Fleishman AP 1975 - Towards a Taxonomy of Human Performance

8/13/2019 Fleishman AP 1975 - Towards a Taxonomy of Human Performance

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important correlates of learning, criterion perform-ance levels, and individual differences and shouldbe applicable to laboratory tasks and to tasks en -countered in on-the-job situations.

Although the need has been recognized (e.g.,Fit ts, 19 62 ; Melton & Briggs, 19 60 ; Mil ler , 19 62 ) ,it is only recently that concerted attempts havebeen made to explore more intensively some of theissues and alternatives in taxonomic developmentin psychology and to proceed on an empirical basisin the evaluation of these alternatives. I wouldl ike to reviewa program of research that has madeat least some beginnings in this area.

Specifically, this article discusses briefly somegeneral problems in the development of taxonomicsystems applicable to descriptions of human per-formance an d tasks. Some alternative approachesandp rovision al classification schemes developed aredescr ibed. Then, some attemp ts to evaluate theutility and validity of these systems are reviewed.Some Taxonomic Issues Early in our research program we reviewed theliterature bearing on taxonomic approaches andconcepts in the behavioral sciences as well as re-lated developments in other sciences (Cham bers,1 9 7 3 ; Farina, 1 9 7 3 ; Theologus, 1973; Wheaton,1 9 7 3 ) . We cannot prov ide the details of this re-view here, but we can indicate some issues thatstood out.PURPO SE OF CL ASSIFICAT ION

We need to be clear on why we are interested intask classification. T he question is important be-cause individuals who attem pt su ch classificationusual ly do not view the development of such asystem as an end, in and of itself. Rather, theyview the system of classification as a tool to in-crease their ability to interpret or predict somefacet of human performance (Cotterman, Note 1 ).This goal is to be achieved by seeking relationshipsbetween that which is classified (e.g., tasks, pro-cesses mediating performance) an d selected vari-ables of interest to a particu lar investigator (e.g.,distribution of practice, training regimens, environ-mental stressors).We canelect to develop a system of classificationhaving u t i l i tyfor a limited area (e.g., the classifica-tion of tasks with respect to which certain trainingmethods are found most effective in promotinghigh levels of task performance), or we may look

for a system from which a variety of applicationsmay stem. For example, we might first classifytasks an d only then relate stressors, learning pr in-ciples, training regimens, etc., to each class of tasksin this system. In this case, classification is de-signed from inception to be general and to serve avariety of users by aiding in the interpretat ion,prediction, or control of a broad range of humanperforma'nce phenomena.With respect to systems having rather specificapplied objectives, classifications dealing withtraining are most num erous. A num ber of investi-gators (Anne t t & D uncan, 19 67 ; Gagne', 19 62 ;Miller, 1966 ; Co t t e rman ,Note 1; Eckstrand, Note2 ; Folley, Note 3 ; Stolurow, Note 4 ) have calledfor systems intended to pe rmi t th e classificationo ftasks into sets of categories that are relativelyhomogeneous with respect to principles of learn-i n g , training techniques, etc. B loom (19 56) hasat tempted to develop a similar taxonomic systemfor th e educational comm unity. However, fewempirical evaluations of such systems have beenattempted.Where broad task classification systems are de-veloped as autonomous structures, which are onlysome time later to be applied to other variables,the classification exercise is an integral step in the.development of theory. The resul tant system pro-vides a consistent conceptual framework, the ele-ments of which eventually are to be used in theinterpretat ion or predict ion of human performance.One is not precluded from seeking specificapplica-tions for such classifications. The point is that aspecific application does not dictate the composi-tion and st ructure of\the system.Learning theorists have engaged in these pur-suits (see Melton, 1964), but as yet there is nocomprehensive system that effectively compares,contrasts, an d interrelates the various human learn-ing "categories."2 Consequently, we have beenunable to formulate a general theory of learningwhich allows dependable generalizations of learn-ing principles to particular classes oftasks. Gagne( 1 9 6 4 ) has been the most systematic in the specifi-cation of general learning categories" and theirpotential implications for ordering principles oflearning.

\1T he au thor is indebted to George W . Wheaton for hiscont r ibut ions to the conceptual phase of this research.2For a recent attem pt in the area of instru men tal con-ditioning, se eWood ( 1 9 7 4 ) .1128 D E C E M B E R 1 9 7 5 A M E R I C A N P S Y C H O L O G I S T


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The ability theorists also have attempted toisolate basic dimensions of behavior on which ageneral theory of human performance might bebased. G u i l fo rd ( 1 9 6 7 ) and I (Fleishman, 1964)have been perhaps th e most explicit in attemptingtointegrate th eability dimensions identified withinthe general framework of experimental psychology.Thus, myassociates and Ihave conducted researchrelating ability dimensions identifiedin research oni nd iv idua l differences tostages of learning (Fleish-m an & Hempel, 1954, 1955), stimulus-responserelations (Fleishman, 1957), skill retention (Fleish-m an & Parker, 19 ,62 ) , part-whole task relations(Fleishman, 1965),effects ofdrugs (Elkin, Freedle,Van Cott, &Fleishman,Note 5), etc. This varietyof studies was possible because we first attemptedtodevelop a standard and consistent classificatorystructure ofhuman abilities an d then attempted totest the feasibilityof this framework across differ-ent areas ofhuman performance. Thisapproach isexamined later in this article.C O N C E P T U A L BASES O F C L ASSIF IC ATIO NAfter the consideration of the purposes of taskclassification, oneneeds to examine thedescriptivebases of taxonomy. A concern here is with thedefinit ion an dmeaningof theconcept task.

Definition of the task. Task definitions varygreatly with respect to their breadth of coverage.At one end of this dimension ar e definitionsthatview the task as the totality of the situation im-posed on the subject. For example, this definitionwould consider ambient stimuli an integral partof the task. T he other end of this dimension isrepresented by definitions that treat a task as aspecific performance. In this case, for example,on e task couldbe to depress the button wheneverthe light comes on. Suffice it to say that verydifferent concepts m ay underlie definitions fallingat either end ofthis dimension.

This diversity of opinion is also reflected in theextent to which tasks aredefinedas being externalto or an intrinsic part of the subject. Some defi-nitions take into account th epropensity of subjectsto redefine an imposed task in terms of their ow nneeds, values, experiences, etc. In the grossestsense, these definitionstreat a task as whatever itis the subject perceives the task to be. Other in-vestigators (e.g., Hackman, 1970) define the taskin terms of stimulus materials an d instruction tothesubject. Theinstructions indicatethe activitiesto beperformed with respect to thestimuli and the

goals to be achieved. Merely giving a person abroken radio wouldnot beassigninghim a task.Most investigators treat tasks as consisting of

interrelated processesand activities. For example,Miller (1966) stated that A task is any set ofactivities, occurr ingatabout th esame time, sharingsome common purpose that is recognized by thetask performer (p. 11).

O ur conclusionwas that we should not debateabou t th e definit ion of a"task" as ifonly on ewerepossible. Rather, wemustadoptordevelopa defi-nition that willpermit th e derivation of termsthatrel iablydescribe tasks anddistinguish among them.These derived terms can provide the conceptualbasis for classification,as w eshall se e later.

There appear to be four major conceptualbasesunder l y ing current task description and classifica-tion.

Behavior description approach In this con-ceptual approach to task classification, categoriesoftasks are formula ted based on observations anddescriptions of what operators actually do whileperforming a task. Most often, overt behaviorssuch as dial setting, meter reading, and solderingar e employed. In spite of the large number ofterms available for this approach to task descrip-tion, relatively fe w descriptive systems have beendeveloped that are based exclusively on operatorbehaviors or activities. McCormick (Note 6) hasemployed this descriptive approach in his studiesof worker-oriented jo b variables (e.g., handlingobjects, personal contact withcus tomers ) ,andFine(Note 7) has used this approach as a basis fordescr ibing worker funct ions in terms of handling( t h i ng s ) , analyzing (data), and negotiating (withpeople).

