dition. A significant practice effect was found
for 7 of the 11 measures; the exceptions were
response time and response accuracy on problem-
solving-confirmation performance, meter response
time, and pattern-identification response time.
There was a significant interaction between task
complexity and practice on both the red and
green lights measures. Inspection of the simple
effects on these two measures showed that there
was a significant practice effect between the two
complex-performance sessions but not between
the simple-task sessions.

TABLE 2. Mean Perforsance by Task Complexity and Practice

Task Couplerity Practice Seuston

Simple Cospiex ‘First Second
Light Monitoring

‘Green reaponse tine 396.07 4

Red response tine hora re
Acsetmettc

Percent correct 058. 38 a

Tiee/problen oie 16585 w0279_—10.29
Problen Solving

‘Solutton, cine/ré 1g8 2 211.95

Contiraation, percent correct responses 35 Sr 30

Confirmation, Hise/response usr vlan 178
Meter Monitoring

Response tine 12.53 23.19 18.28 17.41
Pattern Identification

Percent correct, 99.0 83 82

Tine/probles spe tae 98s
Tracking

Vector RMS error (arbttrary units) 4.64 7 6.33 8.2

ALL tine mensuren are {n seconde; recorded as 1/100 of @ second
stUnderlined patra differ ae pe <05.

The relative contributions of the effects of
practice and task complexity were evaluated for
each measure exhibiting a significant effect by
use of the omega-squared statistic, which pro-
vides an estimate of the proportion of total
variance that is attributable to each etfect.** The
omega-squared statistics, which are presented in
Table 3, show that although the practice effect
is significant for seven measures, that effect is
relatively small in magnitude; it accounts for
no more than 5 percent of the total variance
for any measure. The task-complexity effect,
which is significant on 10 of the 11 measures, is
in every case larger than the practice effect. The
magnitude of the effect of complexity varies
widely between measures, ranging from 6 to 71
percent of the total variance for a given task
measure. The proportions of variance for those
tasks that are most affected by task complexity
are: green lights, 71 percent; red lights, 40 per-
cent; tracking, 24 percent; and meters, 20 per-
cent.

TABLE 3. Ooege” Entinate of Magnitude of Effect of

Stanifteant Complexity and Practice Effects

Couplerity Practice Interaction

Light Nonttoring

Red response tine ‘40 ‘os 05,
Artehmette

Percent correct 08 06

‘Thne/problen tor loa
Problem Solving

‘Solueton, time/response 08

Confirastion, percent correct responses ns.

Conttrantion, tine/response 108.
Meter Monitoring 20 nae
Pattern Identification

Percent correct my 02

Tiee/problen 06 as.
Tracking

‘Vector WMS error (arbitrary units) me 03

C. Factor Analytic Findings. The data used
in the factor analyses were based on the averages
across the two trials for each measure at a given
level of complexity. In all of the analyses, the
principal components method was used with
unity in the major diagonal. Following the rule
suggested by Guttman” and Kaiser, factors
were extracted in a step-wise procedure until a
factor with a eigenvalue of less than one was
obtained. All factors with an eigenvalue greater
than one were then rotated to simple structure
by the normal varimax method. The measure
identification key used in each of the remaining
tables is shown in Table 4,

TABLE 4, Nueber Key for Measures

Measure Nuaber

Simple Complex
Green Lights, Response Time 1 2
Red Lights, Response Tine 2 13
Arithmetic % Correct 3 4
Arithnetic, Time/Problen 4 1s
Problem Solving

Solution Phase, Time/Response 5 16

Confirmation Phase, % Correct Response 6 ”

Confirmation Phase, Tine/Response 7 18
Meters, Response Time 8 9
Pattern Identification, % Correct 9 20
Pattern Identification, Time/Problem 10 a
Tracking, Vector RMS Error u 2



bad

10.

1.

13.

14.

. Chiles, W. D., E. A. All

. Chiles, W.

References

. Bartlett, F. C.: The Measurement of Human Skill,

BRITISH MEDICAL JOURNAL, 4510 :835-838 and
4511 :877-880, 1947.

