Technical Report 498

AN EXPERIMENTAL EVALUATION OF TACTICAL

SYMBOL-DESIGN FEATURES

Michael G. Samet, Ralph E. Geiselman and Betty M. Landee

Perceptronics, Inc.

rDTIC ELECT41

SJUN 22 1W~f

HUMAN FACTORS TECHNICAL AREA .

>.

U. S. Army

Research Institute for the Behavioral and Social Sciences

April 1980

Approved for pubiuc release. diltribution unlimited.

70
U. S. ARMY RESEARCH INSTITUTE

FOR THE BEHAVIORAL AND SOCIAL SCIENCES

A Field Operating Agency under the Jurisdiction of the

Deputy Chief of Staff for Personnel

L. NEALE COSBY

JOSEPH ZEIDNER Colonel, IN

Technical Director Commander

NOT ICES

DISTRIBUTION: Primary distribution of thIs report has been made by ARI.

Please address correspondence concerning distribution of reports to: U.S.

Army Research Institute for the Behavioral and Social Sciences, ATTN:

PERI-TST, 5001 Eisenhower Avenue, Alexandria, Virginia 22333.

FINAL DISPOSITION: This report may be destroyed when It is no longer

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NOTE: The findings in this report are not to be construed as an official

Department of the Army position, unless so designated by other authorized

documents.
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I REPORT NUMBER 2. GOVT ACCESSION NO. 3. RgCIPIENTS' CATALOG NUMBER

Technical Report 498 .. . x " 1

4. TITLE (and Sutitle) S. TYPE OF REPORT & PERIOD COVERED

An Experimental Evaluation of Tactical Annual Technical

Symbol-Design Features 3-16-79 to 3-15-80

G. PERFORMING ORG. REPORT NUMBER

PATR-1063-80-4(2) 7 AUTWOR(&) a. CONTRACT OR GRANT NUMBR(f,)

Michael G. Samet DAHC19-78-C-0018

Ralph E. Geiselman

B~ttvM. Iandea 9. 4p0M. ORGANIZATION NAME AND ADDRESS 10, PROGRAM ELEMENT.PROJECT TASK

PERCEPTRONICS, INC. AREA 6 WORK UNMIT NUMMERS

6271 Variel Avenue 2Q762722A765

Woodland Hills, CA 91367

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U.S. Army Research Institute for the Behavioral April 1. 1980

& Social Sciences 13. NUMBEROF PAGES

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Technically monitored by Leon H. Gellman and Franklin L. Moses,

Human Factors Technical Area, ARI

It KEY WORDS (Confinue o, seieco. .lde if n.cee..wy and idenlify by block number)

Battlefield Information Perception Tactical Symbols

Graphic Portrayal Situation Displays Tactical Units

Human Performance Symbols Unit Symbols

Iconic Representation Symbol Design

Military Symbols Tactical Displays

20 ABSTRACT (Coninue rtw revoere side It necesary end Identify by block number)

Sixteen non-military participants learned each of two symbol sets (conventional,

iconic) to a criterion. Each set contained three basic symbols representing

unit types of armor, mechanized infantry, and infantry. After learning a

symbol set, each participant was shown a series of situation displays, where

some displays contained symbols coded with either perimeter-density or vector

projection to convey supplementary unit-attribute information (unit strength

or firepower reach) needed for typical tactical tasks. For each display, the .

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participant was asked questions corresponding to different behavioral processes

(identification, search, comparison, pattern recognition). Overall, the

results suggested that iconic symbols may not necessarily be preferable to

conventional symbols in certain situations; and, although the portrayal of

suppleiental unit information can slow some aspects of information processing,

certain symbol-design features appear to create less interference than others.

Specifically, (a) iconic symbols did not yield faster identification perform- ance than conventional symbols, and conventional symbols yielded faster

pattern-recognition performance than iconic symbols; (b) the portrayal of

supplemental unit attributes slowed processing of unit-type information in

all four tasks, but vector projection created less interference than perimeter

density in three of four tasks; (c) unit-strength information was processed

faster when it was portrayed as perimeter density, and fire-power reach information was processed faster when portrayed as a vector projection. In a supplementary task which required integration of information from several

symbols into an analytical judgment (threat value assessment), performance

accuracy was found to be insensitive to the conventional versus iconic symbology comparison. The results were discussed in terms of the complexity of

the implications involved in the selection of symbol design features and their

correspondence with tactical concepts.

0 tFIC

=, ' . , ' *.: ' I

i'SIf' CTEO

4 Avai. zi4jor I

Unclassified SECURITY CLASSIFICATION OF TiMIS PAG E(When Datr Entered)
Technical Report 498

AN EXPERIMENTAL EVALUATION OF TACTICAL

SYMBOL-DESIGN FEATURES

Michael G. Samet, Ralph E. Geiselman and Betty M. Landee

Perceptronics, Inc.

Submitted by:

Stanley M, Halpin, Chief

HUMAN FACTORS TECHNICAL AREA

Approved by:

Edgar M. Johnson, Director

ORGANIZATIONS AND SYSTEMS

RESEARCH LABORATORY

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

5001 Eisenhower Avenue, Alexandria, Virginia 22333

Office, Deputy Chief of Staff for Personnel

Department of the Army

April 1980

Army Project Number Information Processing and Presentation

20762722A765

AmPmr@d for public e.; distribaution unllmiL.

tii
ARI Research Reports and Technical Reports are intended for sponsors of

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

for implementation at the time of publication are presented in the last 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.

iv
FOREWORD

The Human Factors Technical Area of the Army Research Institute (ARI) is

concerned with aiding users and operators to cope with the ever increasing

complexity of the man-machine systems being designed to acquire, transmit,

process, disseminate, and utilize tactical information on the battlefield.

The research is focused on the interface problems and interactions within

command and control centers and is concerned with such areas as topographic

products and procedures, tactical symbology, user-oriented systems, information management, staff operations and procedures, sensor systems integration and utilization, and issues of system development.

The current symbology, as provided in FM 21-30 and FM 21-21, is widely

agreed to be inadequate. As a result, a number of Army agencies are

working to evolve special sub-sets of new or modified symbols that are

better suited to their particular information-processing needs. In the

absence of a common frame of reference, these efforts could result in a

proliferation of specialized symbols that meet the needs of some, but not

all, potential users. The present publication tries to identify and

categorize the situational, information, and behavioral factors that

contribute to the effective design and use of visual symbols for representing

the battlefield. This analysis is a necessary first step in the development

of a comprehensive framework, typology, and theory of tactical symbology.

Research in the area of tactical symbology is conducted as an in-house

effort augmented through contracts with organizations selected for their

specialized capabilities and unique facilities. The present study was

conducted by personnel of Perceptronics, Inc., under Contract DAHCI9-78-C-0018.

This research is responsive to requirements of Army Project 2Q762722A765

and related to special requirements of the Combined Arms Combat Developments

Activity, Fort Leavenworth, Kansas. Special requirements are contained in

Human Resource Need 80-307, Optimizing Display of Topographic and Dynamic

Battlefield Information, 81-57 Strategy for Design and Improvement of

Communications, and 81-96 Effectiveness of Multicolor Air Defense Weapon

Systems Display.

