Abilities Interests and Values Their Assessment and Their Integration via the World-of-Work Map

Abilities, Interests, and Values: Their Assessment and Their Integration via the World-of-Work Map

Dale J. PredigerACT, Inc.

This article describes assessments of work-relevant abilities, interests, and valuesand how the World-of-Work Map (WWM) can be used to link them to (a) eachother, (b) Holland’s hexagon, (c) basic work tasks, (d) occupational groups, and (e)occupations. The assessments and their linkage procedures, which are imple-mented in the Career Planning Survey and DISCOVER (a computer-based serv-ice), are intended for use with persons in the early stages of career planning orreplanning. A case study illustrates how results of the assessments are integratedand linked to career options. Then, the theory, practical considerations, andresearch supporting the career counseling use of self-estimates of work-relevantabilities are discussed. Next, the three assessment instruments are described, andthe research contributing to the WWM’s 2000 update is summarized. Finally, anaid is provided for using the WWM with any assessments of Holland’s types (e.g.,those discussed in this journal issue).

Keywords: Career assessment, abilities, interests, work values, ability self-estimates

It is generally recognized that work-relevant abilities, interests, and values areprimary considerations when helping persons with career exploration and plan-ning. Yet, assessments of all three of these characteristics are seldom provided bya single, integrated assessment program (e.g., see Kapes, Mastie, & Whitfield,1994). The purpose of this article is to describe assessments of a wide range ofwork-relevant abilities, interests, and values and how they can be linked to (a)each other, (b) Holland’s (1997) hexagon, (c) basic work tasks (Prediger, 1982),(d) groups of similar occupations, and (e) specific occupations. ACT, Inc. (ACT)uses the three types of assessments in DISCOVER (ACT, 1999), a computer-based career planning system serving 8th graders through adults. The Career

AUTHOR’S NOTE: The author thanks Rick Noeth, Nancy Petersen, and Kyle Swaney for their review ofdrafts of this article. Correspondence concerning this article and requests for reprints should be addressed toDr. Dale Prediger, Senior Research Scientist, ACT Research Division, P.O. Box 168, Iowa City, IA, 52243; e-mail: [email protected].

JOURNAL OF CAREER ASSESSMENT, Vol. 10 No. 2, May 2002 209–232© 2002 Sage Publications

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210 JOURNAL OF CAREER ASSESSMENT / May 2002

Planning Survey (CPS) (ACT, 2000), a paper-based system serving 8th through10th graders, includes the same the ability and interest assessments as DISCOV-ER. Work values are addressed informally.

As summarized by ACT (1999), DISCOVER uses the Inventory of Work-Relevant Abilities (IWRA) to assess abilities, the Unisex Edition of the ACTInterest Inventory (UNIACT) to assess interests, and the Inventory of WorkPreferences (IWP) to assess work values. IWRA and UNIACT provide scores forHolland’s (1997) six types of vocational personalities and work environments.Although IWP research did not support providing scores for Holland’s types,results from all three assessments can be linked to each other and to occupationaloptions via the empirically based World-of-Work Map (WWM)—an extension ofHolland’s hexagon (e.g., see Prediger, Swaney, & Mau, 1993). Accordingly, thehexagon forms the core of the map (see Figure 1), and the RIASEC abbreviationsof Holland’s types (Holland, 1997) appear on the periphery with related careercluster titles.

Together with the WWM and information about 555 occupations organizedby the map’s six career clusters and 26 career areas, the three assessments (two inthe CPS) are intended for use with persons in the early stages of career planningor replanning. The goal of both DISCOVER and the CPS is a comprehensive,work-world search for occupations that have counselee-compatible characteris-tics. Of course, the work-relevant ability, interest, and value assessments can alsobe used in individual counseling involving special concerns.

Later in this article, the bases for the assessments and the WWM are discussed.But first, to provide an overview of what they do (the big picture), their applica-tion is illustrated by a synopsis of a composite case study originally reported inthis journal by Prediger and Swaney (1995). (Prediger, 1999b, reported an exten-sion of the case study.) Because the assessments are components of both computer-based and paper-based services, there are no standard interpretative proceduresor materials. Hence, the case study illustrates the general procedures followed inboth services—procedures that can be used with other assessments reportingscores for Holland’s types (e.g., those discussed in this journal issue). To providea fresh perspective on the case study, the 2000 update of the WWM is usedinstead of the previous edition. Introduced in 1973, the WWM is now part of fiveACT programs serving approximately 5 million persons each year.

THE CASE OF JESSICA VUNDERING

Jessica Vundering (she introduces herself as “Jess”) grew up on a midwesternfarm, helped with farm chores and record keeping, and after graduating fromhigh school, worked as a clerk in a large insurance company. She decided thatwas not for her and is now a 22-year-old, first-year college student. Her tentativechoice of major (people keep asking) is elementary education. Because“Exploring Teaching: A Field Experience,” the course she took during her first

Prediger / ABILITIES, INTERESTS, AND VALUES 211

semester, gave Jess second thoughts about that major, she went to the college’scounseling center to explore other possibilities. Her counselor introduced her to

Figure 1. World-of-Work Map.

Source. Copyright 2000 by ACT, Inc. All rights reserved. Adapted with permission.Note. Case study results are represented by circled initials. C = current occupatonal choice; A =abilities, I = interests; V = work values.


the WWM and to the basic types of work tasks (working with data, ideas, things,and people) that provide its foundation. She gave Jess examples of the work tasksand noted that the WWM summarizes, via the 26 career areas on the map, howoccupations differ with respect to them.

Next, Jess’s counselor pointed out that her tentative choice of major was locat-ed in the education career area, which is in Map Region 12. She asked Jess tomark a “C” (for choice) in that map region (see Figure 1) and explained thatoccupations on that side of the map primarily involve working with people. Jess’scounselor also introduced her to DISCOVER and to IWRA, UNIACT, and IWP.Jess decided to complete all three assessments on DISCOVER.