Behavior-requirements approach A second ap -proach to "task" description emphasizes the cata-logingofbehaviors that ar eassumed to berequiredin order toachieve criterion levels ofperformance.The human operator is assumed topossess a largerepertoire ofprocesses that will serve to intervenebetween stimulus events and responses. There hasbeen a great deal of interest in codifying the re-qu i r ed intervening processes (functions, behaviors,e tc . ) , cataloging tasks in terms of the types ofprocesses required fo rsuccessful performance, an dthen relating to particular training methodologiesth e types of tasks that emerge (see Annett &Dun-can, 1967; Gagne & Bolles, 1963; Miller, 1966;and Eekstrand,Note 2 ) . Typical of thefunctionsused todifferentiateamong tasks ar escanning func-

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tion, short-term memory, long-term memory, de-cision making, and problem solving.

Abili ty requirements approach. The third con-ceptual basis for the description an d classificationof tasks, which we .call the ability requirementsapproach (e.g., seeFleishman, 1 9 7 2 ) , is in manyrespectssim ilar to the behav ioral requ irem ents con-cept. Tasks are to be described, contrasted, andcompared in terms of the abilities that a given taskrequires of theoperator. These abilities are rela-t ive ly end uring at t r ibu tes of the individual per-forming the task. The assumption is made thatspecific tasks will require certain abilities if per-formance is to be maximized . Tasks requ ir ingsimilar abilities would be placed within the samecategory or wouldbe said to be similar.T he abilit ies approach differs from th e behaviorrequi rements approach pr imari ly in terms of con-cept derivation an d level of description. T heability concepts are empirically derived throughfactor-analytic studies and are treated as morebasic un its than the behavior functions.

Task characterist ics appro ach. A fourth ap -proach differs from th e preceding approaches interms of the type of task description that is at-tempted . Th is approach (see Farina &Wheaton,1 9 7 3 ; Hackman, 1970) is pred icated on a defini-tion that treats the task as a set of conditions thatelicit perform ance. These conditions are imposedon the indiv idu al and have an ob jective existencequ i te apart from the activities they may trigger,the processes they may call intoplay,or the abili-ties they may req uire . H aving adopted this pointof v iew, app ropria te descriptive terms are thosethat focus on the task per se. T he assumption ismade that tasks can be described and differentiatedin t e rmsof intrinsic, objective properties they maypossess. These prop erties or characteristics mayperta in to the goal toward which the operatorworks, relevant task stimuli, instructions, pro-cedures, or even to characteristics of the re-sponse(s) o r the task content. T he obvious prob-lem is the selection of those task components thatare to bedescribed, aswellas the particular termsor parametersby means of which description is tobeaccomp lished.

We have seen that tasks can bedefined in severalways, part icularly in regard to the scope of defini-t ion; the extent to which tasks may be treated asobjective entities, clearly apart from the operatorswho perform them; and the extent to which tasksare viewed as processes or structures.

Some M ethodological IssuesWithin the scope of this article I cannot dwellonthe m ore general prob lem s of how to proceedwith classification. I shall discuss instead a n u m-ber of criteria fo r evaluating such systems.

T he requ i rement fo r operational definition ofte rms becomes increasingly critical if the systemis to be used by a broad rang e of specialists. T hedescript ive terms may be completely unfamiliar tomany of these individuals, or even too familiar asin the case of the popular terms decis ion makingand problem solv ing. Although homage is paid tothe need for operational definit ions, few investi-gators have actually generated such definitions.Also, as a min imum requ i rement, the descriptorsemployed in the differentiation an d classificationoftasks must permit nominal sca l ing. That is, aj u d g e mu s t at least be able to ascertain whethereach descriptor applies or does not apply to thepart icular task beingexamined .Also, descriptors must be defined and treatedwithin a system of measurement so that they canbe reliably evaluated. Another criterion requiresthat classes within the system be mutually exclu-sive and exhaustive.

A major criterion isthat classes are desired thathave specific behavioral implications, as with theinterest of Annet t an d Duncan ( 1 9 6 7 ) in classify-ing "tasks"so that each category or class of taskshas specific training req uire me nts associated withit. U ltim ately , of course, any behavioral classifi-cation scheme must make the "match" betweenspecific categories an d behavioral effects. T hedegree to which the "match"can be madewillde-te rmine the pred ictive power of the system . At onelevel, a statement might concern whether or nota part icular environmental variable would affectperformance. At anothe r and more sophisticatedlevel it might be possible to predict the directionan d magni tude of the effect.

A final set of criteria includes efficiency andutil i ty . T he taxonomy should promote communi-cation among its users, be they researchers in dif-ferent areas or specialists who mus t use researchfindings in applied settings.

In our own program we found it useful to layou t these general issues, which we have elaboratedelsewhere. In no sense can we say that our sub-sequent efforts met the rigorous standards calledfor. H owever, they at least prov ide indications ofwhere we fell short an d allow for successive itera-tions toward meeting these criteria.

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a. COMPLEX COORDINATION b>ROTARYPURSUITFigure 1. Examplesof tests foundvalidforpilotselection

In theremainderof this article, I illustrate somedevelopments with two provisional systems, onebased on the ability requirements approach andanother on the task characteristics approach Iconclude with some attempts to link these twoapproaches.

The Abilities ApproachMuch of what is known today about the categori-zationof human skills, at least that which is basedon empirical research, comes from correlational andfactor analysis studies. Such correlational studiesare typically carried out in the psychometric tradi-tion, and until recently, little attempt has beenmade to integrate the ability concepts developedthere into the more general body of psychologicaltheory. Here the fact of individual differences isexploited to gain insights about common processesrequ i red to per form different groups of tasks.Abilities are defined by empirically determined re-lations among observed separate performances.

It has been my feeling, over many years, thatresearch using combinations of experimental andcorrelational methods, properly conducted, can leadto the development of a taxonomy of human per-formance which is applicable to a variety of basicand applied problems and that ability conceptsmayprovide an integrativeframework.

Elsewhere (e.g., Fleishman, 1962) I have elabo-rated on the conceptsofability and skill. Br ief ly ,abilityrefers to amoregeneral capacityof theindi-vidual, related to performance in a variety of hu-man tasks. For example, the fact that spatialvisualization has been found related to perform-ance on such diverse tasks as aerial navigation,

blueprint reading, and dentistry makes this abilitysomehowmore basic.

My interest in this area began when I was re-sponsible for developingpsychornptortests to selectpilots for the Air Force. Figure la shows a testfound valid for pilot selection. The test requiressimultaneous manipulations of stick and rudderpedajs and has a great deal of facevalidity. How-ever, Figure Ib shows another test found equally

^ valid. This test, th e familiar pursuit roter, ha slittle face validity. The subjectisrequired to keepa stylus tip in contact with a moving target. Myfeeling was that we needed basic research on thedimensions of perceptual-motor ability to identifywhat factors in these tests were common to thecriterion performancein more complex tasks suchas piloting.A nextensive series of interlocking experimental-factor-analytic studies, which we have conductedover many years, has attempted to isolate andi dent i fy theability factorscommonto awide rangeof perceptual-motor performances. Essentially,this is laboratory research in which tasks arespecifically designed or selected to test certainhypotheses about the organization of abilities in acertain range of tasks. The experimental batteryof tasks is administered to several hundred sub-jects, and the correlation patterns are examinedthrough factor analysis methods. Subsequentstudies tend to introduce task variations aimed atsharpening or limitingour ability factor definitions.

Through our investigation of a wide range ofseveral hundred different tasks, we have been abletoaccount forperformancein terms of a relativelysmall number of abilities. The following displaygives the labels of11perceptual-motor factors that

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a. Single DimensionalPursuit

b. MotorJudgment

n nU. Stages In asample Item of the stimation of Relative VelocitiesTest.

c.Visual CoincidenceFigure 2 . Examples of tasks used to evaluate thegenerality an d limitations of rate controlability. (From On the R elation Between Abilities, Learning, an dHuman Performance by Edwin A . Fleishman,Ameri-ca n Psychologist, 19 7 2 , 27 ,1017-1032. Copyright1972by the American Psychological Association. Reprintedby permission.)

consistently appear to account for the commonvariance in such tasks. In subsequent studies,defini t ions of these abilities an d their distinctionsfrom one another have become more clearly de-lineated. I will not define all of these here, butextens ive definit ions of each ability exist with illus-trations of the tasks that best measure them(Fleishman, 1964).

