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Technical Paper 332 [~ D

THE EDUCATIONAL EFFECTIVENESS OF

GRAPHIC DISPLAYS FOR COMPUTER

ASSISTED INSTRUCTION

M.V. Moore and L.H. Nawrocki

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U. S. Army

Research Institute for the Behavioral and Social Sciences

September 1978

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U. S. ARMY RESEARCH INSTITUTE

FOR T HE B EHAVIORAL AN D SOCIAL SCIENCE S H

A Field Operating A gency under the Jurisdiction of the H

Deputy Chief of Staff for Personnel

WILLIAM L. HAUSER

JOSEPH ZEIDNER Colonel, US Army

Technical Director Commander

NOTICE S

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the U. S. Army Research Institute for the Behavioral and Social Sciences.

~~~~ The f ndings in thiS report are not to be construed as en official Department of the Army position ,

unless so designated by other authorized documents.

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DEDnDT IIUEI.ITAiIflhJ OA~ E READ INSTRUCTIONS F ~~~~~ ~~~~~~~~ ~ i ex i us.rn s BEFORE COMPLETIN G FORM I. REPORT NUMBER 2. GOVT ACCESSION NO. 3. RECIPIENTS CATALO’ 3 NI UBER

Technical Paper 332 L

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~~~ L~ (end S_kIii1.4 ~~~~~~~~ ‘ 4. TYPE OF REPORT & PERIOD COVERED

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~ THE~~DUCATIONAL EFFECTIVENESS OF~~ RAPHIC ( / .

~~~ ~~~ISPLAYS FOR cO?.~~UTER ASSISTED INSTRUCTION . / Final

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/M. V/Moore~~~~~ L. H./Nawrocki

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U.S. Army Research Institute for the .‘ .,__ !~ .!

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Behavioral and Social Sciences ~ !

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II. CONTROLLING OFFICE NAME AND ADDRESS ,

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58. SUPPLEMENTARY NOTES

19. KEY WORDS (Contin... on rer.r.e aid, if n.c..a~~y end ldtntlfy by block n

~rmb.r)

Graphir~ displays

Computer—assisted instruction

Instructional graphics

20 ABSTRACT (Continu, en ,er.ra. side if n•csss y end Identify by block numb.,)

J This report reviews the literature on instructional graphics and

implications of the findings in terms of graphic displays for computerassisted instruction. It was concluded that (a) assumptions about the

inherent value of graphics for instructional purposes are unsubstantiated

by empirical evidence , and (b) the conditions under which the use of graphics

may increase instructional effectiveness remain to be determined. Comparisons between alphanumeric and graphic displays , and between different

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ICCURITY CI..AISIFICATION OF THIS PAOE(Vhen D~~. laI.ee~

20. — .- graphic representations, suggest that future research should systematically

explore the use of graphics as a function of task requirements , subject—

matter content, and learner characteristics. The research also suggests

that (a) the interpretation of research outcomes is contingent upon the

dependent measures obtained , and (b) particular attention should be given

to measures of delayed retention.

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Technical Paper 332

THE EDUCATIONAL EFFECTIVENESS OF

GRAPHIC DISPLAYS FOR COMPUTER

ASSISTED INSTRUCTION

M.V. Moore and L.H. Nawrocki

UNIT TRAIN ING AND EVALUATION SYSTEMS TECHNICAL AREA

Submitt ed as complete and Approved By:

techni cally accurate, by:

Frank J. Harris A.H. Birnbaum , Ac ting Director

Technical Area Chief ORGANIZATIONS AND SYSTEMS

RESEARCH LABORATORY

Joseph Zeidner

TECHNICA L DI RECTOR

U.S. ARMY RESEARCH INSTITUTE FOR THE BEHAVIORAL AND SOCIAL SCiENCES

5001 Eisenhowe r Avenue , Alexandria , Virginia 22333

Office , Deputy Chief of Staff for Personnel

Department of the Army

September 1978

Army Project Numbers Educational Concepts and

70763731A782 Evaluation

2076271 7A764

Approved for public release: distrib ution un limited.
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~~~~~ —— — _ -~~~~~~~-~~~~--_ — -.

ARI Research Reports and Technical Papers - are intended for sponsors of

R&D tasks and other research and military agencies. Any findings ready for

implementation at the time of publication are presented in the latter part of

the Brief. Upon completion of a major phase of the task, formal recommendations for official action normally are conveyed to appropriate military

agencies by briefing or Disposition Form.

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FOREWORD

The Educational Concepts and Evaluation Work Unit Area of the Army

Resear ch Institute (ART ) performs research and development in areas of

educational technology with applicability to military training. Of

special interest is research in the area of large—scale , computer—based

instructional systems. Development an implementation of such systems

is seen as a solution to such current Army training problems as shortages

of qualified instructor personnel , student populations of w idely varying

abilities, a~ d increased training costs.

Technological advances in computer technology now make it possible

to use sophisticated graphics techniques in the instructional process.

Although it has been assumed that such techniques will improve train—

ing effectiveness , scientific evidence does not consistently suppor t

this viewpoint. This paper is the result of the first phase of an in—

house research and exploratory project investigating the effectiveness

of instructional graphics in computer—based instructional systems.

The effort was initiated in the Unit Training and Evaluation Systems Technical Area in response to the requirements of Army Project

2Q763731A762 , “Computer Administered Instruction ,” FY 1975 Work Program ,

and was continued under Army Project 2Q762717A764 , “Automated Educational Technology and Tra ining Simulation ,” FY 1976 Work Program. The work

unit area has since been transferred to the Educational Technology and

Simulation Technical Area of ARI .

Technical Director
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THE EDUCAT IONAL EFFECTIVENESS OF GRAPHIC DISPLAYS FOR COMPUTER—ASSISTED

INSTRUCT ION

BRIEF

Requ irement:

To determine the current state—of—the—art for the use of graphics

in the instructional process and to specif y critical research gaps , particularly with respect to computer graphics.

Procedure:

A review of the literature related to the use of instructional graphics was conducted. Research findings were analyzed in terms of the degree

to which they did or did not support theoretical assumptions and propositions concerning the instructional value of graphics.

There is considerable ql.iestion as to the instructional effectiveness

of graphics in general. Given the cost of graphics relative to less sophisticated presentations , a substantial effort should be directed toward

specifying the conditions in which graphics may be effectively employed .

Three major factors substantially influence the effec tiveness of graphics:

task requirements, subject—matter content , and learner characteristics.

Utilization of Findings ;

This review resulted in an in—house plan to empirically examine instructional graphics through a series of experiments using a range of

tasks, subject matter , and measured student characteristics typically

encountered in an Army training environment.

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THE EDUCATIONAL EFFECTIVENESS OF GRAPHIC DISPLAYS FOR COMPUTER ASSISTED

INSTRUCTION

CONTENTS

Page

INTRODUCTION 1

WHERE ARE WE? 3

Perceptual Efficiency 4

Realism 8

Learner Preference and Motivation 1 5

Multiple Sensory Input 18

Visuals and Instructional Media 19

Individual Differences 24

Overview 26

CAl AND GRAPHICS 26

Graphic Studies 28

Instructional Strategy : Reinforcement and Sequencing 29

Sununary 32

WHERE DO WE GO? 32

The Definitional Problem 32

Research Framework 34

REFE RENCES 37

DISTRIBUT ION 51

LIST OF TABLES

Table 1. Four experiments manipulating visual

display realism in programed texts 11

LIST OF FIGURES

Figure 1. The Cone of Experience 9

2. Task by Content taxonomy 35

K
THE EDUCATIONAL EFFECTIVENESS OF GRA PHIC DISPLAYS FOR

COMPUTER ASSISTED INSTRUCTION

INTRODUCTION

The impact of computers on the educational community over the last 5

years is self—evident. Even the casual observer cannot fail to note the

substantial increase in the number of articles , journals , professional

organizations , and industrial brochures devoted to computer—based instruction.1 It is hardly surprising that the military , with its heavy commitment to education and training, has been among the leaders in the evaluation and development of computer instruction. The extent of this effort

has been well—documented elsewhere and is not addressed in this report

(Fletcher , 1975; Rich & Van Pelt , 1974).

What is surprising , however , is that a survey of the Army training

establishments indicates a greater degree of optimism among potential

users of computer instruction than among members of the research community

(Sherron , 1976). In effect , Sherron found that the users (the faculty and

staff of Army training organizations ) anticipate that operational implementation of computers in the instructional setting will occur much earlier

than the time forecast by the research and development community. This

discrepancy may exist because those engaged in research and development

recognize that the initial financial investment required for computer—based

instruction is likely to be substantial. In addition , the conditions under

which computer instruction can enhance training effectiveness remain to be

accurately determined.

The introduction of a new technology requires a careful reassessment

of the relationship between cost and expected gains in performance resulting from the technology . In the case of compi ters , this reassessment is

especially difficult , because certain of the capabilities uniquely provided by computers permit the introduction of techniques previously impossible or even unknown. Although the performance value gained by using

these unique capabilities has never been evaluated , they are most likely

to be most costly. This paper is concerned with one of these capabili—

ties, specifically the ability to rapidly generate and modify sophisticated graphic displays. This capability is of particular interest when

the computer is directly employed to present instructional material——

computer—assisted instruction (CAl).

1Computer—based instruction is the generic term encompassing the use of

the computer for the administration , management , and presentation of

instruction.
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The emphasis on CAl display capabilities is not purely arbitrary .

One of the major costs of CAl is that of the input-output devices , i.e.,

student/instructor terminals. The best estimate we have is that , for a

multiterminal CAl system , approximately 50% of the initial investment is

for the terminals and supportive software to drive them . Moreover , a

major factor in terminal cost is the degree of display sophistication

required. Hence , the decisionmaker concerned with allocating resources

in the development of a CAl system must carefully determine the display

requirements of the system. The following succinctly summarizes the

situation :

questions to consider are: Will the user need to portray motion graphically? Is high accuracy of the drawing needed?

Are highly complex rotation and size changes required on a

continuous basis? If the answer to all of these is yes , then

an elaborate and rather costly system is required. But as

the user is willing to relax each of these requirements ,

lower cost results” (Computer Decisions , 1971 , p. 41).

The problem for the decisionmaker , then , appears straightforward:

Specify the system goals , determine the system characteristics that meet

these goals , and then specify the hardware/software requirements that

supply these characteristics. The problem is easily stated but not so

easily accomplished.