. Chiles, W. D.: Methodology in the Assessment of Com-

plex performance: Introduction, HUMAN FACTORS,
9 :325-827, 1967.

. Chiles, W. D: Methodology in the Assessment of

Complex Performance: Discussions and Conclusions,
HUMAN FACTORS, 9 :385-392, 1967.

isi, and O, S, Adams: Work
Schedules and Performance During Confinement,
HUMAN FACTORS, 10:143-196, 1968.

. Chiles, W. D., P. F, Iampietro, and EB. A. Higgins:

Combined Effects of Altitude and High Temperature
on Complex Performance, HUMAN FACTORS,
14 :161-172, 1972.

. Chiles, W. D, and A. E. Jennings: Effects of Alcohol

on Complex Performance,
12 :605-612, 1970.

, A. E, Jennings, and G. West: Multiple
‘Task Performance as a Predictor of the Potential
of Air Traffic Controller Trainees. FAA Office of
Aviation Medicine Report No. AM-72-5, 1972.
Conrad, R.: Missed Signals in a Sensorimotor Skill,
JOURNAL OF EXPERIMENTAL PSYCHOLOGY,
48:1-9, 1954.

Conrad, R.: Adaptation to Time in a Sensorimotor

HUMAN FACTORS,

Skil, JOURNAL OF EXPERIMENTAL PSY-
CHOLOGY, 49:115-121, 1955.
Conrad, R. Timing, OCCUPATIONAL  PSY-

CHOLOGY, 29:3, 1955.

Conrad, R.: The Timing of Signals in Skill, JOUR-
NAL OF EXPERIMENTAL PSYCHOLOGY, 51:365-
370, 1956,

. Fleishman, E. A.: The Prediction of Total Task

Performance From Prior Practice .on Task Compo-
nents, HUMAN FACTORS, 7 :18-27, 1965.
Fleishman, E. A.: Performance Assessment Based
on an Empirically Derived Task Taxonomy, HUMAN
FATORS, 9 :349-366, 1967.

Fleishman, E, A,: On the Relation Between Abilities,
Learning, and Human Performance, AMERICAN
PSYCHOLOGIST, 27 :1017-1032, 1972.

14

15. Fleishman, E. A., and S. Rich: Role of Kinesthetic
and Spatial-Visual Abilities in Perceptual-Motor
Learning, JOURNAL OF EXPERIMENTAL PSY-
CHOLOGY, 66 :6-11, 1963.

Freedle, R. O., A. N. Zavala, and E. A. Fleishman:
Studies of Component-Total Task Relations: Order
of Component-Total Task Performance and Total
Task Predictability, HUMAN FACTORS, 10 :283-296,
1968.

Guttman, L.: Some Necessary Conditions for Com-
mon-Factor Analysis, PSYCHOMETRIKA, 19:149-
161, 1954.

Hayes, W. L.: Statistics for the Social Sciences,
Second Edition, New York, Holt, Rinehart, and
Winston, 1973.

Kaiser, H. F.: The Application of Electronic Com-
puters to Factor Analysis, EDUCATIONAL AND
PSYCHOLOGICAL MEASUREMENT, 20:141-151,
1960.

. Knowles, W. B.: Operator Loading Tasks, HUMAN
FACTORS, 6:155-161, 1963.

Lindquist, E. F.: Design and Analysis of Eaperi-
ments in Psychology and Education, Houghton
Mifflin Company, 1953.

North, R. A., and D, Gopher: Measures of Attention
as Predictors of Flight Performance, HUMAN
FACTORS, 18 :1-14, 1976,

Parker, J. F.: Use of an Engineering Analogy in
the Development of Tests to Predict Tracking Per-
formance. Matrix Corporation report prepared for
the Office of Naval Research under Contract NONR-
3065 (00), 1964.

Parker, J. F., and E. A. Fleishman: Ability Factors
and Component Performance Measures as Predictors
of Complex Tracking Behavior, PSYCHOLOGICAL
MONOGRAPHS, 74:N503, 1960.

Rolfe, J. M.: The Secondary Task as a Measure of
Mental Load. Jn Singleton, W. T., J. G. Fox, and
D. Whitfield (Eds.), Measurement of Man at Work,
London, Taylor and Francis, 1971.