JO EPH ZID R

Tehnical- 3rector

v
AN EXPERIMENTAL EVALUATION OF TACTICAL SYMBOL-DESIGN FEATURES

BRIEF

Requirement:

The design of improved symbology for communicating tactical information

is required in light of the complexities of the modern battlefield and

increasing command and control task demands. The present study evaluated

some candidate design features for tactical symbols by analyzing human

performance data obtained from a series of behavioral tasks relevant to

situation display usage.

Procedure:

Sixteen non-military participants learned each of two symbol sets

(conventional, iconic) to a criterion. Each set contained three basic

symbols representing unit types of armor, mechanized infantry, and infantry,

respectively. After learning a symbol set, each participant was shown a

series of tactical situation displays, where some displays contained symbols

coded with either perimeter-density or vector projection to convey peripheral unit-attribute information (unit strength or firepower reach). For

each display, the participant was asked a pair of questions for each of

four behavioral tasks (identification, search, comparison, pattern recognition), and the speed and accuracy of responses were recorded. In addition,

a fifth task (threat value assessment) required the participants to integrate

several aspects of a display to derive the appropriate response.

Findings:

On the first four tasks, because of near-perfect accuracy, attention was

focused on the assessment of performance speed. The following salient

results were obtained: (a) iconic symbols did not yield faster identification performance than conventional symbols, and conventional symbols yielded

faster pattern-recognition performance than iconic symbols; (b) the portrayal

of unit attributes slowed processing of unit-type information in all four

tasks, but vector projection created less interference than perimeter

density in three of four tasks; (c) unit-strength information was processed

faster when it was portrayed as perimeter density, and fire-power-reach

information was processed faster when portrayed as a vector projection.

With regard to threat value assessment, no difference in performance

accuracy was found as a function of whether the conventional or iconic

symbology was used.

vii
Utilization of Findings

The findings of this experiment can guide the selection of design

features for improved tactical symbology. For example, in the absence

of evidence to the contrary, the present results suggest that conventional tactical symbols may be preferrable to iconic symbols (at least

of the form studied--i.e., blocked, hollow iconic symbols) for use in

certain tasks. Furthermore, although the number of different symbol

dimensions portrayed should be kept at a minimum, some symbol-design

features appear to create less perceptual interference, and have greater correspondence with specific tactical concepts, than others. However, because of the complexity of the performance effects of different

symbol forms combined with peripheral features, a more extensive,

generalized pool of human performance data would be desirable to insure

accurate decisions about symbol designs.

viii
AN4 EXPERIMENTAL EVALUATION OF TACTICAL SYMBOL-DESIGN FEATURES

CONTENTS

Page

INTRODUCTION................................

METHOD..................................9

Participants............................9

Materials...............................10

Procedure.............................16

Integration..............................21

Design and Analysis...........................23

RESULTS................................25

Iconic Versus Conventional Symbology. ................. 25

Symbol-Design Features ....................... 26

Combination of Military Concepts with Design Features. ...... 28

Threat Value Assessment......................28

DISCUSSION..............................29

Iconic Versus Conventional Symbols.................29

Portrayal of Unit Attributes....................32

Threat Value Assessment......................33

SUMMARY..................................33

REFERENCES...............................35

APPENDIX

Appendix A. Sample Instruction Booklet for Learning a Symbolic

Language.........................39

B. Sample Pretest........................49

TABLES

Table 1. Taxonomy of Symbol-Use Processes ........... 3

2. Mean Reaction Time for Answering Pairs of Unit-Type

Questions (In Seconds)...................27

ix
FIGURES Page

Figure 1. Iconic Symbols for Armor ................. 7

2. Conventional Symbols..................12

3. Modified Conventoinal Symbols with Perimeter

Density Feature...................13

4. Blocked Iconic Symbols.................14

5. Blocked Iconic Symbols with Vector Projection

Feature.......................15

6. Experimental Design..................17

x
INTROUCTIUN

Emerging doctrine and advancing technology call for the development of

improved tactical symbology, and considerable effort is being directed

toward that goal (e.g., Ciccone, Samet, and Channon, 1969; Sidorsky,

Gellman, and Moses, 1979). For example, military analysts are focusing

attention on the need to include the graphic portrayal of such key concepts as the dynamic composition of units and unit capability (strength,

reach, mobility, etc.) in tactical situation displays (e.g., Middleton,

1977; Sidorsky, 1977). At the same time, innovations in computer graphic hardware and software have enabled the cost-effective application of

creative symbol-design features such as iconicity, variable density,

flashing, color, vector projection, etc. Thus, a major problem in symbology development involves the identification of promising design

features that exploit the capabilities of automated displays in a manner

that can best serve the information requirements and task demands of

tactical users.

The impact of future symbology on tactical decision making will depend

largely on the extent to which the symbology can be perceived and interpreted by the user (e.g., see Biberman, 1973). Unfortunately, however,

our knowledge of the human factors principles underlying effective symbol design is rather limited. In particular, more empirical data are

required that can be utilized to generate guidelines for the design of

symbols. Since the same military symbols are typically used across an

entire range of display configurations and tactical tasks, the derivation of generalized principles of effective symbol design is a challenging area of research.

In order to bridge the conceptual gap between the design of tactical

symbols and their use in actual tasks, we have adopted the premise that
any such task can be cataloged or decomposed according to perceptualcognitive processes or functions required for successful task performance (cf, Fleishman, 1975). For example, the task of viewing a situation display and determining whether a group of specific enemy units is

in an attack formation might require the operation of behavioral

processes related to identifying these units, finding their locations,

matching their formation with that of a given template, etc. Because of

this relationship between tactical tasks and basic behavioral processes,

which in turn are affected by physical features of symbol designs, the

evaluation of the effects of symbol characteristics on these processes

provides useful human-performance data. Such data then become part of

the reservoir of knowledge needed to establish sound principles for effective symbol design.

Hence, as part of a systematic approach to the investigation of candidate symbol-design features, a taxonomy of typically required behavioral

symbol-use processes has been defined and is presented in Table 1. Not

meant to be an end in itself, the taxonomy is intended to provide a

framework for aiding the planning of research studies, and the interpretation and organization of empirical findings. Although there is probably no such thing as a "best" categorization, the suggested structure

is viewed by the authors as logical, coherent, and useful. The taxonomy

treats the utilization of symbols, in general, as a multi-level endeavor

involving the processing of individual and multiple symbols. The list

of behavioral processes begins with symbology acquisition (learning) and

then spans the entire range of symbol-use activities from detection and

identification of single symbols to the interpretation and integration

of a configuration of several symbols. The processes, as defined in the

taxonomy, are by no means independent since certain higher-level operations are composed of a combination of lower-level operations--for example, counting involves detection, identification and search.

2
TABLE 1

TAXONOMY OF SYMBOL-USE PROCESSES

Symbology Acquisition

Perceptual Learning - acquisition of a code necessary for future

recognition of a form.

Association - acquisition of a mental link between a form and the

concept that it portrays.

Processing Individual Symbols

Detection - acknowledgement of the presence of a form.