P E R C E P T U A L - M O T O R ABILITIESControl precisionMult i l imb coordinationResponse orientationReaction timeSpeed of arm movementRate control(timing)Manual dexter i tyFinger dexterityArm-hand steadinessWrist-fingerspeedAiming

Simila r studies have been carried out in the physi-cal proficiency area, and nine factors have been

ident if ied that account for performance in severalh u nd r e d physical performance tasks:

P H Y S I C A L PROFICIENCY ABILITIESEx tent flexibi l i tyDy namic flexibi l i tyStatic strengthDynamicstrengthExplosivestrengthTrunkstrengthGrossbody coordinationEquil ibriumStamina

Perhaps it might be usefu l to provide some ex-amples of how one examines the generality of anability category and how one defines its limits.The specification of an ability category is anarduous task. The definit ion of the rate controlfactor mayprovide an illustration.

In early studies it was found that this factorwas common to compensatory tracking, for ex-ample, keep a horizontal line in the center of thedial, by compensatory movements of a control, aswell as to following pursuit tasks, for example,keep a gunsight in line witha moving target (seeFigure 2a). To test the generality of this factor,f u r th e r tasks were developed to emphasize re-sponses to stimuli moving at different rates, wherethe tasks were not conventional tracking tasks.For example, Figure 2 b showsa task in which thesub jec t had to time his movements in relation todifferent stimulus rates, but he did not have tofollow a target or to compensate for the target'smovement. The factor was fo und to extend tosuch tasks.

Later studies attempted to discover if emphasison this ability is in judging the rate of the stimulusas distinguished from ability to respond at theappropriate rate. Thus, Figure 2c shows a taskdeveloped where the only response was the tim-ing of button pressing in response to judgmentsabout the location of stimuli moving at differentrates. Performanceon this task did not correlatewith other rate control tasks. Finally, severalmotionpicturetasks,such as the one in Figure 2d,were adapted in which the subject was required toextrapolate the course of an airplane moving acrossa screen. The only response required was on anIBM answer sheet. (Atwhat point did the planesmeet? Points 1, 2, 3, 4, or 5?) These movingpicturetests involving only judgments about stimu-lus rate did not correlate with the group of tasks



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previously found tomeasure"rate control." Thus,ou r definition of.this rate control ability was ex-panded to include measures beyond tracking andp u r s u i t tasks, but was restricted to tasks requiringthe timing of an actual adjustive movement to thechanging stimulus.

A similar history can besketchedforeach abilityvariable identified, and a great number of principlesrelating task characteristics and abilities measuredcan now bedescribed. For example, weknow thatmult i l imb coord inat ion is common to tasks involv-in g simultaneous control actions of twohands, two

feet , or hands and feet, but some feedback indi-cator of coordination is required. Furthermore,this factor does not extend to tasks involving thebody inmotion, such as in athletic tasks. And weknow that fast reaction times are general to audi-tory and visual stimuli, but as soon as more thanone stimulus or response is involved in such tasks,the ability required shifts to response orientation.A nd it isusefu l to knowthat there are four primarystrength factors, not confined to muscle groupsbut dependent on specific task requirements (seeFleishman, 1964).

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Figure 3. Percentage of variance represented by loadings on eachfactor at different stages of practice on the discrimination reaction timetask. Note: Percentage of variance is representedby the size of theshaded areas for each factor. (From "The Relation Between Abilitiesan d Improvement with Practice in a Visual Discrimination ReactionTask" by Edwin A . Fleishman and Walter E . Hempel , Jr., Journal ofExperimental Psychology, 19SS, 49 , 301-312. Copyright 1955 by theAmerican PsychologicalAssociation. Reprinted bypermission.)

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Figure 4 . Comparison of learning curves on the discrimination reaction time task for groups scoring high and low on different ability test measures. (From "The Relation B e-tween Abilities and Improvement with Practice in a Visual Discrimination Reaction Task"by Edwin A . Fleishman an d Walter E . Hempel , Jr., Journal of Experimental Psychology,19S5, 49 ,301-312. Copyright 1955by the American Psychological Association, Repr in tedby permission.)

A B I L I T I E S P R E D I C T I V E O F L E A R N I N GOur subsequent work (e.g.,Fleishman, 19S7, 1960;Fleishman &Ellison, 1969; Fleishman &Hempel,1955 ) attempted to use the ability concepts de-ve loped to predict various learning measures andotheraspects oftask performance, with encouragingresults. The basic method is to give subjects abattery of reference ability tests and then havethem train on a criterion task. Loadings of per-

formance achieved at various states of learning,on the factors denned by the ability factors, arethen examined. In general, these studies, with agreat variety of practice tasks, show that (a) thepa r t i cu la r combinationsof abilities contributing tope r fo r m ance on a task change as practice on thistask cont inues ; (b) these changes are progressiveand systematic and eventually become stabilized;(c) in perceptual-motor tasks, for example, the

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contribution of nonmotor abilities (e.g., verbal,spatial) mayplay arole early inlearning, but theircontribution decreases systematically with prac-tice, relative to motor abilities; and finally (d)there is also an increase in a factor specific to thetask itself not common to the more generalabilities.Figure 3 illustrates one set of findings for a taskinvolving the manipulation of different switches inresponse to different patterns of stimulus lights.Figure 4 depicts these same results in termsoflearningcurves. Wherethe total groupofsubjectsis stratified into those high and low on one ability(e.g., spatial), their learning curves for this taskconverge as practice continues. When the samesubjects are stratified according to high and lowscores on another ability (e.g., reaction time),their learning curves.diverge. Our work relating

abilities to more general performance phenomenaled us to feel that this kind of taxonomic systemmight be worth f u t u re development. For one re-viewofthis work,seeFleishman (1967a).U SE O F TASK STANDARDI ZED BYABILITY MEASURED

A s one illustration, we have carried out a numberofstudiesinwhich"standardized tasks" represent-ing such ability dimensions have been used inlaboratory studies of factors affecting human per-formance. For example, we have observed theeffects of a variety of drugs and dosages on mea-suresof avariety ofreferenceabilitytasks. Thesemeasures sample the perceptual, motor, sensory,and cognitive areas.

HOURS SINCE DRUG HOURS SINCE DRUG7 8 9 1 2 3 4 8 9

MEMORYSPAN

TWO-HANDCOORDINATION

Z= 01 2 --3 --4 --5 -

VISUALACUITYF A R )

Figure 5. Effects of a given dosage of scopolamine in degradingper-formance onseveral different tasks involving different abilities. (Adaptedfrom Performan ce Assessment B ased on an Empirically Derived TaskTaxonomy by Edwin A Fleishman, H u m a n Factors , 1967,9,349-366.Copyright 1967by the H u m a n Factors Society. Rep rinted bypermis-sion.)AMERICAN PSYCHOLOGIST DECEMBER 1 9 7 5 1135


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SESSION 2 SESSION 3Figu re 6. Ad justed mean react ion t ime at eachblock of trials on the react ion time task (Session 2 =random 85-db. noise ; Session 3=pat terned 85-db.no ise ) . (F r om Effects of Interm it tent , Mo derateIntensi ty Noise St ress on Human Pe r formance byGeorge C. Theo logus , George R. Wheaton , and EdwinA. F le i shman, Jour na l of Applied Psychology, 1 9 7 4 ,

59 539-547. C opy r i gh t 1 9 74 by the American Psy-chological Associat ion. Reprinted by permission.)Figure Sgives a fewillustrationsoftheseevents

for agiven dosage of the d rug scopolamine (Fleish-man , 1 9 67 b ; E l k in e tal.,N ote S) . As can be seen,we ar e ge tt ing differential effects; that is , someabi l i t ies within each area were more affected thanothers. The absolute performanc e decrement, t imeto reach max imumeffect, an d t ime to recover de-pended on the abil i ty measu red. For examp le, thephysical abil i ties of dynamic flexibil i ty -and ex -plosive strength showed only sl ight effects, whereasth e motor abil i ties of mul t i l imb coordinat ion an dfinger dexter i ty showed marked effects. Such find-

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SESSION 2 SESSION 3Figure 7 . Ad jus t ed mean in t egrated e rror at eachblock of trials on the rate control task (Session 2=random 85-db. noise ; Session 3 = pat t e rned 85-db .noi se ) . (F r om Effects of In te rmi t t en t , ModerateIn tens i t y Noise S t ress on Hu man Pe r formance byGeorge C . Theologus, George R . Wheaton , an d EdwinA. F l e i sh man ,Jour na l of Applied Psychology, 1 9 7 4 , 59,539 -547 . C opy r i ght 1 9 7 4 by the American Psychologi-ca l Assoc ia t ion . Rep r in t ed b y permission.)

ings indicate why the category motor skill" istoo broad . Similar f indings have been reported forother drugs (Baker , Ge is t , & Fleishman, Note 8).The goal here is to develop what might be called b ehavioral tox icity profi les fo r different classes ofdrugs .

