Field investigation of the relationship among adult curiosity, workplace learning, and job...

HUMAN RESOURCE DEVELOPMENT QUARTERLY, vol. 11, no. 1, Spring 2000 © Jossey-Bass Publishers 5

F E A T U R E

Field Investigation of theRelationship Among AdultCuriosity, Workplace Learning,and Job Performance

Thomas G. Reio Jr., Albert Wiswell

Although curiosity is considered to be a critical motivator of optimal class-room learning among children, little empirical information exists aboutcuriosity’s possible roles in adult learning, especially in the workplace. In thisexploratory study, we hypothesized that adult state and trait epistemic(knowledge-seeking) curiosity would influence workplace learning and jobperformance. The subjects were 233 service industry employees who wereadministered four curiosity instruments, an instrument designed to ascertainsocialization-related learning (a type of workplace learning), and a job per-formance survey. Through structural modeling techniques, we demonstratedthat both state and trait curiosity influenced technical and interpersonal jobperformance through the mediational effects of socialization-related learn-ing. Overall, these findings support the notion that curiosity-induced behav-iors such as information seeking play a meaningful role in workplace learningas well as in job performance. Implications for adult learning, organizationalsocialization, and job performance are discussed.

In important learning environments such as the workplace, curiosity andperpetual learning help individuals make sense of and use increasing amountsof novel and discrepant information. As Kozlowski (1995) and other researchers(such as Dixon, 1997; Senge, 1993) have noted, from the moment employeesprepare to apply for a job, through the process of learning the complex requi-site technical and interpersonal skills demanded by their positions, to the timethey surmount the daily challenges of their ever-changing work environment,they need to be always ready to construct new meanings and new knowledge,and therefore to learn.

Berlyne (1960) considered epistemic curiosity to be an information- andknowledge-seeking activity that is situationally aroused when individuals are

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confronted with information that somehow challenges their beliefs, attitudes,or knowledge. The individuals are then motivated to explore their environ-ment for information that will resolve the resulting conceptual conflict, ulti-mately culminating in the acquisition of new learning and knowledge. Thus,Berlyne essentially considered curiosity to be a temporary motivational statethat stimulates information and knowledge seeking. Day (1971) extendedBerlyne’s seminal work on curiosity by proposing that epistemic curiosity alsoexists as an enduring personality trait, that is, it is plausible that certain indi-viduals find more situations to be more curiosity inducing and for a longertime than other situations, which has considerable research support (for exam-ple, Boyle, 1989; Naylor, 1981; Spielberger and Starr, 1994). Furthermore,Malone (1981) proposed that it might be more meaningful to think of epis-temic curiosity as cognitive because it is motivated by a desire to “bring better‘form’ to one’s knowledge structures” (p. 363). He also noted that there was asensory type of curiosity that involved the attention-attracting value of sensorystimuli such as light and color (for example, colorfully illustrated textbooksand animated computer programs).

The business literature has consistently extolled Berlyne’s (1960) state epis-temic curiosity to be worthy of interest and encouragement with respect toworkplace learning. Robinson and Stern (1997), for instance, associatedcuriosity with self-initiated activity, diverse stimuli, and ultimately, corporatecreativity. Sonnenberg and Goldberg (1992) stressed the importance of foster-ing curiosity in workplace learning situations because it encourages employ-ees to investigate and learn, and thereby increases their openness to change.Similarly, Senge (1990) proposed that “organizations learn only through indi-viduals who learn” and held that a deep inquisitiveness (curiosity) is part ofthe lifelong generative process of personal mastery, one of the five core disci-plines of the learning organization (p. 142). By harnessing and directing thiscuriosity, employees become more committed to an understanding of reality,which becomes part of their organization’s creative process. Alternatively,Tjosvold and Field (1982) noted that managers can affect decision makingby structuring the manner in which group members are allowed to reach deci-sions. Groups instructed to be in a controversy condition searched for moreinformation and explored problems in greater depth (exhibiting more stateepistemic curiosity) than those instructed to be in a concurrence condition. YetTjosvold and Field’s work is the only study noted thus far, and one of the fewstudies overall, that empirically examines the possible influences of curiosity,a potentially powerful adult learning motivator (Long, 1989), on informationseeking and learning in the workplace.