Senders, J. W.: The Estimation of Pilot Workload.
Unpublished Manuscript, 1967.

16.

17.

18.

19,

21,

22.

23,

24.

26.


monitoring and tracking measures would appear
to be the most likely to exhibit evidence of a
time-sharing ability.

It should be noted that, although the problem-
solving task was presented both by itself and as
a part of complex Task A, it is a group-perform-
ance task in the literal sense. Therefore, since
it would quite likely be subject to group influ-
ences, it should be regarded primarily as a source
of increased workload for the purposes of this
study.

The results of the factor analysis for the en-
tire set of measures can be readily interpreted as
providing direct support for the hypothesis that
there is a time-sharing ability that is involved
in complex performance. Specifically, three
orthogonal factors involving the monitoring
tasks emerged: red and green lights performance
loaded under the simple condition on one factor;
meters performance loaded under the simple con-
dition on another factor; and meters and lights
performances both loaded on a third factor un-
der the complex condition. The specific per-
formance requirements of the meter monitoring
task under the simple condition were identical to
those of the complex condition, and the same
was true of the red and green lights monitoring
task. Thus, it seems reasonable to interpret the
fact that these tasks are orthogonal under simple
conditions but related under complex conditions
as evidence of a higher-order process. It also
seems quite reasonable to interpret that high-
order process to be a reflection of differences in
the ability of subjects to shift attention quickly
and efficiently from the active tasks to the moni-
toring.

The factor analyses that were applied sepa-
rately to the Task A and Task B data did not
appreciably alter the general nature of the find-
ings of the overall analysis. In each of these
analyses, the factors on which the monitoring
tasks were found to load under the simple condi-
tion were orthogonal to the factor on which they
loaded under the complex condition. The find-
ings of the fourth analysis, which involved only
the monitoring data, were directly analogous to
those of the overall analysis; there emerged two
simple condition factors, one for lights and one
for meters, and one complex condition factor on

il

which meters and lights loaded. Whether one
chooses to call the factor for the complex condi-
tion complex monitoring ability or time-sharing
ability is perhaps arbitrary, but the results sug-
gest a factor that clearly fits our proposed
definition of a time-sharing ability—a source of
variance for complex performance that is or-
thogonal to the implicated measures for simple
performance.

An important aspect of this study was what
was not found; namely, no complex performance
factor emerged that could be called a Task A
factor or a Task B factor, nor was there a factor
that crossed over the two tasks as a general com-
plex performance factor. Only the monitoring
tasks appeared to have properties that warrant
an inference about time sharing.

The best explanation for this general pattern
devolves from a consideration of the notion of
task priorities. Subjects appear to develop a
hierarchical response strategy in which perform-
ance of a given (higher priority) task is protected
at the expense of lower priority tasks. We have
been generally aware of this for some time in an
observational sense, and we have data from
previous studies that seem to be best interpreted
jn this manner, For example, Chiles and
Jennings® conducted a study on the effects of
alcohol on complex performance. It was found
that, with average blood alcohol levels on the
order of 100 mg%, tracking and monitoring
performance showed significant degradation but
mental arithmetic performance was not affected.
The nature of the arithmetic task was that the
most reasonable explanation of those findings
was that the subjects had “protected” their per-
formance of the arithmetic task, presumably by
devoting more of their attention to it. Therefore,
our interpretation of these findings was that
arithmetic performance was maintained at the
expense of the performance of the other tasks.

If the subjects in the present study are assumed
to be operating with some sort of response hier-
archy, then it is reasonable to argue that the
performance of the higher priority tasks under
both the simple and the complex conditions
would be primarily a function of the skill levels
of the subjects on those tasks. From this it
would follow, then, that performance of the
lower priority tasks (presumably the monitoring



The first analysis was applied to the measures
from all tasks; there was a total of 11 measures
for each of the two conditions of complexity.
The results of this analysis are presented in
Table 5; in this and the subsequent factor load-
ings tables, those loadings that exceeded .60 are
marked with an asterisk for ease of reference.
The correlation matrix on which the analyses
are based is shown in Table 6. _ A total of seven
factors were extracted.