As shown by the initials in Figure 1 (“A” for abilities; “I” for interests), Jess’sIWRA and UNIACT results converged on WWM regions involving things andideas work tasks. Certainly, she had much experience working with things whilegrowing up on the farm. She also recalled that she was one of the few girls in herhigh school class who liked general science and who took both biology andchemistry. Hence, she thought that UNIACT’s Regions 9 and 10 might be tellingher something. Also, it was clear that her tentative choice of major was not in linewith her strongest abilities and interests, as summarized by their map regions.

After Jess completed IWP, DISCOVER compared the work values she hadindicated with the characteristics of each of the 555 occupations inDISCOVER’s comprehensive database. The four career areas containing occu-pations that best fit what Jess valued in a job were reported to Jess in rank order.Jess used the career cluster and career area list (Figure 2) to obtain a sense ofwhat each career area was like. Career Area Q (medical technologies), the careerarea that ranked the highest, seemed especially appealing. So Jess marked a “V”(for values) by its name on her copy of the map.

Jess then used the career cluster and career area list to obtain an overview ofthe career areas and occupations in her IWRA and UNIACT map regions. Shedecided to find out more about Career Areas O, P, and Q. Because DISCOVERorganizes 555 occupations by educational level within career area, Jess was ableto obtain a list of occupations requiring at least 2 years of education/trainingbeyond high school. She printed out DISCOVER’s descriptions of several occu-pations (including related training programs and college majors) and made anappointment with her counselor to discuss how she might further explore and pri-oritize the occupational options she had identified.

Should they be needed as Jess proceeds with self/career exploration, Jess’scounselor has access to her IWRA and UNIACT score profiles for Holland’stypes. Through a look-up table (Table 1) and/or the graphic procedure developedby Miller (1985), the counselor can show Jess how WWM regions are obtainedfor any report of Holland-type scores. (Prediger et al., 1993, illustrated the graph-ic mapping procedure, and Prediger & Swaney, 1995, provided counseling sug-gestions for when map regions do not agree across assessments.) Finally, thecounselor understands that there is much more to the work world than can beillustrated on a flat piece of paper—a map. As explained by Prediger and Swaney


(1995), the WWM attempts to strike a useful balance between work-world com-plexity and simplicity of use.

OVERVIEW OF WHAT FOLLOWS

The remainder of this article describes the assessments introduced in the casestudy and the bases for their integration via the WWM. After a discussion of thewide range of work-relevant abilities, special attention is given to the seldom-

Figure 2. Career clusters and career areas (A-Z) appearing on the World-of-Work Map (Figure 1).

Source. Copyright 2001 by ACT, Inc. All rights reserved. Adapted with permission.Note. Examples of occupations are taken from DISCOVER.

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214


discussed, practical and psychometric advantages of using self-estimates of abili-ties in career counseling. The results of five studies, showing that the use of self-estimates can improve on the validity of test estimates (scores), are summarized.The studies focus on validity for career planning applications. Next, IWRA(which obtains self-estimates for 15 work-relevant abilities) and UNIACT aredescribed, and research documenting the unique career planning informationprovided by IWRA and UNIACT is reported. Attention is then given to the IWPand its research-based link to the WWM.

This article’s final section (Integration of Assessments via World-of-Work Map)begins with an overview of theory and research supporting the Data/Ideas (D/I)and Things/People (T/P) work task dimensions underlying the WWM andHolland’s hexagon. Next, research contributing to the WWM’s 2000 update issummarized. Data for the 1,122 occupations in the O*NET OccupationalInformation Network (O*NET) (Peterson, Mumford, Borman, Jeanneret, &Fleishman, 1999) were used in the update. Finally, procedures for translatingassessment results into WWM regions are described, and an aid (Table 1) is pro-vided for using the WWM with any assessment that reports (or ranks) scores forHolland’s types.

WORK-RELEVANT ABILITIES

As used here, work-relevant abilities include noncognitive abilities in addition tothe usual cognitive abilities, and they subsume “basic and cross-functional skills”(Mumford, Peterson, & Childs, 1999, p. 51). Measures of skill self-confidence,self-efficacy beliefs, and so forth are not discussed because they are the subjectsof other articles in this journal issue and because no one seems to view them asability measures (e.g., see Betz, Borgen, & Harmon, 1996; Campbell, Hyne, &Nilsen, 1992). As noted by Prediger (1999b), “It appears that measures of work-relevant abilities differ sufficiently from measures of ability self-confidence [self-efficacy beliefs, etc.] for both to be helpful when used in conjunction with meas-ures of interests” (p. 296).

Common sense, theory, and research indicate that workers (e.g., accountants,interior designers, insurance agents, machinists, counseling psychologists) differon a wide range of abilities relevant to their work tasks. Informed common senseis reflected in the 17 abilities identified by Jones (1996) on the basis of studies bythe U.S. Department of Labor (DOL) Secretary’s Commission on AchievingNecessary Skills (U.S. DOL, 1992). Harrington and Harrington (1996) identified14 abilities primarily on the basis of earlier work by the DOL.

Regarding theory, Holland (1997) associates 22 abilities and competencieswith his six types. Many of these abilities and competencies (e.g., leadership, per-suasive, social, artistic) are not routinely assessed by tests (if at all). For 12 of theabilities, Holland obtains self-estimates via the Self-Directed Search (Holland,


1994). Also relevant is the theory of work adjustment (Dawis & Lofquist, 1984;e.g., see Table 3.1 on p. 27).