The business literature indicates anecdotally that curiosity is a valuableworkplace personality trait (for example, Giles, 1989; Griffiths and Robertson,1991), but no one has investigated whether this is actually so. Therefore, thereis a need to explore whether being curious plays a previously unknown bene-ficial role in facilitating workplace learning, adaptation to change, and jobperformance.

One important area of workplace learning is the learning associated withthe socialization of new employees (Saks, 1995). Specific job knowledge,acculturation, and interpersonal norms are derived in large part from mentors,supervisors, and coworkers (Copeland and Wiswell, 1994). Accordingly, newemployees must arguably be somewhat curious and therefore actively involvedin gathering the information they need to master the nuances of their positions.Still, although the process of socializing new employees includes a major learn-ing component, little has been done to determine what might motivate thatactivity. Curiosity would seem to merit special attention due to its ability tostimulate and foster learning.

Finally, it seems likely that the ability to learn the technical and interper-sonal skills needed to adapt to a new job is ultimately related to job perfor-mance. Although this is an intriguing notion, the relationship betweensocialization-related learning and workplace job performance has not been thor-oughly examined (Saks, 1995); the possibility that there is a direct relationshipbetween curiosity and job performance has received even less attention.

Review of the Related Literature

Curiosity, Adult Learning, and Human Resource Development. Reeve’s(1989) exploratory laboratory study found support for an interesting model inwhich state epistemic curiosity mediated the relationship between complexstimulus patterns and interest. Reeve concluded that curiosity served a vitalrole in intrinsic motivation. In subsequent work, Reeve (1992) proposedanother model of intrinsic motivation in which curiosity was the initial vitalstep in a two-step process of developing intrinsic motivation. In this model, ifindividuals find an activity to be either novel or interesting, their curiositymight be aroused and intrinsically motivated behavior might occur; otherwise,they might shift their attention to another activity. Citing the work of severaldevelopmental theorists (such as Vandenburg, 1978), Reeve argued thatadults apply the practical skills they developed as a child through curiosity-,exploration-, and play-provoking activities to discovering how adult environ-ments could be changed.

In a large longitudinal study of adults ranging from seventeen to ninety-two years of age (N � 2,436), Giambra, Camp, and Grodsky (1992) observedthat curiosity or information seeking and interest in learning did not lessen aspeople aged. Older adults simply differed from younger adults with respect tohow they sought information. Younger adults preferred to learn through directinteraction, while older adults preferred to learn through more passive means,such as reading. Overall, Giambra, Camp, and Grodsky considered thisobserved stability in information seeking across the adult lifespan to be quiteconsistent with the lack of age differences and changes observed in the ideasfacet of Costa and McCrae’s (1988) Openness to Experience trait scale.(Giambra, Camp, and Grodsky proposed that this scale could be considered ageneralized curiosity measure.)