In terms of Army training , the system goals are usually the training

objectives. A critical assumption is that the objectives are meaningful

and have been evaluated in an acceptable manner. If the system objectives

do not relate to desired performance then , of course , the system will be

ineffective . Fortunately for education and training research , the researcher may develop principles , in terms of general ly stated objectives

or tasks, in parallel with the specification of objectives in terms of

specific behaviors or tasks.

Leaving the question of determining system characteristics until

last , consider the question of specifying the hardware/software requirements that provide desired system characteristics. This problem is relative ly easy to solve , as the literature abounds in relevant information

(Colson , Freeman , Mathews , Stettler , 1974; Kuehn , 1 966; Machover , 1 966;

Miller , 1969; Weitzman , 1973). Although much of this work deals with

performance rather than training systems , such a distinction poses no

difficulty at a molar level of specification.

Finally , consider the determination of system characteristics. It

is here that serious problems may exist. A major activity of educational

research is to provide the data upon which to base decisions regarding

those characteristics necessary to achieve system goals. To the exten t

that these data exist and are sufficient , the specification of system

characteristics will be a relatively easy task. On the other hand , if

the data are insufficient , an area needing further research has been de—

fined. As was stated earlier , a major cost of a CAl system is for the 

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terminals ( including special s o f t w a r e) . This cost in turn is , to a large

extent , a function of the graphics capability required. Therefore , it

would be useful for the CAl system designer to be able to determine

1. The degree to which a graphics capability will enhance instruc—

tional effectiveness and

2. If graphics are desirable, the level of sophistication required.

Unfortunate ly , if the following quotations are any ir.~ ication , the information necessary to answer these questions is less than satisfactory .

Unfortunately , research has not yielded data permitting sweeping generalizations about media. . . . Consequently, good judgment must be used in planning just how to accomplish each

instructional event for the lesson plan (Gagne & Briggs , 1974,

p. 15 1).

The relative effectiveness of alphanumeric versus graphic displays in communicating efficiently , facilitating learning ,

and promoting long term retention should receive more investigation (Rigney & Lutz , 1974, p. 1).

Despite existing folklore to the effect that one picture is

worth a thousand words , there is little in the way of scientific data to support such a contention (Haygood , Leshowitz ,

& Parkinson , 1974 , p. 3).

Although many of us feel that pictorial information is and

should be extremely important to the learning process , .

F nevertheless , when it comes to using graphic capabilities in

instructional situations we seem often to proceed in bumbling

fashion , relying entirely on individual intuition (Bork &

Leahy , 1976 , p. 3).

Clearly , there is little in the preceding quotations to encourage

the decisionmaker. This gap in the state—of—the—art prompts both the

subject matter and the title of this report. The remainder of the report

consists of three sections. Part one , the major portion , rev iews the

literature to date on the instructional effectiveness of graphics , including the special problem of inthvidual differences. The second part briefly discusses CAl research with graphics , and the third portion suggests

F a framework for future research.

L 

WHERE ARE WE?

In an attempt to organize the literature on instructional graphics ,

two things become apparent. First , there is an implicit assumption that

graphics increase the effectiveness of instruction , and second , there are

a number of contentions as to the reasons for this effectiveness. Hence

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the literature that follows is organized on the basis of what might loosely be called theoretical predispositions. These positions range from contentions that intrinsic cues promote perceptual efficiency to emphasis on

extrinsic motivational factors. The rationale for each position is stated ,

the literature relevant to the position reviewed , and a brief summary provided to indicate how well the literature supports the position.

Throughout the literature , cevelopers of pictorial stimuli variously

reason that visuals are effective because (a) they are perceived more efficiently , (b) they are realistic , (c) students prefer them , (d) they unburden overloaded channels , (e) perceptual research has shown individual

differences in visual ability to be an important variable , and (f) visuals

are part of a larger , more advanced instructional system. Experiments designed in part to verify these explanations have failed to support them ,

as will be seen in the following sections of this review. The literature

related to each of these rationales is discussed in turn.

Perceptual Efficiency

The belief that visuals are perceived more readily relates to the

idea that they are intrinsical ly better communicators and will be remembered longer because they provide referents. The concept of the intrinsic value of visuals is rather complex , but in essence it implies that

pictures are perce ived , encoded , decoded , and stored more naturally than

are visual or auditory presentations of verbal stimuli (Paivio , 1969);

hence the assumption that the perceptual or cognitive superiority of pictorial stimuli should facilitate learning: if visuals are perceived nEre

readily than alphanumerics , they should be better teaching devices.

Eye Movement Patterns. Eye movement patterns have been identified in

several studies (Brandt , 1948; Faw & Nunnally , 1967; Hess , 1965; Mackworth

& Morandi , 1967). Subjects tend to fixate on complex areas of photographs

where lines contour sharply (Mackworth & Morandi , 1967). However , complexity does not assure fixation. When two pictures containing attributes

of complexity , novelty , and pleasantness are presented simultaneously ,

subject fixation increases primarily with degrees of pleasantness (Faw &

Nunnally , 1967). These and other studies , particularly Hess’ (1965) pupil dilation measurement , suggest that the subject matter of pictorial

material , not its physical properties alone , influences the stimuli to

which the learner attends.

There is some evidence that attending to stimuli more readily does

not automatically assure more learning. For example , Ryan and Schwartz

(1956) measured recognition time with a tachistoscope , believing that .

“An illustration which required a long perception time must contain confusing or conflicting elements and therefore is less directly relevant

to its purpose” (p. 60). They manipulated three types of pictorial

content——hand , electrical knife , and steam engine cutaway——using four

types of pictorials——photograph s, shaded drawings , line drawings , and

cartoons. They found that line drawings require significantly longer

4 
and cartoons significantly shorter time to be identified. Each stimulus

had also been presented in several different dimension—poses. A signif i—

cant post/object interaction occurred (reminiscent of the many content—mode

interactions cited in the literature). Researchers concerned with instructional effectiveness rather than perceptual efficiency report opposite

findings (Dwyer , 1968a , 1968c).

Along similar theoretical lines , Rogers (1970) presented subjects

with both highly alliterative and nonalliterative alpha numer ic displays,

believing that alliteration from one word would act as a cue for learning

the other in a paired associate learning paradigm . She found , however ,

that until subjects were advised (in a written explanation) to use the

alliteration to their advantage , alliteration did not significantly improve learning.

Color Perception. Perhaps the clearest indication that ease of perception is not sufficient to facilitate learning is the research done

using color. As Brandt (1948) pointed out , color draws attention. Moreover , visual acuity may be enhanced by the juxtaposition of chromatic and

achromatic stimuli; dimensionality may be conveyed by having two colors

lie adjacent to each other , and they will most like ly be perceived in two

different planes; and color may be the major cue in the determination of

the size , distance , and weight of the stimuli (Payne , 1964). Researchers

who have attempted to enhance their instructional programs by adding color

have been largely unsuccessful (Dwyer , 1968a , 1968d , 1968f). There are

undoubtedly conditions in which color can be used as an effective instructional cue; nevertheless , the mere addition of color as an attention—

getting mechanism does not guarantee instructional effectiveness.

Pictures and Associations. The idea that pictures ac t as referents ,

that they are able to be absorbed as one hermetic unit , and that this material can later be reconstructed and decoded , is persistent in the educational literature (Arnheim , 1972; Dwyer , 1972). Experiments addressing

these propositions , however , have shown that a behaviorist view of learning

from pictures by some sort of Thorndike—stamped—in association is simplistic and outdated. In two unusual experiments , Ketchain and Heath (1962 ,

1963) taught students using audiotape and slides. One group saw slides

that related to the topic material , while another saw slides that were

not relevant. A third group (audiotape only) acted as a control. Results

indicated that the nonrelevant slide presentation did facilitate memry

for the topic material better than audiotape only , although not as well

as the relevant slide presentation. Likewise , the associations made to

pictures are more complex than the “associative value of pictures ” implies (Deno, Johnson , & Jenkins , 1968; Otto , 1962; Worth , 1968). When

presented with either a list of words or successive pictorial stimuli to

which subjects were asked to make nonlabeling associations , a greater sim—

ilarity was found to exist between the responses made to the words (which

were independent) than between the responses made to a word and the picture to which it referred (Deno et al., 1968).

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Worth (1968), using Osgood’ s Semantic Differential (Osgood , Suci , &

Tannenbaum, 1957), found that man ipulation of the elements within a picture affected its interpretation. Students tended to integrate elements

within a picture into a unified theme , the n umber of themes increasing as

elements became more dissimilar. Otto (1968) also found that pictures and

their verbal descriptors evoked qualitatively different responses , the responses varying according to which category they belonged. Garrard (1971)

found that careful ly derived sets of data , generated by a computer functioning under a stochastic mode l of human response behavior in a classification scheme for six physics wo~’ds such as “velocity ” and “momentum ,”

produced only moderate to low correlation with actual human responses.

Although it appears that pictures can act as referents , the conditions

under which they do so have not yet been delineated. Hence , the instructional effectiveness of the associational value of pictures remains to be

determined.

Recognition: Auditory versus Pictorial. The nature of the task

employed considerably affects the relation between sensory modality and

encoding efficiency (Ingersoll , 1970; Jensen , 1971). For example, recognition tasks that require the subject to monitor a stimulus have traditionally found that auditory stimuli are more accurately detected than

are visual stimuli. Moreover , if the dependent measure is response latency, the auditory stimuli are responded to more quickly than are the

visual stimuli (Jensen , 1971). Some theorists interpret these results as

indicative of a primary auditory coding mechanism; visual inputs must

first be transformed into this auditory code , hence the longer response

latency. Similarly , female students who were required to count the frequency of oncoming stimuli that were grouped both successively and simul—

taneously (totaling 6,192 decisions per subject ) processed the auditory

stimulus (a sharp click ) more effectively than the visual (a flash ) or

the tactile (pressure to the forefinger ) when the stimuli were presented

successively . As speed of transmission increased , visual and tactile

accuracy decreased sharply (Reese, Robinson , Stevenson , & Volkman , 1960).

Ingersoll (1970), however , indicated that the ability to process auditory

stimuli more efficiently may vary among subjects. He first pretested

subjects for preferred recall. Subjects who displayed preferred auditory

recall remembered significantly more auditory messages , whereas subjects

who displayed preferred visual recall performed better with visual stimuli. In addition , auditory recall exhibited a recency effect , while visual recall exhibited a primacy effect. Thus, ease of perception of pictorial stimuli appears to be situation—specific and varies with indivi dual

differences.

