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T.c huic.I Pup.r 283 tAD I

~~ 

AN EVALUATION OF VISUAL SEARCH BEHAVI OR

ON A CATHODE RAY TUBE UTILIZING

THE WINDOW TECHNIQUE

Thomas M. Granda

~~~~ BATTLEFIELD INFORMATION SYSTEMS TECHNICAL AREA

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Research Institute for the Behavioral and Social Sciences

Febr uary 1978

Approved for pu blic rile.,.; distribution unlimited.

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U. S. ARM Y RE SEAR CH INST ITUT E

FOR THE BEHAVIORAL AND SOCIAL SCIENCES

A Field Operating Agency under the Jurisdiction of the

Deputy Chief of Staff for Personnel

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J. E. UHLANE R COL , GS

Technical Direct or Commander

NOTICES

DISTRIBUTION: Primary distribution of this report has been made by ARI. Please address correspon dence concerning distribution 01 repor ts to: U. S. Army Research Institute for the Behavioral and Social Sciences. ATTN: PERI-P. 5001 Eisenhower Avenue . Alexand ria , Virginia 22333.

FINAL. DISPOSITION: This report may be destroyed when it is no longer needed. Please do not return it to

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The findings In this report are not to be constr ued as an official Department of the Army position. unless so dssignsted by oth er authorized documen ts.

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te. SUPPL EMENTARY NOTES

I9. KEY WORDS (Continu. on r.v.ra. .ld. if n.c. ..av aid id.ntify by block numb.r)

Window technique Display motion relationship

Visual search Serial-parallel information processing

Principle.of moving part CRT display

20. AW STRACT (Ccntlflu. on ,.v~ra• lid. If n.a....ty aid id.ntify by block numb•r)

The visual search task in this experiment involved two conq onents: (1)

moving or changing of stimuli viewed in the window of a cathode ray tube (CRT)

and (2) processing of the stimulus information . In order to view the entire

stimulus field , searchers needed to control which section of the super-display

they saw in the window . The motion relationship between the entire display and 1

the window is analogous to that involving the principle of the moving pavt .

DD ~~~~ 1473 EDITI ON OF I NOV SC IS OBSOLETE 

Unclassified SECURITY CLASSIFICATION OF THIS PAGE (

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Unclassified

SECURITY CLASSIFICATION OF THIS PAOE(BIiai Data tni.rod)

20. (con tinuei~)

The present study considered whether the super-disp lay should be the static

component and the window the moving Component or, whether the super-disp lay

should be the moving component and the window the static component.

The second aspect of thià experiment considered how stimulus information

is processed , in relation to the length of a memorized target list. This

aspect evaluated two general models of human Information processing: serial

and parallel.

Ten participants searched a series of alphanumeric displays , presented on

a CRT , for specific numeric stimuli (targets). Independent variables were

display motion control , length of target list, target density , non—target

density , and window size. The effect of time on performa~

tce was also measured

by blocking trials. Each par ticipant perf ormed at all levels of each var iable

except dispfay.uiotIon. Five participants controlled window motion, and five

controlled super—display motion. The basic experimental design consisted of

a modified central composite design taken from response sut~

face methodolo5Y.

N

In general , results sho~w that a window technique is feasible and yields

satisfactory performance i

~ the context of a visual search task. Data concern—.

ing mode of display motion .control were mixed. Participants using the moving

window found a higher percentage of targets (90.2%) than participants using

the moving super—display (82.0%). However , participants in the moving super—

display group took less time to view the super—display than the moving window

group (161.3 and 177.3 seconds, respectively). There was an interaction

effect between target density and trial block. In the first block of trials,

target detection performance was relatively constant at all levels of target

density. However , in the second and third block ot trials detection , perf or—

stance decreased as target density became greater.

A well—defined target set to be memorized provided evidence favoring

parallel Information processing rather than serial information processing.

Results based on scan rate shoved that participants searched, the display

stimuli as quickly f or seven targets as for five or three targets. Information processing tasks of the type in this experiment may evolve from a serial

mode into a parallel mode as the target set becomes jamiliar.

Results concerning the window technique are potentially applicable to any

task where the entire display cannot be presented at a time.

Results concerning information processing can help to structure the

task in which items to be searched must be kept In memory.

ACCESSION for .—.—-—--—---— -----—-- —.—- #1

NTIS White StI ~,

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UISt. ~~~ SlId/ct $PECê~~ Unclassified SECURI TY CLASSIFICATION OF THIS PAG E(WI~

.a Daia Ent.r.d)
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.1_i— 

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T.c huical Pup.r 283

AN EVALUATION OF VISUAL SEARCH BEHAVIOR

ON A CATHODE RAY TUBE UTILIZING

THE WINDOW TECHNIQUE

Thomas M. Granda

Raymond C. Sidorsky, Work Unit Leader

BATTLEFIELD INFORMATION SYSTEMS TECHNICAL AREA

Robert S. Andrews, Chief

Submitted By: Approved By:

Joseph Zeidner, Director J. E. Uhianer

ORGANIZATIONS & SYSTEMS TECHNICAL DIRECTOR

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

Febni~y 1978

Army Project Number Tactical Operations & Displays

2T16110A91B

* pro~

sd for public release; distribution unlImited.
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~~ 

- -- .‘r ,

I

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

A limited portion of the research effort of the Army Research Institute for the Behavioral and

Social Sciences (ARI) is devoted to In-House Laboratory Independent Research (ILIR), Army

Project 2TI6iI OIA9I B, original research in areas suiting the talents of in-house Army scientists

working in problem areas assigned to ARI. Tasks under ILIR include any one of a variety of basic

or applied research activities, which may contribute toward problem solving within the ARI

mission. For example, the present Technical Paper, completed under the direction of Dr. Edgar M.

Johnson, evaluates two aspects of human perception: visual search with a moving window and

fixed background versus a fixed window and moving background, and serial versus parallel models

of human information processing. Participants searched for specific items on a cathode ray tube

(CRT) display in wiiich only a part of the ent re display could be scanned at a time.

Results are pertinent to research being done in the Battlefield Information Systems Technical

Area of ARI on computerized tactical operations and display technology. In a tactical operations

center, a dense informa tion display may be physically impossible to present legibly on a CRT.

When this occurs, information could be eliminated from the display or only one part of the entire

display could be shown at a time through a window. The present paper indicates the feasibility of

the window technique, which the Technical Area wll explore and develop. 

~ - -~~~ -- -~~~~~~-~~~~~~
AN EVALUATION OF VISUAL SEARCH BEHAVIOR ON A CATHODE RAY TUBE

UTILIZING THE WI NDOW TECHNIQUE

BRIEF

Requirement:

To evaluate the feasibility of using a window tect ~

Iique in visual search on a cathode ray tube

(CRT). When a dense information display is to be presented on a CRT, presenting all the

information at one time is not always possible. One solution is to eliminate some information; an

alternative is to present only one ~

ection of the total information display at a time.

Procedure:

Ten participants searched a 20-row x 50-column alphanumeric CRT display for designated

target numbers. Each person could see only one part of the total display at any time but could

• control which section of the entire display was presented in the “window”.

After mastering the basic techniques in a training session, each part icipant conducted 30

searches with varying levels of target density and non-targe t density of the super-display, varying

window sizes, and varying lengths of target set, i.e., the set of possible target numbers to

remember. Five participants controlled the motion of the window across a stationary super-display and the other five moved the super- display across a stationary window opening. Participants were

scored on the percentage of targets detected, time to scan the entire super-display, number of

movement errors, and scan rates. Effect of task duration was considered by blocking on trials (trial 1-10, 11-20, or 21-30).

Findings:

The window techni que was shown as feasible for searching for target stimuli on a CAT. The

participants found most of the targets and made few movement errors. Target density and the

display-motion relationship were determined the most important variables. A higher percentage of

targets was found by participants using a moving window. However, participants in the moving

super-display group made fewer control errors and took less time to view the entire super-display.

Evidence for a parallel model of informa t ion processing was obtained by varying the length of

the target set. Participants scanned the displays as quickly in searching for seven targets as they did

for five or three targets. -

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Utilization of Findings:

The window technique is applicable to an automated tactical operations center (TOC) situation

in which much information must be displayed to a tactical decisionmaker and the TOC staff. For

example, it may be possible to retain all the detailed information on a tactical map by displaying

only a portion of the entire map at a time. Future research should consider the window technique

in conjunction with an additional time-sharing task.

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AN EVALUATION OF VISUAL SEARCH BEHAVIOR ON A CATHODE

RAY TUBE UTILIZING THE WIND~ J TECHNIQUE

TABLE OF CONTENTS

Page

Chapter 1. BACKGROUND 1

The Principle of the Moving Part 3

Human Information Processing - Serial Versus

Parallel Models 9

Summary of Hypotheses 13

Chapter 2. METhOD 1

~

Particinants 15

Equipment and Stimulus Presentation 15

Task 17

Procedure 17

Independent Variables 22

Dependent Variables 22

Experimental Design 23

Chapter 3. RESULTS AND DISCUSSION 29

Percent of Targets Detected 31

Time to Display 100% of the Super-Disp lay 35

Number of Directional Command Errors at the

Super-Display Boundary

Participant Variability 41

Scan Rate 41

Super-Display Search Patterns 41

Summary of the Major Experimental Results

Chapter 4. GENERAL DISCUSSION 47

Chapter 5. SUMMARY AND CONCLUSIONS 53

APPENDIX A REFERENCES A-i

DISTRIBUTION LIST 

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LIST OF FIGURES

Figure Title Page

1. Window Technique Display Motion Relationships 4

2. Typical Experimental Station i6

3. Special Function Keyboard Overlay 16

4. Super-disp lay 18

5. Windowed Display 18

6. Target Identification Message 20

7. A Windowed Display Resulting from a 5-Row Jump 20

8. Three-factor, Central-Composite Design 25

9. Trial Blocks and Target Density Interaction 34

10. Scan Rate Slopes 43

11. Typical Search Pattern 45

LIST OF ThBLES

Table Page

1. Coded Values of the Levels of the Experimental Variables - - 26

2. 30 Treatment Conditions 27

3. Experimental Design 27

4. Second-Order Muitiple Regression Equation 32

5. Analysis of Variance Table for the Percent of

Targets Detected , Using Median Data 33 

~~~~~— “-— ---- - - ------- -~~~~ •- - ~ •—-~~~~- -~~~- 
___ - —-~~~~~~~~~~~~~~~~~~~~~~~ •—~~~~ ---- ~~~~-~---.- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -—- --~•~ ~~~~~ -.- ---—----- ---• - - - -

LIS T OF TABLES

Table Page

6. Second-Order Multiple Regressi.n Equa tion 36

7. Analysis of Variance Table for the Time (in Seconds)

to Display ioo% of the Super-Display, Using Median

Data 37

8. Second-Order Multiple Regiession Equation for Number • of Directional Command Errors at the Super-Disp lay

Boundary 39

9. Analysis of Variance Table for Number of Directional

Command Errors - 40

10. Analysis of Variance Table for Scan Rates 42 

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ARt TP 283

AN EVALUATION OF VISUAL SEARCH BEHAVIOR ON A CATHODE RAY TUBE

UTILIZING TB~ WINDOW TECHNIQUE

CHAPTER 1

BACKGROUND

Visual search is a fundamental cognitive process pertinent to many

daily activities. Among these activities are searching for a number in

a telephone book , looking for a face in a crowd , locating a certain

street on a map , hunting for a specific item on a grocery shelf , and

scanning the classified ads in the newspaper. -

Visual search is also an important aspect of many jobs. Air traffic

controllers monitor electronic video displays in order to coordinate

aircraft arrivals and departures . Image interpreters search photographic

displays for items that might be militarily important. Medical doctors

examine x—rays for possible abnormalities.