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Confessore and Kops (1998) stressed the notion that “self-directed learn-ing plays an integral role in maintaining and developing learning organizations”because it is an integral part of a learning organization’s ability to reinvent itself,adapt, and learn in the face of new challenges (p. 373). They emphasizedthe importance of self-directed learning in developing people’s capacity tolearn, which is fostered in the favorable learning climate of a learning organi-zation. In a slightly different vein, Tough (1969) and Caffarella (1993) viewedself-directed learning as primarily the type of learning through which individ-uals retain control and responsibility for their own learning in general. In hisinvestigation of the reasons for adult participation in self-directed learningprojects (projects in which one persists with a learning endeavor for sevenhours or more to gain specific knowledge and skill), Tough discovered that sat-isfaction of curiosity was the second most commonly cited motivator. Further,Long (1989) claimed that Berlyne’s (1960) concept of epistemic curiosity is“particularly useful in explaining self-directed learning” because it equatesincreasingly successful learning experiences with the acquisition of advancedknowledge-seeking behavior (p. 3). Likewise, Candy (1991) claimed that byemphasizing self-directed learning activities during instruction, curiosity wouldbe aroused, leading to an “increase [in] information-seeking activities” (p. 57).Finally, Reio and Ward (1998) proposed that curiosity has a beneficial role inpromoting productive, Web-based, self-directed learning activities by foster-ing a healthy outlook toward learning and learning more, which would beespecially relevant for inexperienced, older workers.

In a qualitative research study, Cavalieri (1996) found that curiosity drovethe problem-solving activities of famous inventors. She noted that the Wrightbrothers, upon experiencing many failures in developing the airplane, weredriven by their curiosity to solve their engineering problems and to try and tryagain to make their ideas work. In another example, she discussed Art Jones,who was driven primarily by his curiosity to figure out how to build the bestexercise equipment in the world (Nautilus).

Researchers have noted that the need to manipulate curiosity is one of themotivational instructional strategies used in formal workplace training. In hismodel for designing motivational instruction, Keller (1983) identified curios-ity and interest as the first of four categories of design strategies for motiva-tional instruction. He stressed that designing for “moderate doses” (p. 405) ofcuriosity in training both arouses people’s attention (perceptual curiosity;Berlyne, 1965) and stimulates information-seeking and problem-solvingbehaviors (epistemic curiosity). Berlyne’s concept of perceptual curiosity isquite similar to Wlodkowski’s (1985) notion of the need for stimulation dur-ing adult learning endeavors. (Wlodkowski’s motivational model for adultlearning consists of six parts: attitude, needs, stimulation, affect, competence,and reinforcement.) Wlodkowski proposed that perceptual stimulation isessential to avoid boredom and to sustain the engagement of learners with thematerial to be learned; without it, he wrote, attention wanes and motivational

learning is lost. Finally, Gagne and Medsker (1996), in a summary of the keyconsiderations in designing training experiences, claimed that curiosity isimportant because it fosters motivation for learning; but they cautioned thatoveremphasizing curiosity-inducing instructional strategies could cause thelearner to waste time on unnecessary activities. This could be especially truein novel contexts where learners might initially need a little more structure inorder to focus on the task at hand.

Although curiosity has clearly received the various but limited attentionof researchers in education, business, and psychology, empirical research isneeded to clarify and support the possible relationships between curiosity andvarious types of organizational learning.

Curiosity and Organizational Socialization. Much of the research on thenature of the socialization process has concentrated on employees’ adoptionof organizational values, goals, and attitudes (for example, Schein, 1988). Morerecently, however, more emphasis has been placed on viewing the process froma learning perspective (that is, socialization-related learning). Ostroff andKozlowski (1992) and other researchers (such as Kozlowski, 1995; Millerand Jablin, 1991) have claimed that organizational socialization should beviewed primarily as a process of formally and informally communicating andtransmitting an organization’s technical job knowledge, culture, norms,and procedures. New employees focus on acquiring the information they needto learn the technical and interpersonal skills necessary for their new positions.This technical information comes from such diverse sources as official organi-zational literature, observation, and experimenting with new behaviors.Through mostly informal means, new employees need to be involved in gath-ering the information they need to learn their jobs and adapt to changedconditions. Therefore, organizational socialization is largely an information-seeking process that relies heavily on new employees taking a proactive role inacquiring the information they need to resolve uncertainties and master thetechnical and interpersonal skills required for their positions.