Recognition and Recall: Verbal versus Pictorial. Recognition of

pictures is somewhat better than recognition of alphanumerics when both

types are judged as new or old (previously presented ) (Snodgrass , Wasser ,

Finkelstein , & Goldberg, 1974). Presenting successive stimuli , experimenters have found visual recognition to be highly accurate even under condi—

tions of “noise” (blurred or sketchy presentations) (Day & Beach , 1950).

Magne and Parknas (1963), using either pictorial or alphanumeric slides

presented successively , required the subjects to indicate changes in

6

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plant structure ( roots , e t c .) . Subjects who were both taught and tested

by the pictorial method performed sign ificantly better than those in the

three remaining combinations. Day and Beach ’s (1950) results were similar ,

indicating that pictorial stimuli produced significantly better free recall

than verbal stimuli. Although there is evidence that learners are able to

extract detailed information from pictures, it seems likely that the superiority of pictures is evidenced only for recognition paradigms . Using a

recall paradigm , Bergan , Zimmerman , and Ferg (1971) presented numerical ,

pictorial , and alphanumeric stimul i , variously grouped and displayed on

slides, with four to seven slides presented serially. Their fifth—grade

subjects did not remember any one of the three types of stimuli significantly better than any other , despite grouping. It appears that the

choice of response measure substantially influences the effectiveness of

the graphic presentation manipulated.

Delayed Recall. When testing is delayed , the results of some of the

above experiments change. For example , Jensen ’s experiment (1971) using

delayed recall testing indicatd that the visual mode was significantly

more effective than the auditory mode , with a significant time delay by

mode interaction. Similarly , using both children and adults , Ward and

Naus (1974) determined that color significantly facilitated retrieval of

information that had been initially presented in black and white. Not

surprisingly , Lantz (1974) found that subjects who had previously been

taught a simple and complex wave discrimination task took significantly

longer to produce correct responses, and the response time increased in

direct proportion to the delay schedule. The paucity of research employing the delayed recall paradigm prevents the drawing of conclusions about

the effectiveness of graphics under these conditions.

There are several hypotheses about the nature of the processes between the encoding and decoding phases (Brunner , 1964; Paivio & Yarmey ,

1966). Regardless of the internal process , a methodological problem presents itself. First , pictorial memory is biased by recognition testing.

Pictorial memory cannot be effectively tested in the usual response paradigm , because in nonrecognition testing the subject is required to make a

verbal response, which may require another coding if indeed the information is stored pictorially . How , then , can a subject make a pictorial response? Drawing almost invariably touches upon distinct abilities , yet

drawing is the usual nonverbal dependent measure. On the other hand , most

tasks do not require learners to manipulate the pictorial stimuli with -

which they were instructed; they are more likely to be asked to perform

some perceptual or cognitive task. Pictorial tests are not representative of most tasks that people perform , and as such unduly bias the dependent measure; thus , nonpictorial testing more frequently approaches

real—life performance requirements.

Summary of Research on Perceptual Efficiency . Although there is evidence that at some basic level visual displays facilitate information pro—

cessing , the proportion of variance in the learning situation accounted for

by such factors as eye fixation and color coding is negligible in terms of

predicting the overall effectiveness of visuals for education. Pot 

only7
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has the perceptual efficiency of graphics been questioned , but several

researchers contend that graphics per se do not substantially enhance instruction . Reviewers report that visuals and nonvisuals , or levels of

visuals , when compared for instructional effectiveness , result in the “no

significant difference syndrome” (Allen , 1971; Briggs , 1968; Dwyer , 1972;

Mcxeachie , 1974; Spangenberg, Riback , & Moon , 1973).

Realism

The emergency training requirements of World War II produced a demand

for training simulators and training aids when student/instructor ratios

sharply increased , and the priority of equipment assignment was given

first to combat and second to training. These conditions significantly

affected the direction of subsequent military training, because implicit

in this training posture was the belief that the most effective training

procedures were those that most concretely approximated the job situation.

Longstanding assumptions regarding the educational value of approximating

reality (e.g., a picture is worth a thousand words ) were given credence

and hence perpetuated.

Technological advances brought about the emergence of highly sophisticated audiovisuals , again supported by implicit notions about stimulus

fidelity . The emergence of audiovisuals in peacetime training was supported by these underlying theoretical formulations , which collective ly

became known as the realism theories. Dale’s “Cone of Experience” (Figure

1) represents one attempt to define the relationship between the degree

of realism and instructional media (Magne & Parknas , 1963).

Because graphics pictorially approximate reality, it was assumed that

they were inherently effective instructionil tools. It was further assumed that degree of learning transfer was directly proportional to degree

of pictorial fidelity.

Dwyer Research. The most systematic exploration of the relationship

between graphic level and instructional effe -- veness was conducted by

Francis Dwyer. A complete review of his work is available in the literature (Dwyer , 1972). Dwyer hypothesized that as the level of pictorial

real ity increased , so did the student’s comprehension of the instructional

material. In most of the 11 experiments cited in this section , the paradigm employed by Dwyer was consistent. In seven experhnents , course material about the functioning of the huma n heart was recorded and presented

to the subjects by audiotape , while graphic displays were manipulated on

slides or other projected visuals. In the remaining four experiments ,

subjects were presented with printed text materials , with visual displays

manipulated on book plates. The dependent measures werp four tests: Comprehension , Terminology , Identification , and Drawing. The four tests

could be combined to provide a total comprehension score. The reliability

of these dependent measures was fairly high ; the Kuder—Ri chardson Formula

20 reported between .85 and .95 in all cases.

B

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Visual

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Learning Experience

The Cone of Experience depicts the belief that there is an

increase in learning experience as the instructional presentation goes from highly abstract to high ly realistic. From

E. Dale in Magne & Parknas , 1963 , p. 267.

Figure 1. The Cone of E xperience.