These examples are but a few of the ways in which visual search is

used everyday . In a typical visual search task the searcher proceeds

through the total field to be searched in a reasonably consistent

pattern.

The searcher may scan row by row, column by column , section by

section , or with a more complex pattern . Whichever pattern is used , the

searcher processes each stimulus in search of a particular stimulus,

i.e., the target , or set of stimuli.

In many instances , the cathode ray tube (CRT) is employed as the

visual display device for presenting stimulus material to be searched .

CRTs are widely used in airport traffic control centers , libraries,

• hospitals, etc .

Use of CRTs in visual search tasks, however , is constrained by the

physiological characteristics of the human eye which Impose minimum

resolution requirements on electronic displays. This effective ly means

that in order to display all stimuli at the minimum resolution level,

keeping all stimuli in the same perspective , display stimuli must be

magnified.

Very often magnification results in a situation in which the entire

stimulus field of interest cannot be displayed on the CRT at any given

time. A problem thus arises on how to display visual search fields

electronically which cannot be shown as a whole. It has been

suggested, e.g., Barmack , 1966*, that large CRTs be developed for such

purposes. Such displays do exist today but they are extremely expensive.

*B~~mack , J. E , and Sinaiko , H. W. Human Factors Problems in Computer- Generated Graphic Displays. Study S-234, April 1966.

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ARI TP 283

A possible solution to the problem of displaying a visual search

field on a CRT which cannot be shown in Its entirety is the window

technique. The basic idea of this approach is that the viewer sees only

a portion of the entire display at one time.

The concept is similar to viewing the countryside through a window

of a moving train . The traveler sees only a section of the landscape at

any point in time . A similar technique , the moving map display, has been

used in the aviation field . (Roscoe , 1967*) . However , with the moving

map display, as in the case of a traveler on the train, the viewe r has

no direct control over the area being viewed.

The segment of the moving map displayed to the pilot is a function

of the relationship between the aircraft and the earth ; the particular

section of the countryside viewed by the traveler on the train is a

function of where the train is on the rail system.

The idea of using a window display, or similar techniques such as

scrolling and paging, on a CRT has been addressed by computer software

specialists. (Callan, 1974**; Martin , l973***). However, no attempt

has been made to evaluate these techniques or issues related to the use

of this technique in terms of visual search behavior.

This means that no performance data exist which can be used to evaluate the idea; or if warranted , to specify design criteria for a visual

search system using the window display technique .

The general purpose of this study is to evaluate the window technique in the context of searching for targets that are embedded in a

stimulus field which cannot be viewed in its entirety .

The present situation involves two tasks. One task concerns moving

or changing of the stimuli being viewed in the window ; the other task

concerns processing of the stimulus information . In order for a

searcher to view the entire stimulus field , he will find it necessary to

control the section of the entire visual field he sees in the window .

*Roscoe , S. N. The case for the Moving Map Disp lay . Information

Disp lay, 1967 , ~~~, 44 -46 .

**Callan, J. P. Key Decisions in Designing the Picture Systems .

Socie ty for Information Display, 1974 , 11, 18-23.

***Nartin, J. Design of Man—computer dialogues . Englewood Cliffs ,

N.J .: Prentice—Hall, 1973.

2

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ARI TP 283

One of the primary issues of this task concerns the motion relationship between the entire display and the window, the principle of the

moving part. This study examines the principle of the moving part in

regard to the search and task parameters of target density, non—target

density , window size and task duration.

The second task in this situation concerns the processing of each

stimulus Item in order to make a determination as to whether the stimulus

is a target or a non—target. Of concern here is how the stimulus information is processed in relation to a memorized target set. This aspect

of the study will be used to evaluate two general models of human

information processing : serial and parallel.

The Principle of the Moving Part

A window display technique can be used in a visual search task in

two separate but not necessarily independent modes of operation . The

movement Involved could be automatic , moving at a certain rate and in a

certain pattern with no control exercised by the user—viewer.

In this case research involving the prediction of search times based

on eye fixations as a function of target and non—target stimuli would be

particularly pertinent. (Williams, 1966*). On the other hand , the

pattern and rate of display movement could be controlled by the user—

viewer. The latter situation is addressed in this study .

The decision to permit the user—viewer to control the direction of

movement immediately brings about an interesting question . Should the

entire display be the static component and the window the moving

component? Or , should the window be the static component and the entire

display the dynamic component?

To illustrate the operational difference between the two motion

relationships , see the upper portion of Figure 1. Assume that the

super—display , i.e., the complete area to be searched can be partitioned

into a 3 x 3 matrix (Figure 1(a)).

Each cell of the matrix contains stimuli which are not targets and

may or may not contain a target stimulus . Assume also that the

windowed display can show only one cell at a time and that changing the

portion of the super—display in the window means “jumping” from one cell

to a completely new adjacent cell.

Now suppose the viewer has searched cell 2 ,2, Figure 1(b) and wishes

to see another cell. If the viewer were to execute a “move right”

instruction, what would he then see?

*Williams, L. G. Target Conspicuity and Visual Search . Human Factors

1966 , 8, 80—92.

3

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ARI TP 283

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ARI TP 283

If the window were the moving element and the super—display the

static element , the viewer would see cell 2 ,3 (Figure 1(c)). If the

super—display were the moving component and the window the static component , the viewer would see cell 2,1 (Figu r~ 1(d)).

The lower portion of Figure 1 illustrates that a very similar

distinction is made between the inside—out and the outside—in displays

in engineering psychology . Assume that the aircraft is flying parallel

to the earth (Figure 1(e)) and that the pilot banks the aircraft to the

right . What would the display show?

If the aircraft were the moving component and the horizon the static

component, the display would look like Figure 1(f). If the horizon were

the moving element and the aircraft the static element , the display in

Figure 1(g) would result.

Performance differences have been shown between the use of the types

of attitude displays just mentioned . Quantitative reports of pilot error

indicate that many human errors occur in regard to instrument display

reading. (Johnson and Roscoe , 1970*) .

One particular type of error , a reversal error , was found in connection with the aircraft attitude display . The typical attitude display

studied , still in use today , utilized the aircraft as the static display

element and the horizon as the dynamic display element (see Figure 1(g)).

Pilots sometimes were found to misinterpret the attitude display

which caused them in turn to make an aircraft control movement which

aggravated , rather than ameliorated , the situation. That is, instead of

righting the plane from a banked position , the pilot would proceed into

a steeper bank .

Two commonly used explanations for this phenomenon involve population

• or natural stimulus—response stereotypes and the figure—ground relation—

ship. As Chapanis (l972**) and Kelley (l968***) point out , natural

relationships should be one of the considerations for designing displays

which concern a direction—of—movement relationship.

• *Johnson, S. L. and Roscoe, S. N. What Moves, the Airplane or the

World? Savoy , Ill.: Institute of Aviation, Aviation Research

Laboratory, Technical Report ONR—70—1, June 1970.

**Chapanis, A. Design of controls. In H. P. Van Cott and R. G.

Kinkad e (Eds.) Human Engineering Guide to Equipment Design.

Washington: Government Printing Office , 1972 , 345—380 .

***Kelley , C. R. Manual and Automatic Control. New York : John Wiley

and Sons, Inc., 1968.

5 
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ARt TP 283

In the situation in which a pilot banks his airplane to the right, it seems natural to expect the aircraft display component to bank to the

right. That is, the pilot ’s control movement and the displayed result

correspond .

Since the conmion practice is to have the horizon tilt or move to the

left (the inside—out display), it is easy to see that in periods of

stress or disorientation , the pilot may revert to this “natural” mode of

responding. This is a common type of error for the situation in which

incompatible relationships exist between displays and controls.

(Loveless , 1962*).

A second interpretation of the reversal phenomenon involves the

figure—ground relationship . (Johnson and Roscoe, 1970 , op cit). If

the pilot ’s attention is focused to the outside world he tends to use

the earth as the frame of reference, i.e., the ground , against which his

aircraft, i.e., the figure, moves . When the pilot shifts his total

attention to the inside of the cockpit , it is possible that the figure—

ground relationship can change.

That is, the aircraft is viewed as the frame of reference , i.e., the

ground , against which the dynamic element, i.e., the f igure , of a

display moves. If this perceptual reversal occurs the pilot will likely

be confused about the relationship between the movement on the display

and the display control.

Experimentation involving the inside—out and outside—in disp lays

shows overwhelming evidence in favor of the outside—in display .

Experiments have been referred to by Roscoe (l968**) which show that

even those pilots familiar with the conventional inside—out attitude

display make fewer errors with the outside—in display . Yet the controversy over which should move , the aircraft or the horizon, is still

existent .

As previously mentioned , the display motion question for an aircraf t

attitude display is not unlike that for a CRT display which utilizes the

window display technique. Should the same basic principles hold true

in either case? At least one author thinks so.

*Loveless, N. E. Direction—of—Motion Stereotypes : A Review.

Ergonomics, 1962 , 5 , 357—383.

**Roscoe , S. N. Airborne Displays For Flight and Navigation . Human

Factors, 1968 , 10, 321—332 .