Identification - interpretation of a detected form.

Search - determination of the location of an identified form.

Tracking - sustained detection of a mobile form.

Updating - acknowledgement of an alteration of a form.

Processing Multiple Symbols

Comparison - acknowledgement of sameness and/or differences among two

or more identified forms.

Counting - keeping track of the number of instances that a given form

is encountered.

Pattern Recognition - interpretation of the spatial arrangement of two

or more identified forms.

Integration - combination of information from two or more identified

forms toward a simplified characterization of the set of

forms.

3
Ideally, tactical symbols should be designed to enhance rather than to

inhibit human performance in symbol-processing tasks. The efficacy of

symbol-design features might therefore be assessed in terms of how they

affect performance along the fundamental task-related dimensions belonging to the taxonomy in Table 1. For the purposes of the present

research, emphasis was placed on behavior related to the processing

rather than the acquisition (learning) of symbols--the latter being addressed elsewhere (e.g., Bersh, Moses, and Maisano, 1978). Five

behavioral processes were selected for investigation. These processes,

assumed to be essential in the use of symbols for the accomplishment of

actual tactical planning and/or decision making tasks, were operationally defined as follows: (a) identification--naming of symbolic information appearing in a specified display location; (b) search--enumerating

display locations containing a particular type of symbol; (c) comparison

--acknowledging sameness between one displayed symbol and others; (d)

pattern recognition--locating an attack pattern (wedge formation) of

symbols embedded in a display; and (e) integration--analytical assessment of the overall threat value of units in certain sectors of a

display based upon multiple symbol features. Each of these performance

dimensions was treated in the experimental design as a separate component for analysis.

Given the framework of symbol-use processes as a vehicle for studying

related task performance, the next step in demonstrating a systematic

evaluation methodology was to identify a set of symbol design features

that are worthy of exploration. These features are graphic characteristics of symbols, defined in physical terms, which appear to have an impact on user symbol-processing performance. Analyses of the results and

implications of empirical studies that are relevant to the evaluation

and design of symbol features are available elsewhere (see Ciccone, et

al., 1979; Geiselman, Landee, and Samet, 1979; Hemingway, Kubala, and

4
Chastain, 198). For the present experiment, three different symboldesign features were selected for investigation: iconicity, perimeter

density, and vector projection. Iconicity (i.e., the degree to which a

symbol looks like its referent) relates to a symbol's basic internal

form or shape; perimeter density and vector projection, on the other

hand, can be thought of as peripheral attributes of symbols.

The rationale for the development of iconic symbols is based on their

hypothesized ease of learning and increased associability with the concept they are designed to represent (e.g., Machover, 1977). By allowing

for "natural" associations (Bersh, et al., 1978), the imageability of a

symbol, or the ease with which an accurate mental image of its visual

form can be generated, is likely to be enhanced. In other words, the

iconic symbol, in looking like what is already familiar to the user,

should strengthen assocation formation by taking advantage of the user's

prior learning and conditioning (Foley and Wallace, 1974); the plausibility of this contention with regard to military symbols has received

both theoretical (Middleton, 1977) and empirical (Hemingway, et al.,

1978) support. Furthermore, because well-learned iconic symbols generally offer the user a large number of discriminating visual cues,

their perceptibility and interpretation may be less affected by degraded

viewing conditions such as reductions in symbol size or illumination

(Howell and Fuchs, 1961; Shurtleff, 1974). On the other hand, the added

physical complexity of iconic symbols could, conceivably, decrease learnability (Attneave, 1957) and might increase display clutter (Hemingway,

et al. 1978), consequently leading to performance decrements in certain

tasks. Overall, it is difficult to formulate a clear-cut hypothesis

about the effects on symbol-processing performance of iconicity and its

interaction with other design features.

5
Symbol iconicity can range from photograhic reproduction to abstract approximation. For example, the detailed "tank" symbol presented at the

top of Figure 1 probably contains more information than is required for

efficient and accurate recognition. The detailed silhouette design on

the left-hand side of the figure contains fewer visual cues but seems

sufficient to insure rapid recognition. An even simpler iconic approximation is the "blocked" design on the right-hand side; each blocked figure shown was drawn using a 12 x 28 matrix of small squares. Because

the blocked iconic symbol carries the advantage of relative compatibility with an automated display system, it was selected for analysis in the

present experiment. Furthermore, the outline blocked iconic symbol was

chosen because of the suggestion that simple silhouettes, as opposed to

more detailed forms, may facilitate the speed and accuracy of recognition performance (Chainova, Komarova, and Zonabend, 1974; Yoeli and

Loon, 1972) and because the comparison symbol employed in the experiment

(i.e., conventional military symbol) is also composed, more often than

not, of hollow outlines.

The remaining symbol-design features investigated here are extraneous to

the fundamental form of the symbol. Such peripheral design features

have been advocated for the purpose of conveying supplementary information about a given referent. So, for example, if the referent is an armor unit, an appended feature might be designed to represent the unit's

threat value (Moses, 1977), combat effectiveness (Middleton, 1977),

strength or reach (Channon, 1978), or some other aspect of tactical capability (Sidorsky, 1977). In addition, specific designs for communicating such attributes about units have been suggested in the literature

(e.g., the doughnut symbol proposed by Sidorsky, 1977). For the present

work, two peripheral design features were selected for investigation--

namely "perimeter density" and "vector projection." Perimeter density

coding has been described by Middleton (1977) as a modification to con6
ICONIC IMAGE

DETAILED SILHOUETTE BLOCKED SILHOUETTE

(FILLED)

(OUTLINE)

FIGURE 1. ICONIC SYMBOLS FOR ARMOR

7
-l I l •

ventional symbology in order to portray combat effectiveness. Different

levels of percent combat strength can be represented by proportionally

shading the double box (perimeter) surrounding a conventional (FM 21-30)

symbol. Vector projection, in contrast, has been put forth as a design

feature that emanates from a symbol in a manner that might convey information about the direction and distance of a given unit's firepower

reach (Channon, 1976). Perimeter density and vector projection were

thus offered as symbol design features for portraying specific attributes of unit symbols. However, as will be demonstrated by the experimental design, perimeter density and vector projection can theoretically

be combined with either conventional or iconic symbols.

In sum, the objective of the present research was to assess the impact

of some candidate symbol-design features on user performance in basic

symbol-processing tasks. Three symbol-design features (iconicity, perimeter density, and vector projection) were selected for investigation,

and the effectivenss of each feature was evaluated by examining its influence on both the speed and accuracy of performance with respect to

five behavioral processes (identification, search, comparison, pattern

recognition and integration). Performance on each process was measured

by responses to simple questions about symbols appearing on simulated

battlefield displays. These displays were constructed and employed so

that the symbol design features could be evaluated in a realistic symbol

configuration rather than in isolation. Furthermore, the experimental

design allowed for the determination of whether one symbol-design

feature is better suited for satisfying one behavioral process (e.g.,

identification), whereas another symbol-design feature might be better

suited for satisfying a different behavioral process (e.g., pattern

recognition).