The first factor extracted showed the largest
loadings for the red and green lights under the
simple condition, one of the problem-solving
measures for the simple condition, and the pat-
tern-discrimination time measure under both the
simple and complex conditions. The second
factor showed the largest loadings for the arith-
metic task for both complexity conditions and
for both speed and accuracy. The third factor
showed the largest loading for the meters task
under the simple condition and a slightly smaller
loading for the problem-solving task, percent
measure, during the confirmation phase under the
simple condition. The fourth factor showed
large loadings for only the tracking task under
both the simple and complex conditions. The
fifth factor showed loadings for the problem-

TAMLE 5, Factor Matrix for AIL Heanures After Variax Rotation
Factor Mumber
Meseure
memes 12k
1
a rus
2
5 “08
3
a ‘ee
‘ -
3 ares
5
6 mars
‘
% 33
7
18 a5
A -
fH tf
°
2%
10 #62 a6 ae
2a A 35 m8
n ou «0 ae roe
2 rio <0 <0 008
eigewalue 3.97 1.98 ase 2250
Pouarionce 8 cn Nos

‘ASee Table 4 for code.

solving time measures for both complexity con-
ditions and for both solution and confirmation
phases. The sixth factor showed the largest

TABLE 6. Correlation Matrix for All Measures

Measure
Number* 1 2 3 4 5 6 7 8 9 10 Il 12 13 14 15 16 17) 18 19 20 21
2

3

4

5 08

6 00.20

7 we210 54 235

8 +05 .11 £01 -.10

9 +27) 15.29.16

10 +36 40 655.25 36

iw +30 -.11 -.16 -.16 +20 -.13

12 +35 08. 443.02 +26 65 -.06

13 +39 04.25.02 «19.47 22.62

4 +60 .06 .03 -.07 -O1 217) 24.10 18

15 +83 -,02 -.07 ~.17 +21) 431) 13) 39.26.52

16 --04° 6520.05.25 +07 18 -.12  .02 -.09 -.19 -.07

wv +16 02 -.14 -.12 +28 605 612 =,14 =,11 602 24 06

18 ~-07) .38 -.07) .39 +39 £10.11 -.03 -,08 -.25 -.03  .47 134

19 +21) 405.28 -.21 +03 630-12) 61.39.04 «27.00.00 -.06

20 +32 08.05.04 +68 428 16 21.06.03 «22.08 -.06 25 -.22

21 +21) 404 448.07 +16 663 -.09 653.23) 616.24 -.07 -.23 -.21 41.23
22 +01 -.05 -.07 -.10 -.04 137 -,01 .61 .02 .04 -.04 -,09 117.07) 641 -.21 141 ~.09

*See Table 4


Thirty-nine subjects were tested on two sets
of performance tasks. Each set consisted of
three individual tasks that could be presented
in isolation for a simple-task-performance con-
dition or in combination for a complex-perform-
ance condition. All of the subjects were tested
on both sets of tasks in two sessions of simple-
task performance and two sessions of complex-
task performance.

A factor analysis revealed a single factor
associated with performance of two monitoring
tasks (lights and meters) under the complex
condition, whereas simple performance of these
tasks was represented by two separate factors.
The factor that had high loadings on the moni-
toring tasks in the complex-task situations may
reasonably be interpreted to be reflective of the
existence of a time-sharing ability or skill. At
the levels of complexity, difficulty, and training

13

used in this study, the time-sharing factor was
apparently not important in the performance of
active, more demanding tasks. We suggest that
the best explanation of the findings is that sub-
jects tend to develop a response strategy that
results in their “protecting” their performance
of the active tasks. Thus, the hypothesized
ability is revealed in the ease with which the sub-
jects can shift attention from the active tasks to
the less demanding monitoring tasks.

‘An important methodological implication of
this study is that if research results are to be
generalized to complex jobs such as those found
in aviation operations, then the research tasks
should exhibit an analogous level of complexity.
The findings suggest that selection and screen-
ing programs for complex jobs, such as air traffic
control, would be improved by the use of suitable
measures that tap time sharing as a basic ability.