6

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ARI Ti’ 283 “Although the above principles (i.e., those relating to the

designation of the moving component of a display) were crystallized

because of their relevance to the problems of aircraft flight and navigation displays, they probably are equally valid for numerous other

reasonably corresponding display problems.” (McCormick, 1970*).

Assuming that controlling or moving the window is analogous to the

outside—in display , performance on a search task should be better in

this condition, than in the condition in which the super—display is the

moving component. More precisely , the following hypotheses were made:

Hypothesis 1. More targets will be found by those participants

using the window as the moving component, as

compared to those using the entire display as

the moving component.

Hypothesis 2. Less time will be required to search the entire

display by participants using the window as

the moving component , as compared to those

using the entire display as the moving

component.

Hypothesis 3. A smaller number of movement errors will be

made by the participants using the window as

the moving component , as compared to those

using the entire display as the moving component.

Above hypotheses are clearly a function of the parameters of the

window technique , such as window size, and of the visual search task,

suc.h as non—target density, target density and task duration . Parameters

are included in this study to examine their relevance for this particular

search task and for the hypotheses stated above.

Window size should affect the time to search through the entire

display. The smaller the window , the more time is required to manipulate

the display controls. Window size also may affect the pattern or

• algorithm which the searcher uses to view the entire display one section

at a time.

For instance, if the window is small, the searcher may not overlap

the displays in the window. That is, in changing the window display,

the searcher may “move” to a completely new section of the total search

field.

However , the searcher may decide to limit the amount of new information he displays, if the window is large . This means that successive

displays in the window would overlap in the information presented .

*McCormick, K. J. Human Factors Engineering. New York: McGraw-Hill,

• 1970.

7
ARI TP 283

Non—target density has been shown related to performance in display

oriented tasks. For example, in a target detection task in which stimuli

were presented on a CRT , Baker , Morris and Steednian (1960*) found that as

the number of non—target stimuli were increased , target accuracy

decreased and search time increased . Display studies using different

tasks also reveal that increasing display density decreased performance.

Baker and Goldstein (1966**) investigated problem solving in two display

conditions. In one condition, all possible responses were disp layed ; in

the other condition, responses were displayed which were appropriate at

a given point in the problem solving task . Baker and Goldstein concluded

that performance was degraded when information with only potential

relevance was displayed. In a study on the relative effectiveness of

horizontal and vertical displays using alphanumeric stimuli, higher

density conditions were found to degrade performance in counting,

locating , ~~entifying and comparing tasks. (Coffey , l96l***).

• *Baker, C. A., Morris , D. F., and Steedman, W. C. Target Recognition

in Complex Displays. Human Factors 1960, 2, 51—61.

**Baker, 3. D., and Goldstein, I. Batch vs. Sequential Displays :

Effects on Human Problem Solving. Human Factors, 1966, 8, 225—235.

***Cof fey, J. L. A Comparison of Vertical and Horizontal Arrangements

of Alpha—numeric Material——Experiment I. Human Factors, 1961, 3, -

93—98.8
ARI TP 283

Target density should clearly affect the total time to search for

targets. The more targets in the entire display , the longer one should

take to search the entire display.

Task duration has been shown to affect performance in a wide variety

of situations . Mackworth (1969*) has described a series of studies in

which a vigilance effect may not have been attributable solely to

temporal uncertainty .

Mackworth wrote that “the vigilance decrement. . . may be particular

example of wide—spread phenomenon involving decrease of manual reactivity

to continued or repetitive stimulation.” In the present situation, the

repetitive operational components of the task and the repetitive

stimulation of the display may adversely affect search performance over

time .

Human Information Processing — Serial Versus Parallel Models

As previously mentioned, the present search task requires the

searcher to process each stimulus item in an effort to find the target

stimuli. How is the stimulus item on the display compared to the list

of known targets in the searcher ’s memory?

Two general information processing models have been proposed to

answer this type of question. A serial model of information processing

[ 

would predict that each displayed stimulus would be compared individually

• with each item in the memorized list.

A parallel model of information processing would predict that each

displayed stimulus would be compared simultaneously to the entire

memorized list.

Serial and parallel models of information processing have actually

been developed using two separate but not necessarily independent tasks.

In one task , a designated target is in the array of stimuli. Usually.

the array of stimuli is presented tachis toscopically and is of variable

length. The critical question in this situation revolves around the

search time for a target presented early, as opposed to later , in the

stimulus array.

A fine background for this literature and its relation to the serial

and parallel models is contained in an article by Egeth, Jonides, and

Wall. (1972**) .

• *Mgckworth, 3. F. Vigilance and Habituation. Harmondsworth, England:

Penguin Books Ltd., 1969.

• **Egeth, H., Jonides , 3., and Wall, S. Parallel Processing of Multi—

Element Displays. Cognitive Psychology, 1972, 3, 674—698.

9

- - — ~~~~~ - -—-- ——- — —- ——-

~

-•- ~~—— •- _a_
ARI TP 283

The other task concerning the serial and parallel processing models

typically involves searching a stimulus display for a target that is a

member of a variable length target set. The primary question concerning

the models in this case is whether or not more time is spent scanning for

a target that comes from a long memorized target list as opposed to a

short one.

This latter situation is under investigation in this study . An

historical perspective on this body of work is given by Neisser (1966)

who is also the chief proponent of a parallel model (1963, et a].., 1963

and 1964*). His procedure and methodology have become classic in visual

search experimentation . Basically the procedure is the following.

The Participant is shown the target memory lis t , then the stimulus

field which is typically 50 rows by 6 columns . The participant scans

as in reading, left to right, top to bottom , and then turns a switch

when he detects a target. The basic performance measure is time per

item scanned.

This is represented by the slope of the best fit regression for data

points which show time to find a target as a function of the target

position in a stimulus field . This slope is “...unaffec ted by the time

required to begin scanning, to decide upon a response, or to turn the

switch .” (Neisser, 1963, op cit). -

The slope of this regression line, therefore , is a relatively pure

measure of time required to process the displayed information.

Using the above procedure and methodology, Neisser showed that 10

different targets could be scanned as quickly as one (Neisser , et al.,

1963, op cit). This result was taken as evidence in favor of the

parallel model. Neisser’s experiment lasted for 27 days and results

favoring a parallel model began to appear after several days.

So , if the experiment had been terminated during the first few days,

the results could have interpreted in favor of a serial model. Neisser

himself indicated that the participants spent the first few days learning

the arbitrary set of alphanumerics used as targets , i.e., A , F, K, U, 9,

H, M, P. Z, 4.

*Neisser , U. Cognitive Psychology . New York : App leton—Century—Crofts ,

1966.

Neisser, U. Decision Time Without Reaction Time: Experiments in

Visual Sc anning. American Journal of Psychology, 1963, 76 , 376—385.

Neisser, U. Visual Search. Scientific American, 1964, 210, 94—102.

Neisser , U., Novick, R., and Lazar , R. Searching for Ten Targets

Simultaneously. Perceptual Motor Skills, 1963, 17, 955—961.

10
ARI Ti’ 283

Other experiments (Kaplan and Carvellas , 1965*; and Cavanagh and

Chase, l97l**) have provided evidence for a serial model. In these

studies the results were based on a one—day experiment. Sternberg

(1966***) also obtained results favoring a serial model in an experiment

in which he used a different set of randomized digits in the target set

from trial to~tria1 over a short period of time.

In a second experiment , reported in the same 1966 Science article, Sternberg f ixed the target set and ran the participants over a much

longer period of time , i.e., 60 practice trials and 120 test trials.

Results were essentially the same as those obtained in the first

experiment .

*K~p1an, I. T., and Carvellas, T. Scanning For Multiple Targets.

Perceptual Motor Skills, 1965, 21, 239—243.

**CgvanaugI~, 3. R., and Chase , W. C. The Equivalence of Target and

Non-Target Processing in Visual Search. Perception and Paychophysics,

1971, 9, 493—495.

***Sternb.rg , S. High Speed Scanning in Human Memory . Science, 1966 , 153, 652—654 .

11
ARI TP 283

Kristofferson (1972*) tried to duplicate Neisser ’s results. From

data obtained over a long time period , i.e., 25 days , she could not

obtain evidence for parallel processing. However, her participants ,

unlike Neisser ’s, yielded low error rates. Her conclusion was that highly

accurate performance was incompatible with parallel processing performance.

Yonas and Pittenger (1973**) found results similar to Kristofferson

(1972).

Egeth, Marcus and Bevan (1972***) obtained interesting results by

varying the “naturalness” of the target set. By definition a “natural”

target set contained the digits 1, 2 and 3; an “unnatural” target set

contained the digits 1, 4 and 7. With the “unnatural” target set,

results conformed to a serial model.

That is, scan rate was an increasing monotonic function of the

number of targets in the set. But with the “natural” target set, results

were obtained conforming to a parallel model. That is, the scan rate

was the same regardless of the number of targets in the target set. Also,

since the error rate in this study was low, i.e., 1.5%, the scan rate

did not agree that a low error rate is incompatible with parallel

processing.

Almost all investigators have found that information processing is

serial in the early stages of their experiments . The Egeth, Marcus

and Bevan study (1972 op cit) which used a well—learned target set was

an exception. This study will attempt to replicate the typical finding

that the serial model fits the information processing data in the early

stages of an information processing task.

In other words , some learning or warm-up is needed to proceed to a

more efficient type of information processing , e.g., parallel processing .

In regard to the above, the following hypothesis is put forth.

Hypothesis 4. The scan rate will, increase as the target

memory set becomes larger.

~

1Cristoffers on, M. N. Types and Frequency of Errors in Visual Search .

Perception and Psychophysics, 1972, 11, 325—328.

**yonas, A., and Pittenger, J. Searching for Many Targets: An Analysis

of Speed and Accuracy . Perception and Psychophy~

sics, 1973, 13,

513—516.

***Egeth , H. F., Marcus , N., and Bevan, W. Target—set and response—set

interaction : Implications for Models of Human Information Processing .

Science, 1972, 176 , 1447—1448.

12
ARI TP 283

Summary of Hypotheses

The first three hypotheses are specifically related to use of the

window technique in the context of the present visual search task. The

fourth hypothesis concerns itself with the information processing aspect

of the visual search task.

Hypothesis 1. More targets will be found by those participants

using the window as the moving component, as

compared to those using the entire display as

the moving component.

