twenty to fifty minutes

Duration of play: 1 Introduction: twenty to fifty minutes

Flying time: two to three class periods (fifty minute periods)

Critique: twenty minutes ;

DESIGN MD OPERATING CHAEACTERISTICS:

Stops of play and plot outline : game divided into five stations: station 1; • score sheet marked and food distributed , statiori

2; rumor cards picked up, station 3; rumor cards^

read and discussed, station h; students go to

board and move their token, station 5; numbered

and lettered cards picked up

Player organization : Individual/ team/ coalition: teams

Number of players/ role or team: up to six players per team |f

OTHER NOTES : Aioxiliary theory is the rumor theory in the game

* c 19T3 - R. D. Duke and C. S. Greenblat

418
GAMING-SIMULATION RECORD SHEET*

TITLE: Dialogues on What Could Be

Designer: Joe Falk

Date of construction: Copyright 1973

Subject matter: Evocative communication on any subject or area of interest.

Purpose: A technique to stimulate thinking and conversation to structure but

not control.

Intended use: Senior high, college level dialogues, church or special interest

group dialogues , social or family dialogues

.

Related games: ancestors or descendants - Fireside chats in caves to cocktail

parties in tie and tails.

PRAGMATICS

Availability:

Cost: $1.00 retail - normal distribution discounts apply

Source: The Future Associates, 4935 Wells Dr. , Shawnee Mission, Kansas

66205

Space and paraphernalia:

Space requirements: Cardtable or small (4 person) conversation groupings.

Computer requirements: none unless comparative evaluations are wanted.

Other media required (not provided in kit) : 3" x 5" cards for notes and Intro.

Kit paraphernalia:

Materials and quantities needed: Pack contains 5,000 word booklet on

the subject matter plus 12 3" x 5" evocation question cards. Each group of

4 needs one set of cards . It is better if each individual has his own pack to

prepare for the dialogue and to follow up afterwards.

Standard/custom made:

Documentation:

Personnel requirements : Number of operators needed: none. Everybody is involved as a player.

Operator roles and skills: Explain rules which are brief and included in

pack. Educational input or alternatives in addition to ideas provided

improves the session. Each person is expected to bring some idea to share.

Player characteristics : Number of players: 2/4 minimum - no maximum

Age range: 14 to senior citizens

Prior knowledge or sophistication required or recommended: none

Desired degree of player homogeneity: The more diversified the better

if all are willing to open up

.

Time parameters:

Preparation time: None required

Operator training: Research on ideas on what could be in area of discussion.

Player preparation: Research on ideas on what could be in area of discussion.

Duration of play: 10 minutes per card - 120 minutes total.

Introduction: 5-10 minutes

Flying time: 120 minutes maximum - 60 minutes minimum.

Critique: Each participant might share his reactions with the group for a minute or two. This is a communication development process. Participants get better with practice.

419
DESIGN AlNfi^ OPERATING CHARACTERISTICS:

I

Steps of play and plot outline : Each participant draws an evocative

question card in turn. He is "evoker" for that card - spends two minutes

expressing his feelings on his question and eight minutes evoking his (3)

dialogue mates - then next card is drawn by next "evoker" , Anyone can draw

a card at anytime if bored.

Player organization :

Individual/team/ coalition: Individual - if in a large group we suggest

you divide into groups of 4 and switch groups every 4 cards and continue the

dialogue with others.

Number of players/role or team: Individuals can use introduction

card to indicate their interest or a role they would like to play in the

discussions , they might also mention a book title as an authority base for

their ideas

.

Present stage of development: Usable - 6 topics available - should

evolve into multimedia method plus an unlimited number of subjects or areas

of interest.

OTHER NOTES : The Future Associates as publisher will become a pure

Rochdale merchandising cooperative owned by the people who contribute ideas

and those who make it all happen. Royalties , commissions or fees will be paid

for contributions. Profits will be distributed on the basis of what each member

earns in relation to all members total earnings. A member who contributes

nothing will get nothing

.

*c 1973 - R. D. Duke and C. S . Greenblat

420
GAMING-SIMULATION RECORD SHEET*

TITLE: What Would YOU Do?

Designer: Graduate Assoc . - J. Christensen, C. D'Accurson, N. Frey , S. Juliano

Date of construction: Spring, 1973/ A. Lacks, D. Pfeiffer, J. Zimmerman

Subject matter: Values

Purpose: To provide elementary school children with realistic problems and

alternative solutions which help them to define and accept the

consequences of their actions

Intended use:

Related games: ancestors or descendants - None.

PRAGMATICS

Availability : publication pending

Cost:

Source:

Space and paraphernalia : Space requirements: table or floor space for two-six children

Computer requirements: none

Other media required (not provided in kit) : everything available in kit

Kit paraphernalia:

Materials and quantities needed: all materials are provided in kit-dice,

pieces for players to move , spinner , set of number cards , several sets of

problem cards and board.

Standard/custom-made: dice standard, all other materials custom made

Documentation:

Personnel requirements : Number of operators needed: one

Operator roles 5 skills: operator explains rules, supervises play 5 debriefs.