To resolve their uncertainties about new job settings, the relevant featuresof those settings, and how to accomplish required tasks, individuals must learnthrough “trial-and-error, watching, asking, reading, and practice” (Wiswell,1993, p. 1). This condition applies to new employees as well as seasoned work-ers, because socialization-related learning occurs each time employees obtainnew jobs and enter new organizations. It also applies when employees switchto another department, are promoted, get a new coworker or boss, learn a newjob task, or even go back to school (Morton, 1993; Schein, 1988).

What possible role, then, does curiosity have in the socialization process?Berlyne (1960) posited that epistemic curiosity manifests itself in three ways:observation, consultation, and thinking. Berlyne claimed that during the firstof these activities, observation, individuals place themselves in situations thatfoster learning. He cited examples ranging broadly from seeking gossip tothe systematic observations and experiments of science. During consultation,


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individuals choose to obtain verbal and written information. Examples includeasking questions of coworkers or supervisors, reading organizational literature,and writing letters. Finally, there is thinking. Berlyne considered epistemicthinking to be part of productive or creative thinking, which in this sense refersto gaining permanent possession of new knowledge. (In essence, Berlyne issuggesting that curiosity is a precursor to creativity.) Productive thinking dif-fers significantly from reproductive thinking, in which previously learned infor-mation is called up to help deal with problematic situations.

New employees, who are often in a high state of arousal, are motivated byfeelings of uncertainty, tap many information sources, and employ more strate-gies to learn the interpersonal and technical requirements of their jobs. Amongnewcomers’ socialization-related learning endeavors, Berlyne’s (1960) collativevariables (that is, novelty, uncertainty, conflict, surprisingness, and complex-ity) are particularly relevant. New employees more readily explore novel stim-uli, reflect on complex procedures, remember surprising information, andponder conflicting data. Through these activities they assign meaning to theirexperiences. All of these manifestations of epistemic curiosity and exploratorybehavior are accompanied by observational, consultative, and thinking tacticsthat result in vital learning. Without this learning, newcomers are not as likelyto be socialized (Copeland and Wiswell, 1994), turnover is more likely, and theorganization will more probably suffer.

Saks (1995) informed us that emphasizing formal training during thesocialization process “may increase the rate and speed of newcomers’ adjust-ment and may have lasting effects on future attitudes and [job-related] behav-ior” (p. 223). Relying heavily on Bandura’s (1986) work, Saks claimed that byattending to possible informational sources such as personal mastery and vic-arious learning (quite similar to Berlyne’s [1960] notion of observation), orga-nizations and HRD practitioners can identify ways to strengthen newcomers’self-efficacy and adjustment to work. Attitudes and job-related behavior shouldalso be seen as informational sources in informal learning situations, becausethe socialization process is in large part an informal workplace learningendeavor (Copeland and Wiswell, 1994). Thus, by focusing on improving bothformal and informal learning opportunities, HRD practitioners may be able toenhance newcomers’ socialization-related learning, thereby fostering more pos-itive work-related behaviors and enhancing newcomers’ adaptation to theirjobs. Although it seems that promoting this learning should help newcomersmaster the demands of their jobs and ultimately improve their performance,this relationship has not been adequately explored.

Curiosity and Job Performance. One can hardly argue against the notionthat continuous learning is a necessary component of a workplace that is capa-ble of adroitly handling change. One facet of learning in the workplace couldbe the degree of individuals’ (especially newcomers’) successful socialization-related learning (Ostroff and Kozlowski, 1992; Saks, 1995). Another manifes-tation of learning could be the performance of one’s job, because it is unlikely

that individuals could perform their jobs for any period without someprior and continuous learning, and thus knowledge renewal (Dixon, 1997;Miller and Jablin, 1991).