We have also conducted similar studies on theeffects of different noise stressors (T heologu s,Wheaton, & F le ishman, 19 74 ) . T he rationale ofthis program isthat different components of humantask perform ance wi ll be affected differently as afunctionof the type and levelofstressor,and thatmeasurement of changes in these components wil lp rov ide quantitative evaluations of the disruptiveeffects of the stressor and of man's vulnerabil i tyto it.We used a device, shown in Theologus et al.( 1 9 7 4 ) , designed to measure 10 of the differentpsychomotor abil i ties identif ied. W e found thati n te rmi t t en t , moderate - intens i ty noise (85 db . ) i smore likely to affect performance on tasks empha-sizing some of these abil i ties than others. Fig ure6 shows the signif icant effect of the random inter-mi t ten t noise on the mean reaction time and theabsence of any effect on this measure for thepatte rned noise of the same intensity. H owever,Figu re 7 shows that on the rate control task( t r a c k i n g ) , no effect of either type of noise isdemonst r a ted . Figu re 8 i l lus tratesthat for a time-shar ing task there is no noise effect at first, butth e effects appear to be cumulat ive dur ing con-t inued expo sure. T he results are i l lustrative ofdifferential effects according to task category.O ur feeling was that improved generalizations ofresearch da ta migh t be possible if careful specifi-cations of our task categories were uti l ized, withabil i ty concepts holding the key.M E T H O D S O F E S T I M A T I N GA B I L I T Y R E Q U I R E M E N T SAnother phase of our program ha s involved exten-sivereviewsof the factor-analytic abil i ty literature.O ne of the s t r i k ing findings in this review was thediff icul ty in moving from the factor analysts' defi-nition to a more operational de finition which couldbe used rel iably by observers in estimating theabi l i ty r e qu i r e me n t sof a new task. A large effortin ou r program involved th e successive refinementof such definit ions to improve the ut i l i ty of theseconcepts in descr ibing tasks . A host of differentre l iab i l i ty s tud ies have been condu cted in whichtask d escriptions have been exam ined by indi-



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M u l t i l i m bCoor d i n a t i on

Speed of ArmM ovemen tSimpleRea c t i onTime

Figu re 1 0. Portion of a tentativ e bin ary flow diagram used to make decisions about therelevance of selected abilities for per formin g part icu lar tasks. (From Development of aTaxonomy of H u m a n Performance: A Review of the Third Year's Progress [AIR Tech,Rep. 72 6-T PR3 ] by Edwin A. Fleishman and Robert W. Stephenson.)E V A L U A T I N G T H E U T I L I T Y O F ABILITYR E Q U I R E M E N T S IN C L A S S I F Y I N G T A S K SO ne way toevaluatea taxonomicsystem is in termso f its cap acity to organ ize a portion of the datafound in the hum an performance l i t e ra tu re . In onestudy (Levine, Romashko, &Fleishman, 19 73 ) ou robjective was to examine the feasibility of struc-tu r ing an area of literature according to the abili-t ies required for task performance. T he area ofhuman performance selected fo r examination wasthat of sustained attention in monitoring tasks, inthe so-called vigilance liter atur e. Vigilance is gen-erally considered to involve a change in the detec-tion of infrequent signals over prolonged periodso f time. O ur idea was to examine the tasks usedin these previous studies, to rate them in terms ofthe abilities taxonomy, using our scales, and toclassify the studiesi n termsof the abilities requiredby the tasks used. T he next step was to examinethe data within and between these categories oftasks to see if improved generalizations could bemade about factorsaffecting vigilance performance.T he vigilance area was selected for study forseveral reasons. First, while a variety of differenttasks have been used in previous vigilance research,the range of tasks is not as great as in many otherareas. Consequently, th e number of differentabilities involved is not likely to be large, and this

in tu rn would reducethe complexity of the evalua-tion. Second,a reasonably large number of studieshave been reported on the effects of several selectedindependent variables on vigilance performance,and it is important that enough studies be avail-able to prov ide a sufficient number of data pointswithin task categories. Th i rd , a common dependentmeasure is employed in nearly al l vigilance studies,that is, detection accuracy.The stu dy w as designed to examine (a) the ex-tent to which performancein vigilance tasks couldbe differentiated on the basis of abilities and (b)whether improved generalizations about the effectso f independent variables in vigilance performancewerepossible as a result of such task classifications.Four abilit ies were found to be required for thedifferent task performances in this area, with two,perceptual speed and flexibility of closure, pre-dominat ing .F igure 11 provides some illustrative results whenth e data fo r such tasks were partitioned accordingto levels of an independent variable (whether thesignals were auditory, visual, or b o th ) . We havepl otted pe rcent of target detections at 30 -minu teintervals throughout the first 180 minutes of thevigilance task. It can be seen that regardless ofwhether the abili ty category was percep tual speedor flexibility of closure, overall performance was

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superior under auditory conditions than undervisual conditions. Furthermore, the visual plusauditory condition was markedly superior in num-ber of targets detected to either auditory or visualpresentation.

The important results show that the funct ionsobtained vary with the type of task as defined byou r ability ratings. For the auditory condition,perceptual speed tasks showa severe performancedecrement with time in the task. On the otherhand, there was a very small performance decre-ment for f lexibi l i ty of closure tasks within the first90 minutes, and an increment in performance ac-cu racybeyond that time. For the visual condition,the func t ion describing performance with time inthe task for perceptual speed studies was similarto that obtained for the auditory condition. How-ever, for tasks requiring f lexibi l i ty of closure, th efunct ion in the visual condition was almost thereverse of that for the auditory condition.

Simi lar analyses were made for other variables,such as signal rate. Although the data providedare preliminary, and in several instances functionsare based upon only a few data points, it wasnevertheless possible to infer that the effects of theindependentvariables on performance in a vigilancetask are in part a function of the class of taskimposed upon the subjects. It has been demon-

strated that when studies are categorized by abili-ties required by the task, relationships betweenperformance and time in the task differ markedlyas a funct ion of the selected independent variables.It shouldbeemphasized thatdespite the differencesamong specific tasks in terms of equipment, dis-plays, response requirements, etc., the classificationsystem enabled an integration of results and thedevelopment of functional relationships that wereotherwise obscured.

A more recent study by our staff, along thesesamegeneral lines, was conducted on the effects ofalcohol on human performance (Levine, Kramer,& Levine, 1 9 7 5 ) . A s before, the effort was de-signed to categorize the existing literature onalcohol effects into task groups in order to de-t erminewhether alcohol effects differ as a functionof different types of tasks. Tasks described in theliterature on alcohol effects were grouped togetheron the basis of the abilities required to performthe task using the ability rating scale proceduresdeveloped . A preliminary set of abilities waschosen representing the cognitive, sensory-percep-tual, and psychomotor domains. After the tasksin these studies were grouped according to abilitiesmeasured,pe r fo r m anceon these tasks as a functionof amount of alcohol dosage and timesince dosagewas examined for each class of tasks.