9

~~~~~~~~~~~~~~~~~

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____

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In each experiment , v isual display was man ipulated as a levels variable. A verbal presentation of either alphanumeric or audiotape version

alone served as the control. Dwyer expected a simple line drawing presentation to be less effective than a shaded drawing , which in turn would be

less effective than the heart model level , and so on , the pho tographic

level being the most effective. In three experiments , Dwyer added the

additional variable of color , comparing color and monochrome versions of

his visual presentations (Dwyer , 1968a , 1968d , 196Sf).

Finding no significant differences supporting the realism hypothesis

in his early experiments, Dwyer presented the same material to different

age levels (9th—l 6th graders) and added time to completion and delayed retention as dependent measures ( Dwyer , 1967a , 1968d , 1968f). There was some

variation in sign ificant results from one dependent measure to another ,

and Dwyer himself has stated that his experiments failed to support the

realism theories.

For the sake of clarity , the Dwyer experiments cited here have been

divided according to whether the instructional material was presented by

programed text or by projected materials.

Experiments Using Programed Text Materials. The programed t.

~x t presentation required the student to make a response before cor~~1r~~

1i r ~q.

Plates 2—1/2 inches by ‘—1/4 inches presented several levels of visual

real ism. In the nonvisual version , the term being ~i scus3ed was to~~ct~~bed

alphanumerically or-i the plate. An additional nonpro~ ramed text ‘~ersi n

acted as overall control; no plates we re used in the overall control.

Table 1 shows thit in two of four experiments the black—and—white

photograph presentati~~

.- was more effective than the remaining alternatives.

However , i t is appa r ent t hat th e e ffe ct iveness of grap hic levels varies

from subtest to subtest. For examp le , on the Comprehension and Terminology tests, in no case did students at any level perfo rm better tha n

students who received a nonpictorial version. On the Drawing and Identification tests, however , the photographic and (in one instance) the color

model were significantly better than the nonpictorial levels. These results are undoubtedly confounded by Dwyer ’s use of test stimuli that were

a function of presentation stimuli (Dwyer , 1967b , 1968a).

Time Correlation. Dwyer hypothesized that since they provided additional cues , more realistic visual displays mi ght require greater viewing

time . Previo is experiments had not attended to this notion. Dwyer evaluated this hypothesis through subject report data. In three experiments,

Dwyer asked his subjects to keep a record of how lonq they spent stud ying

the course material ( Dwyer , 1967b , 1 9E’8a , 196Sf). In all three experiments , the r e s u lt s cons istently rejected hwyvr ’s i y ~~~thesis. A l ti i

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Experiments Using Projected Materials. The results of Dwyer ’s experiments using projected materials such as slides, filmstri ps , and instructional television are much the same as in his programed text manipulations

(Dwyer, 1967a , 1968b , 1968d , 1968e , 1968f , 1969c , 1970b). In general , no

presentation was consistently more effective than the alphanumeric presentation (projected alphanumerics) for the Comprehension and Terminology

tests. The Drawing test was marked by significantl y higher scores , simple

line drawings being most effective in six of seven experiments. The Identification test was marked by conflicting results , pictorial presentation

being significant in some experiments and not in others.

In two experiments , Dwyer took delayed retention measures (Dwyer,

1968d, 1968f). In most cases , scores in the alphanumeric condition were

significantly improved , and any initial differences between alphanumeric

and visual presentations were eliminated. In one exception——Terminology

retention scores were higher for subjects in the black—and—white heart

model presentations and in both photographic presentations. These results

are somewhat more readily interpreted if one excludes the terminology ex—

perimental results. Delayed retention scores then sho~i significance for

the alphanumeric presentation only . When compared to delayed retention

scores using programed texts , a discrepancy appears: the simp le line

drawing level shows significant improvement with delayed retention. A

possible explanation for this inconsistency is that these results are due

to an interaction between the disseminating media (in this case , tex : vs.

projected visuals) and the level of visual presentation. For example ,

the programed text undoubtedly allowed for more individualized instruction

because it was self—paced , whereas the slide presentation was group admin—

istered. This concept is discussed in detail in the section or-i visuals

and media.

Related Research. Several researchers have manipulated attributes

of visual displays according to the realism continuum (Cooper & Gaeth ,

1967; Wheelbarger , 1970; Moore & Sasse , 1971). Moore and Sasse (1971)

concluded that developmental factors influence the student’s ability to

learn from pictures. When they manipulated the type (drawing, photograph ,

painting) and size (half—screen , quarter—screen , full screen) of projected slides , they found that the effectiveness of display characteristics

varied with age and grade level of their subjects.

Wheelbarger (1970), whose experiment closely followed the Dwyer paradigm , found that his sixth—grade subjects had difficulty with the material

when visuals were excluded. Thus, research using di fferent age groups

suggests that the instructional effectiveness of graphics varies with

cognitive skills. Wheelbarger divided his subjects according to scores

on the Lorge—Thorndike word norms (94 and below ; 95—110; 11 1 and above )

and presented them with one of several experimental slide conditions :

alphanumeric , shaded drawings , and photographs , the latter two in both

color and monochrome versions. No significant differences were reported

on the operations or recall test; however, students who scored in the

high intelligence quotient (IQ) range and who had been assigned to the

verbal condition scored significantly lower than their counterparts in

12
the other experimental conditions (Wheelbarger , 1970). In contrast ,

Hagaman (1970) reported no si gnificant differences between verbal and

pictorial groups for subjects of varying IQ, although the subjects in the

higher IQ range scored significantly better overall.

Although no significant difference between simple line drawings and

color photographs was reported in learning a task that required subjects

to pair words and pictures , Wicker (1970) reported that the strategy

(mediation or rote ) used by each subject did affect performance. Mediation was more likely to reduce errors in the photographic group. Again ,

it appears that intellectual and educational factors influence the effectiveness of visual displays.

Results of three experiments directl y conflict with the realism theories——with the cone of experience in particular. Following the belief

that realism enhances learning, Cropper (1968) compared the effectiveness

of hands—on performance versus a visual instructional program. The task ,

which required the subject to assemble a three—pole motor , was performed

significantly better by subjects assigned to the hands—on group. However ,

Gropper stated that this superiority was more apparent in the early stages

of testing and suggests that it is the result of motor practice rather

than of superior learning of the task.

In contrast , Austin (1972) found that a manipulative instruction

group did worse than a pictorial pres’-’ntation group. However , since the

lesson content was statistics rather than a perceptual—motor task (having

subjects flip coins to illustrate probability theory), the results may not

be meaningful in the traditional sense of manipulation. Finally , Laner

(1955) tested the effectiveness of motion pictures versus still pictures

derived from the motion pictures for teaching a perceptual—motor skill

for which he believed the subject needed to Irnderstand the functional interrelationships of parts in motion. Three immediate tests were administered : draw a rough sketch , answer 18 oral questions, and assemble the

trigger mechanism . No significant differences were found attributable

to presentation mode .

Realism and Color. The dimension of color has been of particular interest to researchers of graphic presentation , in part because color enhances realism . The Dwyer paradi gm included the addition of color to each

visual level in three of his experiment s (Dwyer , 1967b , 1968d , 1968f).

Dwyer stated that the addition of color did not result in an overall positive effect (Dwyer , 1971); color did , however , seem to have a somewhat

consistent effect in Dwyer ’s experiments. For example , for programed instruction , the shaded drawing was not as effective as some visual presentations. For projected materials , however , shaded drawings could be

enhanced by the addition of color. The color heart model in the programed

presentation was effective , whereas the black and white was not (for the

Identification and Drawing tests). It is possible , then , that tasks that

require a more visual response may , at some levels , be enhanced by the

addition of color.

13
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Results of other experiments manipulating color in the realism continuum are very similar (Hagaman , 1970; McCoy , 1962; Vandermeer , 1954;

Wheelba rger , 1970; Wicker , 1970). The Wheelbarger and Wicker experiments

already described found no significant difference attributable to the use

of color. Hagaman instructed all of his students with the same materials ,

but he varied the level of realism and use of color in his test stimuli.

He presented his third—grade subjects with 17 pictures and object names:

color picture, black—and—white picture , monochrome line drawing , or object

name alone. Results indicated no significant differences related to response stimuli. Additional analysis revealed , however , that boys responded

significantly better to tests with color pictorial stimuli (Hagaman , 1970).

McCoy hypothesized that an audience would rate color film presentations as more real than black—and—white presentations of the same (documentary ) material. Results indicated the reverse; the audience more

frequently judged the monochrome version as realistic (McCoy , 1962).

This result is probably due to more frequent exposure to monochrome

documentaries.

In an experiment designed to tap a visual and social class interaction , Morgan (1971) presented either color or black—and—white illustrations

in texts on tractor repair and mower maintenance. Subjects were chosen

from ninth graders enrolled in the South Carolina public school agriculture

classes and , by quota sampling, were assigned to experimental conditions

according to race and economic status. Colored illustrations did not have

a significant effect on either immediate or delayed retention (6 weeks).

Upper—class white subjects , however , did somewhat better on the color

presentation.

Summary of Research on Realism. The hypothesis that highly realistic

graphic presentations teach material more effectively than do less realis—

tic presentations has much face validity . However , the hypothesis is not

supported by the literature. Though experimentation in this area is marked

by lack of replication , it appears that if realistic visuals significantly H

enhance learning , this result should be reflected in the literature——yet

it is not. There is evidence , however , that several factors may influence

the effectiveness of visual display. As seen in the previous studies ,

the effectiveness of visuals has varied with the dependent measure em—

ployed. There is an indication that some subject matter is more conducive

to visual presentations than others. IQ or mnemonic devices , or possibly

other subject characteristics (e.g., age), may interact with types of vi—

suals. In addition , color , which is often thought to increase realism , has

limited applicability. Rather than being intrinsically effective , color

appears to enhance selective visuals , particularly in those experiments

which use visuals as part of the response requirement. Generally, then ,

use of visuals should be carefully weighed against task , subject matter ,

and student characteristics.

14
Learner Preference and Mo t ivation

The opinion that visuals significantly affect learning because they

create a pleasing learning situation , are positively moti .ating , etc.,

is prevalent in education today. Research on learner preference for certain instructional stimuli is seen as a valuable adjunct to any instructional development program; newer technology studies are often accompanied

by post hoc measures of a learner ’s attitudes toward the instructional

situation (Dwyer , 1967d; Siegel , 1973).

Some efforts to experimentally measur e preference as arousal have

also been made; the most notable be i ng the Hess research (1965) on pupil—

lary response. Media preferences measured by physiological data such as

pulse have also been attempted (Bruha , 1970; Silber , 1969). These researchers found some reaction to film as a media , but more frequently

they found reactions to film content. More important, Bruha found a d.is—

crepancy between teacher and student preferences. There are , however ,

little data to support the notion that a subject ’s preference for a particular kind of instructional stimulus necessarily affects performance.

Subject preferences do not necessaril y enhance the teaching effectiveness of particular modes , but there is evidence that preference does

significantly reduce attrition (Wali , 1970). In a study of adult learner

preferences in Iran , Wali found that both teacher choice of mode and student preferences for mode reduced the dropout rate. Thus , in the long

run , learner preference may affect learning.

Children ’s Preferences. A review of the literatur e of visual preference has been made by Spaulding (1955), who reported the following: Children prefer books with brilliant color illustrations; these illustrations

should cover at least half a page , ideally a whole page; and realism of

the illustration takes precedence over color , as children prefer realistic

black—and—white to colorful nonrealistic presentations. Children ’s visual

preferences are reported to change as they develop , according to Spaulding ’s

review. Younger children often pr€fer specific colors , such as red . They

also prefer simple line drawings , whereas by fifth grade , most children

prefer more complex illustrations (such as photographs) over simple ones

(85% vs. 15%). Younger children prefer that the content of illustrations

(and thus the stories they accompany) be about familiar things , wh ile

older children prefer the exotic. For example , younger children prefer

stories about domestic anima~ s, and older children prefer stories about

wild animals.

Adult Preferences. Adult illustration preferences are somewhat different from children ’s, with some variability owing to sex differences.

Overal l , women prefer illustrations containing more classical themes, and

men prefer sports and do not mind mildl y gory scenes. Spaulding (1955)

reported , however , that both sexes lacked interest jr-i photograph s with new

or unfamiliar materials (P .q., amb i gu ous) or those “that were vague as to

content or action ” (p. 39).

15

.14
—~‘-~~- - ~~~~~~

Attention and Preference. The possibility that content is a strong

factor in determining preference is suggested by Kaplan , Kaplan , and

Wendt (1972). They found that , contrary to popular opinion , preference

for illustrations could not be explained on a simplicity—complexity dimension. In their experiment , content (pastoral vs. urban ) had the greatest effect, some scenes being preferred to others. Sloan (1972) also

found that content significantly affected preference , but in her study

of varying socioeconomic levels , style of presentation and sex of subject

also significantly interacted. Overall , males preferred the more realistic

presentations to line drawings , and females showed more varied responses.

Increasing the size of photographs in newspapers has also been found

to increase attention to a certain pictorial; when a picture was large ,

subjects read the accompanying text more often. In the same way , color

increased attention to particular stimuli , and color pictures elicited increased reading of material. But alphanumeric displays such as headlines

produced an interactive effect between the meaning of the headline and

size . The headline had to be phrased so as to complete a thought before

subjects attended to the subsequent text (Spaulding, 1955).

Visual Preference and Performance. Overall then , there is some evidence to indicate that preferences for visual materials are a function of

several individual characteristics , including age and sex. However , the

proposition that these factors significantly affect learning from materials

containing the stimuli preferred by a particular group , and indeed that

these preferences will act as screening devices , is not supported by the

literature. For example , Laughery and Fell (1969) found that despite

learner preference for the visual mode , subjects in a memory—span task

performed better on the auditory than on the visual p :esentation of

material.

There is some evidence that preferred visua . stimuli may be counterproductive in some instructional situations. For example , Halbert (cited

by Spaulding , 1955) found that illustrated versions of a text elicited

more ideas from children , but that these ideas were more often than not

directed away from the central theme of the material. In essence , the

illustrated text created more distractions than did the nonillustrated

version. She concluded that if the task is to teach about a particular

concept , illustrations may be counterproductive .

Color and Preference. Perhaps the most wide ly accepted belief about

the effectiveness of any one stimuli , or attribute of an illustration , is

that a color version of an illustration will more effectively communicate

an idea than a monochrome version of the same material. The assumption

for this belief is that color is pleasant and thus a very strong motivator

(Dwyer , 1971; Laner , 1955). There is little doubt that most subjects prefer color illustrations (Vandermeer , 1954), but as with overall preference

for visuals , there is little evidence that this preference significantly

affects performance when color and monochrome presentations are compared.

For example , Vandermeer showed five black—and—white films to 9th and 1 0th

graders. Subject matter included maps , rivers, snakes, sulfur , etc.

16
Dependent measures were both verbal (sentence completion , multi ple choice )

and nonverbal (pictures , graphs). The results of tests given both immediately after the screening of the material and after a 6—week delay

showed no significant difference due to the addition of color. Replication of the same paradigm for ninth graders with no delayed retention

tests had the same results , although subjects in this experiment reported

that they preferred color presentations , and subject matter did positively

interact with this preference , with no sex differences.

In an attempt to measure the positive attitude toward the use of

color , Wright and Gardner (1960) had men (of whom two—thirds were blue—

collar workers) rate three versions of four three—color pictures , using

Osgood’s Semantic Differential (Osgood et al. , 1957). The author hypothesized that color was an additive type of stimuli and that preference for

color would show up as a response evoked jr-i an additive manner. They

found that in some cases subjects responded to color independently of

pictorial content , but in others there was a strong color and content

interaction.

Summary of Research on Learner Preference. The literature indicates

that visual preferences do exist , perhaps correlated with other factors

such as age , sex , and socioeconomic position. However , there is little

evidence to support the notion that preferences for particular visual

stimuli affect performance. This latter statement does not necessarily

contradict the laws of motivation and learning. It may very well be that

subject preference measures include more factors than were initially apparent. For example , asking subjects to describe their preferred instructional modes may elicit either “Which do I like the best? ’ or “By which

do I learn best?” Farr ’s research (1970) addresses this issue. Subjects

were assigned to instructional methods accor~Iing to which method they

thought they would learn best by——not identical to which they preferred.

Subjects performed significantly better when using the method of their

cho ice. Thus it is suggested that attitudes about learning may be implicit

in the preference measure chosen.

There is little research on preference—prediction in visuals. Visual

likes and dislikes are usually measured post hoc (Dwyer- , 1972) rather

than by assigning subjects on the basis of their preferences. Schiff

(1970) demonstrated that experimentally mani pulating preference and content in the visual situation may be awkward. Believing that content

would affect evaluation of a film , in particular the estimate of the

duration of the film (the dull films being judged as longer) , Schiff

measured like—dislike and perceived duration of several films. The re—

sults were not si gnificant; subjects ’ estimates of film duration were

hi ghly inaccurate in all phases of the experiment. This result suggests

that subject report of effectiveness of some preference factors may be

hi ghly unreliable.

17

L - _ ________
Preference does not appear to be an important variable in instruction

per Se. Furthermore , little research has addressed the separate components

of preference. Until an organized body of literature supporting preference

as a factor in visual learning is developed , preference for visuals does

not appear to justify their use.

Multiple Sensory Input

The belief that graphics can increase learning because they add additional sensory input is present in educational technology folklore today.

Several researchers have addressed the issue of simultaneous presentation

of multiple media (Cody , 1962; Devoe , 1965; Olsen , 1969). Advocates

theorize that if one medium will suffice , then two or three must be better; or they espouse the shotgun approach——if an effective method is not

known , try everything. These theories have their basis in the hypothesis

that simultaneous presentations unburden overloaded sensory channels. Two

types of research have been described: experiments manipulating stimuli

on a more basic sensory encoding or perceptual level (as presented in the

previous section on perceptual efficiency , and those evaluating multimedia

in the instructional environment.

The basic research findings have been described in a review by Devoe

(1965), who reports a growing body of literature indicating that “human

perception is essentially a one channel system” (p. 6). There is some

evidence that simultaneous transmissions of simple material can be processed effectively (Devoe , 1965; Mowbray , 1954; Sumby & Pollack , 1954).

Usually , however , simultaneous stimuli (such as auditory and visual signals ) are handled alternately (Broadbent , 1956; Devoe , 1965; Fitts , 1971;

Kristofferson , 1965). Though the results of the research in this area

are highly complex , in most studies simultaneous transmission did not

necessarily increase the effective processing of the stimuli; in fact ,

in some experiments subjects performed worse than chance ( Mowbray , 1954).

Thus it does not appear that , at a basic level , simultaneous transmissions

necessarily unburden overloaded channels.

Within the instructional environment , the results of experiments

testing the effectiveness of simultaneous media presentations have varied.

Despite these findings , simultaneous presentations of every conceivable

kind of audiovisual have been popular gimmicks , based on the belief that

they lead to more efficient storage. In a study by Olsen (1969), a medical self—help course was taught by one of several presentations using audiotape and one other media , such as slides or movies. Scores on tests

designed to measure the traditional verbal knowledge aspects were not

significantly different. However , performance of the first—aid tasks

showed a significant gain in performance scores as more sophisticated

media were added. In an experiment by Cody (1962), combinations of read—

irig , listening , and note—taking were investigated. No interference was

indicated as a result of the extra techniiiues; however , the most effective method was silent reading.

18
Though attitudes toward simultaneous presentations probably do nu.t

have a more influential effect in this area than they do in other educational contexts , there is evidence that attrition rates may be drastically reduced by the use of multimedia packages. In one case , attrition

dropped from 40% to 8% (Hall , 1971).

In summary , the basic premise that simultaneous presentations of

visual stimuli are able to unburden overloaded channels has not yet been

substantiated. Moreover , the generalizability of this premise to the

instructional environment does not appear to be warranted.

Visuals and Instructional Media

In the late 1950’s and early 1960’s , several movements toward the

use of some audiovisual technology began on a nationwide level. For example , language laboratories became an adjunct to language learning , and

closed—circuit TV appeared on university campuses and in many high schools.

Overall , the movement was toward more sophisticated audiovisuals; audiovisuals were transformed from the notion of teaching aids to actual teaching devices. Overhead transparencies, filmstrips , films , etc., were

quickly replaced by television language laboratories , sophisticated simultaneous training devices (Stoltz , 1971), and computer—assisted instructional systems.

As technology advanced by leaps and bounds , however , the instructional course ware for these systems progressed slowly . Material for

training devices in particular could be easily updated to keep up with

equipment changes. Course material for teaching troubleshooting on a

piece of missile tracking equipment illustrates this point. Some systems

and system approaches were abandoned early , whereas other concepts became

popular. Instructional television falls among the latter; it is among

the few systems on which much evaluative research has been done.

Several studies have examined alternative instructional media. Although there is no specific theory relating visuals and media , media

studies provide an indirect means of evaluating instructional graphics ,

as certain media readi ly lend themselves to graphic depiction of material.

Indeed , in some instances the primary rationale for selecting a particular medium is the capability of that medium to generate sophisticated

graphics. Instructional television (ITV ) is a prime example of this

latter category .

Television . Visual disp lays are intrinsic to an ITV approach. It

was believed that the student could benefit from both an organized lesson and the accompanying displays , includinq closeups and detail of the

actual laboratory setting, wit hout leaving his seat. Programs were less

expensive to produce, because many students could be taught by one instructor on a closed—circuit line. Research looking at some of the factors influencing the effp c ’-iveness of television for instruction is plentiful , yet the results still are somewhat inconclusive. There is little

1 ~~
doubt that television can be a very effective instructor (Anderson , 1972;

Bart , 1971; Dwyer , 1968f; Jackson , 1955). Bart described some variability in effectiveness , due to socioeconomic class , in his experiment with

third—grade students. Dwyer maintained that the notion of the ability

of television to accurately simulate the laboratory setting (say , a physics experiment), show detail , etc., is an oversimplification of the design process , as illustrated by his visual realism experiment s (Dwyer ,

1972). He stated that an increase in the amount of information contained does not necessitate an increase in information conveyed to the

learner. Furthermore , Dwyer asserted that most televised instruction

programs are the result of the producer ’s creativity and not systematic

instructional strategies.

There is evidence , however , that television can be systematically

evaluated by properly designed research. For example , both Barrington

(1971> and Jackson (1955) designed programs using effectiveness feedback .

In Barrington ’s experiment, two variations of the same material were presented , the first being taped instruction (TI) of a regular classroom

lecture, and the second an edited version of the first , using animation

and cutting out extra noise and background. Subjects , matched for ability and sex , were assigned to one of the treatments. Results indicated

the edited program was more effective . However , there were no significant ability or treatment interactions (Barrington , 1971).

The Jackson research concentrated on determining principles that

would aid the instructor in designing effective visuals for instructional television presentations. Staff members from the Human Engineering

Division of the Special Device Center , U.S. Navy , rated 105 existing programs for visibility (i.e., clarity of the televised image ) on a 14—item

Likert scale (reliability = .85 — .96). The ratings fell into a normal

curve , with the first quartile very good and the fourth quartile noor.

Next , a display containing all the positively rated features was constructed. The other displays were then reconstructed to include portions

of the properties derived. Ratings on the revised displays increased

significantly . Finally , displays were rated by the experimenters according to the derived principles , and predictions about their ratings were

made. Predicted ratings correlated significantly with actual ratings

(r = .90). In all , 31 principles were delineated on the assumption that

high display quality facilitated learning.

Color. Experiments testing the effectiveness of televised instruction included manipulating color versus black—and—white presentations

(Booth , 1971; Kanner & Rosenstein , 1960). Results have mimicked color

studies previously described , with rio significant differences attributable to the addition of color but some significant color—content

interactions.

20
— ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

For example , the Kanner and Rosenstein paradigm selected 11 lessons

from three Army Military Occupational Specialties (MOS). They presented

black—and—white or color versions of each lesson; each lesson was given

three times arid followed by imnediate testing. Some of the test items ,

called “color items ,” either had color as an integral part of the phrasing

of the question or the subject was required to have specific color knowledge (for example , one question pertained to a certain colored resistor

and its value in ohms). Only one lesson , Range Tracking , resulted in

higher scores attributable to the addition of color. The decision to

develop lesson materials in black and white followed. The experimenters

felt that the results were due to a color—content interaction , or the

small percentage of color material shown to be significantly more effective (11%) did not warrant the overall use of color.

Booth (1971) explored the affective value of color. In response

to the idea that color may elicit unwanted emotional arousal , second— ,

third— , fourth— , and sixth—grade students of varying socioeconomic backgrounds were presented with either color or monochrome presentations.

Prior years of viewing color television did not constitute a significant factor. However , a significant developmental trend was noted. The

second—grade students tended to internalize attitudes portrayed in black

and white more than those in the color version , and the trend for sixtn—

grade students was exactly the reverse. Fourth—grade children were described as being in a transition period.

Visual versus Auditory Media. Overall , visuals have been reviewed

across modalities as having some positive , yet variable , results. Day and

Beach (1950 ) report in their review that for paired associate learning,

difficult material is better presented visually , and s impler material is

better presented auditorily. In addition , the younger children did not

benefit from visuals as did the older children or the more intelligent

children.

Visuals versus auditory modes, particularly the auditory presentation found in TI , have been compared in several experiments (Cooper &

Gaeth , 1967; Dworkin & Holden , 1959; Edgertori , 1957; Hanneman , 1968).

Some of the variability in results has been attributed to content—mode

interactions , as in a study by Edgerton (1957) wherein learners gained

more from the use of pictures (slides) on some materials than on others.

A developmental effect included in the content—mode interaction was

noted by Cooper and Gaeth (1967), who presented material to students in

grades 4 , 5, 6, 10 , and 12 by visual or auditory modes. Supplementing

the Day and Beach observations cited above , these authors suggest that

the ability to gain from pictures peaks somewhere in late childhood , and

that by grade 12 students function better in a verbal (text and aural)

mode than in a visua l mode. This proposition is also suggested by Collins

(1971), who found that second graders perform equally wel’ on several

kinds of visual—alphanumeric presentations teachinq spelling. Collins

used both an achievement test and a 1—week delayed retention test.

21 

—-~~----—- - -~~~~ - -~~~~~~ —- ~~~~-~

--