Studies documenting work-relevant ability differences across occupations haveinvolved test estimates of abilities, job analysis (JA) data, and expert ratings.Prediger (1989) summarized the results of several studies, and he reported newresearch that involved DOL JA data for occupations in the Dictionary ofOccupational Titles (DOT) (U.S. DOL, 1991). Ability ratings were available for14 of the 15 abilities listed in Table 2. When grouped by Holland type, the DOToccupations differed in sensible ways on those abilities. For example, R-typeoccupations had the highest mean ratings for mechanical ability and manualdexterity, and E-type occupations had the highest mean ratings for meeting peo-ple and sales abilities.

What appears to be the most recent evidence regarding the wide range ofwork-relevant abilities has been provided by the DOL report (Peterson et al.,1999) on the development of O*NET. Expert ratings and job-incumbent rat-ings for 46 skills (e.g., reading, writing, math, information organization, persua-sion, management) generally showed sensible (work-relevant) differences acrossoccupations.

Finally, ACT (2000) summarized the theory and research (beginning withAbe & Holland, 1965) leading to the identification of the abilities listed in Table 2.A primary consideration was comprehensive coverage of Holland’s types, asshown by their initials under the Table 2 career cluster titles. Although it wouldcertainly be possible to add abilities to the list, practical considerations suggestedotherwise (ACT, 2000).

Limitations of Test Estimates of Abilities

Unfortunately, it is difficult (if not impossible) to obtain test estimates formany of the work-relevant abilities identified by common sense, theory, andresearch. Ability test batteries typically assess only three or four work-relevantabilities beyond reading, numerical, and language use (e.g., see Kapes et al., 1994).Those that are assessed may be operationally defined by narrow test exercises anda brief sample of behavior (e.g., consider the typical spatial and clerical tests). Asindicated by the lower section of Table 2, abilities especially relevant to Holland’sartistic, social, and enterprising types are seldom assessed. This seriously affectsthe comprehensiveness of a work-world search for occupational options.

Even if test estimates for a comprehensive set of work-relevant abilities couldbe obtained, they would likely require a substantial amount of time andresources—time and resources that may not be available in services providingcareer counseling for the many. Also, because the ability estimates would likelybe based on a diverse set of tests, the identification of ability strengths and weak-nesses would be difficult due to differences, across tests, in norm groups andscore scales.


Advantages of Self-Estimates of Abilities

When the goal is a work-world-comprehensive search for counselee-compatiblecareer options, one way around the limitations of ability test estimates is to useself-estimates. As discussed in the section on IWRA, self-estimates can systemati-cally and efficiently address a wide range of work-relevant abilities (e.g., see Table2). More important, perhaps, they can make work-relevant self-concepts evident

Table 2Assignment of 15 Work-Relevant Abilities

to Career Clusters Similar to Holland Types

Career Clustera

Science and Social Administration BusinessTechnical Technologyb Arts Service and Salesb Operations

Ability (R) (I) (A) (S) (E) (C)

Abilities for which test estimates may be available

1. Reading X X2. Numerical X X X3. Language usage X X X X4. Spatial perception X X X5. Clerical X6. Mechanical X7. Scientific X

Abilities for which test estimates are seldom available

8. Creative/literary X9. Creative/artistic X

10. Manual dexterity X11. Meeting people X12. Helping others X13. Sales X14. Leadership

(management) X15. Organization X X

Source. From ACT (2000, p. 19). Adapted with permission.Note. An X indicates which abilities are used to obtain career cluster composite scores.a. Abbreviations for related Holland (1997) types are shown in parentheses.b. These titles will replace the current Inventory of Work-Relevant Abilities (IWRA) and UnisexEdition of the ACT (UNIACT) Interest Inventory titles (science; business contact) when IWRA andUNIACT are next revised.


to the counselor and counselee—and, thus, open for discussion. As Super (1957)noted more than 40 years ago, “In choosing an occupation one is, in effect,choosing a means of implementing a self-concept” (p. 196).

Various procedures are used to obtain self-estimates of work-relevant abilities.For example, see Harrington and Harrington (1996), Holland (1994), Jones(1996), and the O*NET Web site (http://online.onetcenter.org). Whether anyone of those procedures has a psychometric advantage appears to be an openquestion. The procedure used by IWRA (see section on IWRA) combines fea-tures of each of the procedures (e.g., ability descriptions, examples of activities,an anchored response scale, normed scores). The 15 abilities listed in Table 2 arebroadly defined in everyday terms so that self-estimates can be informed by every-day experience—firsthand and vicarious. Normed scores are reported for each ofHolland’s six types.

Some persons may question the use of ability self-estimates because theyassume self-estimates must be inaccurate. Certainly, one could question their usein college admissions or personnel selection. However, the context here is careercounseling. Regarding research, Mabe and West (1982) summarized the findingsof their (yet-to-be-replicated) meta-analysis of 55 studies involving self-evaluationsof ability (self-estimates) as follows: “It appears that under certain measurementconditions, self-evaluation of ability may closely correspond to performance oncriterion measures” (p. 294). (Also see Osberg & Shrauger, 1990.) Prediger(1999a) noted that the two types of ability estimates are subject to similar kindsof distortion (e.g., due to limited experience, response style, deliberate enhance-ment, or cheating). One must also consider whether the test estimates and self-estimates assess the same ability constructs—for example, spatial ability and cler-ical ability, as operationally defined by test items as versus examples of everydayactivities and experiences. Because one cannot assume that every test score andevery self-estimate is accurate, both may be the problem if correlations betweenthe two types of ability estimates are low. Validity comparisons are needed toaddress the accuracy concern noted above (see the next section).