1 0 0

9 0o 800)

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P E R C E P T U A L SPEEDI F LE X IB I L I TY OFCLOSURE

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I I I I I I30 60 90 12 0 150 180

T 30 6 0 9 0 1 2 0 1 5 0 1 8 0

Time i n Task Min.)30 60 90120150 180

Figure 11 . Median percentage of correct detections as a function oftime in the task and ability category fo r different sensory modes. (From Evaluat ion of an Abilities Classification System for Integrating andGeneralizing Hum an Performance Research Findings: An Application toVigilanceTasks" by Jerrold M. Levine,Tania Romashko, and Edwin A .Fleishman, Journal of Applied Psychology, 1973, 58 , 149-157. Copy-right 1973 by the American Psychological Association, Reprinted bypermission.)AMERICAN PSYCHOLOGIST DECEMBER 197S 1139


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.1 0 .2 0DOSAGE (g/kg)

.3 0 .40 .50 .60 .70 .80 .90 1 .00

-10UJozpe -20

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Figure 1 2 . Median percent decrement as a func t ion of alcohol dosageand predominant ability. (From Effects of Alcohol on Human Per-formance : A n Integra t ion of Research Findings Based on an AbilitiesClassification by Jerrold M. Levine, Gloria G. Kramer, and Ellen N.Levine, Journal of Applied Psychology 1975 , 60 , 285-293. Copyright1 9 7 5 by the American Psychological Association. Reprinted by per-mission.)

Figu re 1 2 depicts performance as a functionofdosage, for the ability categories of selective atten-tion,perce ptual speed, and control precision. Wh atis plotted is the perform ance decrem ent, relative tocontrol groups, for increasing dosage levels. Theplots are in termsof grams of alcohol per kilogramof body weight . The numb er of data points aresmall , dependen ton studies found in the literature,an d therefore conclusions and interpretations weremade with caution. However, each point is anaverage of several studies, and there is a strikingsimilarity in the rate of performance deteriorationwith increasing alcohol dosages for the perceptualspeed an d co ntrol precision tasks. This situationis somewhat different, however, for tasks involvingselectiveattention. T he data suggest thatperform-ance on tasks involving this cognitive ability ismore seriously impaired with increases in dosage.Other results suggest that the greatest impact ofalcohol on performance occurs when an hour ormore elapses between administration of alcohol andtask per form ance . Fu rther, when these conditionsprevail, theselective attention and perceptual speedtasks are most hampered by alcohol and the con-trol precision tasks least hampered.Taken together these results indicate that th erate an d degree of deterioration are a functionofboth dosage levels and task categories. K nowled geo f the task categories improves the prediction thatcan be made about human performan ce. Again,despite differences among the specific tasks in the

l i te rature in terms of displays, response require-ments, performance index, technique of alcohol ad -ministration in different studies, etc., the categori-zation of tasks used in these studies, according toability req uire me nts, appears to allow an integra-tion of results and the development of functionalrelationships that otherwise might be obscured.Several other kinds of evaluation of the abilitiestaxonomy have been made. One has involvedvalidating the ability ratings made by observersagainst actual factor loadings obtained on the sametasks (Theologus&Fle ishman, 19 7 3) . Such evalu-ations have led to further refinementsof the scales.Task Characteristics ApproachIn asecond general app roach to taxonomic develop-ment , our project staff (Farina &Wheaton, 19 73 )has worked with what has been termed the taskcharacteristics approach. Asmentioned earlier,thisapproach attempts to provide for the descriptiono f tasks in terms of a variety of task-intrinsicpropert ies includ inggoals, stimuli, procedures, etc.Knowledge of how pe rfor m anc e varies, as a resul to f manipulating the characteristics of tasks, mightprov ide a basis for estimating p erfo rm anc e on othertasks whose characteristics could be described.The de ve lop me nt of task characteristics receivedinitial gu idance from a definition of the term task.A task was conceived of as having several com-ponents: an exp licit goal, procedu res, inpu t st imuli,

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T A S K C O M P O N E N T S TASK CHARACTERISTICSmber of O u t p u tUnitration (or Which an O u t p u t U n t tU Ma inU ine tmber of E lam en t p e r Ou t p u t Un i tW o r kLoad Impoted by Tfcek GoalDif f i cu l t y ofCos A t t a i n m e n t

-STIMULUS-RESPONSE' B of Op e r a t o r C on t r o lonTime/Feedback LagReUtlP ec t B ion Mak in gFig ure 13. Conceptual scheme of task character-

istics:Relationship among the terms task components ,an d characteristic. (From Development of a Taxon-omy of Human Per formance: The Task Character is t icsApproach to Performance Predic t ion [AIR Tech. Rep.7 2 6 - 7 ] by Alf r ed J. Farina, Jr., and George R.Wheaton.)

responses, and stimulus-response relationships. Inorder to differentiate among tasks, the componentsof a task were treated as categories within whichto devise task characteristics or descriptors.

F igure 13 clarifies the relationship among theterms task , task components , an d characteris tics.Each characteristic was cast into a rating scaleformat that presented a definit ion of the char-acteristic and provided a 7-point scale with definedanchor points and midpoints along with examplesf o r each poin t (Smith &Kenda ll , 1 96 3) . A sampleratingscale is shown in F igu re 14 .

Many different reliability studies have been con-ducted. Relations between values obtained from3-judge groups and larger groups were high, and ahuman factors background by raters was foundhelpful. O f primary interest here are studies inwhich ratings of task characteristics have predictedactual task performance. In an illustrative study(Farina &Wheaton, 1 9 7 3 ) , judges rated 37 taskson 19 scales. T he criterion performance score re-ported for each task was converted to obtain theaverage nu mb ero f un i t s p roducedper unit t ime.

The six most reliable scales were chosen foranaly sis. For each of these scales, the ratings pro-vided by three judges were averaged to obtain asingle value on each scale for each of the tasks.T he specific task d escrip tive scales emp loyed in thes tudy were (a) s t imulus durat ion, (b ) numbero fo u t p u t units , (c) duration fo r which an ou tpu tunit is maintained, (d) simultaneity of responses,

(e) numberofprocedural steps, and (f) variabilityof stim ul us location.The results showed that four predictors ac-counted for approximately 7 0% of the variance inthe criterion measure (after correction for smallsamplebias). It waspossibleto specify those taskcharacteristics that contributed most to perform-ance. Several replications of such studies havebeen completed, the most recent of which haveemployed more complex training devices used bytheNavy (Mirabella &Wheaton, Note 1 1 ) where

Rate thepresent taskon thisdim ension.Definitions

High regularityRegularintervals,periodicoccur-rence. Also refers tostimuluswhichiscon-stantly present.

Medium regtdarilyIrreg-ularintervalsbut aper-ceivablepatterno foccur-rence.

2

Low regularityVery ir-regular intervals; stimulusoccurrence isaperiodic.

Examples Respondingtounitsonan assembly line.Lookingat a pictureon a wall.

Receiving Morsecode.

Detecting random sig-nals on a CRT dis-play.Figure 1 4 . Example of a task characteristic scale.(From Development of a Tax onomy of Human Per-fo rmance: T he Task Character is t ics Approach to Per-formance Predic t ion [AIR T ech. Rep . 72 6-7 ]b y Alfred

J. Farina, Jr., and GeorgeR. Wheaton.)A M E R I C A N P S Y C H O L O G I S T D E C E M B E R 1 9 75 1141


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it was possible to predict learning time through aknowledge of the ratings of the tasks on criticaltask dimensions.

Overall these efforts have tentatively demon-strated that it ispossible to describe tasks in termsof a task-characteristics language an d that thesetask characteristics m ay represent important cor-relates ofp e r formance .Linking Abilitiesa ndTask RequirementsWe now presen t a final set of results, relevant totask taxonomy and hu man performance .

We have encouraging results from studies whichind icate that it is possible to bui ld up a body ofprinciples about interactions of task characteristicswith abi l i ty req ui rem ents through exper imental -correlational studies in the laboratory. The ap-proach is to develop tasks that can be varied alongspecified task dimensions, to administer these tasksto groups of subjec ts wh o also receive a series of reference ability tasks known to sample certainmore general abil i ties (e .g. ,spatial orientation, con-trol prec ision) . Correlations between these refer-ence tasks and scores on variations of the criteriontask specify the abil i ty requirem ents (and changesin these requirements) as a function of task vari-ations.

In ear l ie r s tudies (see F le ishman, 19 S7 , 1 9 7 2 ) ,subjects were required to press a button wi thin ac ircula r ar rangement of bu t tons on the controlpane l in response to particular l ights thatappearedin a circular arrangement of lights on a displaypane l . T he correct button depended on the posi-tion of the l ight. Su bjec ts performed under sevendifferent conditions of display-control comp ati-bi l i ty , where the display panel was rotated from0, 45, 90, 135, and 2 7 0 . These same subjectsalso performed on a series of spatial, perceptual,an d psychomotor reference tasks.