8
In addition to the investigation of direct effects of the various

symbol-design features on processing performance, an assessment was made

of the indirect effects of displaying a given symbol-design feature not

needed for task performance. For example, consider how the use of vector projection to specify some supplementary military concept might affect performance on the identification of unit type (as portrayed by a

conventional or iconic symbol). Although such extraneous information is

irrelevant to unit identification, its presence can increase display

clutter or cause interactions which decrease performance on the primary

task. One other research concern was to determine which pairing of the

military concepts (unit strength, firepower reach) with the attribute

symbol-design features (perimeter density, vector projection) is more

effective. Overall, such considerations were viewed as important in arriving at conclusions about the potential effectiveness of each symboldesign feature.

METHOD

Participants

The participants were 16 non-military individuals between the ages of 20

and 30, 8 males and 8 females. Each received a flat rate of $4.00 for

the experimental session which lasted about 1.5 hours. In addition, a

bonus of up to another $3.00 was provided which they were instructed

would depend upon the speed and accuracy of performance. Each participant was tested individually by the same experimenter, and the sex of

the participants was counterbalanced across the one between-participants

factor in the design.

9
Materials

Thirty-six tactical battlefield displays were generated for use in the

experiment. Samples of these displays are presented in Figures 2, 3, 4,

and 5. A dark line down the center of each display represented the line

on the battlefield said to separate the friendly and enemy forces (the

"battlefield line"). The friendly forces always were portrayed on the

left side of the battlefield; and the enemy forces always were shown on

the right side. The vertical-by-horizontal dimensions of each display

were 9 x 14 inches, and this area was marked off into 126 small squares.

These squares were labeled with the letters A-N horizontally and with

the numbers 1-9 vertically. Thus, each square could be identified by a

letter and a number, such as square C-4, or square A-2. The battlefield

as a whole was divided into three major sectors from top to bottom: the

Northern sector (rows 1, 2, and 3), the Central sector (rows 4, 5, and

6), and the Southern sector (rows 7, 8, and 9).

The friendly and enemy forces were composed of three basic types of units: armor, mechanized infantry, ana infantry. No more than one unit

was portrayed in any given square on a display, and the friendly and

enemy forces always contained 30 units each. In total, six different

scenarios (configurations of units) were constructed, with six different

versions of each scenario. Three versions were prepared using the conventional symbols (FM 21-30) for the three types of units used, and the

remaining three versions were prepared using blocked iconic symbols.

Examples of displays with conventional symbols are shown in Figures 2

and 3, and displays with iconic symbols are shown in Figures 4 and 5;

note that the iconic symbols for the friendly and enemy forces are rotated so that they oppose each other.

1I
For each type of symbology, two versions of each scenario included the

portrayal of one symbol-design feature (perimeter density as in Figure

3, or vector projection as in Figure 5), which represented certain supplementary tactical information (unit strength or firepower reach) about

each unit. As outlined below, the pairing of military concepts with

symbol-design features was counterbalanced across participants and was

not confounded with the military concepts. A third version of each

scenario did not include the portrayal of tactical information beyond

unit type, as in Figures 2 and 5. Thus, the 36 displays were generated

from b different scenarios, 2 types of symbology (iconic or conventional), and 3 levels of a symbol design feature (perimeter density, vector

projection, or no feature portrayed).

When a symbol-design feature was included in a display, three levels of

the feature were used representing (a) 100% strength or 60 KM firepower

reach, (b) 50% strength or 40 KM reach, and (c) 0% strength or 20 KM

reach. Three corresponding levels of perimeter-density were: all four

sides blackened in, two sides blackened in, or no sides blackened in

(see Figure 3). The vector projection consisted of four small circles

emanating from the side of the symbol closest to the center of the

display. Three vector projection levels were: all four circles blackened in, two circles blackened in, or no circles blackened in (see Figure 5).

In a given display, one or two contrived configurations of units were

embedded within each set of forces. The general pattern that was embedded was referred to as an "attack" formation--a wedge shape, composed of

seven units, pointed toward the battlefield line. One wedge shape

within each set of forces in every display was composed of all armor units. (The vertex, or lead armor unit, of a wedge is located in squares

F-b and J-5 in Figure 2, F-4 and I-6 in Figure 3, F-4 and K-4 in

11
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Figure 4, and F-5 and K-5 in Figure 5.) In addition, for displays that

included perimeter-density or vector projection, a second wedge shape

within each set of forces was specified by seven unit symbols (of mixed

unit types, i.e., infantry, mechanized infantry, and armor) with full

density coding (e.g., see vertex at D-5 and J-4 in Figure 3) or fullyblackened vector projections (e.g., see vertex at G-5 and 1-6 in Figure

5), respectively. These patterns were the basis for questions regarding

spatial pattern recognition.

Procedure

The general layout of the experimental design for a single participant

is illustrated in Figure 6. The procedure was divided, first of all, on

the basis of the symbology factor (conventional or iconic symbols). The

order in which the two levels of the symbology factor was presented was

counterbalanced across participants. All data pertaining to one of

these symbol sets, except data from the integration task, were collected

before the other set was learned; and a sample booklet used to teach the

participants one of the sets is presented in Appendix A. Also, a

pretest was given to each participant before proceeding with each half

of the experiment to insure that each symbol set was mastered to an acceptable level. (A sample pretest is presented in Appendic B.) Each

participant was required to be able to complete this pretest within

three minutes and with no more than two errors before continuing with

the experiment. These cutoffs were chosen on the basis of a brief pilot

study and represent the 75th percentiles of the pilot participants' performance on the time and accuracy dependent variables.

The procedure was divided, second of all, on the basis of the type of

behavioral task (identification, search, comparison, spatial pattern

recognition, and integration); the order of presentation of the first

16
IDENTIFICATION

SEARCH

S COMPARISON

S PATTERN co RECOGNITION

INTEGRATION

CONVENTIONAL ICONIC

S YMBOLOGY

FIGURE 6.

EXPERIMENTAL DESIGN

17
four tasks was counterbalanced across participants, but the integration

(threat-value assessment) task was always done last because of the extensive instruction that was necessary to enable a participant to perform that task.

Within each of the ten experimental segments created from the combination of the symbology and behavioral task factors, three displays were

presented on paper, one at a time: One included the perimeter density

symbol-design feature, one the vector projection feature, and one included neither of these features. The same three displays were presented in sequence for the identification, search, comparison, patternrecognition, and integration tasks within each level of the symbology

factor. Half of the participants learned each of the two design-feature

by military-concept combinations (perimeter density = unit strength,

vector projection = firepower reach; or vice versa). Thus, the only

between-participants factor in the design was the feature-concept combination factor.

For each behavioral task except integration (threat-value assessment), a

total of ten questions were asked. The procedure for the integration

task is described separately later. In each'of the other four tasks, a

pair of questions was asked for each display that referred to unit type

(armor, mechanized infantry, or infantry); and for those displays that

included an attribute symbol-design feature (perimeter density coding,

vector projection), an additional pair of questions was asked that referred to the military concept associated with that feature (unit

strength or firepower reach). The experimenter recorded the

participant's verbal responses to the questions and also recorded the

total time (using a stop watch) that a participant took to answer a pair

of questions. The reaction time in answering a single question was taken as the interval between the experimenter's completion of reading the

lb
question and the participant's completion of answering the question.