Some persons may be concerned that self-estimates of abilities are subject toracial/ethnic and gender bias. Certainly, that is a legitimate concern regardingtest estimates of abilities. The test-relevant literature on the possibility ofracial/ethnic bias is too vast to discuss here. Regarding gender differences, theyhave been found, for example, on test estimates of mechanical and clerical abil-ities (e.g., see American College Testing, 1988; Psychological Corporation,1992). Perhaps these differences reflect bias. But as Anastasi and Urbina (1997)observed, “Differences in the experiential backgrounds of groups or individualsare inevitably manifested in test performance. . . . Insofar as culture affects behav-ior, its influence will and should be detected by tests” (p. 545). The same wouldseem to apply to self-estimates of ability. In any case, self-estimates (self-concepts)are prime topics for career counseling, during which they may be clarified andrevised. The only alternative is to discount them.


Validity of Self-Estimates and Test Estimates of Ability: A Comparison

The common sense, theory, and research summarized above indicate thatoccupations differ on a wide range of abilities. Because ability test batteries typi-cally assess relatively few work-relevant abilities, important abilities may be missed(e.g., sales, leadership, organization, artistic). In contrast, self-estimates can efficient-ly address a wide range of work-relevant abilities by drawing on self-knowledgebased on everyday experiences. But how do the validities of self-estimates and testestimates compare?

The validity data summarized below were obtained because of their relevancefor career planning—as versus predicting success in a specific occupation and soforth. As documented by Prediger (1998), a common way to determine an assess-ment’s career planning validity is to find the percentage of criterion group (e.g.,occupational group) members whose membership is predicted by the assess-ment’s scores—that is, the “hit rate.” This validation model asks, in effect,whether members of a given occupational group would have been referred tothat group by their scores. Thus, this validation model is consistent with a pri-mary use of career assessments—to identify personally relevant career options.

An ongoing, systematic survey of the vocational psychology literature over theyears, a Social Science Citation Index search (http://www.webofscience.com) onMabe and West (1982), and PsycINFO keyword searches (http://www.csa.com)on ability tests (etc.) and self-estimates (etc.) yielded no studies comparing thecareer planning validity of self-estimates and test estimates beyond the five sum-marized by ACT (2000). The results of those studies are briefly reported below.More extensive summaries and references were provided by ACT (2000).

Across the five studies, self-estimates for Abilities 7 through 15 in Table 2 wereobtained via an early edition of IWRA. Test estimates were obtained for Abilities1 through 6. The number of tests ranged from 6 (American College Testing,1988) to 10 (U.S. Department of Defense, 1995). To obtain a comprehensive setof work-relevant abilities, the self-estimates and test estimates were scaled andcombined to form six ability composites. (In one of the studies, self-estimateswere used instead of test scores.) The composites were based on the four abilitiesflagged for each of the six career clusters in Table 2. Criterion group hit rates fortest estimates, alone, and ability composites were obtained via discriminantanalysis (DISANL) followed by the application of Bayes’s rule (Nurusis, 1990).One of the studies also compared hit rates for test estimates and self-estimates forthe same six abilities (Abilities 1-6 in Table 2).

Four of the five studies involved students in Grades 11 or 12; the fifth involvedcollege students primarily in Grades 13 and 14. In one of the studies, 12thgraders were assigned to Holland-type criterion groups on the basis of vocationaleducation program after being screened for success and satisfaction with pro-gram. In the other four studies, students were assigned to Holland-type criteriongroups on the basis of occupational choice. (Prediger, 1998, summarizedresearch that supports the use of choice-based criterion groups.) They were asked


how sure they were that their occupational choice would still be their first choice1 year later. The response options were very sure, fairly sure, and not sure. In thestudy with the smallest sample, students giving the third response were excludedfrom the hit rate analyses. In the other three studies, those giving the second orthird responses were excluded. After screening on certainty of choice, samplesizes ranged from 356 to 1,620.

Across the five studies, criterion group hit rates for test estimates of abilitiesranged from 28% to 39%, with a median of 34%. (The chance hit rate was 17%.)Hit rates for the ability composites that included self-estimates ranged from 34%to 43%, with a median of 42%. The ability composites had higher hit rates (weremore valid) in each of the five studies. Thus, the comprehensive assessment ofwork-relevant abilities made possible by the inclusion of self-estimates increasedcareer planning validity beyond that obtained via test estimates typical of test bat-teries. For perspective, the ability composite hit rates are similar to those typical-ly reported in studies using Holland-type interest scales (e.g., see Swaney, 1995,for a summary).

It might be argued that test-estimate validity would have exceeded self-estimatevalidity if test estimates had been available for all 15 abilities involved in theabove studies. However, the results of the study that compared test-estimate andself-estimate hit rates for the same six abilities counter this argument. The test-estimate and self-estimate hit rates were 39% and 41%, respectively.

In summary, the results of five studies comparing the career planning validityof self-estimates and test estimates of work-relevant abilities show that using self-estimates improves on the validity of test estimates. Some might argue, however,that these results were obtained because the self-estimates simply reflect interests,which affect occupational choice. This argument is addressed in the section fol-lowing the sections on IWRA and UNIACT.

IWRA

Overview of IWRA

As noted above, ACT (2000) summarized the theory, research, and practicalconsiderations leading to the identification of the 15 abilities assessed by IWRA(see Table 2). Comprehensive coverage of Holland’s (1997) types was a primarygoal. The same publication also contains a copy of IWRA and an overview of itsrationale, development, scoring, and psychometric characteristics.

IWRA describes each of its 15 abilities in broad, everyday terms, and thedescriptions are accompanied by examples of common, ability-related activities.The goal is to elicit informed self-estimates (e.g., see Norris & Cochran, 1977)of the abilities—that is, self-estimates informed by experience (firsthand andvicarious); feedback from parents, peers, teachers, employers, and so forth; and


test estimates, when available. Organization ability, for example, is described asfollows:

Keeping track of tasks and details; doing things in a systematic way[boldface in original]. Consider your ability to keep to a schedule; to seewhat needs to be done first, second, etc.; to store things (pictures, clip-pings, tools, etc.) so they are easy to find. (ACT, 2000, p. 70)

Sales ability is described as “Influencing people to buy a product, service, ortake a suggested course of action [boldface in original]. Consider your ability tochange someone’s mind; to bargain; to make a sale; to persuade a group” (ACT,2000, p. 70).