We were able to show systematic changes in theabi l i ty factors sampled by the criterion task as afunct ion of degree of rotation of the display panel,from th e ful ly comp atible (0 ) condition. Pro-gressive rotation of the l ight panel was found toshift th eab i l ity r equ i r ementsfrom perceptual speedto two other factors: resp onse orientation andspatial orientation . Perceptual speed wasmeasuredin the upright and sl ight displacement conditions.The other abilitieswere measured at larger displayrotations. Here,individualdifferences along knownabi l i ty d imensionsa re used to explore the relations

between tasks and the characteristics ofpeoplewhocan perform the tasks most effectively. O f course,these ar e problems faced every day by personnel,training, engineering, and systems psychologists.

A s tudy jus t comple ted (Wheaton, Shaffer,Mirabella, Fleishman, Note 1 2 ) has taken us astep closer in applying this paradigm to an opera-tional task. T he task used was that of the Navysonar operator. The task consisted of aud itorysignal identif ication in which subjects were to de-termine the ident i ty of a variety of complex soundsrepresenting various types of ships. Each time asignal was presented, subjec ts had to determinewhether it belonged to a cargo ship, warship, sub-marine, or l ightcraft. Used in this form, the cri-terion task had the added virtue of high face va-l id i ty , inasmuch as it closely resembled the taskof a passive sonar operator.T wo task characteristics were selected for ma-nipulation: signal duration and signal-to-noiserat io. Nine different task conditions were gen-erated according to a factorial arrangement of thesetwo variables. Stimu li were presented fo r either9, 6, or 3 seconds, and under one of three signal-to-noise ratios. B ackg round noise was set at 5dB, 0 dB, or +5 dB referenced to the intensity ofthe signal to be identif ied. Each of the nine differ-ent task con diti ons generated in this manner wasrepresented by a tape containing 100 signals, 2 5for each ship category.

T he exper imental procedure which was followedwas to admin i s te r a batte ry of 24 specificallyselected tests to all subjects prior to their involve-ment in the auditory signal identif ication cri teriontask. The battery contained tests representing avar ie ty ofwell-established factorsin the perceptual ,cognitive, an d mem ory domains of performance .Upon completion of the battery and followingextensive training in ident i fy ing the ship sounds,subjects performed under the nine different cri-terion task cond itions. Figu re IS showsthat varia-t ions in the two task characteristics really made adifference in ac tual performance . B u t what of therelation of the ability factors to these changes intask characteristics?

Of the five separate ability factors that wereidentified in the test battery, th e auditory per-ceptual abi l i ty was found to be most related tocriterion task perform ance. Fig ure 1 6 shows thatwithin each signal duration, the loadings on thisfactor increased as background noise grew louder.The same was generally true within each level ofbackground noise where loadings on the auditory

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I N T E N S I T Y O F B A C K G R O U N D N O I S E R E L A T I V E T O S I G N A L S T R E N G T H

Figure 15. Identification accuracy as a function ofth e task conditions, background noise, an d signal dura-tion. (From Methods for Predicting Job-Ability Re-quirements: 1. Ability Requirem ents as a Function ofChanges in the Characterist ics of an Auditory SignalIdentification Task [AIR Tech.Rep. 73-5]b y GeorgeR . Wheaton, Ellen J. Shaffer, Angelo Mirabella, an dEdwin A.Fleishman.)perceptual factor increased in magnitudeas signaldurations grew shorter. In other words, the con-tribution of this ability to individual differences inperformance increased as the criterion task becamemore difficult. There appeared to be two criticallevels for each task dimension. Thus, signals canbe decreased from 9 to 6 seconds without muchchangein the auditory perceptual requirement, buta fu r the r decrease to 3secondsincreases thisabilityrequirement substantially. It is also shown thatat this short signal level,anincrease inbackgroundnoise to equal intensity produces a further require-ment fo r this ability, beyond which an additionalincrease in sound level produces little effect onthe ability requirement. Knowledge of these taskconditions allows us to be much more precise inspecifying the ability requirements for effectivecriterion performance. Loadings on this abilityalsowere shown to vary according to the typeofsignals (cargo ships, light craft , warships,and sub-marine) to be ident i f ied . These findings can beexplained on the basis of the task characteristicsof these particular auditorystimuli.

The final study to be described involved the ex-tension of this paradigm to cognitive or "higher

order" reasoningtasks (Rose, Fingerman, Wheaton,Eisner, &Kramer, Note 13). In the present in-stance, we examined representative tasks faced byelectronic troubleshooters and maintenance per-sonnel.

The criterion task was ananalog of a fault-find-ing or troubleshooting situation. Working withwir ing diagrams, the subjects' task was to deter-mine which one of a number of possible break-points was actually fau l ty . Each wiring diagramcontained a number of logic gates, switches, andprobe points (see Figure 17). In Figure 17, thesmall boxes (1, 2, 3, 4, and 5) represent switches,the lettered points (A through L) represent light-bulb sockets, and the starred points (1 through9) indicate the possible locations of faults (orbreaks) in the wires. The logic gates operatesimply: Current will flow through the OR gate ifeither Switch 1 or Switch 2 is on. For current toflowthrough the AND gate (on figure), currentmustenter thegate along both input wires.

45i

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QUJI353025

I

3seconds 6seconds~ 9seconds

I-5db O d b +5db

RELATIVEINTENSITYOFBACKGROUND NOISEFigure 16 . Estimated loadings of the auditoryper-ceptual factor as a function of background noise levelfor each signal duration. (Adapted from Methodsfo r Predicting Job-Ability Requirements: 1, AbilityRequirements as a Funct ion of Changes in the Char-acteristics of an Auditory Signal Identification Task[AIR Tech. Rep. 73-5]by George.R. Wheaton,EllenJ. Shaffer, Angelo Mirabella, and Edwin A.Fleishman.)

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8B c *

m 6*7Figu re 17 . C ircu it diagram problem representingfirst levels of formal difficulty and perceptual com-plexity. (From Methods fo r Predic ting Job-Ability

Requirements: II . Ability Requirements as a Func-tion of Changes in the Character is t ics of an ElectronicFault-Finding Task [AIR Tech . Rep . 7 4 -6 ] by And rewM. Rose, Paul W . F ingerman , George R . Wheaton,Ellen J. Eisner , an d Gloria G . Kramer.)T he subjects tested the points byplacing a light

bu l b at various points in the circuit and pressinga switchor combinationofswitches. For example,(on figure) to see if Point 9 is faulty you wouldplace abu lbat B andpressSwitch 9 . Other pointsare more difficult to test. For exam ple, it takestwo probes to see if Point 1 is fau l ty : first, youshouldput thebu lbat C and press Switches 1 and9 . If the bul b does not l ight, either 1 or 9 isfaul ty . Second,y ou should put the bu lb at B andpress Sw itch 9. If the bulb l ights, 9 is not faul tyan d 1mu s tbe the breakpoint.This basic task wasvaried along twodim ensions:formal difficulty an d perceptual complex ity. Vari-at ions in formal difficulty involved increasing thenumber ofpossible breakpoints and the number oflogic gates. Fig ure 1 8 is a third-level problem with6 gates and 24 possible breakpoints.

Variations in the second task dimension involvedchanging the perceptual organization of the cir-cuits. The first level is a straightforward ,left toright circui t with no crossed wires. The secondlevel rearranges the locations of the switches onthe same circuit, creating several crossed wires.T he third level (see Figure 19) changes the loca-tions of both the switches and the logic gates. Al-though this looks confusing, the actual circuit inFigure 19 is exactly the same as the one in thelast two figures.Subjec ts were first given training in the me-chanics of using th e d iagrams to test for break-points. Several criterion measures ofperformancewere collected, including how fast the problemswere solved, how many trials were required, andhowefficiently subjects solved them. The efficiencymeasure was defined as the proportion of break-points that w ere eliminated by each test the subjectused relat ive to the m axi mu m break points he couldhave eliminatedon that test.

T he task was analyzed according to the abilitieshypothesized to contribute to task performance.A com prehensiv e battery of 2 1 abil ity tests wasselected and ad min istered to all sub jects who thenperformed on the 18 troubleshooting problems ina replicated 3 X 3 design. T he order of presenta-tion was counterbalanced.