Hypothesis 2. Less time will be required to search the entire

display by participants using the window as the

moving component , as compared to those using

the entire display as the moving component.

Hypothesis 3. A smaller number of movement errors will be made

by the participants using the window as the

moving component , as compared to those using the

entire display as the moving component .

Hypothesis 4. The scan rate will increase as the target memory

set becomes larger.
_________ 

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ARI TP 283

CHAPTER 2

METHOD

Participants

Ten United States Army enlisted personnel who were stationed in the

Washington, D.C. area, served as participants. Each participant met

both the following criteria: first, 20—20 vision, correc ted or

uncorrected; second , a score of 100 or higher on the general technical

test contained in the Army classification battery. The nine male and

one female enlisted participants ranged in age from 18 to 22.

Equipment and Stimulus Presentation

All participants used one of four equally equipped experimental

stations (Figure 2). Each booth included a desk with a Control Data

Corporation , model 211, alphanumeric CRT. A special function keyboard

overlay (Figure 3) specifically designed for this study was used to

overlay the standard keyboard . The experimental booth was illuminated

with office level lighting. CRT glare and reflection were minimized .

A dedicated telephone network was used as a communication device between

the participants and the experimenter.

During the experiment , the participants were seated directly in

front of the CRT with easy access to the keyboard which was positioned

directly below the CRT.

The CRT and the keyboard were linked to a Control Data Corporation

computer, model 3300. Control of experimental conditions and on—line

monitoring were accomplished by the experimenter via the experimenter

CRT. All response data were automatically stored on magnetic disk for

analyses .~

In the practice and experimental trials, participants were self—

paced in that following the termination of a trial, they could start the

next trial whenever they wished.

The stimuli presented on the CRT consisted of the letters D, E, H,

K, M, N, P, U, V . W, X, and Y , and the numbers 1, 2, 3, 4, 5, 6, 7, 8,

and 9. Stimuli were of two types, targets and non—targets .

The entire set of non—targets was displayed on each trial. Both

targets and non—targets were taken from rectangular distributions . The

CRT display refreshment rate was 50 frames per second and each “new”

window appeared “instantaneously” displayed to the participant.

*The computer program which presented the experimental stimuli and

collected participant data was written by Mr. Charles Marshall,

Research Support Croup , ARI .

15
ARI TP 283

• .

Figure 2. Typical Experimental Station.

9 0

-J

Figure 3. Special Function Keyboard Overlay.

i6 

-~~ -- -----— - -- -—- -

~~~~~~~~~~~~~~~~~~
Task ARI TP 285

The basic task was to search for a predefined set of consecutive

numbers , i.e., the targets , in a field of numbers and/or letters , i.e.,

the non—targets. The total field searched was a 20 row by 50 column

position matrix , i.e., the super—disp lay. This 1000 position matrix

was partially filled with targets and non—targets.

A typical super—disp lay is shown in Figure 4. The participants , of

course , cou ld not see the super—display in its entirety. Fi gure 5 shows

a typical windowed display, i.e., a part of the super—disp lay seen by

the participants.

The experimental task contained two subtasks. First , the participants searched for and reported a target which was always located some—

where in the first portion of the super—disp lay presented. On some

trials, more than one target was located in this section.

The upper left—hand corner of this window was always the first row

and first column of the super—display. In the second subtask , participants searched the remainder of the super—display for targets using the

window technique , since only a portion of the super—disp lay could be

seen at one time.

Procedure

Upon the partici pants ’ arrival at the laboratory , they were briefed ,

in general , about the major phases’of the experiment. Partici pants were

then randomly assigned to experimental stations. Detailed instructions

for the experiment were located in the booth next to the CRT . These

instructions are available , on request from the Army Research Institute.

A maximum of four participants took part in the experiment at the same

time.

The experimental session was divided into two phases , training and

performance measurement. The training phase was further separated into

two sections corresponding to the two subtasks.

The first section of the training period was devoted to instructing

the part icipant on the procedure used to repor t a ta rget , to ente r the

target location , and to scan for targets.

To report a targe t , the participant had to depress the “T RP” key,

i.e. , the target report key. He then entered a four digit coordinate

indicating the location of the target on the super—display. Lastly,

he depressed the “T LC” key , i.e., the target location key , to confirm

the location .

17
—~~~—-‘ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

ARI IT 283

•

1 

.

I . ~~. 

____

I I .

.. ‘ 

i

______ 3 . . 3 .. _________________

Figure 4. A Super-display that contains 580 non-target stimuli , 7

target stimuli and a target memory length of 5.

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18 

This display is a portion of the super-display in Figure 4.

_____________ - -— ---—- -~- ----~~~~~-
ARI TP 283

The first section of training also addressed itself to reporting

quickly and accurately and locating the first target in each trial.

This proceeded as follows. Prior to the start of each trial , i.e., the

first view of each new super—disp lay , the participants were shown a

f ive—second target identification message (Figure 6).

The message contained two items of information. First , it identified the numbers which were targets for the upcoming trial. Second ,

the message disp layed a fixation point which indicated exactly where

the first row and first column of the super—disp lay would appear on

the CRT .

This procedure allowed the participants to start searching for

target immediately without having to search for the upper left—hand

corner of the windowed disp lay . When the stimuli appeared , the participants were instructed to search quickly from left to righ t , top to

bottom , as in reading. They were told that this was their first task

in each new trial.

The first instructional phase was complete for a participant when

he achieved a scanning rate , i.e. , t ime per stimulus character scanned ,

between .03 and .25 seconds for 8 out of 10 consecutive 30—second

trials. These scanning rates correspond to lower and upper rates

found in the literature .

The scanning rate was determined by dividing the t ime to find the

target by the number of non—targets preceding the target plus one. The

t ime to find the target was the time between the onset of the trial and

the depression of the target report key by the partici pant (see the

“T RP” Key in Figure 3).

The scanning rate for the 10 consecutive trials was computed on a

moving average basis. A series of 50 such 30—second trials was

available for this phase. Between 13 and 44 practice trials were

required for the 10 participants.

In the second section of training, the partici pants were trained to

control the disp lay movement. Disp lay movement was controlled by

directional command keys , i.e., the arrow keys , and the “M” key which

permitted the participant to set the rate of movement (See Figure 3).

The directional keys allowed the participant to control which part

of the super—disp lay appeared in the window . To explain how the disp lay

movement was controlled , assume that the partici pant was in the condi—

tion in which the super—disp lay was the static component , i.e.. the

frame of reference , and the window was the dynamic component.

Also , assume the following : the participant completed searching the

w indowed disp lay in Figure 5; the partici pant chose to “move” the dynamic component five rows and/or five columns at a “jump” (defined by

the contents of the upper right—hand corner of Figure 7); and , the

partici pant wished to view rows 10 through 14, stay ing in columns 1

through 20 of the super—display. 

19

— 

-,

~- -- ~

- -

~ - -- 
ARI TP 2-~~

* FIXATION POINT

TRR&ET SET IS 1,2,3~

4

~

5

Figure 6. 

- 

Target Identification Message for a target memory ieng~

n

of S and a 9 row by 20 column window.

__ _I

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Figure 7. A Windowed Display that shows five new Rows from

The Super-Display shown in Figure 4.

20 

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