Player characteristics : Number of players: two-six plus unlimited observers.

Age range: K-5 , inclusion for role play manual for utilization in upper grades

(6-8)

Prior knowledge or sophistication required or recommended: None/

Desired degree of player homogeneity: not necessary

Time parameters : Preparation time: 40 minutes

Operator training: 30 minutes

Player preparation: 10 minutes

Duration of play:

Introduction: done during player preparation

Flying time: minimum 30 minute - variable with sophistication of participants

Critique: 15 minutes

421
DESIGN AND OPERATING CHARACTERISTICS:

Steps of play and plot outline : Player moves his piece through prescribed path on board, length of each move dependent upon throw of dice , at certain junctures player must make a decision as to which path to take. At

other times certain locations dictate drawing of a problem card. Child makes

a decision about how he would solve the problem with random consequences.

Player organization :

Individual/team/ coalition: Individual

Number of players/role or team:

OTHER NOTES:

*c 1973 - R. D. Duke and C. S. Greenblat

422
GAMING-SIMULATION RECORD SHEET*

TITLE: INTERACT

Designer: Brent D. Ruben, Ph.D.

Date of construction: 1973

Subject matter: Human Communication , social interaction , S mass communication.

Purpose: Instructional social science

Intended use: High School and UniversityRelated games: ancestors or descendants - Intermedia , Brent D. Ruben,

Albert D. Talbott, Henry G. LaBrie III, Lee Brown.

Communication System Simulation , Albert Talbott, Brent Ruben

PRAGMATICS

Availability : Cost: $5.00 per Manual for participants

Source: Mercer House Press, P.O. Box 681, Kennebunkport , Maine

Space and paraphernalia: Space requirements: variable

Computer requirements: none

Other media required (not provided in kit) : variable'

Kit paraphernalia:

Materials and quantities needed: 1 manual per participant, instructor

simulation parameter guide sheet.

Standard/custom-made:

Documentation:

Personnel requirements : Number of operators needed: variable; 1 -several

Operator roles and skills: variable; depending upon focus, goals, etc.

Player characteristics : Number of players: 25-several hundred

Age range: variable 9 above 16

Prior knowledge or sophistication required or recommended: variable

Desired degree of player homogeneity: variable

Time parameters : Preparation time: variable with number of players, etc.

Operator training: variable

Player preparation: variable

Duration of play:

Introduction: several hours

Flying time: several days to two years

Critique: integral to game

Conference Needs - Table and chairs for discussing the simulation

with interested parties

423
DESIGN AND OPERATING CHARACTERISTICS

:

Steps of play and plot outline :

(See Gaming-Simulation Record Sheet for details)

Player organization :

Individual/team/coaUtion:

Number of players/role or team:

OTHER NOTES:

*c 1973 - R. D. Duke and C. S. Greenblat

424
GAMING-SIMULATION RECORD SHEET*

TITLE: TEMPO

Designer: Robert L. Sutliff

Date of construction: 1964-1969

Subject matter: Music

Purpose: Education or Recreation

Intended use: General Music Classes

Related games: ancestors or descendents - Bingo

PRAGMATICS

Availability : Cost:

Source: Not available

Space and paraphernalia: Space requirements:

Computer requirements: None

Other media required (not provided in kit) : Phonograph

Kit paraphernaUa:

Materials and quantities needed:

30 Game Boards, 30 Answer Booklets, 75 "calling" cards, 1 Record

Standard/custom-made: Standard

Documentation:

Personnel requirements : Number of players: 2 - ? Age range: 6 and up

Prior knowledge or sophistication required or recommended: None

Desired degree of player homogeneity: None is necessary

Time parameters : Preparation time: 3 minutes

Operator training: None

Player preparation: None

Duration of play : indefinite

Introduction:

Flying time:

Critique:

425
DESIGN AND OPERATING CHARACTERISTICS

Steps of play and plot outline :

Player organization :

Individual/team/coalition: Individual

Number of players/role or team: 2 - ? OTHER NOTES:

*c 1973 - R. D. Duke and C. S. Greenblat

426
GAMING-SIMULATION RECORD SHEET*

TITLE: The Marriage Game

Designer: C. S. Greenblat, P. J. Stein, andN. F. Washburne

Date of construction: 1970-73, Published 1974

Subject matter: Marital decision-making

Purpose: anticipatory socialization for marriage and parenthood

Intended use: classroom use on college level and also use by marriage counselors.

Related games: ancestors or descendants - None.

PRAGMATICS

Availability : Cost: not yet determined

Source: Random House , Inc . New York , New York

Space and paraphernalia : Space requirements: classroom

Computer requirements: none

Other media required (not provided in kit) : Name tages

Kit paraphernalia:

Materials and quantities needed: Each book serves one student and is

consumed during play.

Standard/custom-made: standard

Documentation:

Personnel requirements : Number of operators needed: one

Operator roles and skills: interpreter of rules

Player characteristics:

Number of players: from two to several hundred

Age range: college and up.

Prior knowledge or sophistication required or recommended: High School grads.