This time was summed for the two questions in a pair. Examples of these

questions (and the figure referred to by each) are as follows:

Identification

(1) Unit Type: In square J-3, what is the name of the unit?

(Figure 3.)

(2) Strength: In square D-8, what is the percent strength of

the unit? (Figure 3.)

(3) Reach: In square K-7, what is the kilometer reach of the

unit? (Figure 5.)

Search

(1) Unit Type: In the central sector of the enemy side, name

all of the squares that contain infantry units. (Figure

2.)

(2) Strength: In the northern sector of the friendly side, name

all of the squares that contain units with 100 percent

strength. (Figure 3.)

(3) Reach: In the southern sector of the enemy side, name all

of the squares that contain units with 2U kilometer reach.

(Figure 5.)

19
Compari son

(1) Unit Type: Un the friendly side in row 4, name all the

squares that contain the same type of unit as in J-4.

(Figure 2.)

(2) Strength: Un the enemy side in row 5, name all the squares

that contain a unit that has a greater strength than the

unit in C-5. (Figure 3.)

(3) Reach: On the friendly side in row 2, name all the squares

that contain a unit that has a greater reach than the unit

in H-5. (Figure 5.)

Pattern Recognition

For these questions, the participants were first read the

following instructions:

"I will now ask you to find attack patterns. You

will be told which side (enemy, friendly) of the

map to look on and how the wedge has been formed

that yuu are to find (all armor units, all units

at 1OU% strength, all units with 60KM reach). In

identifying the location of an attack wedge, you

simply name the square containing the unit that

is at the point (vertex) of the wedge pattern.

That is, you are to give the letter-number designation for the lead unit's location on the map,

such as H-6."

(1) Unit Type: For the friendly side, identify the attack pattern composed of armor units. (Figure 2.)

20
(2) Strength: For the enemy side, identify the attack pattern

composed of units at 100% strength. (Figure 3.)

(3) Reach: For the friendly side, identify the attack pattern

composed of units with 60 KM reach. (Figure 5.)

To insure that the participant understood what response was expected for

each type of question, feedback was given on the first occurrence of

each type of question. This feedback included information concerning

the accuracy of the participant's responses and the rationale for the

correct answers when errors were made.

Integration

In a final part of the experiment, each participant again was shown a

series of six battlefield displays, corresponding to the six displays

shown during the first part of the experiment. This time, the participant was asked to compare the "threat value" of the other groups of military units also shown in the display. The threat value of a group of

units was said to be determined jointly by four factors:

(1) The total number of units in the group.

2) The type of units (armor units have greater threat value

than mechanized infantry units which in turn have greater

threat value than infantry units).

(3) The distance of the units from the battlefield line

separating the enemy from the friendly units (units closer

to this line have greater threat value).

21
(4) The percent strength or firepower reach of the units (the

greater the strength or reach, the greater the threat

value).

For each display, the participants were asked three types of questions

in a fixed order. First, they were asked which of the four corner sectors (that is, the Northern and Southern sectors on both the friendly

and enemy sides--thus omitting the two central sectors) had the greatest

threat value. Second, they were asked which of the four corner sectors

had the least threat value. Third, they were asked which side (enemy or

friendly) had the greatest threat value overall. For this third question, all three sectors (the Northern, Central, and Southern) on a given

side were to be considered as a block for comparison with the combined

three sectors on the other side.

The participants were told that they would not be given enough time to

compute the threat value in any comprehensive or time-consuming manner.

"For each question, you will be required to compare

sectors in an overall way and to make an estimate

after only 20 seconds. Do not try to count the

number of units in a sector since you won't have

time and also because number alone does not determine threat value; i.e., unit type, closeness to

battlefield line, and strength and reach also play

a role.

One practice trial (using a practice display) was given with feedback

before this phase of the experiment was begun.

22
Design and Analysis

The analysis of the data collected during the first part of the experiment, which excludes the integration (threat-value assessment) task, was

divided into two major segments, one concerning the questions referring

to unit type, and one concerning the questions referring to unit attributes (unit strength and firepower reach as portrayed by the two

symbol-design features). Within each of these two segments, four analyses were conducted, one corresponding to each of four tasks (identification, search, comparison, pattern recognition). Thus, eight analyses

were performed in all. Each analysis consisted of an analysis of covariance on the log reaction-time data using the accuracy data as a covariate. The analysis of covariance was used to partial-out the effects

of any speed-accuracy trade-off from the reaction-time data as a standard normalization procedure for such measures.

The design tor each of the analyses concerning questions pertaining to

unit type is as follows: 2 (Symbology: conventional symbols, iconic

symbols) x 3 (Symbol Design Feature: perimeter density, vector projection, none) x 2 (Combination of symbol design feature with military concept: density = strength, vector = reach; or vice versa). The

feature-concept combination factor was the only between-participants

factor. The design for the analysis concerning questions pertaining to

the unit attributes (strength, reach) was identical to the above design.

However, because questions regarding unit attributes could not be asked

when such attributes were not portrayed, the factor of Symbol-Design

Feature had only two levels (perimeter density and vector projection).

The design for the analysis of the accuracy data collected during the

final portion of the experiment concerning threat-value assessment was

23
as follows: 2 kSymbology: conventional symbols, iconic symbols) x 3

kSymbol Design Feature: perimeter density, vector projection, none) x 2

(Combination of symbol design feature with military concept). The

dependent variable was the percentage of correct responses on the three

threat assessment questions; since a fixed time (2U seconds) was provided for each response, reaction time was not meaningful for this task.

For purposes of scoring the participant's responses in the threat value

assessment task, arbitrary linear weights were assigned to each threat

dimension. The threat-value for each sector in each display was then

computed as follows:

n

Threat Value = Ti x Di x A.

i =1

where for each of the n symbols present in the sector, T refers to the

threat-value weight for the type of unit (armor = 3, mechanized infantry

= Z, and infantry = 1), D refers to the weight for the distance from the

battlefield line (each of the two squares closest to the battlefield

line = 3; the third, fourth, or fifth squares away from the battlefield

line = 2; and each of the two squares farthest from the battlefield line

= 1), and A* refers to the weight for the unit attribute portrayed (100

percent strength or bUKM reach = 3, 5U percent strength or 40KM reach

2, and zero percent strength or 20KM reach = 1). The attribute weight

A) is included in the equation only for displays that contain the portrayal of unit-attribute information (percent strength or firepower

reach). As an example, in Figure 3, the corner sector with the largest

*When no unit attribute was portrayed, A was omitted from the computational formula.

24
threat value is the upper left-hand corner (threat value = 118); whereas

the corner sector with the lowest threat value is the lower left-hand

corner (threat value = 48). In this display, the enemy side has the

greater overall threat value (enemy = 329, friendly = 326).

RESULTS

The eight analyses of the accuracy data for the unit-type and unitattribute questions in the identification, search, comparison, and

pattern-recognition tasks showed no significant effects. For these

tasks, 96% of all responses were correct. Thus, attention is directed

toward the reaction-time data for those tasks.