~~~~~~

-

~~~~ 

---
ARI IT 2~ 3

To view the desired rows , the participant would have depressed the “ “ directional command key and then the “ STOP ” key . (If the “STOP ”

key were not depressed , the moving component would continue to move until

the 20 row by 50 column super—display boundary was exceeded). The

displayed result of depressing the above two keys is shown in Figure 7.

If the participant was in the condition Li which the window was the

static component and the super—display was the moving component , the

directional commands were reversed. For example , the display shown in

Figure 7 would result if the participant depressed the “ t “ key and the

“STOP ” key .

When a participant told the experimenter that he was familiar with

the keyboard and task requirements , he was given a series of four—minute

trials.

The second phase of training was completed when the participant was

able to bring into view at least 90% of the super—display in 9 out of 10

consecutive trials , computed on a moving average basis . The same series

of 50 trials used in the first part of training session was used in this

part of the training session.

If the display criteria was not met within the 50 available practice

trials, the series was restarted from the beginning . The number of

trials needed to meet the display criterion ranged from 17 to 59.

Participants were advised that they were being monitored continually

via the experimenter ’s CRT to insure that they were following instructions

during both sections of training . The participants were instructed to

call the experimenter on the intercom phone if they had any problems .

For a typical participant , the experimenter visited the experimental

station four to five times during the practice trials .

When the practice trials were completed , the participants were given

45 minutes for lunch . Upon return from lunch , the participants were

given five warmup trials after which the 30 experimental trials were

given. The experimental trials were divided into three blocks at 10

trials each. In between blocks of trials , participants were allowed to

take a one—to two—minute break in Lhe experimental station. This perf or—

mance phase of the experiment required 2 1/4 to 3 hours per participant .

The following is a brief stmunary description of a single trial :

a) The participant initiated the trial by depressing the “T RP”

key;

b, The target identification message appeared for five seconds ;

c) The upper left—hand corner of a new super—display appeared (this

was the beginning of the four—minute trial);

21
ARI TP 283

d) The participant searched for the targe t (s); and ,

e) The participant was notified that the four—minute trial was over

and the next one was ready to begin.

The first task of the participant in each trial was to find the target

in the initial windowed display using the scanning technique learned in

the first instructional phase. After finding the first target , the

participant was free to search for the remainder of the targets in what- ever manner desired.

Independent Variables

There were six independent variables in this experiment.

1. Number of target stimuli in the super—display . The levels were:

(a) 1; (b) 4; (c) 7; (d) 10; and (e) 13. The targets were randomly

distributed throughout the 20 X 50 super—disp lay .

2. Number of non—target stimuli in the super—display . The levels

we re : (a) 180; (b) 380 ; (c) 580 ; (d) 780; and Ce) 980 . All rows of the

super—display contained an equal number of non—targets in any particular

trial . The non—targets were randomly distributed over the super—display .

3. Window size. The levels were : (a) 100; (b) 140; Cc) 180;

(d) 220; and (e) 260 . Each window size was a product of the rows and

columns . The window was always 20 columns wide . This corresponded to

having windows with 5, 7, 9~ 11, and 13 rows .

4. Length of target set s i.e., the set of possible targets fo r a

pa rticular trial. The levels were : (a) 1 (the target was 1); (b) 3

(the targets were 1—3); (c) 5 (the targets were 1—5); (d) 7 (the tar—

gets were 1—7 ); and (e) 9 (the targets were 1—9).

5. Trial blocks . The levels were : (a) trials 1—10 ; (b) trials

11—20; and , (c) trials 21—30.

6. Display m otion. The levels were : (a) the static component

was the super—display and the moving component was the window ; and (b)

the static component was the window and the moving component was the

super—display.

Dependent Variables

There were four dependent variables in this study.

1. Percent of the targ~

’ts detected . That is, the number of targets correctly identified in a trial divided by the total number of

possible targets for that trial .

2. Time (in seconds) to display 100% of the super—display on the

CRT.

22 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ --- -——
ARI IT 283

3. Number of directional command errors at the boundary of the super—

display . An error was defined as a directional command which requested

a display movement which would have resulted in “j umping” farther off

the super—display with no new stimuli than had just been presented on the

previous windowed display. This dependent variable was intended to be

analogous to the pilot reversal error in which the pilot attempts to

return his aircraft to its normal attitude, but moves the control so that

the aircraf t banks to an increased angle.

4. Scan rates (i.e., slope of time to find a target in the first

windowed display on each trial, divided by the number of non—targets

plus one) for target memory lengths 3, 5, and 7.

Experimental Design —

A typical factorial design involving K variables can yield valuable

results concerning expected higher—order interactions . If the higher—

order interaction terms are thought negligible , however, they are

derived needlessly at the expense of time and participants.

Of course, each additional experimental variable increases the number

of participants needed by a multiplicative factor. A dilemma thus

arises in disciplines such as human factors when a multitude of variables

are of concern .

Within the context of a conventional factorial design , a choice must

be made between experimental designs which incur high costs associated

with the use of many variables , and relatively inexpensive designs which

involve only a very few variables at a time.

One solution to this problem involves the use of more economical

research designs such as response surface methodology (RSM). “Response

surface methodology is a procedure and a philosophy for the design, the

conduct , the analysis and the interpretation of experiments performed to

determine the quantitative relationship between a dependent variable

(the response) and one or more quantitative continuous independent

variables” (Simon, 1970*). A particular RSM procedure , the central

composite design , was modified for this investigation because of the

addition of two variable types not customarily included in the analysis .

Before the actual design used is specified , the central composite design

is briefly discussed.

*Simon , C. W. The Use of Central—Composite Designs in Human Factors

Engineering Experiments. Culver City , Calif: Ilughes Aircraft Co.,

Display Systems and Human Factors Department , Technical Report AFOSR

70—6, December 1970.

23

— ——
ARI TP 2B3

The central composite design is based on the assumption that , at

most , a second—order regression equation, i.e., a quadratic equation , is

sufficient to describe the dependent variable , the response surface , in

terms of the independent variables . That is, the researcher believes

that a relationship between , let us say , three independent variables can

be adequately described by an equation of the type:

Y=b +b X +b X +b X +b X2 +b X2 b X2

o 1 1 2 2 33 4 1 5 2+6 3

+ b X X + b X X + b X X .

71 2 81 3 9 2 3

In the above equation b0 is the intercept point and b1 through b

9

are the coefficients of the corresponding terms in the polynomial. This

equation is typically calculated using the least squares technique.

The power of the central composite design resides in the fact that

it requires fewer data points than usually associated with a typical

factorial.

For instance , as seen above , a 3x3x3 factorial would require 27 data

points; whereas a complete three factor central composite design would

require only 15 data points to determine a complete second—order

equation of the type shown above.

This design is illustrated in Figure 8 (taken from Clark & Williges, 1972*) to allow the reader to see the distribution of data points in

3

in experimental space . The data points consist of 2 “factorial points”

(2’~

) and 2x3+l additional “star points” (2K+l), including a “center

point”.

Additional observations at the center point are included in the

design to “ ...help create a uniform information surface... and to

..supply an estimate of experimental error .” (Simon , 1970 op cit).

Thus , it is possible to use a relatively few participants to explore

and define a K—dimension experimental space using a second—order

multiple regression technique.

*Clark , C., and Williges , R. C. Central—Composite Response Surface

Methodology Design and Analyses. Savoy , Ill.: University of Illinois.

Institute of Aviation , Aviation Reøearch Laboratory , Technical Report

ARL—72—10/AFOSR—72—5, June 1972.

24

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ARI TP 2e3

Star

Center Point

I

X~

-o

2~ Factorial

— x - — ~ •_~~~~~ ~~— ~~~— 2

x

l

Figure 8. Three-factor, Central-Composite Design.

(From Clark and Williges, 1972, op cit.)

RSM utilizes an analysis of variance on the regression analysis “to

test the significance of the given partial regression weights and to

test for a significant lack of fit which might indicate additional

parameters are necessary in the regression equation .” (Clark and Williges ,

1973*). The individual weights are tested only to provide an estimate

of the relative importance of the independent variables in the response

surface. A significant lack of fit means that a regression equation of

the third order , or higher , might be needed to fit the data. This can

be accomplished by adding more data points thereby using RSM as a

sequential experimental design (Cochran and Cox , l957**; Williges and

Simon, 1971***).

*Clark , C., and Williges , R. C. Response Surface Methodology Central—

Composite Design Modifications for Human Performance Research . Human

Factors, 1973 , 15 , 295—310 .

**Cochran , W. G., and Cox , G. M. Some Methods for the Study of Response

Surfaces. In Experimental Designs. New York : Wiley , 1957 , 335—375.

***Willigeg , R. C., and Simon , C. W. Applying Response Surface

Methodology to Problems of Target Acquisition . Human Factors, 1971,

13, 511—519 .

25 
_

ARI TP 283

The basic design used for the present experiment was a completely .

within participant four variable central composite design. Two additional

orthogonal variables of interest were added and appropriately fitted

into the regression analyses and the analysis of variance so that second- order interactions could be obtained using all six variables. To

simplify the analyses and to decrease dependence between the coefficients

of the polynomial , all levels of all variables were converted to coded

scores (Table 1). The coded scores for the basic four variable central

composite design , arranged in orthogonal blocks (Cochran and Cox, 1957 ,

op cit) are given in Table 2.*

All 10 participants received all the levels of variables one through

five. The participants were randomly assigned to the two display motion

groups , variable six . The basic experimental design is shown in Table 3.

Table 1. Coded Values of the Levels of the Experimental Variables

Coded Value

Variable -2 -1 0 +1 +2

1-Total targets in SD 1 4 7 10 13

2-Total non-targets in SD 180 380 580 780 980

3-Window size 100 140 180 220 260

4-Memory set length 1 3 5 7 9

5-Trial blocks 1-10 11-20 21.30

6-Display motion groups WD SD

Not.. Entries for variable 6 refer to the dyn amic comp onent ; SD is the super-di splay end WD is the

windowed disp lay.

*The data analysis program for the central composite analysis was

programmed by Eloise D. Lyles , Computer Center , ARI.

26

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
ARI TP 285

Table 2. 30 Treatment Conditions .

The conditions are defined by the coded Values of the first four independent

variables in three orthogonal blocks .

Iflocks

1 - 2 3

~~1 ~~2 ~~3 14 ~~ X2 X3 x1 .a

~ 

x3

1 1 1. 1 2 0 0 0 1 1 1-1

—1 —1 —l —1. —2 0 0 0 —l — 1 —1 1

1 1—1 --i 0 2 0 0 1 1 -1 1

—l —l 1 1 0 —2 0 0 —1 —l 1 —1 . 1—1 1 — ]. 0 0 2 0 1 —3. 1 3. — 1 2. —1 1 0 0 —2 0 —l 1 —1 — 1

1 —1 —1. 1 0 0 0 2 1 —l —1 — 1

—3. 1 1 — 1 0 0 0—2 — 1 1 1 1

0 0 0 0 0 0 0 0 0 0 0 0

o 0 0 0 0 0 0 0 0 0 0 0

Table 3~ Experimenfal Design

Display Motion Participants Trials

Group __________ __________ __________

(Moving

Component) i 10 11 20 21 30

1

Windowed

Display

_________ 

9

2

SuperDisplay

____________________ 

10

27 
ARI TP 283

CHAPTER 3

RE SULTS AND DISCUSSION

The four dependent measures used in this study were :

(1) percent of the targets detected in a trial;

(2) time , in seconds , to display 100% of the super—display on the

CRT for each t’ial;

(3) number of directional command errors at the boundary of the

super—display on each trial; and

(4) scan rate, i.e., slope of the time to find the first target

on each trial divided by the number of non—targets plus one , in target

memory length conditions 3, 5, and 7.

Analyses for the first three dependent variables are based on summary

data .

Data were summarized across participants because the primary interest

was in describing the dependent variable in terms of the independent

variables , i.e., the response surface , and its implications for theoretical issues.

Individual differences were coni~idered irrelevant to this objective

and would have complicated the response surface needlessly.

For the first two dependent measures , the raw data were collapsed

across participants by using the median value at each treatment , i.e.,

each combination of variables .

For the third dependent variable , the raw data were collapsed across

participants by using the average of the dependent measures at each of

the 60 experimental points. The means were used because the median

scores for this variable resulted in a distribution with a small range

that was severely truncated to the left . This distribution was due to

the multitude of zero entries .

The fourth dependent variable was the slope of the scan rate. Due to

the nature of the central composite design which provided only one

treatment combination at the first or fifth -level of the target memory

length variable , i.e., conditions 1 and 9, the slope could be computed

only for target memory lengths 3, 5, and 7.

The first three dependent variables were analyzed in two ways . First,

a second—order regression analysis on the coded scores was computed

using the least squares technique .

29 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 
ARI TP 285

Second , an analysis of variance was calculated , using the coded

scores , to evaluate the significance of the coefficients of the regression

equation .

Coded scores were used in both analyses to simplify the analyses .

The use of real scores often produces the situation in which coefficients

of the regression terms are not independent . With the use of coded

scores, all but the coefficients of quadratic terms are independent of

one another.

To express the coded relationships in terms of the real values , the

following transformation equations were used. The subscripts c and r

stand for coded value and real value, respectively:

(i) Target density (TD ) TD~ = 

~~r -

3

(2) Non-target density (ND ) I

~

m

~ = ND r - 580;

200

(3) Window size (w) W = W - 180

c

TM - 5 (Ii.) Targe t memory = r

length (TM) 2

(5) Trial blocks (B) B = B - 2

1

(6) Display motion (D) -l = Window moves

1 = Super-display

moves.

The analyses of variance for the performance measures of percent

targets detected , time to see the whole super—display , and number of

directional command errors were based on a general program for analyses

involving central composite, response surface designs (Clark , Williges

and Carmer, 1971*; and Clark and Williges, 1972 op cit).

*Clark , C., Williges, R. C., and Carmer , S. G. General Computer

Program for Response Surface Methodology Analyses. Savoy , Ill.:

University of Illinois, Institute of Aviation , Aviation Research

Laboratory , Technical Report ARL—7l—8/AFOSR—71-l, May 1971.

30
ARI TP 283

Percent of Targets Detected

The second—order multiple regression equation using coded data for

the independent variables and median data for percent targets detected

are given in Table 4. Beneath the regression equation , the multiple

regression (R) and the coefficient of multiple determination (R2) for

the first and second—order regressions are presented .

The second—order equation explains a considerably larger proportion

of the variance than the first—order equation (.676 to .348). This

additional explained variance is due to the quadratic terms , i.e., the

interaction terms and the squared terms .

Note that there is no D2 term, because there were only two levels of

this variable. At least three levels are needed to compute a squared

term. This is also true of the remaining second—order regressions .

In the analysis of variance table for percent of targets detected

( Table 5), one sees that the second-order regression was significant

beyond the .01 level and the lack of fit was not significant. Disp lay motion and target density were significant beyond the .01 probability

level.

The display motion group , which used the window as the dynamic

component , found a significantly greater percentage of targets than the

group that used the super—display as the moving element ( 90.2% and

82.0% , respectively).

No main effect was associated with blocks . Thus, the replications

term was pooled across blocks in this analysis .

The effect of target density was diminished by the fact that the

target density and trial block interaction term was significant at the

.05 level. Figure 9 illustrates the interaction involving target

density and trial block with all other factors constant .

At all levels of target density, in the first block of trials

target detection performance was relatively constant . However, in the

second and third trial blocks, the percent of targets detected differed

greatly depending on the level of target density .

Generally, in the second and third trial blocks, the fewer the

targets , the greater the probability that participants would find all

targets . Participants often stopped searching with substantial time

left in the trial, e.g., 30—60 seconds .

31
—~~~~~~

ARI TP 28~ -

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< ~<

z c~ c~ ~ ~ Es E~ a Es -

m w i-I in

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+ + I + + -

~~

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a.,

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32

~ 

-—.----- 
- - -*

ARI TP 2-~3

Table 5. Analys is of Var iance Table for the Percent

of Targets De tec ted , Using Median Data

Source df MS F

Regression (26) 192.739 2.65**

Target flensity (Tn) 3. 892.638 12.27**

Non Target Density (ND) 3. 150.521 2.07

Window Size (W) 1 111.021 1.53

Target Memory Length (TM) 1 172.521 2.37

Blocks, Trial (B) 1 245.025 3.37

Display Motion (D) 1 1008.600 3.3~~97**

TD X TD 2. 5.2.80 .07

TD X ND 1 38.281 .53

TD X W 3. 175.781 2.42

TD X TM 1 63.28 1 .87

TD X B .1 850.781 ll.70**

TDXD 1 .521 .01

ND X ND 1 308.073 4.24*

ND X W 3. 132.031 1.82

ND X TM 1 38.281 .53

ND X B 2. 132.031 182

NDXD 3. 4.688 .06

W X W 1. 17.037 .23

WXTM 1 7.031 .10

W X B 1 225.781 3.10

W X D 1 221.081 3.04

TM X TM 1 112.537 1.55

TM X B 1 7.031 .10

TM X B 1 63.02] .87

B X B 3. 85.008 1.17

BXD 1 9.025 .12

Residual a 

(33) 72.743

Lack of Fit b 23 73.252 1.02

Rep lications 10 71.572

T,tal (59)

a

Error term for all F—tests except Lack of Fit

bError term for Lack . of Fit F-test

*p < 05

•*~ p< .01

33

L _________
All TP 283

100 —

90-

80- :::~~ (.zo)

1J

S

El

U

El

p4

(

~ )

70 -

60- I I ~1

-l (1-10) 0 (11-20) 1 (21-50)

Inturaction effect of target density and trial blocks as me~ ur.d by percent of targets detected. TD is in abbreviation

for target density. The numbers to the left of the perentheses are the coded values and the numbers inside th .

parentheses are the real values.

Figure 9. Trial Blocks

34 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
ARI TP 283

Usually, this occurred only after the participant displayed almost

all of the super—display and at least a few targets had been reported .

Participants apparently considered the search task essentially completed

after they had seen most of the super—display and reported several

targets.

Table 5 shows that the squared term for non—target density was

significant. This indicates that detection performance was better for

the upper and lower levels of the non—target density levels than for the

middle range . It is easy to see why participants detected more targets

when non—target density was low; it is not readily apparent why more

targets should be detected where the non—target density was high.

Perhaps, participants scanned all stimuli more carefully when the display

contained more stimuli.

In Table 5 the number of Fs less than one is greater than is found

in a typical analysis of variance . The basis for this is that all but

one of the F tes ts are composed of a numerator with one degree of

freedom. This results in an F test that is conservative . In fact , Simon

(1970 op cit) has stated that with few degrees of freedom, a conservative

alpha level, e.g., 0.10 may be adopted .

Time to Display 100% of the Super—Disp~~y~

The second—order multip le regression equation for time to display

100% of the super—display is shown in Table 6. As with target detections, considerably more variance was explained by the second—order

equation (.799) than by the first—order equation (.629).

In the analysis of variance table (Table 7), the second-order regression is seen as significant, whereas the lack of fit and the blocking

terms were not significant.

Similar results were obtained for the percent of targets detected.

Significant main effects were obtained for target density , non—target

density, window size and display motion.

The significance of target density appears due to the fact that in

general the more targets there were in the display , the more were

reported . And , the more targets that were reported the more time was

taken in reporting the detections and locations.

For non—target density, the time to display 100% of the super—

display was greater for those in the conditions in which more non—target

stimuli were displayed. This simply indicates that participants took

more time to process a greater number of non—targets .

35

___________
All TP 283

I

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4 

~< 

~< .!4

0 m 

(

.0 N 

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-

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~

O 

~

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a. s-i ~~ 

C

+ I + I 

+

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Es 

~

c

~~

~< 

~< 

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+ + i 

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S.

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o C C

to 

• 0.-

C) at N N 5 )

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~ I-i 

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‘

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II

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H

Cl 