Desired degree of player homogeneity: Not needed

Time parameters : Preparation time: Two hours

Operator training: Two hours

Player preparation: Two hours

Duration of play: 8 to 10 - 50 minute periods or equivalent

Introduction: 2 hours

Flying time: 8 to 10 hours

Critique: variable

427
DESIGN AND OPERATING CHARACTERISTICS

Steps of play and plot outline :

See Manual

Player organization : Individual/team /coalition: coalition

Number of players/role or team: couples

OTHER NOTES:

*c 1973 - R. D. Duke and C. S. Greenblat

428
GAMING-SIMULATION RECORD SHEET*

TITLE: "Reservation"

Designer: Rod Stadskley 5 Ron Wagner

Date of construction: Fall 1973

Subject matter: Indian Life on a Reservation

Purpose: Develop awareness of what Indian Life is like on a Reservation

Intended use: Sensitized White People

Related games: ancestors or descendants -

PRAGMATICS

AvailabiUty : 1974

Cost: ??

Source: Contact: Ron Stadsklev Institute of Higher Education,

Box 6293 University, Alabama 35486

Space and paraphernalia : Space requirements: a room and some tables

Computer requirements: None

Other media required (not provided in kit) :

Kit paraphernalia:

Materials and quantities needed:

Standard/custom-made

Documentation:

Personnel requirements : Number of operators needed: One

Operator roles and skills:

Player characteristics : Number of players: 12-48

Age range: 7th grade - adult

Prior knowledge or sophistication required or recommended: None

Desired degree of player homogeneity: None

Time parameters : Preparation time:

Operator training: 1-2 hours

Player preparation: None

Duration of play: 2 hours and up

Introduction: 20 minutes

Flying time: 1 f and up

Critique: 1 hour - 5 hours

429
DESIGN AND OPERATING CHARACTERISTICS:

Steps of play and plot outline : Elect tribal chairman, obtain

employment, decide what to do with your 24 hours a day and see what

results it brings you .

Player organization : Individual/team/coalition: all three

Number of players/role or team: 1 per role - could easily split roles

also has team dimension, 1/4 of players on a team.

OTHER NOTES:

*c 1973 - R. D. Duke and C. S. Greenblat

430
GAMING-SIMULATION RECORD SHEET*

TITLE: Get the Connection?: A Game for Teaching Social Science Concepts

Designer: Richard L . Dukes

Date of construction: 1972-3

Subject matter: Any Social Science Concepts which can be pictorially represented

Purpose: teaching social science concepts

Intended use: classroom teaching devices

Related games: ancestors or descendants - games incorporating Layman Allen's

CAP Claims (Equations , On Sets , etc.)

PRAGMATICS

Availability : Cost: N/A

Source: Paper describing the Game may be obtained from the Author

Space and paraphernalia : Space requirements: One or several small tables; one table per/4 player Game

Computer requirements: None

Other media required (not provided in kit) :None; chalk board would be helpful.

Kit paraphernalia:

Materials and quantities needed: Magazine pictures depicting concepts,

(players make gameboards from these pictures) large piece of acetate to

cover board, several grease pencils, several chips.

Standard/custom-made:

Documentation:

Personnel requirements : Number of operators needed: 1

Operator roles and skills: Operator administrates the game. and provides

guidance to players

Player characteristics : Number of players: any number in groups of four players each

Age range: High School - College

Prior knowledge or sophistication required or recommended: None

Desired degree of player homogeneity: Same or similar familiarity with

concepts to be taught

Time parameters : Preparation time: 10 minutes

Operator training: familiarity with rules 5 concepts to be taught

Player preparation: None

Duration of play:up to 5 1-hour sessions may be used for construction a play

Introduction: 15 minutes of game.

Flying time: 40 minutes (minimum

Critique: 10 minutes

431
DESIGN AND OPERATING CHARACTERISTICS:

Steps of play and plot outline : Players compete with other to

arrive at best description (in concepts) of common elements of 2 of four

pictures. Players in other groups act as Judges, they attempt to identify

which two of four pictures are being described by the concepts

.

Player organization : Individual/team/coalition: Individuals compete with each of the

other players in their own four person game group. Players in other groups

act as judges during certain portions of the game.

Number of players/role or team: l player/role; 4 roles/team

OTHER NOTES:

*c 1973 - R. D. Duke and C. S . Greenblat

; 1 i

432
GAMING-SIMULATION RECORD SHEET*

TITLE: Much Ado About Marbles

Designer: Armand Lauffer

Date of construction: 1973

Subject matter: Articulation between economic, political, and welfare structure

Purpose: in an urban community

Intended use: Classroom (Undergraduate 5 Graduate)

Human Service Professionals 5 Community Leaders

Related games: ancestors or descendants - Variant of "They Shoot Marbles

Don't They?" by Fred Goodman

PRAGMATICS

Availability : Cost: $50

Source: GSIP.O. Box 1747, F.D.R. Station, New York, New York 10022

Space and paraphernalia : Space requirements: Table S 100 sq. ft, of space

Computer requirements: None

Other media required (not provided in kit) : Blackboard

Kit paraphernalia:

Materials and quantities needed:

Standard/custom-made

Documentation:

Personnel requirements : Number of operators needed: One

Operator roles and skills:

Player characteristics : Number of players: 6 to 60

Age range: Junior High students to adults

Prior knowledge or sophistication required or recommended: None

Desired degree of player homogeneity:

Time parameters : Preparation time: None

Operator training: None

Player preparation: None

Duration of play:

Introduction: None

Flying time: 2 years

Critique: 1 hour to several days

433
DESIGN AND OPERATING CHARACTERISTICS:

Steps of play and plot outline :

(See Gaming-Simulation Record Sheet for details)

Player organization : Individual/team/ coalition:

Number of players/role or team:

OTHER NOTES:

*c 1973 - R. D. Duke and C. S, Greenblat

434
GAMING-SIMULATION RECORD SHEET*

TITLE: Decent Clinical Simulations

Patient Management Simulations . (Roche) , Clinical Simulations for Nursing

Designer: Stanley Wolf

Date of construction: 1971-3

Subject matter: Clinical judgment in medicine and nursing

Purpose: Continuing medical education , in-service & pre-service nursing education

Intended use: Institutional m.ailings by Roche, direct sales to nursing education

institutions and individuals by DC.

Related games: ancestors or descendants - Tab item, Patient Management Problems

PRAGMATICS

Availability : Cost: Roche PMS provided without charge; Clinical Simulations in Nursing will

Source: Roche 5 Docent Corporation be about $1 per unit.

430 Manville Road

Pleasantville , New York 10570

Space and paraphernalia : Space requirements: Not relevant

Computer requirements: None

Other media required (not provided in kit) : None

Kit paraphernalia:

Materials and quantities needed: Concealed Image Marking Pen and

Concealed Image Simulation Book

Standard/custom-made

Documentation: Research currently going on in 40 medical schools

Personnel requirements : Number of operators needed: None

Operator roles and skills: None

Player characteristics : Number of players: Monastic

Age range: Adult

Prior knowledge or sophistication required or recommended: Varies

Desired degree of player homogeneity: As a branching simulation, there is

little homogeneity required.

Time parameters : Preparation time:

Operator training: None

Player preparation: 5 minutes

Duration of play: 20 minutes - 60 minutes

Introduction:

Flying time:

Critique:

435
DESIGN AND OPERATING CHARACTERISTICS

Steps of play and plot outline :

(See General Introduction in attached sample)

Player organization : Individual/team/coalition: Not relevant

Number of players/role or team: Monastic use only

OTHER NOTES:

*c 1973 - R . D . Duke and C . S . Greenblat

436
GAMING-SIMULATION RECORD SHEET*

TITLE: Terminex

Designer: Rowbatham et al

Date of construction: 1971 - in process

Subject matter: The dying process - telling of the diagnosis.

Purpose: Consciousness-raising for health care professionals.

Intended use: Teaching of basic students; in-service education.

Related games: ancestors or descendants - None known

PRAGMATICS

Availability : Cost: In mimeographed form; in development

Source:

Space and paraphernalia : Space requirements: 1 Room at least 40 x 40, adjaceni hallway

Computer requirements: None

Other m.edia required (not provided in kit) :

Kit paraphernaha:

Materials and quantities needed: Mimeographed sheets for roles and

instructions (in development) .

Standard/custom-made:

Documentation:

Personnel requirements : Number of operators needed: One

Operator roles and skills: Orientation, running, post-game discussions

Player characteristics : Number of players: 15 players (SM.D.g; 5 patients; 5 observers)

Age range: Teens and beyond

Prior knowledge or sophistication required or recommended: Health care

professional (or others such as health sociologists , social scientists of

Desired degree of player homogeneity: not necessary; ~ | other discipline can be diverse

Time parameters : Preparation time:

Operator training: ??

Player preparation: 1/2 hour

Duration of play:

Introduction: 1/2 hour

Flying time: 2^ hours

Critique: 1 hour -

437
DESIGN AND OPERATING CHARACTERISTICS:

Steps of play and plot outline : Each M.D. interacts with each patient

twice -- once in a "pre-interview" , and second — to tell the diagnosis. The

observers judge the degree to which the M.D. reached a pre-set goal for the

mode of telling

.

Player organization : Individual/team/coalition: "teams" are M.D. - observer; these two rotate

among the patients.

Number of players/role or team: Rotating - M.D. - patient - observer

OTHER NOTES. been tested with medical students , graduate nurse

students, faculty at Duke University.

Game runner — Shirley Smoyak (has participated in development)

*c 1973 - R. D. Duke and C. S. Greenblat

438
GAMING-SIMULATION RECORD SHEET*

TITLE: Acres

Designer: George Didot , Jr

Date of construction: Used since 1971

Subject matter: City land use, development 5 environmental impact.

Purpose:

Intended use: Stress dynamic interaction of economic/political decision-making

teaching used to date in several courses in different schools.