McCloy, Campbell, and Cudek (1994) defined performance as “behaviorsor actions that are relevant to the goals of the organization in question” andwrote that it “is multidimensional” (p. 493). Motowidlo and Van Scotter (1994)identified what they considered to be two conceptually satisfying dimensionsof job performance—task performance and contextual performance. The firstdimension, task or technical job performance, is the behavior associated withmaintaining and servicing an organization’s technical core. It refers to the directtransformation of an organization’s raw goods into the goods and services thatit produces. Examples would be teaching a college class, cashing one’s pay-check at a bank, operating a printing press in a newspaper plant, or plantinga tree. By contrast, the second dimension, contextual or interpersonal job per-formance, is a function of one’s interpersonal skill knowledge, that is, it sup-ports the broader social environment in which the technical core mustfunction. Specifically, interpersonal job performance is most closely related tohelping and cooperating with desirable organizational behavior.

Although no investigation has been undertaken to explore epistemiccuriosity’s possible influence on workplace job knowledge, Loewenstein (1994)has examined the relationship between curiosity and perceived knowledge ina laboratory setting. Interestingly, he found support for the notion that curios-ity and knowledge are positively related and that curiosity could even increaseas employees accumulate knowledge in a particular domain.

To summarize, we have reviewed the existing literature and discussed abroad range of human curiosity research. Curiosity was found to be an essen-tial component of adult learning, yet there has been little empirical investiga-tion of its role and relevance in adult learning contexts such as the workplace.We also reviewed the socialization literature and found that the organizationalsocialization process has been increasingly recognized as a learning process inwhich employees proactively seek technical and interpersonal information tolearn the ropes of the organization. Interestingly, we found little researchexploring the conceivable relationships between socialization-related learningand a meaningful indicator of workplace learning—job performance. No priorresearch was encountered that investigated curiosity’s role in this learningprocess as well.

Although some support exists for the relationship between curiosity andclassroom learning performance, no research was detected that related work-place job performance to adult curiosity.

Our literature review revealed a very real need to investigate the possibleinfluence of curiosity on adult learning in general and on workplace learningin particular. This new information would perhaps alert the field to the impor-tance of curiosity in motivating and directing adult learning, and afford sup-port for fostering curiosity and learning in the workplace.


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Purpose of the Study and Research Hypotheses

Deming (Senge, 1993) declared that people’s intrinsic motivation and curios-ity to learn may be thwarted as they mature, especially in workplace settings,with particularly detrimental effects on both their creativity and theirconcomitant capacity to accommodate change. A more thorough understand-ing of curiosity’s role in organizational learning (such as, socialization-relatedlearning) and job performance would aid our comprehension of curiosity’sfunction in improving formal and informal organizational learning, and facil-itate its promotion. Such knowledge could assist practitioners as they promotethe adaptation and socialization of employees to the workplace through train-ing and employee development in general. Fostering curiosity and learningcould improve employee job performance. Consequently, the purpose of thisexploratory research was to investigate empirically the possible roles and influ-ences of adult state and trait curiosity and socialization-related learning onworkplace job performance.

Although this was an exploratory study, our probing of the literature ledus to believe that the following specific hypotheses were warranted (Holtonand Burnett, 1997):

HYPOTHESIS 1. There is a positive, statistically significant relationship between adultstate and trait epistemic curiosity and socialization-related learning.

HYPOTHESIS 2. There is a positive, statistically significant relationship between adultstate and trait epistemic curiosity and job performance.

HYPOTHESIS 3. The influence of adult state and trait epistemic curiosity on thevarious dimensions of job performance is mediated through socialization-relatedlearning.

Research Method

This section describes the sample, instrumentation, and procedure utilized toinvestigate the hypotheses.

Subjects. The combined sample (N � 233) consisted of 152 men and81 women, ranging from seventeen to sixty years old, from four companies inthe service industry: one small (n � 25) and one midsized (n � 117) land-scape company, a mid-sized division of a Fortune 100 computer services com-pany (n � 70), and a small printing company (n � 21). All four of thesecompanies from the mid-Atlantic region of the United States were well knownand well respected in their respective parts of the service industry.