Figure 18. C ircuit d iagram problem representingthe third level of formal difficulty and first level ofpe rcep tua l complex ity . (From Methods fo r PredictingJob-Ability Requirements: II. Abili ty Requirementsas a Function of Changes in the Characterist ics of anElectronic Fault-Finding Task [AIR Tech . Rep . 74 -6 ]by Andrew M. Rose, Paul W . Fingerman, George R .Wheaton, Ellen J. Eisner, and Gloria G.Kramer.)

Figu re 19 . C ircu it d iagram problem represent ing theth ird levels of both formal difficulty an d perceptualcomplexity. (From Methods fo r Predicting Job-Abil-it y Requirements: II. Ability Requirements as a Func-tion of Changes in the Characterist ics o f an ElectronicFault-Finding Task [AIR Tech. Rep. 74-6] byAndrewM. Rose, Paul W . Fingerman, George R . Wheaton,Ellen J. Eisner,and Gloria G. Kramer.)

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Without going into the details of the results andmany different analyses, we can illustrate the im-portant findings with a few figures. First,wewillexamine different criterion measures of perform-ance. Figure 20 shows that changes in levels ofth e task dimensions of both formal difficulty andperceptual complexity made a difference in cri-terion performance. Here we have plotted meant ime to solution across all problems. Figure 21shows that for another criterion measure, namely,number o f trials to solution, formal difficulty madea difference, but perceptual complexity made lessof a difference.

Figure 22 shows that for a third criterion mea-sure, efficiency of performance, both task dimen-sions made a difference, with the greatest effectsoccurr ingat the highest level of complexity onbothdimensions. These results, of course, underscoretheneed to look at different criterionmeasures.

oP8

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u

5

45

4

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PER C EPTU A LCO MP LEX IT Y

I 2 3F O R M A L DIFFICULTY

Figure 2 0 . Geometr ic mean time to solution as afunction of changes in formal difficulty an d perceptualcomplexity . (From Methods fo r Predicting Job-Abil-it y Requirements: II . Ability Requirementsas a Func-tion of Changes in the Characterist ics of anElectronicFault-Finding Task [AIR Tech. Rep. 74-6]by AndrewM. Rose, Paul W. Fingerman, George R. Wheaton,Ellen J. Eisner, and Gloria G .Kramer.)

HOC O

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P ERCEP T UALCOMPLEXITY

FORMAL DIFFICULTY

Figure 2 1 . Geometric mean trials to solutionas afunction of changes in formal difficulty andperceptualcomplexity. (From Methods fo r Predicting Job-Abil-it y Requirements : II . Ability Requirementsas aFunc-tion o f Changes in the Characterist ics of anElectronicFault-Finding Task [AIR Tech. Rep. 74-6]by AndrewM. Rose, Paul W. Fingerman, George R. Wheaton,Ellen J. Eisner, and Gloria G .Kramer.)But what about the linkage of ability require-

mentsto these criterion performances,as afunctionof differences in these task characteristics? Sev-eral clear factors emerged in the factor analysisof the ability tests, but I will confine our resultsto those abilities found most related to task per-formance. Figure 23shows clearrelationsbetweenthe task characteristics and particular ability re-quirements, where mean trials to solution is usedas the criterion measure. The abilityflexibility ofclosure was related to performance and increasedin importance as difficulty increased on both di-mensions. Associative memory was critical onlyat the first level of perceptual complexity.

Figure 2 4 illustrates the f indings using th e effi-ciency criterion measure of performance. First ofall, it is evident that this criterion was the mostpredictable. Again, we see that flexibility of

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1 .15

1.10_lEK 1.05uia.

1.00

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90

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PER C EPT U A LCOMPLEXITY

2 3FORMAL DIFFICULTY

Figu re 22 . Mean arcsin square root efficiency pertrial as a function of changes in formal difficulty andperceptual complexity . (From Methods fo r PredictingJob-Ability Requirements: I I . Ability Requirementsas a Function of Changes in the Characteristics of anElectronic Fault-Finding Task [AIR Tech. Rep. 74-6]by Andrew M. Rose, Paul W. Fingerman, George R .Wheaton, Ellen J. Eisner, and Gloria G. Kramer . )

i Factor1 - FLEXIBILITY OFCLOSURE/SPATIAL SCANNING Factor2 - SYLLOGISTIC REASONINGI Factors- INDUCTION

FORMAL DIFFICULTY PERCEPTUAL COMPLEXITY

Figure 2 3 . Estimated loadings of the criterionmea-sure, geometric mean trials to solution fo r differentability factors under the different task conditions.(F rom Methods for Predicting Job-Ability Require-ments: II. Ability Requirements as a Function ofChanges in the Characteristics of an Electronic Fault-Finding Task [AIR Tech. Rep. 74-6] by Andrew M.Rose, Paul W. Fingerman, George R . Wheaton, EllenJ . Eisner, an d Gloria G. Kramer . )

Factor 1 - F L E X I B I L I T Y OF C L O S U R E /SPATIAL SCANNINGFactor 2 - S Y L L O G I S T I C R E A S O N I N GFactor 3 - A S S O C I A T I V E MEMORYFactor 5 - INDUCTION

FORMAL DIFF ICULTY PERCEPTUAL COMPLEXITY

Figure 2 4 . Estimated loadings of the criterionmea-sure, arcsin square root efficiency per trial, fo r differentability factors under the different task conditions.(From Methods for Predicting Job-Ability Require-ments: II. Ability Requirements as a Function ofChanges in the Characteristics of an Electronic Fault-Finding Task [AIR Tech. Rep. 74-6] by Andrew M.Rose, Paul W.Fingerman, George R . Wheaton, Ellen J.Eisner, an d Gloria G . Kramer . )closure is the most important ability in this task,and its importance increases with increased diffi-cultyon both task dimensions. A reasoning abilityr ema ins stable across conditions, and associativememory and induction drop out, but at differentlevels ofperceptual complexity.

There were some differences depending on thecriter ion measure,and some measures were clearlymore predictable than others. But there are com-mon results across criterion measures. The con-t r i bu t ion of one ability, flexibility of closure, in -creased across all criterion measures with changesin both task dimensions. The requirement for asecond ability, syllogistic reasoning, remained con-stant for most measures across all conditions. Formost criterion measures, memory ability showedlow or decreasing predictions as conditions weremade more diff icu lt .

We can say that results with this cognitive taskconfirm the f indings with psychomotor an d withperceptual tasks and extend the principles to morerealistic job-related tasks. If one were to predictf rom these abilities which individuals woulddowellon these tasks, the choices would depend on thetask characteristics and the criterion measure se-lec ted.

There are two general types of trainingor selec-tion decisions implied by the data. One type,typified by the pattern of loadingsof the flexib ilityof closure factor , occurs when a change in taskcharacteristic results in a change in importance of

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particular abilities bu t does not require differentabilities. H ere a change in cutoff value on the rele-vant test is the appropriate decision. The secondtype of decision occurs when changes in task de-mandschange thecom binations of abilities involved(as with our efficiency measure). In such situa-tions, th e implication is that different individualswould be selected if the nature of thetask changed,or the training would need modification, or thetask would need to be redesigned to be in accord-ance with the trainee population.

These studies have demonstrated empirically thatthe patte rns of abilities related to criterion per-formance may undergo changes as specific char-acteristics of atask ar e systematically manipulated.W e are currently d etermining whether such rela-tionships can be inferred and what information isneeded by task analysts who must estimate theability requirements for a given task configuration.