Related games: ancestors or descendants - Best comparison is CLUG

PRAGMATICS

Availability : Cost: yet certain - available late '73

Source: Dartmouth College, Project Compute - Kiewit Computation Center,

Hanover, New Hampshire

Space and paraphernalia : Space requirements: Classroom

Computer requirements: Uses time-sharing Fortran; run to date on GE 635

Other media required (not provided in kit) : Iwill be on CDC 6600

Game board desirable - sometimes use forms for input

Kit paraphernalia:

Materials and quantities needed: Manuals

Standard/custom-made:

Documentation: Manuals

Personnel requirements : Number of operators needed: 1. 2 preferred

Operator roles and skills: Introduction & review of events; initial aid with input

Player characteristics : ^

.' Number of players: 10-20

Age range: 16+

Prior knowledge or sophistication required or recommended: Usable at introduction or advanced levels; need no computer knowledge

Desired degree of player homogeneity: Depends on play desired

Time parameters : Preparation time:

Operator training: If familiar with gaming , a week on 5 off of "playing"

Player preparation: 1-2 hrs . 8 then learn with play. ~~]with it. Duration of play:

Introduction: Should play at least 6 rounds, up to 20+ to date;

Flying time: play 2-3 rounds per week in courses; could accelerate

Critique: if desired for gaming-only use

439
DESIGN AND OPERATING CHARACTERISTICS:

Steps of play and plot outline : Preliminary manual available; could

bring abbreviated instructions and sample output. Background article with

John Sommer in Recent Developments in Urban Gaming

,

Simulation Council

Proceedings Series, Volume 2. Up to 9 teams (2-3 players each) represent

business, residents and government; maker decisions on land purchase,

development , business applications S operation , transportation , environment

,

employment, pricing, taxes, zoning, public spending S investment, schools,

utilities, etc. Done in time-sharing mode with status 8 map reports available.

Business, environmental and community reports generated end of round.

Player organization : Individual/team / coalition

:

Number of players /role or team:

OTHER NOTES :

*c 1973 - R. D. Duke and C. S. Greenblat

1

440
GAMING-SIMULATION RECORD SHEET*

TITLE: Obstacle Course

Designer: John T . Foster, Jr.

Date of construction: January 1, 1972 - September 1, 1972

Subject matter: Disorganized Health Clinic

Purpose: Teach university students in nursing and social welfare about

Intended use: [client frustrations .

Related games: ancestors or descendants -

PRAGMATICS

Availability : Cost: $6.50

Source: Instructional Simulation Design, Inc. , FOB 3330 Leon Station

Tallahassee, Florida 32303

Space and paraphernalia: Space requirements; Table and six chairs

Computer requirements: None

Other media required (not provided in kit) : None

Kit paraphernalia:

Materials and quantities needed: 1 playing board, 1 card deck,

play money, 1 die, 6 player's manuals (All needed materials are present in the kit.)

Standard/custom-made:

Documentation:

Personnel requirements : Number of operators needed: 1 Operator roles and skills: This person should have read both the player

manual and the instructor's handbook.

Player characteristics : Number of players: 6-4

Age range: Adult

Prior knowledge or sophistication required or recommended:

undergraduates in social welfare 5 nursing.

Desired degree of player homogeneity:

Time parameters : Preparation time:

Operator training: 1^ hours

Player preparation: None

Duration of play: li hours

Introduction: 5 minutes

Flying time: 7 minutes

Critique: Varies

441
DESIGN AND OPERATING CHARACTERISTICS:

Steps of play and plot outline : Young professionals play roles of

clients in a health center which is poorly organized.

Player organization : Individual/team/ coalition: Individual

Number of players/role or team:

OTHER NOTES:

*c 1973 - R. D. Duke and C. S. Greenblat

442
ATTENDEES FROM THE NATIONAL GAMING CONFERENCE 1973

Charles H. Adair

Inst. Florida State University

301 Education

Tallahassee, Florida

Layman E. Allen

Inst. University of Michigan

1407 Brooklyn Avenue

Ann Arbor, Michigan 48104

R. H. R. Armstrong

Inst. I.L.G.S.

University of Birmingham

P.O. Box 363

Birmingham, England

Alvin Battle

Inst. Dept. of the Treasury

Internal Revenue Service

1111 Constitution Avenue, N.W.

Washington, D.C. 20224

Jeff Bruninga

Inst. Governor State University

169 Lester Road

Park Forest, Illinois 60466

Virginia Buus

Inst. Campus Ministry

900 Hilgard Avenue

Los Angeles, California 90024

Thomas C. Ball

Inst. Ketron, Inc.