IWRA is untimed and usually takes less than 10 minutes to complete. Level 1serves students in Grades 8 through 12; Level 2 serves college students andadults. Self-estimates for each of IWRA’s 15 abilities are reported on the same 5-point scale, and brief descriptions are provided for each scale position. For exam-ple, 5 = high (top 10%) and 4 = above average (top 25%). IWRA users indicatehow they believe they rank compared to persons their age. After self-estimateshave been provided for each of the 15 abilities, users are asked to review their esti-mates and make any revisions suggested by the review. Raw scores for IWRA’s sixcareer clusters (hence, Holland’s RIASEC types) are obtained by summing thepoints for the four abilities assigned to each cluster (see Table 2). The result is ascore for each of IWRA’s Career Cluster Ability Scales. Scale titles correspond tothe career cluster titles in Table 2.

Prediger (2002) summarized recent research showing that cross-sectionalsamples can exhibit substantial differences, from ability to ability, in the extent ofself-estimate “optimism.” These differences make the comparison of raw self-estimates of abilities problematic at best. For this reason, IWRA uses nationallyrepresentative, combined-sex norms to obtain stanines for the Career ClusterAbility Scales. For both DISCOVER and the CPS, WWM regions are deter-mined from the three highest stanines (as discussed in this article’s concludingsection). Standard errors of measurement (SEMs) are taken into account whenthis is done. (For IWRA reliability data, see ACT, 2000.)

Validity

The theory and research leading to the identification of IWRA’s 15 abilities arerelevant to its content and construct validity. As noted above, comprehensivecoverage of Holland’s (1997) RIASEC types was a primary goal. The relevanceof IWRA abilities for Holland’s types was recently examined, empirically, byPrediger (1999a). Using IWRA self-estimates obtained from two cross-sectionalsamples of 12th graders (Ns of 6l8 and 4,387), he found a good fit betweenIWRA’s factor structure and the D/I and T/P work task dimensions underlyingHolland’s hexagon. Thus, IWRA’s construct validity was supported. More impor-


tant, IWRA’s factor structure was shown to be similar to the factor structure ofoccupations and basic interests (e.g., see Prediger, 1996, and this article’s con-cluding section on the WWM).

Regarding IWRA’s criterion-related validity, the section comparing the careerplanning validity of self-estimates and test estimates reported the results of five hitrate studies involving an early edition of IWRA. In each study, the use of abilityself-estimates improved on the career planning validity of test estimates. Hit ratedata for the current edition of IWRA (two studies) are reported in the section fol-lowing the description of UNIACT.

Mean score profiles for occupational choice groups provide another way tolook at IWRA’s criterion-related validity. As reported by ACT (2000), the occu-pational choices of Grade 12 students in two cross-sectional samples were usedto establish RIASEC criterion groups. For both samples, all six criterion groupsscored highest on the Career Cluster Ability Scale corresponding to the group’sHolland type. For one sample, the hexagon location of the second highest scalewas adjacent to the Holland type of all six criterion groups. For the other sample,this was true for five of the six criterion groups. These results provide additionalevidence of IWRA’s criterion-related validity.

UNIACT

Overview of UNIACT

Relatively little will be said here about UNIACT because so much has beenwritten following its 1977 introduction and 1989 revision—for example, see the128-page technical manual (Swaney, 1995) and the article on using UNIACT incareer planning (Prediger & Swaney, 1995). UNIACT is part of five ACT programs/services and is completed by approximately 5 million persons each year. It differsfrom earlier editions of the ACT Interest Inventory in that it contains items thathave similar response distributions for females and males.

As with IWRA, coverage of Holland’s RIASEC types was a primary goal whenUNIACT was developed/revised, and scale titles correspond to the cluster titlesin Table 2. UNIACT items emphasize work-relevant activities (e.g., sketch pic-tures, fix a toy, help settle an argument) that are familiar to most persons—eitherthrough participation or observation (firsthand or vicarious). For reasons noted byKuder (1977), occupational titles and job duties are not used. Each of the sixUNIACT Career Cluster scales contains 15 items; a three-choice response for-mat (dislike, indifferent, like) is used. UNIACT is untimed and usually takes lessthan 15 minutes to complete. Level 1 serves students in Grades 8 through 12;Level 2 serves college students and adults.

The manner in which UNIACT’s six scores are reported differs across the serv-ices that use it. In DISCOVER and the CPS, scores are reported as staninesbased on nationally representative, combined-sex norms, and WWM regions are


determined from the three highest stanines. As with IWRA, SEMs are taken intoaccount. (For UNIACT reliability data, see Swaney, 1995.)

Validity

The procedures used to ensure that UNIACT’s items adequately addressHolland’s types are relevant to its content and construct validity. Evidence thatthese procedures were successful is provided by studies of UNIACT structure(i.e. construct validity) based on scale intercorrelations. As noted in this article’sintroduction and the discussion of IWRA, theory and research indicate that theD/I and T/P work task dimensions underlie Holland’s two-dimensional hexagon.Targeted principal components analyses (PRINCOs) of UNIACT scale intercor-relations for nationally representative samples of 8th, 10th, and 12th graders anda cross-sectional sample of adults were used to obtain scale correlations with thetwo work task dimensions. As reported by Swaney (1995), plots of the correlationson the two dimensions provided a good approximation of Holland’s hexagon.Similar results were obtained in separate analyses for females and males. (Alsosee Prediger & Swaney, 1995.)