~~~~ 

-

~~~ -
:!

In the Dworkin and Holden experiment (1959), filmstrip and auc’iotape

presentations versus TI—designed by the same instructor were compared for

their effectiveness in teaching atom bonding material to engineering

graduate students matched for education and previous course grades. No

significant difference was noted in course achievement. However , questionnaires did yield significant attitude trends . The audiotape was

criticized as being too fast (135 words per minute (wpm) compared to an

average rate of speech of 120 wpm). In addition , 40% of the students in

the experimental group said they would have liked a chance to ask questions. However , student opinions did not correlate with any trend in

achievement.

Motion as an Instructional Cue. A few studies have directly compared

alternative audiovisual media. For example , when slides or filmstrip

methods are compared to moving film presentations , the actual movement of

r the stimuli describes the major difference. Sometimes the richness of

detail , particularly the detail of the simulated environment , has been

described as a contrasting factor (Devoe , 1965). Television and video—

tape have had reported effectiveness in training by reproducing behaviors

that the subject can later alter , such as gymnastics (James , 1971). In

an educational context , videotape was found to aid practice teachers in

their teaching behaviors. Students in the experimental videotape group

received significantly higher ratings in their practice teaching than did

the control group who had TI practice sessions rather than videotape feedback (Jensen & Young , 1972).

Absence of background noise is also described as a factor contrasting television and TI (Sprague , 1955), and there is some evidence that

background noise is a negative factor; but overall , motion is usually

described as the important addition (Dwyer , 1969; Houser , Houser , &

Van Mondfrans, 1970; Laner , 1954). The addition of motion addresses

either or both of two specific strategies the instructor is using. First ,

there is the attention—motivation value of motion; researchers have looked

at two aspects here. Dwyer found that motion (operationally defined as

pointing to the important area of the heart in videotape presentation) ,

did not significantly affect performance (Dwyer , 1969). Sprague (1955)

compared the effectiveness of four types of visual presentation of in—

formation about machines to sixth— and seventh—grade boys and girls.

Magazine clippings , commercial film , and combinations of the two comprised the experimental conditions , and magazine clippings presented as

a filmstrip comprised a fourth condition. No significant difference on

subsequent tests was attributed to mode , except that subjects having

higher ability did better on the commercially produced film than did

those with lower ability. On the other hand , Gettinqer (1971) did find

significant differences between videotape and still—picture presentations and subject (fifth and sixth graders) performance in identif ying

motion.

22
The second strategy for using motion is to facilitate later

perceptual-motor behavior. The subject is thought to be better able to

understand the interrelated movements in a performance task by vicariously experiencing the task through film. Laner (1954) tested that idea by

presenting a filmstrip or film of how to repair a broken window sash .

The instruction included how to disassemble , repair , and reassemble the

materials. The filmstrip presentation was made from 51 still blowups

from the film. It was believed that these frames did not include motion

and overall were much less sophisticated than the film presentation. The

dependent measure was a 23—item performance test in which the subject was

rated on his ability to make the repairs; time to completion was not measured. Results indicated no significant differences attributable to

method used , although previous carpentry experience did prove to be

significant.

Last, a comparison was made between alphanumeric and aural presenta—

tions of descriptive captions accompanying a movie demonstrating to agricultural students methods for grading cereal grains (Harineman , 1968).

Both identification and performance measures were taken. Students in the

visual group (alphanumeric) did significantly better on the identification tests than did students in the aural group. However , no performance

differences were found.

Media and Instructional Strategy. The idea that one medium is intrinsical ly more effective than any of the other media is simplistic.

The specific factors that enhance learning in the instructional situation are no longer restricted to the context of particular equipment ,

but rather are considered within the total instructional system , which

includes the instructional strategy . The strategy is usually built into

the system , and flexibility for changing this strategy varies from system to system.

Many researchers have written that direct comparison of one system

with another is not a valid approach , since the basic strategies are mark—

edly different in many cases. For example , CAl programs typically employ

reinforcement , self—pacing, individualized sequencing, etc., whereas instructional television provides a more directive type of teaching and is

oriented to group rather than individualized instruction. Texts may differ also; in addition to their visua l layouts , the decision to present

examples and then generate rules or vice versa is implicit in the writing

of the material.

In contrast , decisions about instructional strategy may also be made

independently of the instructional system. In relation to learning from

visuals , several experiments illustrate that ~ertain instructional techniques , such as the use of advance organizers , post—organizers , and interrogative or imperative captions, can be effective (Au subel , 1960; Bertou ,

Clasen , & Lambert , 1972; Butts , 1956; Dwyer , 1970; Neu , 1951).

23 