1400 Wilson Blvd., 12th Floor

Arlington, Virginia 22209

Richard F. Barton

Inst. Texas Tech. University

College of Business Administration

Lubbock, Texas 79409

Dr. H. A. Becker

Inst. University of Utrecht

2 Heidelberglaan

Utrecht, The Netherlands

Wm. Boles

Inst. Penn State University

S-126 Division of Man-Environment Relations,

University Park, Pennsylvania

David Bresnick

Inst. Baruch College, City University of

New York

23rd & Lexington,

New York, New York 10010

Maxine Champion

Inst. Dept. of the Treasury

Internal Revenue Service

1111 Constitution Avenue, N.W.

Washington, D.C. 20224

Stuart L. Cipinko

Inst. University of Redlands

246 Fourth Street

Redlands, California 92373

Jennifer Clarke

Inst. University of Pittsburgh

803 Bruce Hall

Pittsburgh, Pennsylvania 15260

Don H. Coombs

Inst. Simulation/Gaming/News

Box 3039, University Station

Moscow, Idaho 83843

Shirley D. Craig

Inst. University of Pittsburgh

7070 Forward

Pittsburgh, Pennsylvania 15217

Russell H. Bronstein

Inst. Dept. of the Army

222 Lisbon Drive

Newport News, Virginia 23601

Edward A. Davis

Inst. APL/JHU

8621 Georgia Avenue

Silver Spring, Maryland 20910

443
Jerry Debenham

Inst. University of Utah

2324 Evergreen Avenue

Salt Lake City, Utah 84109

Gene DePrez

Inst. Rochester Institute of

Technology

One Lomb Memorial Drive

Rochester, New York 14623

Dr. Frank P. Diulus

Inst. S.U.N.Y. College at

Buffalo

Bacon Hall 312B

1300 Elmwood Avenue

Buffalo, New York 14222

Charles Dollar

Inst. Oklahoma State University

Dept. of History

Stillwater, Oklahoma 74074

Dr. Richard D. Duke

Inst. University of Michigan

321 Parillake

Ann Arbor, Michigan 48103

Richard L. Kukes

Inst, University Colorado

at Colorado Springs

4225 B. N. Carefree Circle

Colorado Springs, Colorado 80917

Jacquelyn Engle

Inst. Silver State School

R2, Box 466A

New Albany, Indiana 47150

Leona Farris

Inst. University of Akron

215 A Schrank Hall

Dept. of Home Economics

Akron, Ohio 44325

Allan G. Feldt

Inst. University of Michigan

3105 Sunnywood Drive

Ann Arbor, Michigan 48103

Gail Fennessey

Inst. Academic Games Associates

4000 Linkwood Road

Baltimore, Maryland 21210

Esther Fink

Inst. CUNY

162 St. Johns Place

Brooklyn, New York 11217

Rev. Mallick J. Fitzpatrick, S.J

Fordham Prep School

E. Fordham Road

Bronx, New York 10458

Byron M. Ford

Inst. APL/JHU

8621 Georgia Avenue

Silver Spring, Maryland 20910

John T. Foster, Jr.

Inst. F.A.M.U.

2202 Mulberry Blvd.

Tallahassee, Florida 32303

John H. Geiger

Inst. Metroplan, Inc.

57 North Maple Avenue

Basking Ridge, New Jersey 07920

Nancy Glandon

Inst. University of Redlands

Sociology Department

Redlands, California 92373

William I. Gorden

Inst. Kent State University

School of Speech Communication

Ke"t, Ohio 44240

Harold Guetzkow

Inst. Northwestern U.

1834 Sheridan Road

Evanston, Illinois 60201

G. Gutenschwager

Inst, Washington .University

School of Architecture

St. Louis, Missouri 63130

John D. Henderson

Inst. Ontario Educational

Communications Authority

2180 Yonge Street

Ontario, Canada

444
John T. Hersney

Inst. University City Science

Center

3508 Market Street

Philadelphia, Pennsylvania 19104

Pamela Hodgson

Inst. OECA

Canada Square

2180 Yonge Street

Toronto, Ontario, Canada

I M45 2C1

Dr. John G. Honig

Inst. Dept. Army

7701 Glenmore Spring Way

Bethesda, Maryland 20034

Peter House

Inst. EPA

5330 - 41st Street, N.W. - Washington, D.C. 20015

Norman P. Hummon

Inst. University of Pittsburgh

1140 Beh, U. of Pittsburgh

Pittsburgh, Pennsylvania 15261

David Larry Johnson

Inst. U.S. Govt. Fort Lee, VA.

4106 Montreal Avenue

Prince George, Virginia 23875

Dr. Harold S. Johnson

Inst. Michigan State University

P.O. Box 828

E. Lansing, Michigan 48823

David W. Jones

Inst. Northeastern 111.

Planning Commission

10 S. Riverside Plaza, 16th Fl.

Chicago, Illinois 60606

Richard Kaiser

Inst. Southwestern Michigan

College

Dowagiac, Michigan 49047

Judy Karshmer

Inst. University of Massachusetts

Apt. 362 Puffton Village

Armhurst, Massachusetts

Margort Kennedy

Inst. University of Pittsburgh

Kant Str. 154a

1000 Berlin, W. Germany

Michael Kennedy

Inst. University of Kentucky

College of Architecture

Pence Hall

Lexington, Kentucky 40506

William V. Kennedy

Inst. Western Pennsylvania Conservancy

204 - 5th Avenue

Pittsburgh, Pennsylvania 15222

Daniel L. Klassen

Inst. SUNY at Stony Brook

Huntington Computer Project

Stony Brook, New York 11790

Dr. L. M. Knolle

Inst. University of Pittsburgh

454 Maple Avenue

Pittsburgh, Pennsylvania 15218

John Lackmann

7370 S. Shore Drive

Chicago, Illinois 60649

Armand Lauffer

Inst. University of Michigan

1015 E. Huron

Ann Arbor, Michigan 48104

R. Stanley LaVallee

Inst. U.S. General Accounting Office

Rm. 6909, 441 G Street, N.W.