Technical Report Documentation Page

1. Report No. 2. Government Accession No. 3. Recipient's Catalog No.
FAA-AM-76- 1

4. Title and Subtitle 5. Report Date
AN INVESTIGATION OF TIME-SHARING ABILITY AS A May 1976
FACTOR IN COMPLEX PERFORMANCE 6. Performing Organization Code

[8. Performing Organization Report No.

7 Author's) Alan E, Jennings, M.S.
W. Dean Chiles, Ph.D.

9. Performing Organization Nome and Address 10. Work Unit No. (TRAIS)
FAA Civil Aeromedical Institute
P.O. Box 25082 TT. Contract or Grant No.

Oklahoma City, Oklahoma 73125

T3. Type of Report and Period Covered

12. Sponsoring Agency Name and Address

Office of Aviation Medicine OAM Report
Federal. Aviation Administration
800 Independence Avenue, S.W. 14. Sponsoring Agency Code

Washington, D.C. 20591

15. Supplementary Notes

This research was conducted under Task AM-C-76-PSY-57.

16. Abstract
Thirty-nine men were tested on a total of six tasks; performance was measured
on each task presented individually and on two complex tasks made up of three~
task subsets. The tasks measured monitoring, arithmetic, pattern-discrimination,
tracking, and problem-solving performance, Two separate test sessions were
conducted for each of the individual tasks and for each of the two complex tasks.

Factor analyses were performed on the resultant data to determine if there would
merge a time-sharing ability, defined as a reliable source of variance associated
with complex performance but independent of simple-task performance of the
constituent tasks. A factor was found that showed high loadings for two different
monitoring tasks for complex performance but negligible loadings for these tasks
for simple performance; separate inécependent factors were found for the two
monitoring tasks when they were performed under simple-task conditions. The
monitoring measures appear to possess properties that would be expected of measures
of a time-sharing ability. The findings suggest that a suitable measure of
time-sharing ability would be of value in the selection and screening of candidates
for complex jobs.

17. Key Words 78. Distribution Statement
Complex Performance
Time-Sharing Ability Document is available to the public
Divided Attention through the National Technical Information

Service, Springfield, Virginia 22151.

19. Security Classif. (of this report) 20. Security Classif. (of this page) Bi. No. of Pages | 22. Price
$3.00 PC
Unclassified Unclassified 95 MF

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized



tasks) under the complex conditions would be
primarily a function of the ability of the subject
to shift attention from a higher priority task to
scanning and detecting signals on the lower
priority tasks, The results of the factor analyses
clearly suggest that the skills that are important
in the simple situation are also those that are of
primary importance in the complex situation in
the case of the arithmetic, pattern-discrimination,
and (at least during the initial solution phase)
problem-solving tasks. The results relating to
these active tasks also clearly suggest that the
findings for the monitoring tasks were not simply
some sort of complementary process in which
subjects who were better, for example, on the
arithmetic task simply had more time to scan the
monitoring displays. The orthogonality of the
active task and monitoring task factors suggest
that the skills underlying the performance of
these two types of tasks are independent.

The extent to which the tasks used in this
study may or may not yield “factorially pure”
measures of fundamental abilities is only an
academic concern. These tasks were selected
originally because, and the rationale for their
continued use is, they were judged to measure
behavioral functions of relevance to complex
performance as it is found in operational aviation
systems. The content validity of these tasks has
been confirmed by a large number of operational
personnel. For this reason, it is of no particular
concern that, for example, the pattern-discrimi-
nation-response time measure loads on the same
factor as the red and green lights measure under
the simple condition in the overall analysis and
on the factor on which the meters task loads
under the complex condition in the analysis of
the Task B measures. It will be noted that there
was ambiguity in the loadings of the pattern-
discrimination time measure in the overall anal-
ysis; it had rather large loadings on the first
factor for both complexity levels, but it also had
moderate loadings for the complex-monitoring
(time-sharing) factor, factor 6. It should also
be noted that the measure of accuracy in the
problem-solving task, confirmation phase, is
rather unstable, presumably because there is very
little variance on this measure; most subjects
make very few errors in entering the second
solution.