Although there were many different job titles, all participants were placedinto three broad categories for the purpose of the study: managers, serviceworkers, and administrative aides. Managers (individuals whose primary

responsibility is to supervise other employees in order to attain organizationalobjectives) were 15 percent of the sample, service workers (individuals whoactually provide the “real” service an organization has to offer in direct day-to-day contact with internal and external customers and who have no supervi-sory requirements) made up 70 percent, and administrative aides (individualswhose primary responsibilities are to ensure smooth interoffice paper flow andto field and direct customer inquiries) constituted 15 percent.

The mean age of the sample was 32.5 years (SD � 8.8). A majority(86 percent) of the participants were Caucasian, 9 percent were African Amer-ican, 3 percent were Hispanic, and slightly more than 1 percent were Asian.Almost 64 percent of the subjects earned less than $30,000 per year; only22 percent earned more than $40,000 annually. Roughly 62 percent of the sam-ple had at least some college experience. Overall, the typical participant was amale Caucasian under the age of forty, with at least some college, earned lessthan $30,000 per year, and had less than two years of tenure on his present job.

Instrumentation. A number of instruments were employed to explore thevariables of interest in this study. Overall, four curiosity, one workplace learn-ing, and one job performance instrument were used.

Curiosity Measures. A wide range of measures reported in the literature wereinvestigated. Adult curiosity scales were found most commonly to have beendesigned as self-report measures of curiosity as either a motivational state (forexample, Naylor, 1981) or a personality trait (for example, Zuckerman, 1979),in efforts to operationalize the central construct of a certain theoretical position.From our examination of the literature, four curiosity scales were selected thatmost closely met the needs of the exploratory nature of our study and the con-ventional reliability and validity standards of our field.

Although we considered the reported reliability and validity claims of eachinstrument’s authors in our preliminary decision-making processes, Boyle’s(1983) excellent critical review of the curiosity test development literatureserved as the final basis for our eventual measure selection. In particular, Boyleprovided considerable evidence for the inter-item reliabilities (.70 to .93) anddiscriminant and construct validities of each instrument selected for the study,yet he expressed some reservations about each measure’s apparent test-itemtransparency. He called for designing test items that more objectively measurethe curiosity construct “but at the same time have no immediately obvious con-nection with curiosity” (p. 391). He noted that this would serve the purposeof controlling respondent susceptibility to response sets such as social desir-ability and acquiescence, thereby strengthening the validity of the participants’responses. Ainley (1987) provided further support for the discriminant valid-ity of all but one of the curiosity instruments we selected when she noted thateach of the scales, when correlated with a verbal and numerical abilities test,had “resulting correlations [that] were all close to zero [.00 to .21]” (p. 56).She concluded that it would be reasonable to deduce that the curiosity mea-sures were not simply measuring general ability.


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Although we concede that using four scales adds considerably to the com-plexity of the study, the preliminary nature of this inquiry, we believe, demandsthe use of a number of well-studied instruments to provide thorough coverageof the range of curiosity behaviors reported in the literature. Thus, based onthe preponderance of research evidence supporting each measure’s use, curios-ity levels were assessed with the following paper-and-pencil self-report scales:the Melbourne Curiosity Inventory (MCI; Naylor, 1981), the State-Trait Per-sonality Scale (STPI; Spielberger and others, 1980), the Sensation SeekingScale–Form V (SSS-V; Zuckerman, 1979), and the Novelty Experiencing Scale(NES; Pearson, 1970).

We also acknowledge that it is quite likely that the MCI and the STPIare moderately positively correlated, especially because the subscales of bothstate-trait curiosity instruments loaded similarly on the same general curiosityfactor in Olson and Camp’s (1984) factor-analytic study with a sample of col-lege students. Notwithstanding, the researchers did not report the actualcorrelation between the two measures. We consider this information vitalbecause the STPI can be used only by permission of the instrument’s authorfor research purposes. Conversely, the MCI’s ready availability would facilitatefurther investigations into adult curiosity. This possibility alone, we believe,merits the measure’s inclusion in our study.