Washington, D.C. 20548

Mrs. Barry R. Lawson

Inst. Harwell Assoc.

Pinnacle Road

Harvard, Massachusetts 01451

445
Patricia Luciani

Inst. N.Y. State Council

on Architecture

792 Columbus Avenue

New York, New York 10025

John P, Marchak

Inst. Changing Times

Education Service

1729 H Street, N.W.

Washington, D.C. 20006

Michael McCarthy

Educational Testing Service

Princeton, New Jersey 88540

Larry A, McClellan

Inst, Governor State University

923 White Oak

Park Forest South, Illinois 60466

George M. McFarland

Inst. S.S.S.

221 Willey Street

Morgantown, West Virginia 26505

Richard McGinty

Inst. University of So. California

3601 S, Flower Street

Los Angeles, California 90007

Harvey Mettfe

Inst. Long Island University

Graduate School of Education

Greenvale, New York 11548

Roy I. Miller

Inst. Environmental Simulation Labs.

University of Michigan

Ann Arbor, Michigan 48103

S. K. Moorthi

Inst. John Hopkins University

% 1026 Crystal Mall Bldg. //2 Arlington, Virginia 20460

John Muller

Inst. Lutheran Social Services

2635 - 16th Street, N.W.

Washington, D.C. 20009

Earl S. Mulley

Inst. Center for Simulation Studies

740 Demun

St. Louis, Missouri 63105 .-

'

I Irving B. Naiburg, Jr.

18 East 64th Street

New York, New York 10021 A

M. N. C. Nair

Inst. Governors State University

Park Forest South, Illinois 60915

Gerald Neufeld

Inst, Florida State

Rm. 418, 415 N. Munroe

Tallahassee, Florida 32301

Jack Newhouse

Inst. West Virginia State

Dept. of Education

1900 E. Washington St. | Charleston, West Virginia 25305

Landon Nichols

Inst. Eastern Kentucky University

366 Transylvania Park

Lexington, Kentucky 40508

Kenneth Park

Inst. New Jersey Dept. Education

Office of Planning

R.P.&E., New Jersey Dept. Education

225 W. State Street

Trenton, New Jersey 08625

Phil Patterson

Inst. EPA

6118 30th Street, N.W.

Washington, D.C. 20015 I

Charles H. Postma

Inst. Ashland College

Ashland College

Division of Education

Ashland, Ohio 44805

Tricia Y. Martin

Unknown Address

446
J.inda K. Pratt

Inst. National Laboratory for

Higher Education

122 Radcliff Circle

Durham, North Carolina 21101

Erwin Rausem

Didactic Systems

Box 457

Cranford, New Jersey 07016

Earl J. Reeves

Inst. University of Tulsa

600 S. College

Tulsa, Oklahoma 74104

R. Roger Remington

Inst. RIT

Rochester Institute of Technology

One Lomb Memorial Drive

Rochester, New York 14623

Carl H. Rinne

Inst. University of Michigan

at Flint

1321 E. Court Street

Flint, Michigan 48503

Clark D. Rogers

Inst. University of Pittsburgh

803 Bruce Eall

Pittsburgh, Pennsylvania 15260

Karin Rolett

Inst. University of North Carolina

Dept. of Health Education

School of Public Health

Chapel Hill, North Carolina 27514

Larry Ross - Inst. Governors State University

31 Krotiak

Park Forest, Illinois 60466

Frank S. Rubin

Inst. M.S.S.D. Gallaudet

Kendall Green - 7th & Florida Ave.,N.E. " Washington, D.C. 20002

447

Frederick C. Ryan, Jr.

Inst. Office of Planning, N.J.

Dept. of Education

225 W. State Street

Trenton, New Jersey 08025

Robert M. Sarly - Inst. RADIUS

36B South Hill Park

London NW3, England

Carla Schissel

Inst. University of Rochester

260 Crittenden Blvd.

Rochester, New York 14642

Dr. Daniel Schores

Inst. Austin College

P.O. Box 1601

Sherman, Texas 75090

Teresa Sherr

Inst. Westat. Inc.

11600 Nebel Street

Rockville, Maryland 20852

Richard I. Shrager

Inst. NIH

National Institutes of Health

Bldg. 12A, Rm. 2007

Bethesda, Maryland 20014

Richard Schusler

Inst. Kansas University

Bailey Hall

Lawrence, Kansas 66044

Connie Seidner

Inst. Boston University

27 Kingman Road

Newton, Maryland 02161

Herman Sievering

Inst. GSU

College of Environmental Science

Park Forest S, Illinois 60466
James Sinopoli

Inst, Governors State University

1996 City View

Eugene, Oregon 97402

Peter Smit

Inst. University

Noorderstraut 5

Utrecht, Netherlands

Shirley A. Smoyak

Inst. Rutgers University

4 Roney Road

Edison, New Jersey 08817

Edward J. Springer

320 Cathedral Street

Baltimore, Maryland 21201

Ron Stadsklev

Inst. University of Alabama

I.H.E.R.S,

Box 6293

University, Alabama 35486

Mary Ann E, Steger

Inst. Southern Illinois University

Route 1

Harrisburg, Illinois 62946

Barbara Steinwachs

Inst. University of Michigan

Extension Gaming Service

412 Maynard

Ann Arbor, Michigan 48104

Susan T. Tait

Inst. State Dept.