12

Although this type of study requires repli-
cation before final acceptance of the validity of
the concept of time-sharing is warranted, there
are, nonetheless, some important implications of
these findings for research methodology. The
findings strongly support an argument we have
presented elsewhere:?*°° if the goal of a re-
search effort is generalization to complex opera-
tional tasks, then the tasks used must involve an
element of complexity analogous to the time-
sharing demands characteristic of the target
operational situation.

In this regard, the “time-sharing ability”
identified in our study is clearly related to the
“divided-attention ability” referred to by North
and Gopher® in interpreting their results on
the prediction of success in flight training. The
findings are also quite compatible with the argu-
ment that complex tasks are more likely to be
sensitive to environmental and procedural vari-
ables than are simple tasks. The findings suggest
that selection and screening programs for com-
plex jobs, such as air traffic control, might very
well be improved by the incorporation of suitable
measures that tap time sharing as a basic ability.
Furthermore, these findings provide indirect.
support for the use of secondary tasks to assess
the workload properties of primary tasks.

Vv.

It has long been held that people differ with
respect to their ability to master complex jobs.
In the operational context, this ability is often
referred to as though it represented variations
in the facility with which people can simul-
taneously perform two or more tasks in a “time
shared” manner. However, the existence of such
an ability has never been quantitatively verified.
This study attempted to determine whether such
an ability could be isolated that is specific to
proficiency in complex performance. For the
purpose of this study, and within the context of
the tasks employed, time-sharing ability was de-
fined as “a reliable source of variance that con-
tributes to performance of complex tasks but is
independent of simple task performance of the
constituent tasks.”

Summary and Conclusions.


reason to believe that task elements involving
disparate behavioral functions would also exhibit
such properties.

The applicability to our problem of the work
typified by Conrad on dial monitoring suffers
in that the skill level on one task element has a
very direct effect on the apparent difficulty of
performing the second task. Thus, the Conrad
findings are compatible with the time-sharing-
ability hypothesis, and Bartlett’s concept of tim-
ing in skill is closely allied, but the results of
those studies cannot be held to substantiate the
hypothesis.

Thus, we see that although the existence of a
time-sharing ability is widely assumed in dis-
cussions of job requirements, definitive quantita-
tive evidence of such ability is lacking. The
methodology of factor analysis offers one ap-
proach to the development of the desired evi-
dence. Within that context, the hypothesized
time-sharing ability would be defined as a reliable
source of variance that contributes to perform-
ance of complew tasks but is independent of
simple-task performance of the constituent tasks.
This is the definition of the concept time-sharing
ability that we propose to use in this paper.
The specific way in which this would be revealed
in a factor analysis would be by the finding of
an orthogonal factor with large loadings for
some tasks (measures) when performed as a
part of a complex task but small loadings on
these same tasks (measures) when performed
individually. This factor should also show large
loadings on other tasks performed as a part of
a different complex task.

The purpose of this study is to examine two
different complex tasks by using the factor ana-
lytic method to determine whether any of the
performance measures exhibit the above described
statistical properties that could be construed as
evidence of a time-sharing ability.

IL Method.

A. Apparatus. In this study, the testing was
carried out by using the Civil Aeromedical In-
stitute (CAMI) Multiple Task Performance
Battery (MTPB). This test battery was de-
signed to test and measure a variety of skills
judged to be important to aircrew performance

but it was not intended to be a simulator of
any particular system.t The MTPB consists of
five subject testing panels and associated pro-
gramming and scoring circuitry. The panels
contain the displays and response controls for
six different tasks, each of which may be pre-
sented in isolation or in any combination of
tasks. The six tasks are very briefly described
in the following sections; see Chiles, Alluisi, and
Adams‘ for a more complete description.

1. Warning lights. This is a choice reaction-
time task involving monitoring of five green
lights and five red lights. Under each light is a
pushbutton switch. The green lights are nor-
mally on and the red lights are normally off;
the subject is structed to push the button under
the light whenever a light changes state. Signals
were introduced at randomly selected intervals
with a mean intersignal interval of 30 seconds.