More recently, Day, Rounds, and Swaney (1998) obtained good hexagonapproximations in analyses of UNIACT intercorrelations for 11th- and 12th-grade Caucasian Americans, African Americans, Asian Americans, MexicanAmericans, and Native Americans. All analyses were conducted separately forfemales and males. The above results appear to provide good support forUNIACT’s construct validity.

Regarding UNIACT’s criterion-related validity, more than 30 studies havebeen conducted, with occupation, occupational choice, or college major servingas the criterion. Both longitudinal and cross-sectional designs have been used,and samples have included 12th graders, 2- and 4-year college students, andemployed adults. Criterion group hit rates were obtained in 14 studies (23 sets ofRIASEC criterion groups; 68,000 persons) that used the highest UNIACT score(high-point code) to predict criterion group membership. Across the studies, hitrates ranged from 31% to 55% (median of 42%; chance = 17%). As documentedby Swaney (1995), these hit rates compare favorably with those of other interestinventories assessing Holland types.

Another way to look at criterion-related validity is to see how criterion groups,as a whole, score on a set of scales. Swaney (1995) provided three-letter (Holland)code summaries based on the mean interest scores of 648 criterion groups (N =79,040). Two thirds of the groups consisted of college students or adults, and fornearly half of the groups, the mean scores were obtained in studies with a longi-tudinal design. Approximately 75% of the criterion groups scored highest on theUNIACT scale appropriate to their group. The chance rate was 17%. Again,results compare favorably with other assessments of Holland types. (Also seePrediger & Vansickle, 1992.)


CONSIDERATIONS REGARDING INTEGRATION OF ABILITY AND INTEREST ASSESSMENTS

As noted above, some might argue that using ability self-estimates improves onthe career planning validity of test estimates because self-estimates simply reflectinterests, which affect occupational choice. Results of research involving bothIWRA and UNIACT, summarized below, address this argument.

Evidence of Uniqueness

Correlations between IWRA and UNIACT scales were reported by ACT(2000). Across four cross-sectional samples of high school students, correlationsfor parallel RIASEC scales were generally in the forties. Median correlationswere .40, .43, .43, and .45, respectively. These correlations suggest common vari-ance ranging from only 16% to 20%. However, they are based on one pair ofscales at a time (which is common in the research literature). Because careerassessment interpretations are generally based on multiscore profiles, theseinterindividual correlations do not reflect the degree of overlap in the occupa-tional options suggested by IWRA and UNIACT score profiles.

One way to estimate overlap is to obtain IWRA and UNIACT high-pointcodes for each member of a sample. Across the four samples, only about 35% ofthe students would have been referred to the same Holland type had their IWRAand UNIACT high-point codes been used in a search for occupational options.Thus, results of both types of IWRA-UNIACT analyses contradict the argumentthat ability self-estimates simply reflect interests.

Independent and Agreement Validity

Although validity data for ability and interest measures are typically reportedseparately, it is also important to know whether the scores commonly reported tocounselees have independent and agreement validity (Prediger, 1999b) when themeasures are used in tandem. Hence, IWRA and UNIACT high-point codeswere used to obtain RIASEC criterion group hit rates for 12th graders in the twosamples cited above. Students were assigned to criterion groups on the basis ofoccupational choice screened on certainty (as discussed earlier). For both sam-ples, the separate hit rates for UNIACT (44% and 41%) were somewhat higherthan for IWRA (38% and 35%). However, the IWRA hit rates for UNIACT miss-es (the independent hit rates) were 25% for both samples, which is substantiallybetter than chance (17%).

The same two samples were also used to determine agreement hit rates. WhenIWRA and UNIACT high-point codes agreed, the hit rates were 57% and 50%.


These hit rates were substantially higher than the hit rates for IWRA and UNI-ACT used separately (see above). Thus, in both types of analyses, the tandem useof IWRA and UNIACT improved on the validity of IWRA and UNIACT, usedalone. When these results are considered in the context of the evidence ofuniqueness summarized above, it is clear that IWRA’s ability self-estimates do notsimply reflect interests. (Also see Tracey & Hopkins, 2001.)

Interpretation of Profile Shape

As summarized by Prediger (1998), the literature indicates that scores based oninterest scales using Likert-type responses (as most basic interest scales do) aresubject to differences in the tendency, across persons, to provide like, dislike, andso forth responses—regardless of item content. This results in scores that reflectwhat is variously known as acquiescent style, response bias, or response style. Ina study involving 10 widely used interest inventories, Prediger obtained the fac-tor structure underlying the RIASEC interest scores of persons in 23 diverse sam-ples (N = 53,429). PRINCOs of the interest scores showed that all of the RIASECscales had high positive correlations with the first (and by far, the largest) princi-pal component. Across the 23 samples, the median correlation was about .65.Prediger noted that this response-style component directly affects interest profilelevel.

To determine whether interest profile level indicates strength of interest inaddition to response style, Prediger (1998) obtained criterion group hit rates forpersons with high and low UNIACT score profiles. For two cross-sectional sam-ples of 12th graders, RIASEC criterion groups were based on occupationalchoice screened on certainty. For an 8-year follow-up sample of adults who com-pleted UNIACT in Grade 11 or 12, RIASEC criterion groups were based on cur-rent occupation. If interest profile level reflects strength of interest, one wouldexpect higher hit rates for the high profile groups. However, the high and lowprofile groups had similar hit rates.

On the basis of these results, Prediger (1998) concluded that “there is no reasonto believe profile level indicates strength of interest” (p. 209), and he suggestedthat counselors interpret interest profile shape, not level. This appears to be espe-cially important when counselors use interest measures in tandem with measuresof ability and/or measures of ability self-confidence, self-efficacy, and so forth.(Regarding research on the meaning of IWRA profile level, see Prediger, 1999a.)