~~~ -~~~~~~ - - -~~~~~~~~~~ --~~~ 
T’III~

For slide presentations , questions as captions do not appear to be

as effective as declarative or imperative captions (Butts , 1956; Dwyer ,

1970a). In Butts’ experiment , both immediate testing arid 2—week delayed

tests showed imperative and declarative captions to be more effective

than questions as captions , except in the case of one content area .

For written text , there is evidence that advance organizers facilitate learning (Ausubel , 1960), and television presentations have shown a

positive effect for interspersed questions followed by a short pause

(Bertou et al., 1972). Other attention—getting devices were manipulated

by Neu (1951). In his paradigm , both relevant and irrelevant material

were used to direct the subject ’s attention to particular procedures.

The visual attention—getting devices were of questionable relevancy; for

example , when demonstrating that 3 metal ruler should be oiled , an oil

can appeared as the word “oil” was spoken. Nonrelevant stimuli included

pretty girls and cows ’ tails. The results diu not indicate that Neu ’s

extra visual cues iided learning; in iact , scores on both a 104—item

multiple—choice test (KR20 = .94) and a 77—item recall test indicated

that irrelevant devices were cistractors in that they lowered scores.

In summary , since visuals are associated with the visual aids or advanced

system described previously , their value is difficult to assess. Research

on instructional strategy indicates that some methods of presenting the

learner with material are more effective than others. The success of

some media may be due t

~~ the Ir amenability to effectively use instructional principles rather than to the use of visuals.

Programing material f~~r a computerized presentation , televised presentation , or film requires —lore planning than do most TI presentations.

This attention to detail and .rganization probably accounts for a good

deal of the effectiveness of the medium . if system engineering principles were applied tc TI or t , less—sophisticated media such as slid€

projection , the effecti~ - -~ ’~ss of ho’- h would probably be increased (Radan

& Zuckowsky , 1969 , 197(); ~

J.S. Civil Service Commission , 1971). Research

on system comparisons must be revi~~~ed careful ly. As Gropper (1968)

stated , most experimentation of this natur e is invalid , since it does

not compare two equally -~e1l—constructed methods.

Although it is valuable t ’ examine experimentation on instructional

media , the results of such ~x~ erime ntation are confounded by a number of

factors , including th~ ins truct ~onal st r ategy , the subject matter , the

physical demands (If the hardware , ari~1 the system goals.

Individual Differences

As has been disr o,sed previously, secondary results from a number of

exper iments have suggested that graphic effectiveness is in part a function of learner ct -jr i c teri~ tics . The examination of individual differences has received ;onsiderat-l .~ i mpetus with the introduction of aptitude

by treatment ln~~

e r c ~tion (

~~TI) methodology . As early as 1957 , the application of ATI Ir tIi do- r ~

- w~~ - sIq ’-lt ed for milit ary training (Edgerton ,

— - _ ___ ~4
-- 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

1957); however , development of education and training devices has been

disappointingly slow . The following discussion deals briefly with the

characteristics that appear most relevant to educational graphics research .

Educators maintain tha t individual differences , especially in the

traditional instruction context , hold back some students and allow others

to excel , thereby acting both to the advantage and disadvantage of instruction. It was hoped that instruction could be de .gned with these

differences in mind. But as Tailmadge and Shearer (1971) indicated ,

the process of identif ying the most relevant individual differences is

much more difficult than it first appeared to be. Educators have persisted in studying the question , maintaining that normative data collection and program development geared toward the average student (who does

not exist) overlooks the individua ’ and suits no one (Snow & Salomon ,

1968). The goal of ATI methodology is , then , to elucidate the most

powerful effects and to develop adequate screening devices for assigning subjects on the basis of the important differences.

Programed instruction (P1) is a type of individualized program . It

does not necessarily take into account known individual differences , except the need for self—pacing. Many studies relating specific cognitive

and personality variables to either media or instructional strategies

have been conducted. The resulting significant interactions are almost

as numerous as the studies themselves. For example , research indicates

that some subjects will benefit more from visual presentations than will

other subjects (Bush , Gress , Smith , & McBride , 1965; Levin , Divine—

Hawk ins , Kerst, & Guttman , 1974; Tallrnadge & Shearer , 1971). There is

also evidence that visual effectiveness in education is dependent upon

cultural and physical limitations (Fitzpatrick & Hansen , 1973; Kilbride ,

Robbins , & Freeman, 1968; Miller , 1973).

ATI studies have ranged from those seeking individual differences related to broad educational techniques , such as mode interactions (Goldberg , -

1972), to those concentrating more on the subject—generated characteris— - -

tics of the interaction, such as personality. Learner types have been

proposed (Britt , 1971; Haskell , 1971). Britt’s study was correlational ,

using 59,000 subjects ranging in age from 9 to 19 years plus a large corn—

puter analysis of millions of correlation coefficients from the data.

From these data , three learner types were deduced. Haskell’s procedur e

was more conventional. He determined that learner type could be related

to adjectives operationally defined by scores on tests (e.g., Friendliness on the Edward’s Personal Preference Schedule).