The MCI is a forty-item, self-report questionnaire of both state and traitcuriosity (twenty items in each subscale). The state curiosity measure asksrespondents to designate how they feel on a 4-point scale (ranging from almostnever to almost always) at a particular moment, while the trait scale asks howthey feel generally. Examples included items such as “I want to know more”and “New situations capture my attention.” Again, the STPI is similar to theMCI in that it has both state and trait curiosity scales (4-point scale, ten ques-tions each), in addition to ten-item state and trait subscales of anger and anx-iety (not examined in this study). The curiosity subscale includes statementssuch as “I am in a questioning mood” and “I feel stimulated.”

The SSS-V is a forty-item scale. Respondents are asked to assess whetherthey best like either choice A or choice B for each item. The test consists of fourfactor subscales: disinhibition, boredom susceptibility, thrill and adventureseeking, and experience seeking. Zuckerman, Ulrich, and McLaughlin (1993)defined sensation seeking as “the need for varied, novel, and complex sensa-tions and experiences and the willingness to take physical and social risks forthe sake of such experiences” (p. 563). Thus this type of curiosity is not theinformation seeking or epistemic kind of curiosity; rather, it arises as a resultof boredom or the need for stimulation (Zuckerman, 1979). Still, it is entirelypossible that learning could be a by-product of participating in sensation-seeking activities such as mountain climbing or exploring new places. The dis-inhibition subscale represents the seeking of sensation through sexual activity,partying, and social drinking (for example, “I like wild parties”). Boredom sus-ceptibility reflects a low tolerance for boredom and restlessness when there isa lack of varied stimulation in the environment (for example, “When you can

predict almost everything a person will do and say, he or she must be a bore”).Thrill and adventure seeking describes the desire to seek sensation throughunusual or sometimes risky physical activities such as mountain climbing(for example, “I often wish I could be a mountain climber”). The fourth sub-scale, experience seeking, measures the seeking of unusual experiences andsensations and the unconventionalness of an individual’s lifestyle (for exam-ple, “I like to explore a strange city or section of town by myself, even if itmeans getting lost”).

The NES is an eight-item scale consisting of four twenty-question sub-scales measuring the subjects’ propensity to seek novelty. This tendency is bro-ken down into four scales on the basis of the source of stimulation and the typeof subjective experience. The source of stimulation can be internal or externalto the individual, and the subjective quality of the experience can be cognitiveor sensational. Pearson (1970) combined these classifications into a two-by-two model, yielding four forms of novelty seeking: external cognitive, internalcognitive, external sensation, and internal sensation. Individual examples ofeach subscale included asking the respondents whether they like or dislike“finding out how a carburetor on a car works,” “thinking about why peoplebehave the way they do,” “scuba diving in the Bahamas,” and “letting myselfgo in fantasy before I go asleep,” respectively.

Socialization-Related Learning Measures. Socialization-related learning wasour operationalization of workplace learning and was determined with a mod-ified version of the Workplace Adaptation Questionnaire (Morton, 1993), a self-report, twenty-two-item instrument consisting of three subscales measuringemployee socialization-related learning and one subscale measuring satisfac-tion with learning experiences. Participants indicated the extent to which theyagreed with each item on a five-point scale ranging from strongly disagree tostrongly agree. The four subscales are job knowledge, acculturation to the com-pany, establishing relationships, and satisfaction with learning experiences. Thefirst three subscales were designed to measure, in essence, the learning associ-ated with the socialization process and are based on Morton’s extensive factor-analytic research, in which a large number of socialization-related learningitems derived from the literature were included in a pilot study and subse-quently screened using a retention criterion of .5 and above-factor loadings.Three factors emerged: establishing relationships, acculturation, and job knowl-edge. We modified the job knowledge subscale by adding three of the next-highest loading items on that factor, resulting in an eight-item subscale toprovide a technical skill balance to the instrument. We believed that the othertwo learning subscales were primarily tapping interpersonal skills. Thus,Morton’s research indicated that the socialization process, especially for employ-ees with less than two years of tenure on a particular job, consisted of threebasic aspects, all building on the others. First, information is proactively soughtthrough developing relationships with coworkers; second, direction and infor-mation are sought from supervisors; and finally, as a result of actively seekinginformation through coworkers and managers, job proficiency develops.