IWP

IWP obtains preferences for attributes on which occupations typically differ(e.g., extent of physical activity, training time, income, public contact). Work-


relevant interests and occupational attribute (OA) preferences (work values) aresimilar to some extent. But the similarities are far from identities. Following areview of related research, Dawis (1991) concluded that “the two domains aredistinct, if overlapping” (p. 847). (Also see Super, 1995.) In addition, assessmentsof these constructs have a different focus (Dawis, 2001). Interest inventoriesaddress the extent to which a person likes specific work-relevant activities, occu-pational titles, and so forth. Work value inventories, on the other hand, focus onthe importance (to the person) of specific OAs. In this regard, “wanting interest-ing work” can be considered to be a work value.

Overview of IWP

The 30-item IWP’s rationale, development, research support, and WWM link-age procedure are described by Prediger and Staples (1996), who also provided acopy of the inventory. (For reasons noted below, only 16 of the 30 IWP items areused in the linkage procedure.) IWP is embedded in DISCOVER’s Inventory ofWork-Relevant Values (IWRV), which is untimed and takes about 15 minutes tocomplete. It contains those IWRV OAs that tend to characterize an occupationacross work settings (see examples above) rather than OAs specific to a given worksetting (e.g., short commute, flexible hours, respected employer). Persons expresstheir preference for each IWP item (OA) by choosing one of four responseoptions: very important, somewhat important, not important, don’t want. Eachoption is defined. For example, the first option is defined as follows: “This char-acteristic is very important [boldface in original] to me. I really want this char-acteristic in my work” (Prediger & Staples, 1996, p. 52).

The literature review resulting in the identification of IWP OAs is relevant toIWP validity, as are the procedures used to obtain OA ratings for occupations andto identify the OAs used in the WWM linkage procedure (a topic addressedbelow). Research on IWP, IWRA, and UNIACT uniqueness, independent valid-ity, and agreement validity is under way. Regarding the uniqueness and validityof work value assessments in general, see Dawis (2001).

IWP-WWM Linkage Procedure

A PRINCO of OA ratings for a cross section of 497 occupations showed that,contrary to IWRA and UNIACT, IWP results could not be reported by Hollandtype. Hence, the IWP-WWM linkage procedure could not use WWM regions.On the basis of test-retest reliability data, five OAs were eliminated from the link-age procedure. Additional analyses (one PRINCO, two DISANL) identifiedseven OAs that were primarily education related. Because educational plans areseparately addressed by DISCOVER, these redundant OAs were candidates forexclusion from the WWM linkage procedure.


To identify OAs that could be used in the linkage procedure, a DISANL wasconducted on the OA ratings for 497 occupations grouped by the six career clus-ters paralleling Holland’s types (Table 2). Substantial and sensible differentiationof clusters was obtained for 12 OAs (e.g., occupations in the social service clus-ter had high ratings on public contact; those in the technical cluster had low rat-ings). Thus, IWP criterion-related validity was supported. The IWP-WWM link-age procedure uses the 12 OAs identified in the DISANL and 4 OAs includedon the basis of special considerations (e.g., high income, an education-relatedOA, was included because of its endorsement rate in two field studies involvinghigh school students).

Prediger and Staples (1996) described 12 guidelines used in developing theIWP-WWM linkage procedure. For reasons they noted, the expected utility(compensatory) decision-making model was used rather than the sequentialelimination model. (See Lichtenberg, Shaffer, & Arachtingi, 1993, for a com-parison.) Of the 16 OAs noted above, those to which users respond very impor-tant, somewhat important, or don’t want are included on the user’s “linkage list.”A user’s preference for a given OA is then compared with the OA’s rating for eachDISCOVER occupation, and an expected utility is assigned to each occupation,as determined from the nature of the match. Expected utilities for an occupationare then summed across all OAs on the user’s linkage list to obtain a total degree-of-fit score for the occupation.

After degree-of-fit scores are obtained for all occupations, mean scores are cal-culated for the occupations in each of the WWM’s 26 career areas. Career areasare ranked on those scores, and the top four career areas are reported to the user.Their location on the WWM can readily be compared with the map regionsreported for IWRA and UNIACT. Users wishing to explore any of IWP-relatedcareer areas can request a rank-ordered list of occupations that best fit their workvalues. DISCOVER, of course, provides descriptions of the occupations and rel-evant education/training.

INTEGRATION OF ASSESSMENTS VIA WWM

As illustrated by the case study, the WWM is used to link work-relevant abili-ties, interests, and values to each other and to occupational options. More gen-erally, it provides an overview of the work world—how groups of similar occupa-tions (career areas) compare with respect to basic work tasks. But, because themap was developed for use as a career planning tool, it is not intended to providea precise scientific statement. Rather, the goal is to strike a balance betweenwork-world complexity and simplicity of use. The same goal led to the develop-ment of two versions of the map—one for professionals (Figure 1) and one forcounselees (available to readers on request). The career areas and their locationson the two versions of the map are identical. The formats differ somewhat because


of their audiences (e.g., the one for counselees does not include Holland’sRIASEC types).

The empirically based WWM was developed in 1971 to 1972 and last updat-ed in 2000. Because the map’s bases in theory and research have been discussedin numerous publications over the years (e.g., ACT, 2000; Prediger, 1981, 1996;Prediger et al., 1993; Prediger & Swaney, 1995), only a brief overview is provid-ed here. The overview begins with a discussion of the D/I and T/P work taskdimensions that provide the foundation for the map. The WWM uses thesedimensions and its 26 career areas to summarize similarities and differencesamong occupations.