-

~~~~

0 

(N 0 I-s ~~

~~ 0 5Y~ 

(0 N 

0

~~~~~~~~~~~

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N

(N I — ,-i s-I m U0 + I + + + C C

~~~

0 I PU C .

-- 

~4

)

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v

in

-

~iz a-,•N z 36
All TP 283

Table 7. Analysis of Variance Table for the Time (In Seconds)

To Display 100% of the Super-Display , Using Med ian Da ta

Source df MS F

Regression (26) 2348.70 5~ Ø 3**

Target Density (TD) 1 33443.52 71.63**

Non Target Density (ND) 1 7879.69 16.88**

Window Size (N) 1 2685.02 5•75*

Target Memory Length (TM) 1 20.02 .04

Blocks , Trial (B) 3. 250.00 .54

Display Motion (D) 1 3856.02 8.26**

TD X TD 1 435.54 .93

TD X ND 1 185.28 .40

TD X W 1 282.03 .60

TD X TM 1 140.28 .30

TDXB 1 87.78 .19

TD X D 1 117.19 .25

ND X ND 1 54.29 .12

ND X W 1 175.78 .38

ND X TM 1 1069.53 2.29

NDXB 1 52.53 .11

ND X D 1 1210.02 2.59

WXW 1 35.75 .08

W X TM 1 69.03 .15

N X B 3. 331.53 .71

W X B 1 1092.52 2.34

TM X TM 1 5087.50 10.90**

TMXB 1 34.03 .07

TMXD 1 11.02 .02

B X B 1 1702.53 3.65

B X D 1 547.60 1.17

Residua].

a 

(33) 466.87

Lack of Fit b 23 572.76 2.56

Replications 10 223.33

Total (59)

a

Error term for all F-tests except Lack of Fit

bError term for Lack of Pit F-test

< .05

p < .01

37
All TP 283

For the independent variable of window size , the smaller the window

size the more time it took to display 100% of the super—display . This

was expected since the smaller the window, the more operations the

participant must perform on the input keyboard .

As for the display motion factor , the group which used the window as

the moving component took more time to display 100% of the super—display

than the group which used the super—display as the moving component ;

177.3 seconds and 161.3 seconds , respectively.

The squared term for target memory length was significant at the .01

level (Table 7). The participants took more time to see 100% of the

super—display when the target memory length was in the middle levels as

compared to the extreme levels.

Number of Directional Command Errors at the Supet-Display Boundary

This variable is indicative of the relative number of reversal errors

that occur in searching the super—display . It was not possible to

determine reversal errors when the participant was not on a super—display

boundary . The condition existed because it would be difficult to

determine whether the participant made a reversal error , or was just

interested in seeing a particular portion of the super—display .

If a participant was on a super—display boundary , however, it could

be readily assumed that he did not want to move farther off th~ superdisplay.

Table 8 provides the second—order regression equation for the number

of directional command errors at the super—display boundary . Again , as

with detections and display time, the second—order regression explained

more of the variance than the first—order regression (.670 to .323).

The analysis of variance for the directional command errors is shown in

Table 9.

As in the previous analyses the regression was significant , and the

lack of fit and the blocking terms were not significant . There were

significant main effects for target density, non—density , and display

motion.

For target density, the less targets there were , the more directional command errors were made by the participants. This may indicate

that the participants concentrated more on finding targets than on

moving the display when they didn ’t have many targets to report .

For non—target density, the participants made more directional

command errors with fewer non—target stimuli . Perhaps the more open

area in such a CRT display , the more likely that confusion may result

due to the lack of stimulus background .