Iconic Versus Conventional Symbology

Only two of the eight analyses of the reaction-time data showed significant effects involving the symbology factor, and both of these analyses

concerned the pattern-recognition task. First, participants were able

to find "attack" patterns based on unit type (all armor units) faster

when conventional symbols were used than when iconic symbols were used

(b.15 sec versus 8.06 sec, F(1, 13) = 4.32, p < .04). Second, participants were able to find "attack" patterns based on unit attributes (all

IU0% strength or all 60KM reach) faster when conventional symbols were

used than when iconic symbols were used (5.68 sec versus 7.08 sec, F(1,

13) = b.5U, p < .U4), except when vector projections were used to portray reach. It is not immediately clear why the latter condition should

have produced deviant results. In general, however, certain patterns of

symbols can be located faster in a display of the type studied if conventional symbols are used. In addition, neither units themselves nor

unit attributes were easier to identify (name) when iconic symbols were

used (unit-type questions, F < 1; unit-attribute questions, F(1, 13) =

25
2.64, p > .05). An advantage for iconic symbols could not have been

offset by prior exposure to conventional symbols because the present

participants were non-military individuals with little or no prior exposure to the conventional symbols. In addition, each symbology was

learned to a strict criterion in this experiment.

Symbol-Design Features

The portrayal of unit attributes in the displays was found to slow the

reaction time in all four of the task analyses concerning questions

about unit-type information. The main effects of design feature in the

four analyses were as follows: Identification, F(2, 27) = 25.6, 2 <

.uUl; Search, F(2, 27) = 4.07, p < .03; Comparison, F(2, 27) = 27.1, j <

.UU1; ana Pattern Recognition, F(2, 27) = 25.2, 2 < .001). However, in

three of these tour tasks (identification, comparison, pattern recognition,, the portrayal of an attribute by perimenter density coding slowed

reaction times more than did the use of vector projection. These

results are shown in Table 2. (Tukey's HSD post-tests were applied to

eact of the main effects of design feature with a significance level of

p .Ub adopted for all comparisons.) Thus, even though both design

features interfere with the processing of unit-type information to some

extent, the vector-projection feature slows down the extraction of

unit-type information from a display less than does the perimeterdisplay feature. The perimeter-density design feature was also found to

yield slower reaction times than the vector design feature for unit attribute questions, but only in the comparison task, F(1, 13) = 4.26, p <

.05.

26
TABLE 2

MEAN REACTION TIME FOR ANSWERING PAIRS

OF UNIT-TYPE QUESTIONS (IN SECONDS)

DESIGN FEATURE

TASK PERIMETER VECTOR

DENSITY PROJECTION NONE

Identification 5.21 > 3.86 > 3.10

Search 14.45 = 14.73 > 11.47

Comparison 14.30 > 11.82 > 8.50

Pattern Recognition 19.30 > 14.44 > 10.07

Note: All indicated differences were significant at p < .05.

27
Combination of Military Concepts with Design Features

The processing of unit attribute information, under certain condtions

was found to be faster when perimeter density was used to portray unit

strength and vectors were used to portray unit reach, as compared to

when the reverse combination was used. With the search task, the

Design-Feature x Combination interaction effect was significant, F(1,

13) = 5.4, p < .04. Performance in processing unit-attribute information was faster when perimeter density was used to portray unit strength

rather than reach (6.03 sec versus 8.73 sec), but performance did not

differ as a function of which military concept was associated with the

vector-projection design feature. The Symbology x Design x Combination

interdction effect was significant, F(1, 13) = 5.5, p < .04. Performance in locating the "attack" patterns based upon unit-attribute information was faster when perimeter density was used to portray unit

strength, regardless of the symbology used (5.57 sec versus 6.94 sec);

but processing was faster when vector projection was used to portray

unit reach, though only when iconic symbols were used. It is not clear

why the "density = strength, vector = reach" combination produced faster

reaction times only in these specific conditions; but since the reverse

combination did not produce significantly faster performance under any

of the conditions studied, it is probably the case that certain design

features are more suitable to portray certain unit attributes than others.

Threat Value Assessment

In spite of the apparent difficulty of the threat-value assessment task,

the average percentage of correct responses was 73.7%, in contrast to a

33.3% chance level. It is of interest that these evaluations of the

complex displays were not affected by the type of symbology used

28
F < 1). Thus, the iconic symbols used here did not facilitate the

summarization or integration of the symbolic information displayed.

This result is consistent with the findings that neither the identification, search, comparison, nor pattern recognition tasks were performed

more quickly with iconic symbols.

The only significant source of variation in the threat-value assessment

data was the main effect of symbol design feature, F(2, 14) = 3.79,

p .Ub. A Tukey's test showed that the assessment of overall threat

was more accurate when no design features were portrayed. The mean percentage of correct responses (out of three) was 72.0% for perimeter density, 64.6% for vector projection, and 84.3% when neither symbol design

feature was used. Thus, when one less factor was figured into the symbol

integration task, performance was significantly better. However, whether this improvement resulted from the reduction in perceptual characteristics (symbol design features) or from the simplified analytical assessment (computation) cannot be determined from the present data.

DISCUSSION

Iconic Versus Conventional Symbols

The results of this experiment illustrated that iconic symbols did not

facilitate human performance over conventional (FM 21-30) symbols for

the range of symbol-use tasks that were studied. In each of the comparisons made here, either no differences in performance were obtained as a

function of conventional versus iconic symbology or the conventional

symbols were found to yield superior performance. When the

participant's task was to locate a specified pattern of symbols in a

display, reaction times were shorter with conventional symbols than

29
with iconic symbols. One explanation of this result is that the iconic

symbols used here were more complex than their conventional counterparts, where complexity is defined by the number of different lines and

angles present in the symbol (Attneave and Arnoult, 1966). Such complexity might impair pattern recognition by reducing the discriminability of symbol-design features (Estes, 1972). In this regard, Hemingway,

et al., (1978) have suggested that iccnic symbols "create more clutter

than most existing symbologies," especially when many symbols are

displayed simultaneously.

The complexity of iconic symbols, however, might be shown to shorten

reaction times if the symbols in a display were allowed to overlap considerably, as would be necessary if superimposed symbols were used to

portray combined arms forces. This is because the well-learned features

of the iconic symbols would serve as discriminative cues (cf. LaBerge,

19Yb); whereas with super-imposed conventional symbols, the identity of

the component shapes might be obscured. In the present experiment, this

possibility could not be tested since no two symbols were allowed to

overlap.

It is surprising that identification (naming) performance was not found

to be faster with iconic symbols, particularly in light of previous

research findings that iconic symbols are ranked as more meaningful than

conventional symbols (Hemingway, et al., 1978) and that iconic symbols

are recognized with fewer errors under degraded viewing conditions

(Howell and Fuchs, 1961). However, the participants used in the present

experiment, although unfamiliar with conventional symbology were able to

learn these seemingly less meaningful images and manipulate them both

visually and mentally as fast as they could perform these same operations with iconic symbols. One explanation for this result is that only

three different types of units were used in the present experiment.