Other types of ATI studies have emphasized the particular problems

arising from a specific learning environment; for example, O’Neil’s anxi—

ety studies in the case of CAl (O’Neil , 1972; O’Neil , Speilberger , &

Ha nsen , 1969). Also , since visuals have been counterproductive in some

experiments and have been criticized as distractors , some studies have

tested the distractability of visuals. Bee (1966 ) did so in a non—CAl

context and found significant sex differences——females were more vulnerable to distraction than males. On the other hand , Tobias (1973) did

25
not find distractability to be a significant factor in the CAl context .

In effect, although ATI methodology appears promising, those characteristics of particular importance to the use of instructional graphics

have not yet been clearly identified.

Overview

The literature reviewed does not readily lead to a summary of the

effectiveness of pictor ial presentations in education and training. The

exper imental results show no linear trends that clearly determine how

the instructional program developer (or teacher) should select visuals ,

or in which situations they should be used. The commonsense approach

is restricted to face validity , as research does not definitely support

the use of pictorials according to any consistent criteria . However , it

has been substantiated that pictorials can and do , in specific instances,

have an effect on some instructional programs.

Significant differences appear in a variety of studies , although

many of these differences are too small to have practical application.

Some instructional progr ams are enhanced by the use of pictor ials , as

attested by several of the studies cited. In effect , the variable re—

suits obtained from experimentation (hence the lack of generalizability)

suggest that while pictures do aid some kinds of learning, the specific

conditions are not accurately known. Nonetheless , three major factors

that must be accounted for do emerge: subject matter , task requirements,

and learner population characteristics.

CAl AND GRAPHICS

As the literature search progressed , it became clear that reported

research directed toward evaluating the instructional effectiveness of

graphics in a CAl context , par ticularly interactive graphics , was almost

nonexistent. This section therefore discussed overall evaluations of

CAl and related techniques , in order to identify characteristics inher—

ent in CAl relevant to determining the contribution of graphics per se.

Colnputer_,rssisted instruction , computer—based instruction , or

computer—managed instruction all refer to new educational technology

media that have the potential of presenting the student with material

conditional upon his responses. This interactive characteristic is

unique to CAl. CAl critics often rebuke CAl presentations as expensive ,

automatic page—turners for otherwise programed instruction . This judgment may be partly correc t, but the ~~rd “automatic” is not necessarily

derogatory , because it is this feature that permits large amounts of in—

structional material to be presented to many students in a single session. Moreover , interactive graphics is a potential found only in the

CAl approach. No textual presentation can provide graphic feedback con—

ditional upon the student ’s response.

26 

—- --

~ -- -~~~~~~~~~~

-.
~~~~~~~~~~~~~ ‘‘

~~~~~~~

In the past decade , many content areas have been presented via CAl .

Although rigorously defined material such as mathematics and grammar has

been emphasized , several major conferences have been devoted to the development of computer curricula (Proceedings of the 2nd , 3rd , and 4th

Conference on Computers in the Undergraduate Curricula , 1971 , 1972 , 1973).

The literature cited here includes several of these content areas , notably

physics , mana gement , and math (Bennett , Bignell , & Bradley , 1972; Bork ,

1971a , 1971b , 1972 , 1973a , 1973b , 1974a , 1974b; Hammond , 1971; Hertlein ,

1972; Martin , 1973; Peters , 1969; Shostack & Eddy , 1971; Wylen & Schwartz ,

1973).

The amount of research evaluating CAl is not as substantial as one

might expect. Educators apparently feel that CAl is a future reality ;

consequently , CAl research appears to have been more development—oriented

than evaluative .

In a state—of—the—art paper , Jerman (1972) cites several ways in

which a CAl approach can facilitate education today .

These assumptions that lead us to place as much hope as we

do in CAl are the following: (1) man is capable of learning more than he is being asked to learn; (2) there are a

manageable number of different approaches to instruction

that can be tailored to individual differences among students; (3) through careful diagnosis insight can be gained

on how one ought to go about individualizing instruction;

(4) reinforcement and feedback should be immediate during

instruction; (5) in each instance the quality of education

that a person receives ought to be the highest possible.

(lanni in Jerman , 1972 , p. 466)

It becomes evident, then , that the CAl approach allows not only for edu—

cation and training but also for experimental research. The majority of

experimental research seems to be geared , here , towar d learning theory

manipulations rather than improvement of the CAl product.

In his review , Atkinson (1968) specifies three kinds of CAl systems:

the drill and practice approach , which acts as an adjunct to TI; the dia—

logue system , in which the student has complete control over sequence of

learning events and natural language responses to an unrestricted mode ;

and the tutorial program which may be seen as an alternative to TI. This

discussion focuses on the latter system .

In his study of the effectiveness of CAl , Atkinson used first graders

who participated in a CAl reading program. The control group took a CAl

ma th course. Atkinson ’s approach to his data analysis was somewhat different from that of other CAT studies. Rather than measuring the difference in rate of responding (which he reported to be small), he took fre—

quency data , measuring the total number of responses made. The difference

between the amount of material covered by the slowest and fastest child

27
____ — - - -.

was 4 ,000 responses in the 6—month experimental period. Atkinson concluded

that CAl does have the potential to meet individual needs. The educational

effectiveness of CAl also showed very positive results. Gain scores on

the California Achievement Test and the Hartley Reading Test showed that

the experimental group’s scores were significantly higher in all subtests

(such as Vocabulary and Pronunciation) except Comprehension. Atkinson ’s

results suggest that in order to determine the beneficial effects of CAl ,

one cannot rely upon the traditional verbal—oriented dependent measures.

The literature seldom disputes the instructional technologists ’ claim

that CAl is an effective instructional tool; several revie.iers have presented evidence that CAl is no less effective than TI (Anderson , 1967;

Gagne & Rohwer , 1969). But objections about some aspects of the instructional situation have been raised. Foremost of these objections is the

conjecture that the CAl situation is highly anxiety producing, and that

feedback in particular can have a detrimental effect on an anxious subject. To test this hypothesis , O’Neil et al. (1969) took both trait anxiety (A—trait) measured by the State Trait Anxiety Inventory (STAI )

(Spielber ger , Gorsuch , & Lushene , 1969) and state anxiety (A—state)

measured by systolic pressure. Variation in subject performance was

related to A—state and difficulty of material. Hansen and O’Neil (1970)

reported similar findings . In a later experiment , rather than assuming

the CAl situation to be inherently anxiety—producing (stressful), O’Neil

(1972) presented subjects with negative feedback in his stress condition.

High A—state subjects performed worse than low A—state subjects , a result

somewhat inconsistent with drive theory . A significant periods effect

was also reported , in which errors decreased temporarily across lessons.

Tobias (1973) studied the effects of interrupting the subject during

the CAl presentation , calling this factor distractability. Results indicated no learning decrease , but an increase in time to completion. The

method of presentation was also man ipula ted by having the subject respond

overtly or by having the subject read. The overt response was correlated

with better performance; however , it as also correlated with state anxiety , -

which was measured at four separate times in the presentation .

Results of several exper iments, then , do not support the hypothesis

that CAl is an anxiety—producing situation that will have negative effects

on performance or personality. In addition , correlation between A—trait

measures (as screening devices) and A—state measures is somewhat low ,

r = .4 — .7 (Spielberger , Gorsuch , & Lushene , 1969).

Graphic Studies

CAl evaluation has been more of ten limited to the developmen t of

lesson content for specific subject matter than concern with experimental

comparisons between alternative techniques. For example , much effor t has

been made to develop CAl courseware for physics (Bardwell , 1971; Bennett ,

Bignell , & Bradley , 1972; Bork , 1971a, 1971b , 1972 , 1973a , 1973b , 1974a ,

1974b; Martin , 1973). These programs have sophisticated presentations of

28
ma ter ials , including drill , practice , and tutorial lessons; most include

graphics. Developers of this material have strongly advocated the development of pictorial material for CAl (Bork , 1974a). Some experimenters

(and students) have gone to great lengths to generate graphics , even using

pen plotters (Hertlein , 1972; Hurle , 1970; Papert and Solomon , 1972).

To date , then , the move to include pictorials has been hand—in—hand with

hardware development, without data to substantiate its need. No doubt ,

the belief in the need for pictorials for CAl has held over from audiovisuals and the belief in the positive instructional effects of pictures.

A more experimental approach , more ful ly utilizing the distinct p0—

tential of CAl , has been described by Hammond (1971). He predicts that

the ability of CAl to produce variable graphic feedback will enhance

decisionmaking and diagnostic training. For example , medical students

may learn the art of diagnosis using a probability approach. When presented with symptoms , the student generates graphic displays of how he

works with the data , alongside displays generated by successf ul clinicians

handling the same data. This procedure circumvents the right answer/

wrong answer paradigm more likely to appear in other content areas.

Other uses of interactive computer graphics include labor—management

feedback (Balke , Hammond , & Meyer , 1973). However , no empirical evaluation of the effectiveness of interactive graphic presentation has been

made .

Instructional Strategy: Reinforcement and Sequencing

Since its inception , CAl has been closely allied to learning theory ,

both because it resulted from the Skinner paradigm and subsequent progr amed instruction, and because it was a fruitful testing ground for

learning theory hypothesis testing. The CAl presentation necessitates

decisions concerning the presentation of material. Some of these options are central to old learning theory disputes. For example , the

method of administering reinforcement requires several decisions; one

such decision concerns the type of reinforcement that should be used.

Existing CAl programs have often used familiarity with small children——

“Very Good , Patti !” For adults , programs have provided randomly sampled , system—generated reinforcing phrases—— ”Fine. You ’re doing great,”

or “Exactly right!” Some other types of reinforcement must also be de— 4

cided a priori , including decisions about feedback and reinforcement

delays. Without presenting the mass of literature on the reinforcement

issue , we can cite evidence that in some cases delayed reinforcement will

enhance learning (Sassenrath & Yonge , 1968) but that the type of task may

interact with the effectiveness of t

~ e delay (Lintz & Brackbill , 1966).

The type of reinforcement used may influence the subject’s achieve—

ment motivation , which may in turn influence the effectiveness of the

procedure. There is evidence that the effectiveness of high—incentive

condition s (money bonus) is different from th~ effectiveness of low—

incentive conditions. Bahrick (1954) found less incidental learning

29
F!,-- .

under high—incentive conditions, a result that may generalize to the

learning of detailed information——e.g., subjects who have less incidental

learning may learn fewer details.

Decisions about the size of demonstration units and presentation

length of lessons must also be made , although there is little research

to address these two factors. In addition , one of the most controversial

questions in educational research is whether to present rules followed by

examples or to present examples that help the student to derive rules.