38

_
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~-- - - -

~~~~~~~~~~~~~ - -~~-—-~~~

- All TP 283

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0

~54 2

59

~
ARI TP 283

Table 9. Analysis of Variance Table for Number of

Directional Command Errors.

Source df MS F

Regression (26) .351 2.70**

Target Density (TD) 1 1.080 8.24**

Non Target Density (ND) 1 1.080 8.24**

Window Size (W) 1 .213 1.6~ Target Memory Length (TM) 1 .030 .23

Blocks , Trial (B) 1 .506 3.86

Display Motion (D) 1 1.440 10.99**

TB X TD 1 .001 .01

TD X ND 3. .320 2.44

TD X N 1 .500 3.82

TD X TM 1 .020 .15

TDXB 1 .125 .95

TDXD 1 .213 1.59

ND X ND 1 .115 .88

ND X W 1 .080 .61 -

ND X 111M 1 .180 1.37

NDXB 1 .405 3.09

NDXD 1 .213 1.63

N X N 1 .504 3.85

N X TM 1 .320 2.44

WXB 1 .005 .04

WXD 1 .480 3.66

TM X TM 1 .244 1.86

TMXB 1 .125 .95

TMXD 1 .163 1.24

BXB 1 .271 2.07

BXD 1 .380 2.90

Residuala (33) .131

Lack of Fit 23 .102 .52

Replications1’ 10 .197

Total (59)

aError term for all F—tests except Lack of Fit

bError term for Lack of Fit F-test

<.0 5

p < .01

• Not.: Th. analysis uses averaged data for errors at the Su~ er -Dis pIay bound ary

40

——-- - —-- ~~~~~—---

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

- -
- -

- ARI TP 283

Significantly more directional command errors were made by the motion

display group which used the window as the dynamic component , 0.69 , as

compared to the group which used the super—display as the dynamic

element , 0.38.

Participant Variability

Summary data (medians and means) procedures were utilized because

individual differences, while anticipated , were not considered as

paramount to the issues involved . However, separate analyses were

conducted to determine the extent of these differences .

For percentage of targets detected , time to display 100% of the

super—display, and numbers of directional command errors , the proportion

of variance accounted for by participants was .195, .259, and .210 .

This high inter—participant variability was probably due to the fact

that the small number of participants were selected on the basis of two

very general criteria (see Participants, Chap ter 2 ).

Scan Rate

The analysis of variance (Hays , 1973*) of scan rate , i.e., slope

in the target memory length conditions 3, 5, and 7 can be seen in Tab le

10. Target memory length was not significant. No consistent pattern

emerged for scan rate as a result of the considerable variability

between participants.

To illustrate the variability, the scan rates f or each of the 10

part icipants at each of the three target memory length levels are

graphically presented in Figure 10.

Super—Display Search Patterns

Data were also obtained concerning the search patterns employed by

the participants in searching the entire super—display . Basically , the

participants “jumped” to non—over—lapping displays . That is, they

changed the “14” command to the size of the display .

Then , they changed the display by depressing a directional command

key , and af ter one “jump”, immediately depressed “STOP” key. By using

this algorithm, it was possible to search the entire super—display without displaying the same stimuli twice. A typical pattern of “jumps”

is shown in Figure 11.

*Eays, W. L. Statistics for the Social Sciences. New York: Holt ,

Rinehart and Winston, 1973, pp. 568—574.

41

-

~

—- - -— ---- - ~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
A.RI TP 283

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ARI TP 283

‘:•

~~ “1

’

~

T ~~~~~~~~~~

I 2

~

:•

~ 

>

Number of Stimuli 

~

Scanned

-; 10- ,

#•

~

0 

S I / 0

O /

0 / ••

..

~~~ Target Memory Length B 5 —

3

/ s

~ ——— 5 / ___ 7 0— I I

0 50 100 150

Number of Stimuli Scanned

(Page 1 of 2)

Scan rare slopes are shos#n for each participant in target memory length conditions 3, 5, and Z

Figure 10. Scan Rate Slopes

1

~3 

---- -

~ -~~~~~~~~~~~~~~~~~~~~ -~~~~~~~ -- --~~~~- - - - ~-•~~--

~~~~
ARI TP 283

15 / -

/ //

s6 - 

$7

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,

,/

~ 

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,:r:

~

I

0 50 100 150 0 50 100 

~

150

Number of Stimuli Scanned

(Page 2 of 2)

Also included are the median value slopes acro~ participants for the three target memory

Mi~gth condition&

Figure 10. Scan Rate Slopes 

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

~~~~~~~~~~~~
ARI TP 283

Super-Display Columns

0 10 20 30 50

0~ I I

0 1 2 5 - I

-— —I

10 I

Cd I -l

S.

14 3

15- I I I I •

1 

I I

20~ I r3 I I

1 I 1 6 7 I B -L~ •

~~~ 0 ~~~ I I ‘ I

I I I I

L .J- —— — — _4 — — 9

5 10 15 20

Windowed

Display

Columns

Figure 11. Typical Search Pattern

Participants employ a pattern whereby the solid rectangle represents the super-display.

The dashed lines represent the windov.ed displays. The numerals represent the succession

of “jumps,” with zero representing the position of the display at the beginning of each

trial. 

-

~~~ - ---- - - ~~~~ -~~- ~~~ --—-~~~~-- -~~~~~ - --- ~~~----—-—-—---~~~~~~~
ARI TP 283

Summary of the Major Experimental Results

Each of the three primary dependent measures , percent of targets

detected , time to display 100% of the super—display , and number of

directional command errors at the super—display boundary , was adequately

described by a second—order regression equation (Tables 7, 7, and 9). In

each case thE. proportion of variance explained by the second—order

regression equation was relatively high and considerably better than a

first—order regression (Tables 4, 6, and 8). The results can be summarized in terms of the hypotheses stated in the introduction as follows :

Hypothesis 1 stated that the group using the window as the moving

component would find more targets than the group using the super—display

as the moving component . This hypothesis was confirmed.

Hypothesis 2 stated that the group using the window as the moving

component would display 100% of the super—display in less time than the

group using the super—display as the moving element . This hypothesis was

not confirmed.

In fact , the exact opposite occurred . The moving super—display group

displayed 100% of the super—display in significantly less time than the

moving window group .

}lyi othesis 3 stated that the group using the window as the moving

component would commit fewer reversal errors than the group using the

super—display as the moving component .

Again, not only was -:he hypothesis not confirmed but the opposite

effect was shown. That is, the moving window group made significantly

more errors than the moving super—display group .

Hypothesis 4 stated that information processing would be slower for

the larger target memory length conditions than for the shorter target

length conditions . This hypothesis was not confirmed. There were no

significant differences between information processing rates for the

target memory conditions .

Thus, the group that used the window as the moving component found a

greater percentage of the targets , but took more time to display 100%

of the super—display , and made more directional errors than the group

that used the super—display as the moving element .

46

--~ ---~~~~~~~~~~~~~~~~ --~
ARI TP 283

CHAPTER 4

GENERAL DISCUSSI ON

The window technique appears to yield satisfactory performance in

searching a large area on a small screen. However, display motion

results based on aircraft display studies clearly cannot he extrapolated

to those involving a user—viewer who can directly control the windowed

display presented on a CRT.

The perceptual factors that people bring into a general display

situation may be very much the same. Nevertheless , chances for

perceptual confusion and disorientation may differ vastly from one

specific display situation to another.

For instance , moving the window was assumed more natural than moving

the super—display . It seemed that the larger component , the super—

display , would be thought of best as the ground , and that the smaller

component , the window , would be thought of as the figure . However,

this view was much too simplistic . Results , although mixed , favor the

super—display as the moving component .

In this study , the display motion relationship was more subtle than

in the aircraft display studies . In the aircraft situation , regardless

of which display the pilot used , the airplane was always moving .

In the present study this type of motion was not present . Prior to

entry into the experimental booth the participant experienced himself

as the moving object and the world around him as stationary . This

would be the same experience that pilots have prior to getting into the

cockpit.

When a participant in this study sat down to view the display , he

became the stationary object and the CRT display passed before him.

In other words, the participant himself , the CRT frame , and all that

the participant saw in peripheral vision remained stationary and became

the frame of reference or the background . The only motion in this

situation was the display which moved in front of the participant .

In conjunction with this frame of reference , participants in the

moving window group might have visualized the situation as one in which

they were operating a television camera and the display they saw on the

CRT was a result of a “camera movement” which they themselves made .

Chapanis (1972 op cit) cautions against use of such intervening

mechanisms to control movement display directions . However , in this

study such an intervening mechanism could have led to disorientation .

The above interpretation implies that the moving super—display group

should find a greater percentage of the targets. But this was not the

case. The moving window group found a greater percentage of targets

than the moving super—display group . 

~ --~~

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~~ _- ~~-~~~~~~~~~ - - - ~~~~~~~ --~
ARI TP 283

The moving window group possibly experienced more difficulty with

display movement. Thus, the group spent more time seeing the entire

display , made a greater number of directional command errors , and spent

more time looking at sections already seen. This would then yield a

greater probability that a target would be detected .

The present task environment may not be representative of the real

world . Therefore, a number of empirical questions arise. For instance

the participant was isolated from other people and extraneous visual

activity. The only obvious visual motion that occurred took place on

the CRT.

Suppose the participant was in an environment in which other people

moved about while he was trying to perform his visual search task.

Would the fact that the participant could see others move in his peripheral vision affect the display—control relationship?

Perhaps the assignment of additional task(s) requiring participants

to move about the experimental area would have been more realistic .

Would the user—viewer moving about affect the display motion relationship?

Performance utilizing the window technique also could be affected

by whether the display is dynamic or static. The value of a computer—

linked CRT increases immensely when the data being displayed change

rapidly. This situation would make hard copy displays ineffective.

The question remains on how people perform with a dynamic display which

cannot be viewed in its entirety.

The task type factor is also very important. Using the window

technique for viewing sections of a super—display that can be treated

as separate displays, as in searching, is one situation .

What about the case in which information must be culled and

integrated from different and relatively distant sections of the super—

display? Is the window technique applicable to this type of task?

Within the context of a static visual search task the window technique has been shown to be a feasible and satisfactory approach . In

general , many of the targets were found with relatively few errors .

In regard to the performance criteria and search parameters, this

study provided the opportunity to make tentative recommendations for

window display tasks.

48 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 
ARI TP 283

In terms of non—target density , the present study confirms the

earlier results of Baker, et al. (1960 op cit) that detection performancs

could be improved by essentially masking out as much irrelevant stimuli

as possible. This conclusion , of course , assumes that a computer

algorithm can be implemented which extracts only unneeded information .

Target density also affected time to display 100% of the super—

display (Table 7) and number of directional command errors at the

super—display boundary (Table 9). The more targets there were, the more

time was used , and the more errors were made .