In the general case, such judgments occur whena job is analyzed to determine what abilities mayserve as abasis for selection ofpersonnel or , giventhat personnel will not be preselected, to serve asa basis for formulating training programs. In thespecial case, these same kinds of selection andtraining decisions willbe required whena newtaskis encountered which bears some specifiable re -semblance to an old task for which selection andtraining programs have been developed. In eithercase, task analysts need a method for predictingjob-abil i ty requirements which shortcuts th e pro-cess of studying each situation empirically, withlittle generalization across cases. This need was,of course, anticipated by Lawshe ( 1 9 S 2 ) an dGuion( 1 9 6 5 ) , in their workon synthetic validity, and byPrimoff ( 1 9 5 7 ) at the Civil Service Com mission.To be of real utility, such a method must alsopermit assessment of the impact that systematicchanges in thenatureof a taskhave on job-abilityrequirements.Summary StatementI have tried to lay outsome general issues in tax-onomic deve lopment and to give some examples ofmeasurement approaches and methods ofevaluationof taxonomic systems. Some studies were shownin which predictions and generalizations about hu-man performance may be enhanced through appli-cations of such taskclassification systems. I thinkwe have gained some additional understanding ofcriterion performance as a result of this work.From our work thus far, a few additional observa-

tions are possible. The search for a single generaltaxonomy is not likely to be successful for all pur-poses. We may, indeed, need several task classifi-cation systems for several purposes, with the link-age between them und erstood and specified. Ataxonomic system linking ability requirements andtask characteristics appears to hold promise forprovid ing an organizing framework. T he processwill be an iterative one. Taxonomies are,not outthere to bediscovered; some invention is required.However, this invention must be grounded in em-pirical data, research, and evaluation. The re-search p aradigm describ ed, which includes com-binations of experimental and correlational meth-ods, seemsa usefulway to goabout it .

R E F E R E N C E N O T E S1. Cot te rman,T. E. Task classification: An approach topartially ordering information on h uman learning

( W A D C T N 58-374) . Wright-Patterson A ir ForceBase, Ohio: Wright-Pat tersonAir Development Center,1959.2 . Ecks trand, G. A. Current s ta tus of the technology oftraining (AMRL-TR-64 -86 ) . Wright-Patterson A irForce Base, Ohio: Aerospace Medical D ivision, Sep-tember 1964.3 . Folley, J. D., Jr. Deve lopment o f an improved method

o f task analysis an d beginningsof a theory of training( N A V T R A D E V C E N 12 18-1) . Port Washington, N.Y . :U . S . N aval Training Devices Center, Jun e 1964.4 . Stolurow, L . A taxonomy of learning task character-istics ( AM RL - T D 12 -64 -2). Wright-Patterson AirForce Base, Oh io : Aerospace Medical Research Labora-tories, January 1964.5. Elk in , E. H., Freedle, R . 0., Van Cott, H . P., &Fleishman, E. A. E f f e c t s of drugs on h uman perform-ance: The e f f e c t s of scopolamine on representat ive hu-m an performance tests (AIR Tech. Rep. E-25). Wash-ington, D .C . : American Institutes for Research,Augus t1 9 6 5 .6 . McCormick, E. J. The development , analysis , and ex-perimental application of worker-oriented job variables(Fina l report ; ONR Nonr-1100 [19]). Lafayet te ,Ind.:Purdue University, 1964.7 . Fine, S. A. A functional approach to a broad scalemap of work behaviors (HSR-RM-63/2). McLean,V a . ; Human Sciences Research, Sep tember 1963.8. Baker, W. J., Geist,A .M., &Fleishman, E. A. E f f e c t s

o f cylert (magnesium-pemoline) on physiological , physi-ca l proficiency, and psychomotor performance measures A I R Tech. Rep. F-31). Washington, D.C .: AmericanInstitutes for Research, August 1967.9 . Romashko, T., Brumback , G. B., & Fleishman, E. A.Th e development of a procedure to validate physicaltests: Physical requirements of the fireman's job (AIRTech. Rep . 37 5-1 ). Washington, D.C.: Am ericanInsti-tutes for Research, June 1974 .

10.Romashko, T., Brumback, G. B., &Fleishman, E. A.Th e development of a procedure to validate physicaltests; Physical requirements of the sani tat ion man' s jo b(AIR Tech. Rep. 3 7 5 - 2 ) . Washington,D.C. : AmericanInsti tutes for Research, October 1973.

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11. Mirabe l la , A., & Wheaton, G. R. Effects of task indexvariat ions on transfer of training cri teria( N A V T R A E Q U I P C E N 7 2 - C - 0 1 2 6 - 1 ; A m e ri ca n Insti-tu tes fo r Research Contrac t N 6 1 3 3 9 - 7 2 - C - 0 1 2 6 ) . O r -lando, Fla.: U.S. N avy Train ing Equip ment Center ,September 1973 .12 . Whe a ton , G . R . , Shaffer, E. J . , Mirabella, A ., &Fleish-m a n , E. A. Methods for predictin g job-ability require-ments: 1, Ability requirements as a function of changesin the characteristics of an auditory signal identificationtask (AIR Tech. Rep. 73-5) . Washington, D.C. : Ameri -

ca n Institutes fo r Research, September 1973.13. Rose , A. M., F i ng e rman , P. W., Wheaton, G. R ., Eisner,E ., & K rame r , G . Methods fo r predicting job-abilityrequirements: II. Abil i ty requirements as a junction ofchanges in the characterist ics o f an electronic fault-f inding task (A IR Te c h . Re p . 7 4 - 6 ) . Washington, D.C . :Amer ican Inst i tu tes fo r Research, August 1974.R E F E R E N C E S

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Fle i shman, E. A. Per form anc e assessment based on anempirical ly der ived task taxonomy. Human Factors,1967 , 9 , 349 -366 . ( b )F le ishman, E. A. On the relation between abilities, learn-ing , and human per formance. American Psychologist ,1 9 7 2 , 27 , 1017-1032.F le ishman, E . A., Ellison, G . D . Prediction of transferan d other learn ing phenomena from ability and per-sonality measures. Journa l of Educational Psychology,196 9 , 60,300-314.Fl e i shman , E . A ., &He mpe l , W . E., Jr. Changes in factors t r u c t u r e of a comp lex psy chomo tor test as a fun ctionof practice. Psychometrika 1954, 18, 2 3 9 - 2 5 2 .F le ishman, E . A ., & Hempel , W . E., Jr . The relation be-tween abil i t ies and improvement with practice in a visuald iscr iminat ion reaction task. Journa l o f ExperimentalPsychology, 1955 ,4 9,301-312.Fle ishman, E . A., K inkade , R . G ., & Chambers, A. N.Development of a taxonomy of human pe r fo rmanc e : Areview of the first year 's progress. JSAS Cata log .ofSelectedDocuments in Psychology, 1 9 7 2 , 2 ,3 9 . (Ms. N o.I l l ) (Also available as AIR Tech. Rep. 72 6-TPR1.Washington, D.C.: American Institutes for Research,Nove mbe r 1968 . )F le ishman, E . A ., & Parke r , J . F. Factors in the reten-tion an d re learn ingo f perceptual -motor sk i l l . Journa l ofExperimental Psychology, 1 9 6 2 , 64 , 2 1 5 - 2 2 6 .Fle i shman, E. A., &S tephenson, R. W. Deve lopment of at axonomy of human pe r fo rmanc e : A review of the thirdyear ' s progress . JSA S Cata log of Selected Documentsin Psychology, 1 9 7 2 , 2, 40-41. (Ms. N o. 113) (Alsoavai lab le as AIR Tech. Rep. 72 6-T PR3 . Washington,D .C . : Amer ican Inst i tu tes fo r Research, September 1970 . )F le ishman, E . A ., T e ichner , W. H . , & Stephenson, R . W .Dev e lop ment of a taxonomy of human pe r fo rmanc e : Areview of the second year 's progress. JSA S Cata log ofSelected Documents in Psychology, 1 9 7 2 ,2,39-40. (Ms.No. 112) (Also avai lable as AIR Tech. Rep. 7 26 -TPR 2.Wash ing ton , D.C .: A merican Institutes for R esearch,January 1970 . )

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Gold Medal AwardT he Trustees of the American Psychological Foundation invite th e members of theAmerican Psychological Association to nominate candidates for the 1 9 7 6 GoldMedal Award. The Award is given to an Am erican psychologist in recognition ofa distinguished an d long-continued record ofscientif ic and scholarlyaccomp l ishments .T he Award is l imi ted to psychologists 65 years of age or older and is also l imitedto those residinginN orth Am erica. N ominat ions should be accompanied by a state-me nt highlighting the accomplishments of the nom inee. N omin ations should beaddressed to : Secretary, Am erican Psychological F ou nd ation, 12 00 Sev enteenthStreet, N.W., Washington, B.C. 2 0 0 3 6 , to be received no later than March 15, 1976.T he decision will be made by the Trustees of the Am erican Psychological Founda-tion.