Other sequencing problems include when and how to present difficulty

levels.

Mayer and Greeno (1972) suggest that rule/example sequence ef fec ts

are dependent on whether the goal places emphasis on using the rule (performance) or on more cognitive aspects (knowledge ) such as formulating

new rules, i.e., the extrapolative versus the interpolative needs of the

tasks.

Additional cuing and sequencing effects have also been described.

Low—ability subjects are reported to respond significantly better to programs using many instructional cues (highlights , arrows pointing, etc.),

whereas higher ability subjects are more sensitive to the sequencing of

material (Hall , 1971).

Other factors relevant to CAl include human factors elements such

as size , marginality , and distribution of type , all of which may interfere wi th reading (Gregory & Poul ton , 1970) and the accoustical environment , which may be distractive (Knirk , 1970). Both these factors may

influence learning. Some material may elicit a credibility gap; an

example is the psychological material presented by Fiks (1964), who reported subject mistrust of the psychological instructional material employed. Other media such as TV are more resistant to credibility gaps

(Addis , 1970).

Programed Instruction (P1 ). Much of the research relevant to CAl

instructional strategy has been derived from research using other techniques , particularly P1. Fiks (1964) made one of the most comprehensive

evaluations of the effectiveness of P1 when he presented material on

space travel , auto safety , and psychology to visitors to the Indiana

State Fair. Fiks manipulated feedback delay and also obtained a three—

question, Likert—type attitude measure, as well as educational and demographic data. His results indicated a significant content—difficulty

main effect. As the percentage of confirmations decreased , the number

of errors increased. In addition , there were significant interactions

on the overt—covert dimension in relation to attitude; subjects reported

that they liked P1 better when they were writing (overt) than when they

were not (covert). Attitude toward P1 did not appear to affect perfor—

mance ; however , a credibility gap for the psychology material was evi—

denced . A curvilinear relationship between education and feedback was

hypothesized; the lowest educated subjects liked P1 progressively more

30
__________________________

as feedback was increased , and the more highly educated subjects displayed

a reverse trend. Subjects also reported favoring complete rather than

partial feedback . Fiks concluded that systematic population variance occurs with programed instruction,

Self—Pacing . As P1 research continued , it became more evident that

self—pacing alone could not account for all individual differences. Fry

(1972) tried to determine which qualities of the self—paced instructional

situation would influence performance. He pretested subjects for achievement (above and below the median on the SAT ) and for inquisitiveness,

using a battery of tests purported to account for 50% of the variance

for “inquisitiveness ” (Shulman , Loupe , & Piper , 1970). Material was

then presented in one of four ways: (a) student controlled instruction

(Sd), a self—paced method in which subjects were encouraged to ask questions; (b) a structured presentation that combined expert opinion and

used the questions generated by the first group; (c) a random presentation; and (d) a control group of TI. Subjects were assigned on the basis

of their aptitude and inquisitiveness scores to one of the four treatments. The subject matter was computers. High inquisitive/high aptitude

(HI/HA) subjects did equally well on the SCI and random conditions and

less well on the expert condition. Fry determined that this result was

due to the challenge of working with random material and recommended

that, in general , Sd be used for HI/HA subjects. HI/HA subjects performed best on the expert material , and about the same on SCI and random .

Thus inquiry may be a significant factor in self—paced instruction.

Woodruf f , Faltz , and Wagner (1966) reported that although initially

P1 was thought to compensate for individual variation , other variables

such as personality , attitude , reading ability , and IQ significantly

affected performance on P1. Subjects were grouped according to high ,

medium , and low ability derived by combining IQ, grade point average

(GPA ), and science grades. High—ability subjects made proportionately

the fewest mistakes; in contrast to other groups , their mistakes were

errors of nonresponse rather than incorrect responses. Several personality characteristics such as achievement need were also measured, using

the Edwards Personal Preference Schedule and Gordon Personal Inventory

factors (Cautiousness , Original Thinking, Personal Relations , Vigor).

These factors were positively correlated with the number of correct

responses per frame .

Additional Factors. Other research has indicated that course corn—

pletion time for P1 is significantl y less than that for more traditional

methods (Chrisman , 1970). Some researchers believe that P1 is ideally

suited for the application of learning theory principles. For example ,

Skypek (1971) determined two methods for teaching new words: Phase One ,

which maximized acquisition; and Phase Two , which maximized retention.

These methods could easily be programed without lQsing continuity of

presentation. Skypek’s research reflects the synergistic relationship

between learning theory research and CAl proqram development today .

31
Delayed retention studies have not necessarily shown that P1 is more

effective than other modes. Garrard (1969) manipulated P1, TI , and f ilm

when presenting material to nursing students. A multiple—choice test

showed P1 significantly better at immediate testing but evidenced no

significant differences at delayed testing.

Summary

Little if any research exists that directly addresses the instructional effectiveness of graphics in CAl. Research that contrasts CAl

with other media or other techniques (in order to evaluate graphic effectiveness) must be considered with caution. The apparent advantages of

advanced audiovisual technology may be due as much to the inherent instructional design requirements as to graphic capabilities.

WHERE DO WE GO?

Two major conclusions can be drawn from the research review . First,

it is clear that the addition of graphic instructional material does not

guarantee an increase in instructional effectiveness. Although this point

appears obvious , such an assumption underlies the bulk of the research

reported and is responsible for a number of theories or propositions regarding selection of the “best” media and the design of displays for the

presentation of graphic material. This same assumption may account for

the paucity of research directly addressing the area of interactive computer graphics.

The second major conclusion is that although there apparently are

conditions in which graphics may be an important adjunct to the instructional process , there is currently no systematic means of identifying

these conditions. This situation exists because definitional and methodological differences make it difficult to do a cross—comparative analysis

of research findings. Hence , the first step for future research in this

area is to develop a framework that can ass ist in better structuring of

research outcomes.

The Definitional Problem

Although the term “display” includes any method for presenting in—

formation (Kidd, 1962 ; McCor mick , 1970), the emphasis on graphics restricts this term to visual displays. Unfortunately , the term “graphics”

itself is not clearly defined. For distinguishing different presentation

modes , however , certain categories emerge rather consistently.

At a minimum, a distinction is made between alphanumeric and other

forms of information presentation (McCormick , 1970; Nawrocki , 1973).

Alphanumeric presentations are those restricted to the use of character

sets with a direct referent to linguistic information. In addition ,

32

L.
most human factors discussions of visua l information distinguish between

several forms of nonaiphanumeric information , i.e., graphic information

(Colson , Freeman , Mathews , & Stettler , 1974; Hitt , Schutz , Christner ,

Ray , & Coffey , 1961; Saul , 1954). In general , these distinctions fal l

into three clusters: special symbols with predesignated referents; graphs

and charts indicating spatial—temporal relationships ; and depictions of

objects or events via representations with varying degrees of fidelity.

A cluster derived by factor analysis , based on cognitive ability , appears as part of Guilford’s (1967) structure of intellect model. Guilford

proposed a semantic , symbol ic , and figural categorization scheme for information presentation. Hence , Gu ilford’s model supports both an alphanumeric (semantic) and at least a dichotomous graphic (symbol and figural)

distinction.

Based on the preceding discussion , the authors propose the following

categorization scheme for visual presentations:

1. Alphanumeric——the presentation of information via a set of

characters with direct linguistic referents , mutually agreed

upon by a language community; and

2. Graphics——nonalphanumeric information presentation , to include

a. Symbolic——character sets in which each character has a

predesignated , but nonlinguistic , referent to a specified

object or concept;

b. Schematic——two—dimensional line representations of spatial

or temporal relationships; and

c. Pictorial——representation of objects or events , to include

their relationships , but with the representation having

some degree of fidelity to the physical characteristics of

these objects or events.

These definitions are suggested as an initial step toward providing

a baseline for future research and minimizing problems in semantics. Admittedly there is room for refinement of these definitions , and clearly

many visual displays will combine features characteristic of more than

one category . However , the evidence cited previously suggests tha t the

four—category scheme is a reasonable compromise between several alterna—

tives . In any case , research would benefit from explicit definitions of

terms such as graphics and visuals.

33
Research Framework

Research on instructional graphics should take into account the

three major variables identified in this report: Task , Content, and

Individual Differences. In terms of Task and Content , a number of

taxonomies exist, albeit on a descriptive level. A promising taxonomy

that combines features derived from previous efforts is that of Merrill

and Boutwell (1973).

Merrill and Boutwell developed a taxonomy which considers both the

content and task (behavior) dimensions (Figure 2). It is likely that a

number of ambiguities in the area of instructional graphics woul d be

clarified by adopt ing this taxonomy as a means for compara tive analysis

of future research results.

The most promising approach to determining the influence of m di—

vidual differences is the Aptitude by Treatment Interaction (ATI) design .

Those population characteristics which appear to have potential predictive value have been discussed in the ATI section of this review. Other

critical characteristics remain to be determined , and experimentation

that correlates a number of aptitude measures to the dependent variables

will be necessary prior to true ARI experimentation.

Finally , the dependent measures chosen should be as inclusive as

possible. The realism research indicates that overall performance will

be difficult to interpret if visual and verbal task components have not

been isolated. Moreover , the same research suggests that delayed retention measures may reduce or eliminate effects obtained using meas ures

of immediate retention. A systematic research program is underway within ARI , based on the framework described.

34
- - -

~~~

Higher Order Problem

Rule Us ing Solving

Rule Using Analysis Component

Rule Using

Classification Classification Stimulus Set ~~sponse

and/or

Stimulus Set:

Discriminated Discrete Definition Rule Higher Rule

Recall Memory

Paired Concept Principle Problem

Associate

Content Dimension

Figure 2. Task by Content taxonomy

(adapted from Merrill and Boutwell , 1973).

35
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•

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50 

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1 Denve r Federal Ctr, Lakewood . AIM: BLM

12 Defense Documentation Center

4 Dir Psych , Army Hg. Russell Ofcs , Canberra

1 Scientific Adver , Mi) Bd. Army Hg, Russell Ofca. Cenberr.

1 Mn and Air Attache, Austrian Embassy

1 Centre tie Recherche Des Fac te uj rs . Humaine di Ia Defense

Natnonale , Brussels

2 Canadian Joint Statt Washing ton

I C/Air Staff , Royal Canadian AF , AIIM: Pert SId Anal B’

3 Chief . Canadian Def Rich Staff . AIIM: C/CAOS(W(

4 British Oaf Staff . British Embassy . Washington

52

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