30
Perhaps with a far greater number of different symbols (as required in

processing information from actual tactical displays), the iconicity

variable would play a more important role. Another explanation is that

two of the iconic symbols (armor and mechanized infantry) were highly

similar, and that this led to slowed overall processing times for the

iconic symbol set. In this regard, a high degree of feature redundancy

among members of a symbol set has been found to impair discrimination in

terms of response latency (Bjork and Murray, 1977; Egeth, 1966). However, a similar case could be made for the conventional symbols since the

armor and infantry symbols combine geometrically to yield the symbol for

mechanized infantry. Unfortunately, the reaction times were not recorded for individual symbols (see Procedure section); therefore, this explanation could not be evaluated. A third explanation for finding no

perceptual advantage for the iconic symbols is that only outline

silhouettes--rather than filled-in silhouettes (see Figure 1)--were

utilized; suggestions have been made that the latter might be perceived

more accurately and more quickly (Chainova et al., 1974; Yoeli and Loon,

1972). A final possibility is that the use of mirror images of the

three basic unit symbols to portray enemy versus friendly forces may

have contributed to a slowed processing of the iconic forms in comparison to the conventional forms. That is, with the iconic symbols, participants had to be aware of six distinct symbol shapes which were required to represent the three types of units because the enemy units

were portrayed as facing the friendly units (see Figure 4); whereas with

the conventional symbols, only three different basic shapes were necessary since directionality was not portrayed in the basic symbol shapes

(see Figure 2).

31
Portrayal of Unit Attributes

The present results also illustrate that the portrayal of unit attributes, such as unit strength or firepower reach, by adding symbol

features, interferes with the processing of unit-type information. In

four tasks (identification, search, comparison, pattern recognition),

reaction times were significantly longer for answering questions referring to the type of units portrayed when a symbol-design feature (perimeter density or vector projection) was varied in the displays to

represent a unit attribute. Thus, there is a trade-off between

representing essential information in a display (Sidorsky, 1977) and

minimizing clutter (Hanby and Shaw, 1969; Simonsen, 1977). However, in

three of these four task analyses, the use of the vector-projection

design feature was found to slow performance on unit-type questions to a

lesser extent than did the use of the perimeter-density design feature.

This result suggests that, even though greater display clutter retards

certain types of information processing, the degree of interference can

be minimized through the careful choice of design features. Apparently,

a vector projection does not alter the perceptability and discriminability of the core unit symbols as does the perimeter-density design

feature.

In addition, the results suggest that an appropiate choice of design

feature is not simply a function of which features produce less display

clutter; but rather, as illustrated in the reaction time data for the

unit-attribute questions, certain design features appear to be more compatible with certain military concepts than others (Bersh, et al.,

1978). Specifically, the portrayal of firepower reach with vector projections and unit strength with perimeter-density coding led to faster

reaction times than did the reverse pairing. Perhaps the vector projections 'appear as gun barrels or bullets "extending" from a unit, and in a

32
sense this design feature is in itself somewhat iconic. In contrast,

perimeter-density coding, an alteration of the core unit form, may be

more compatible with unit attributes describing the internal composition

of the unit, such as unit strength.

Threat Value Assessment

The results for the symbol integration or threat value assessment task

provide some interesting implications. First of all, the high level of

accuracy on this task--irrespective of whether conventional or iconic

symbols were used--suggests that participants can chunk and integrate

symbolic information together rapidly to make meaningful, and relatively

accurate assessments about a given symbol configuration. This finding

is consistent with the results of Badre (1979), who studied tacticalsymbol chunking using a memory paradigm, as well as with the conclusion

of Wheatley (1977) that abstract information such as threat can be

judged reliably when represented in multi-dimensional form. Secondly,

the improvement in performance when fewer symbol dimensions needed to be

integrated suggests that the reduction of unnecessary detail and display

clutter (Simonsen, 1977) may enhance anlaytical judgments. In fact, one

way of achieving such reductions in tactical displays might be through

the use of selective (adaptive) call up of only critical symbols (units)

or symbol dimensions (Channon, 1976).

SUMMARY

In summary, the present experiment illustrates an approach to the

evaluation of candidate tactical display symbologies based on human performance criteria. In this approach, performance is assessed in relation to fundamental behavioral processes thought to underlie the routine

33
use of complex battlefiela displays. The results, within the constraints of the experiment, suggest that:

(1) Iconic symbols (at least of the form studied--i.e.,

blocked, hollow iconic symbols) are not necessarily identified faster than conventional symbols, and such iconic symbols may not be conducive to locating certain embedded patterns of symbols rapidly.

(2) The portrayal of supplementary information about units

through the use of peripheral design features slows the

processing of unit-type information, although vector projections produce less interference than perimeter-density

codings. Furthermore, vector projection is more compatible

with the portrayal of firepower reach, and perimeterdensity coding is more compatible with the portrayal of

unit strength, rather than vice versa.

(3) Analytical assessments involving the integration of many

symbols can be made more accurate when fewer symbol dimensions neea to be processed.

These findings have important implications for the design of improved

and new tactical symbologies for the future--especially if they are supported by additional experiments in which a greater number of different

symbols are used, and/or instances of symbol overlap are allowed.

34
REFERENCES

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Journal of Experimental Psychology, 1957, 53, 221-227.

Attneave, F., & Arnoult, M. D. The quantitative study of shape and pattern

recognition. In L. Uhr (Ed.), Pattern recognition, New York: Wiley, 1966.

Badre, A. N. Selecting and representing information structures for battlefield decision systems. U.S.Army Research Institute (Alexandria, VA), ARI

Technical Report TR-79-A20, June 1979.

Bersh, P., Moses, F. L., & Maisano, R. E. Investigation of the Strength of

Association Between Graphic Symbology and Military Information. U.S. Army

Research Institute (Alexandria, VA), Technical Paper 324, 1978.

Biberman, L. M. (Ed.) Perception of displayed information. New York:

Plenum Press, 1973.

Bjork, E. L. & Murray, J. T. On the Nature of Input Channels in Visual Processing. Psychological Review, 1977, 84, 472-484.

Chainova, L. D., Komarova, I. A. & Zonabend, F. I. Complex Psychophysiological Evaluation of the Readability of Symbolic Information. Royal Aircraft Establishment (Farnborough, England), Report No. RAE-Library Trans1777, October 1974. (AD-BOOO-773)

Thannon, J. Graphic Gobbledegook. Military Intelligence Magazine. 1976,

1(3).

Ciccone, D.S., Samet, M.G., & Channon, J.B. A Framework for the Development

of Improved Tactical Symbology. U.S. Army Research Institute (Alexandria,

VA), ARI Technical Report 403, August 1979.

Egeth, H. E. Parallel versus Serial Processes in Multi-dimensional Stimulus

Discrimination. Perception and Psychophysics, 1966, 6, 245-252.

Estes, W. K. Interactions of Signal and Background Variables in Visual Processing. Perception and Psychophysics, 1972, 12, 278-286.

Foley, J. E. & Wallace, V. L. The Art of Natural Graphic Man-Machine Conversation. Proceedings of the IEEE, 1974, 62, 462-471.

Fleishman, E. A. Toward a Taxonomy of Human Performance. American Psychologist, 1975, 30, 1127-1149.