2. Meter monitoring. This task involves mon-
itoring. four meters mounted across the top of
the subject panel. Normally, the meter pointers
are moving at random around a mean vertical
position. The subject responds to a shift in the
mean position of the pointer by throwing the
associated lever switch in the direction of the
deflection. The signals are introduced at ran-
domly selected intervals, with a mean intersignal
interval of 1 minute.

3. Mental arithmetic. In the arithmetic task,
the subject is required to add two numbers and
substract a third number from the sum of the
first two without using paper and pencil. The
problem elements were numbers from 10 to 99,
selected with the restriction that neither digit of
the third number should be identical to the cor-
responding digit of either of the first two num-
bers. The arithmetic task is machine paced, and
a new problem is presented every 20 seconds.
Both response time and accuracy are measured
on this task. Accuracy is determined as a per-
centage of all problems presented.

4. Pattern identification. The display for the
pattern identification task is a screen on the
lower left of the subject’s panel. This screen
consists of a six-by-six matrix of close-butted
lights covered by a translucent panel. A stand-
ard pattern is presented for 5 seconds followed
by 2-second presentations of two comparison


AN INVESTIGATION OF TIME-SHARING ABILITY AS A
FACTOR IN COMPLEX PERFORMANCE

I. Introduction.

People concerned with training personnel for
complex jobs have long recognized that indi-
viduals differ with respect to the ease with which
they are able to master multiple-element jobs and
there are some complex jobs that some people can-
not master. As stated by Chiles, Jennings, and
West’ on the basis of discussions with instructors
at the Federal Aviation Administration (FAA)
Academy, a number of trainees are eliminated
from the air traffic controller training program,
not because they lack specific academic or other
skills, but because they are deficient in the con-
current performance of the variety of tasks of
which the controller’s job is composed. An anal-
ogous belief has been expressed by flight in-
structors about flying trainees.

Underlying these notions is the implicit hy-
pothesis that the acquisition of skill on a complex
task, considered in its entirety, somehow rests on
the learning of task features that “emerge” when
the component tasks are combined to produce the
complex task. These notions also assume that
the emergent features of a complex task are not
only quantitatively but also qualitatively differ-
ent from the sum of the requirements of the
individual tasks. Thus, although the supporting
evidence comes largely from anecdotal observa-
tion, the wide acceptance of the position that
there are abilities (or, perhaps, an ability)
specific to complex performance provides one
reason for seeking to determine if, in fact, such
a phenomenon exists and can be quantified.

Another line of reasoning also suggests the
possible existence of such an ability. Knowles.
in considering the problem of workload measure-
ment, describes a technique in which the per-
formance levels maintained on auxiliary or
secondary tasks are used to indicate the level
of workload imposed by the performance of a

primary task. In discussing this technique,
Senders’* lists several assumptions on which this
methodological approach to workload measure-
ment rests. Two of those assumptions are directly
relevant to the purposes of this study: (1) the
operator is a single-channel system, and (2) the
channel has a fixed capacity. We interpret the
concept of a single-channel system in this context
to mean that an individual can do only one thing
at a time. (For present purposes we will dis-
regard the fact that some tasks can be learned to
the extent that performance of such tasks can
proceed more or less autonomously.) With this
interpretation, it follows that if the operator is
given two or more tasks to do “simultaneously,”
attention is shifted back and forth between tasks
at a rate intended to insure adequate levels of
performance on the individual tasks. The idea
of a fixed-channel capacity simply means that
there is a limit to the number of things the op-
erator may be asked to do within a given set of
time constraints without some degradation of
performance on one or more individual tasks.

The secondary task approach was used by
North and Gopher* in a study of performance
in a divided attention task as a predictor of
success in flight training. This study required
subjects to perform a one-dimensional compen-
satory tracking task and a digit-processing re-
action time task both individually and in
combination. They found that measures of both
tasks taken during complex performance dis-
criminated reliably between “high-potential” and
“low-potential” trainees, whereas measures taken
during performance of the tasks singly did not.
North and Gopher interpret their results as re-
flecting differences in the ability of the subjects
to distribute their attention between the two
tasks.