These results are attributed to the fact that the participants

stopped searching the display in order to report and enter target

location via the keyboard .

In situations in which increased search time and/or increased

directional command errors are critical , changing the method of reporting

a target may be advisable. For instance, if the requirement is merely

to indicate the location of a target , a light—pen or a touch panel

device may substantially improve performance.

If , on the other hand , an analysis of a target is required , e.g.,

to find the type of target or the strategic implications of the target

location , it may be beneficial to have one man report the target and its

location , and another man to perform the target analysis.

As predicted , window size was inversely related to the time to

display 100% of super—display . This effect was attributed to the

additional motor activity needed to display the entire super—display .

Thus, if search time is critical and if the display is not cluttered ,

a larger window size should be employed . This suggestion is somewhat

tentative, however, in view of the fact that the super—display itself

was not very large , i.e., 20 rows by 50 columns .

Performance was found constant over time (Tables 5, 7, and 9). However trial blocks and target density were involved in an interaction

effect (Figure 9) as marked by the percent of targets detected .

It seemed as if the more targets in the later trials , the probability was less that they would all be detected . To counteract this

possible effe ct , displays known or suspected to have a greater number of

targets should be presented and searched earlier in the search time

period .

49

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ARI TP 283

Results concerning scan rate tend to favor a parallel processing

model rather than a serial processing model. The scan rate was notsignificant for target memory lengths . Participants scanned the display

stimuli as quickly for seven targets as they did for f ive or three

targets.

The composite data for all 10 participants in each target memory

length condition indicates no significant differences between target

memory conditions.

However , there was much variability between participants for the

scan rates. For instance , the graph for participant five (Figure 10)

shows an increased slope for longer target memory lengths . However, the

exact opposite can be seen in the graph for participant 10, i.e.,

decreased slope for longer target memory lengths .

Scan rate results agree with the Egeth , Marcus and Bevan ’s (1972

op cit) study . In the Egeth, et al study , as in the present investigation , participants worked with familiar target sets. Neither study

produced evidence for serial processing in the early stages of information processing .

Parallel processing is possib ly a primary function of how well the

target set is learned. Learning may take place during the course of an

experiment , (e.g., Neisser , et al., 1973 op cit) or in the course of

everyday experience.

Thus, when a well—learned set of items, e.g., consecutive numbers

is used as the target set, there is no need to practice . Performance

equivalent to parallel processing can be observed readily .

These results have Implications for both serial and parallel models.

The models can be though t of , not as independent , but as evolutionary

stages in learning to process information efficiently .

The serial model describes the result of information processing of

unfamiliar target sets dur ing early practice. The parallel model

describes the result of information processing with an unfamiliar set

after much practice has occurred , i.e., the target set has been well—

learned , or in early practice using familiar target sets.

The evolving concept of information processing is similar to the

ctnrnking process of memory storage capacity 01111cr, 1956*). This

process essentially recodes information into fewer parts or chunks with

more information contained in each chunk.

*Miller, G. A. The Magical Number Seven, Plus or Minus Two : Some Limits

on Our Capacity For Processing Information . Psychological Review,

1956, 63, 81—97.

50
- - 

- 

-

ARI TP 283

— For example , a two—stage chunking process might be the recoding of

the binary digits 001110000111. Conversion of the binary digits to

octal yields 1607; these four octal digits can be converted to the year of the settlement of Jamestown , the first permanent English settlement

in North America.

In terms of the information processing well—learned target stimuli

may be recoded or reorganized in memory somehow so that a more eff icient

process of searching , i.e., parallel processing , is developed .

The fact that target search time is not affec ted adversely by the

length of the target list as long as that list is very well-learned has

an important implication for visual search tasks.

Information processing can be improved by clearly defining each item

in the target set, and by constructing the target list so that it

conforms to a chain of well—associated stimuli.

51

_
r ____

ARI TP 283

CHAPTER 5

SUJ ~

Y AND CONCLUSI ONS

This study investigated two aspects of a search task in which the

entire search f ield , i.e., super—display , cannot be displayed at one time.

One aspect concerned the use of the window technique ; the other concerned

processing the stimulus information in regard to length of the memorized

target list.

The principle of the moving part was investigated in relation to use

of a window technique to determine which element of the display should

be controlled , the window or the super—display .

In general, results show that in the context of a search task, a

window technique is feasible and yields satisfactory performance; however,

the results were mixed.

A higher percentage of targets was found by participants using a

moving window . But participants in the moving super—display group made

fewer control errors and took less time to view the entire super—display .

This result suggests that the display motion situation in this task

is a complex one, and not sufficiently analogous to aviation displays

to justify direct extrapolatá~on from aviation research data.

Future research should consider more closely simulating a real world

physical environment in which motion is not confined to the CRT display .

Evidence for a parallei. model of information processing was obtained in

early search trials with the use of a well—defined target memory set.

Participants scanned the display stimuli as quickly for seven

targets as for five or three targets. An information processing

concept was discussed which evolves into a parallel mode from a serial

mode as a function of the familiarity at the target set.

53 

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ARI TP 283

APPENDIX A

REFERENCE S

Baker, C. A., Morr is, D. F., and Steedman , W . C. Target Recognition in

Complex Displays. Human Factors, 1960, 2, 51—61.

Baker , J. D., and Goldstein, I. Batch vs. Sequential displays : Effects

on Human Problem Solving. Human Factors, 1966, 8, 225—235.

Barmack, J. E., and Sinaiko , H. W. Human Factors Problems in Computer—

Generated Graphic Displays . Study S—234, April 1966.

Callan , J. F. Key Decisions in Designing the Picture Systems. Society

for Information Display, 1974, 11, 18—23.

Cavanaugh , J. R., and Chase , W . C. The Equivalence of Target And Non—

Target Processing in Visual Search . Perception and Psychophysics, 1971,

2.

~ 

493—495 .

Coffey, J. L. A Comparison of Vertical and Horizontal Arrangements of

Alpha—numeric material——Experiment I. Human FactOrs, 1961, 3, 93— 98.

Chapanis , A. Design of controls. In H. P. Van Cott and R . G . Kinkade

(Eds.), Human Engineering Guide to Equipment Design. Washington :

Government Printing Office , 1972 , 345—380.

Clark, C., Williges , R. C., and Carmer , S. G. General Computer Program

for Response Surface Methodology Analyses. Savoy , Ill.: University of

Illinois , Instutute of Aviation , Aviation Research Laboratory , Technical

Report ARL—7l—8/AFOSR—71—l, May 1971.

Clark , C., and Will iges , R. C. Central—Composite Response Surface

Methodology Design and Analyses. Savoy, Ill.: University of Illinois ,

Institute of Aviation , Aviation Research Laboratory , Technical Report

ARL—72—1O/~FOSR—72—5 , June 1972.

Clark , C., and Williges, R. C. Response Surface Methodology Central—

Composite Design Modifications for Human Perfo~manee Research . Human

Factors, 1973, 15, 295—310.

Cochran , V. G., and Cox , C. M. Some methods for the Study of Response

Surfaces . In Experimental Designs. New York: Wiley , 1957, 335—375.

Egeth, H., Jonides , J., and Wall , S. Parallel Processing of Multi—

element displays. Cognitive Psychology, 1972 , 3, 674—698.

Egeth, H. E., Marcus , N., and Bevan, W. Target—set and Response—set

Interaction: Implications for Models of Human Information Processing.

Science, 1972, 176 , 1447—1448.

Hays , W. L. Statistics for the Social Sciences. New York: Holt,

Rinehart and Winston, 1973.

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ARI TP 283

Johnson, S. L. and Roscoe, S. N. What Moves, the Airplane or the World?

Savoy , Ill.: Institute of Aviation , Aviation Research Laboratory,

Technical Report ONR—70—1, June 1970.

Kaplan, I. T., and Carvellas , T. Scanning for Multiple Targets.

Perceptual Motor Skills, 1965, 21, 239—243.

Kristofferson , N. N. Types and Frequency of Errors in Visual Search .

Perception and Psychophysics, 1972, II, 325—328.

Kelley, C. R. Manual and Automatic Control. New York: John Wiley and

Sons , Inc., 1968.

Loveless , N. E. Direction—of—Motion Stereotypes : A review . Ergonomics,

1962, 5, 357—383.

Mackworth, J. F. Vigilance and Habituation. Harmondsworth , England:

Penguin Books Ltd., 1969.

Martin, J. Design of Man—Computer Dialogues. Englewood Cliffs , N.J.:

Prentice—Hall , 1973.

Miller , C. A. The Magical Number Seven , Plus or Minus Two: Some Limits

on Our Capacity for Processing Information. Psychological Review, 1956,

63, 81—97.

McCormick , E. J. Human Factors Engineering. New York: McGraw—Hill ,

1970.

Neisser , U. Decision Time Without Reaction Time : Experiments in Visual

Scanning. American Journal of Psychology, 1963, 76 , 376—385 .

Neisser, U. Visual Search . Scientific American, 1964, 210 , 94—102.

Neisser, U., Novick , R., and Lazar , R. Searching For Ten Targets

Simultaneously. Perceptual Motor Skills, 1963, 17, 955—961.

Neisser , U. Cognitive Psychology. New York : Appleton—Century—Crofts,

1966.

Roscoe , S. N. The Case For the Moving Map Display . Information Display,

1967, 4, 44—46.

Roscoe, S. N. Airborne Displays for Flight And Navigation. Human

Factors, 1968, 10, 321—332.

Simon , C. W. The Use of Central—Composite Designs In Human Factors

Engineering Experiments. Culver City, Calif.: Hughes Aircraft Co.,

Display Systems and Human Factors Department , Technical Report AFOSR—70—6,

December 1970.

A-2

L __ .~~~~~~~~~~~~ 
— - - 

—~~C. - - ’

~~ -.---- -‘~ —-_--—,,._-

t ~~~~~~~~ ARI~~~~285 - Steinberg, S. High Speed Scanning in Human Memory. Science, 1966 , 153, 652—654.

Williams, L. C. Target Conspicuity And Visual Search . Human Factors,

1966 , 8, 80—92.

Williges, R. C., and Simon , C. W. Applying Response Surface Methodology

to Problems of Target Acquisition. Human Factors, 1971, 13, 511—519 .

Yonas , A., and Pittenger, J. Searching For Many Targets. An Analysis of

Speed And Accuracy . Perception and Psychophysics, 1973, 13, 513—516 .

I • A-3

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