M/MS, Rm. 2238NS

Washington, D.C. 20520

Albert D. Talbot

t

Inst. University of Iowa

School of Journalism,

Iowa City, Iowa 52242

Mary Talley

Inst. DREW

1815 - 37th St., N.W.

Washington, D.C. 20007

Harriet Tamminga

Inst. University of Denver

1949 So. Emerson

Denver, Colorado 80210

Barbara Tarker

RBS

1700 Market St., 17th Floor

Philadelphia, Pennsylvania

Sivasailam Thiagarajan

Inst. CITH

2853 East Tenth

Bloomington, Indiana 47401

Jay C. Thompson

Inst. Ball State University

Area of Curriculum, Teachers Colleg

Mancie, Indiana 47306

Myron Uretsky

Inst. NYU

100 Trinity Place

New York, New York 10006

Violet L. Wagener

Inst. Simulation/Gaming/News

7060 Roaring Fork Trail

Boulder, Colorado 80301

Jerry K. Ward

Inst. NDATC

10206 Bushride Dr.

Elliott City, Maryland 21043

Andrew Washburn

Inst, use

3601 So. Flower St.

Los Angeles, California 90007

Major J. D. Watson

Inst. US Naval Academy

7109 Thrasher Road

McLean, Virginia 22101

M. Whithed

Inst. Temple

Political Science Dept.

Philadelphia, Pennsylvania 19122

448
Georgeann Wilcoxson

Inst. UPUSA

475 Riverside Dr., Rm. 1168

New York, New York 10017

Clarence M. Williams

Inst. Gallaudet College

Kendall Green

Washington, D.C. 20002

Don Wolff

Inst. City University of

New York

72 Kendall Road

Kendall Park, New Jersey 08824

Harlan Wright

Inst. Temple University

233 " 1300 W. Columbia Avenue

Philadelphia, Pennsylvania 19122

Cathy Greenblat

Inst, Rutgers University

Dept. of Sociology,

Douglass College

New Brunswick, New Jersey 0890:

Dette Klaus

Inst. Technical University

Berlin

38 Koebis Strasse

1 Berlin 30, Germany

449
FORM NBS-114A (1-71) b '5. DEPT. OF COMM. 1. PUBLICATION OR REPORT NO. 2. Gov't Accession

BIBLIOGRAPHIC DATA tt^p -,Qr- No. SHEET 1®S SP-jy?

3. Recipient's Accession No.

4. TITLE AND suBTiTLEsiDitdaticii aiid OaJuing. Proceedings of the

12th Annual Symposium National Gaming Council and the

4tn Annual ijonierence iniernaiionai oimuiaiion ana Gaming Association^ iiBS, GaitherelsurA', Md., Se-oteiuTjer

5. Publication Date June 1974

6. Performing Or^nization Code

7. AUTHOR(S)

John E . Moriarty, Editor

8. Performing Organization

9. PERFORMING ORGANIZATION NAME AND ADDRESS

NATIONAL BUREAU OF STANDARDS

UhFAKIMhNI Or COMMLKCh

WASHINGTON, D.C. 20234

10. Project/Task/Work Unit No. 4314591

11. Contract/Grant No.

12. Sponsoring Organization Name and Address

National Bureau of Standards

Technical Analysis Division

13. Type of Reaort & Period Covered Proceedings

Conference: 9-17 to 9-19

14. Sponsoring Agency Code

15. SUPPLEMENTARY NOTES

Co-sponsors: The United States Environmental Protection Agency

Rutgers University . Library of Congress Catalog Number: 74-704

16. ABSTRACT (A 200-word or less factual summary of most significant information. If document includes a significant

bibliography or literature survey, mention it here.)

This document contains the proceedings of a Gaming Conference along with many

formal papers assembled to provide a comprehensive collection of up to date

gaming information. The proceedings are divided into three major sections,

namely, Theory and Evaluation, Design and applications. Each section contains

the text of informal workshops held during the Conference and a selection

of formal papers . There is a significant amount of reference material cited

in the formal papers along with timely questions and challenges explored and j amplified in the workshops .

1

r

i

. - --- 1

s

17. KEY WORDS (Alphabetical order, separated by semicolons)

Computer; decision-making; games; learning; manual games; simulation.

18. availability statement

[^Xnlimited.

1

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TO NTIS.

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UNCLAS^FIED

21. NO. OF PAGES

458

20. SECURITY CLASS

(THIS PAGE)

XX

UNCLASSIFIED

22. Price $4,25

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