Basic Work Tasks Dimensions

As noted in this article’s introduction, the WWM is an extension of Holland’shexagon. Accordingly, the hexagon forms the core of the map, and Holland’sRIASEC types appear on the periphery with related career cluster titles. Researchreported in the publications cited above indicates that the bipolar D/I and T/Pwork task dimensions underlie Holland’s hexagon in the manner shown by thehexagon’s positioning on the map. The structural analyses summarized in thesections on IWRA and UNIACT are also relevant, as is research by Tracey(1997), who obtained D/I and T/P factors in a PRINCO of self-efficacy beliefsregarding work tasks. Recent research involving three diverse occupational data-bases is reported for the first time in the section that follows.

Most, if not all, occupations have some involvement with the four basic worktasks: working with data (e.g., facts, numbers, files, business procedures), ideas(e.g., insights, theories, new ways of saying or doing something), things (e.g.,machines, tools, living things, and materials such as food, wood, and metal), andpeople (e.g., people one serves, cares for, informs, leads, persuades). But usuallyonly one or two of the basic work tasks capture the primary nature of an occupa-tion. For example, an accountant may work with ideas, but the primary purposeis not to create ideas. Rather, it is to organize, record, verify, and so forth data ina systematic manner. Stated differently, when data-related work tasks are primary,ideas-related work tasks tend to be secondary. Similarly, when ideas-related worktasks are primary, data-related work tasks tend to be secondary. The same appliesto the bipolar things and people work tasks.

WWM’s Bases in Research

During the WWM’s 2000 update, career area content and map locations weredetermined from three databases: (a) expert ratings (Rounds, Smith, Hubert,Lewis, & Rivkin, 1998) on Holland’s six work environments for each of the 1,122occupations in O*NET, (b) JA data for 1,573 recency-screened occupations in


the DOT (U.S. DOL, 1991) electronic database update (DOT, 1999), and (c)Holland-type mean interest scores (four interest inventories, six samples) for per-sons pursuing 640 (sometimes overlapping) occupations. These databases pro-vided three diverse perspectives for the WWM update: (a) general nature of work(expert ratings), (b) detailed nature of work (JA data), and (c) interests of workers(mean interest scores).

The three databases were used to obtain D/I and T/P work task dimensionscores for each of the 1,122 O*NET occupations. For many of these occupations,scores for all three databases were available. For the D/I scores, correlations fordatabase pairs were as follows: rating-JA (.78), rating-interest (.78), and JA-interest(.75). For the T/P scores, the correlations were .81, .77, and .74, respectively.These correlations, which are unusually high for scores based on diverse assess-ment procedures, provide good support for the work task dimensions. As expect-ed, correlations between the D/I and T/P scores ranged near zero.

Initially, work task dimension scores were used to plot O*NET occupations ineach of the previous map’s 23 career areas. The assignments of occupations tocareer areas were then revised to increase career area homogeneity with respectto basic work tasks. In addition, some career areas were combined, and newcareer areas were created. After a second set of plots was obtained, occupationalassignments were again revised. This process continued until career area homo-geneity stabilized. Purpose of work and work setting were also considered. Figure2 arranges the career areas by career cluster and provides occupational examplesdrawn from DISCOVER.

How WWM Regions Are Obtained

As noted in the case study, a person’s IWRA and UNIACT scores for Holland’stypes are used to obtain WWM regions. The procedure begins with the applica-tion of formulas (originally presented by Prediger, 1981, and most recently dis-cussed by Swaney, 1995) that produce D/I and T/P scores through the use ofscore weights based on the hexagon’s geometry. Although the formulas can beapplied to all six Holland-type scores, DISCOVER and the CPS use only thehighest three scores—that is, three-letter (Holland) codes. These scores arereplaced with scores of 4, 2, and 1 in the formulas. Research (Prediger, 1981)showed that the D/I and T/P scores obtained from three-letter codes correlate inthe low .90s with D/I and T/P scores obtained via the six-score procedure.Because three-letter codes reflect profile shape rather than profile level, their useis in keeping with the considerations noted earlier in this article.

It would be possible to use D/I and T/P scores to report a person’s WWM loca-tion as an exact coordinate point. However, map locations are reported in termsof two or three map regions—in keeping with the level of score reliability and themap’s use in the early stages of career planning. Score reliability is also taken intoaccount in determining the rank order of the RIASEC scores. A complex set of


decision rules address instances of tied scores, and depending on the nature ofthe ties, split map regions may be reported. When score profiles are flat, or con-flicting Holland types are tied for highest (e.g., R, A, E,), no map regions arereported.

Table 1 shows the relationships between three-letter codes and formula-basedmap regions. Because there are 120 three-letter codes and only 12 map regions,the same map regions can be associated with different three-letter codes. Predigerand Swaney (1995) explained how map regions reflect the configuration andinteraction of scores for Holland’s types, and they noted that this might best beunderstood through use of Miller’s (1985) graphic mapping procedure. As illus-trated by Prediger et al. (1993), the mapping procedure can be used to helpcounselees see (literally) how their WWM regions were obtained.

Implications for Career Counselors

With the aid of Table 1 and related materials, the WWM can be used by any-one who wishes to integrate career assessments that report scores for Holland’stypes (e.g., those discussed in this journal issue) and link them to career options.Full-sized copies of the map, the “list,” and career area charts that group the 555DISCOVER occupations by career area and education/training level are available,at no charge, from the author. Of course, integration and linkage is automatic forusers of DISCOVER and the CPS. As summarized in this article, DISCOVERand the CPS assess work-relevant abilities (IWRA) and interests (UNIACT). DIS-COVER also assesses work-relevant values (IWP). The CPS uses IWRA andUNIACT. IWRA makes a unique contribution to both services because it assessesthe wide range of abilities relevant to work-world-comprehensive career explo-ration and planning.

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Documents

Abilities Interests and Values Their Assessment and Their Integration via the World-of-Work Map