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Geiselman, R. E., Landee, B. S., & Samet, M. G. Graphic Portrayal of Battlefield Information: Volume III. A Selective Annotated Bibliography for

Tactical Symbology. Perceptronics (Woodland Hills, CA), Technical Report

PFTR-1063-79-1, January 1979.

Hanby, T. C. & Shaw, A. The Effects on the Legibility of Maps of Increasing

Information. U.S. Army Research and Development Group (APO New York), December, 1969.

Hemingway, P. W., Kubala, A. L., & Chastain, G. 0. Study of Symbology for

Automated Graphic Displays. U.S. Army Research Institute (Alexandria, VA),

Technical Report 78, May 1978.

Howell, W. C. & Fuchs, A. H. The Study of Graphic Language. Ohio State

University (Columbus, OH),Report RADC-TR-61-76, October 1961.

LaBerge, D. Perceptual learning and attention. In Estes, W. K. (Ed.),

Handbook of Learning and Cognitive Processes. Vol. 4. Hillside, NJ:

Laurence Erlbaum Associates, 1976.

Machover, C. Does the Emerging Technology Meet the User's Needs? In Proceedings of the Computer Graphic Symposium. Ft. Hood, TX: TCATA, Augu-st1977.

Middleton, N. User Perspectives of Tactical Computer Graphics Requirements.

In Proceedings of the Computer Graphic Symposium. Ft. Hood, TX: TCATA,

August 1977.

Moses, F. L. More Efficient Symbols for Present and Future Needs. Proceedings

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Shurtleff, D. Legibility Research. Proceeding of the Society for Information

Display (Second Quarter), 1974, 15, 41-51.

Sidorsky, R.C. A Concept Paper for a Symbology that Portrays the Tactical

Capabilities of Friendly Units. U.S. Army Research Institute (Alexandria,

VA), Unpublished manuscript, 1977.

Sidorsky, R. C., Gellman, L. H. & Moses, F. L. Survey of Current Developments

in Tactical Symbology: Status and Critical Issues. U.S. Army Research Institue (Alexandria, VA), Working Paper HF 79-03, May 1979.

Simonsen, F. A. Image and System: Graphics and Physical Systems Design. In

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Wheatley, E. An Experiment on Coding Preferences for Display Symbols.

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Yoeli, P. & Loon, J. Map Symbols and Lettering: A Two Part Report: Part

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(London, England), Final Technical Report, January 1972.

37
APPENDIX A

SAMPLE INSTRUCTION BOOKLET

FOR LEARNING A SYMBOLIC LANGUAGE

39
LEARNING THE SYMBOLS

On the battlefield displays that you will see, some basic symbols are

used to represent different types of military units. You must learn what

these symbols represent so that you can answer questions about them. The

types of military units that we will use are armor (a group of tanks),

infantry (a group of soldiers on foot), and mechanized infantry (a group

of soldiers transported in vehicles). The three basic symbols used to

represent these types of units are as follows:

armor unit

infantry unit

mechanized infantry unit

Please make sure that you can give the names of these symbols from memory.

In addition, on some displays, we will represent certain characteristics

of the military units. The characteristics include resource strength

(what percentage of a unit's typical resources, such as weapons,

ammunition, supplies, etc. are currently available for use--100%, 50%,

or 0%), and firepower reach (how far, at present, can a unit shoot with

its weapons--60 kilometers, 40 kilometers, or 20 kilometers). These

characteristics of the military units are portrayed as follows:

41
Strength

Strength is portrayed by blackening in a number of sides of the symbol

representing a unit. The number of sides blackened in corresponds to

different levels of strength as follows.

100% - If all four sides of a symbol are blackened in, that means

that the unit is at 100% of its original strength (weapons,

ammunition, supplies, etc.).

1armor unit - 100% strength

infantry unit - 100% strength

Imechanized infantry unit - 100% strength

50% - If two sides (the top and the bottom) are blackened in,

that means that the unit is at 50% strength.

armor unit - 50% strength

infantry unit - 50% strength

mechanized infantry unit - 50% strength

42
0% - If no sides are blackened in, that means that the unit is

at 0% strength.

armor unit - 0% strength

infantry unit -0% strength

mechanized infantry unit -0% strength

43
Reach

Reach is portrayed by a chain of four circles sticking out from a symbol

in the direction of the battlefield line separating the enemy and friendly

forces. These circles will either all be "hollow" (oooo), two will be

blackened in (seoo), or all four circles will be blackened in (see*).

The number of circles filled in corresponds to different levels of reach

as follows.

60 KM - If all circles are filled in, that means that the unit

has a 60 kilometer reach capability, which is equal to

six squares on the map.

armor unit- 60 KM reach

Zinfantry unit - 60 KM reach

mechanized infantry unit -

60 KM reach

44
40 KM - If half of the circles (the first two nearest the symbol)

are blackened in, that means that the unit has a 40 kilometer, or four square, reach capability.

armor unit- 40 KM reach

infantry unit - 40 KM reach

mechanized infantry unit -

40 KM reach

20 KM - If none of the circles are blackened in, that means that

the unit has a 20 kilometer, or two square, reach

capability.

armor unit - 20 KM reach

infantry unit - 20 KM reach

mechanized infantry unit -

20 KM reach

45
Attack Patterns

Finally, you will be asked to find an "attack" pattern of symbols in either

the friendly or enemy side. For purposes of this study, we will define

an attack pattern as a wedge shape. Friendly attack patterns face to the

right (>), enemy attack patterns face to the left (<). An attack pattern

is composed of 7 units (3 units on each side of the unit "in the lead").

The valid attack patterns are:

7 armor units (regardless of their strength or reach)

7 units of 100% strength (regardless of the types of units)

7 units with 60KM reach (regardless of the types of units)

Attack patterns defined by the strength (100%) or reach (60KM) may contain

a mixture of unit types or they may be composed of one type of unit (such

as infantry). The three legitimate attack formations facing left and right

are shown on the following two pages.

46
Enemy Attack Pattern

0

0

QD A wedge made

of all armor

0 units.

00

A wedge made of

units all at 100%

strength.

A wedge made of

units all with

60 KM reach.

47
Friendly Attack Pattern

0

CA wedge made

of all armor

units. (regardless of

0strength or reach)

C A wedge made of

units all at 1001

strength. (regardless of

QD the type or types of units)

A wedge made of

C m units all with

60 KM reach. (regardless

Fof the type or types of units)

48
APPENDIX B

SAMPLE PRETEST

49

........ . T -. ,
PRE-TEST

(1) Unit Identification

Write the names of the following units in the corresponding blanks.

Write only the unit names (the first one is filled in for you).

(2) Reach and Strength Assessment

Write the reach or strength of each of the following units in the

corresponding blanks. Write only the reach in kilometers or the

strength in percentage terms for each unit (the first two are

filled in for you).

51

-' -
(3) Attack-Pattern Identification

Put a check next to any of the following patterns that are

acceptable, legitimate attack patterns, as defined in the

instructions.

ab

c d

52
e f

0

0O

g h'

53
0 0

o 01

o0

k1

54

L
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57
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