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The job knowledge subscale refers to the extent to which respondentsreported mastering the tasks of their jobs (such as, “I can complete most ofmy tasks without assistance”). Acculturation to the company is a five-itemsubscale measuring the extent to which employees have learned the norms, val-ues, and culture of their organizations (for example, “I know what the accept-able image is for my organization”). Establishing relationships, the five-itemthird subscale, assesses employees’ ability to identify coworkers who can pro-vide useful information or who know their way around the organization (forexample, “I know which of my coworkers are interested in helping me”).Finally, the four-item satisfaction with learning experiences subscale evaluatesemployees’ satisfaction with their learning experiences at the organization (forexample, “I am satisfied with the feedback I have received about my perfor-mance on the job”). This final subscale was not relevant to our study.

Examining the instrument through our preliminary factor-analytic workprovided substantial support for continued use of the instrument. Internal reli-abilities and item-factor loadings on each subscale were virtually identical tothose reported by Morton (1993), providing evidence for the instrument’s sub-scale factor stability and generalizability in her research conducted with work-ers in a government agency (see Reio, 1997, for a detailed examination of herinstrument).

Job Performance Measures. Job performance and its two dimensions, tech-nical and interpersonal performance (Motowidlo and Van Scotter, 1994), wereassessed with a self-reported questionnaire developed for our study. Thisinstrument was based on Reeve’s (1989) interesting exploratory research mea-suring task performance in a laboratory setting. The six-item instrument con-sists of three two-item subscales: overall job performance, technical jobperformance, and interpersonal job performance. Sample items include,“How would you rate your overall job performance?” “How would you rateyour overall level of technical skill knowledge?” and “How would you rate youroverall level of interpersonal skill knowledge?” The other question in each sub-scale asks respondents to compare their overall job performance and techni-cal and interpersonal skill knowledge to that of their peers. Thus each of thesix questions asks employees how they perceive their current performance ontheir jobs. The total instrument’s reliability was .90.

Procedures. Due to the recommendations of Ainley (1987) and Langevin(1971, 1976), we resolved to use strictly self-reported paper-and-pencil mea-sures of the variables of interest in our study. Langevin and Ainley bothreported considerable confusion in prior curiosity research when teacher andpeer ratings, performance ratings, and self-report measures were utilized.Teachers’ and peers’ ratings of curiosity, for instance, were often highly corre-lated and thus confounded with intelligence. Langevin (1971) also reportedconsiderable ambiguity when comparing the results of using self-report curios-ity measures to the results of using curiosity performance measures that requireparticipating in some curiosity-inducing task. To control for these problems,

therefore, Ainley stressed the use of one type of curiosity measure for adultcuriosity research, especially because she held that self-report curiosity mea-sures possess the most solid theoretical basis. Hence, for the sake of reliablecomparison among all of our designated research measures, we deemed it mostsensible to adhere to Ainley and Langevin’s logical and reasonably validatedprotocol in which all of the research measures should be of one type.

Because we employed self-report measures exclusively in our research, wealso needed to stress that each of these research measures was based on therespondent’s perceptions, which could introduce obvious limitations intothe findings of the research (for a well-researched review of the limitations ofself-reports and how to correct them subsequently, see Schwarz, 1999). Job per-formance, for example, could fairly be considered perception of job performance,yet all of the measures could be carefully thought about in this way because oftheir self-report nature. Thus, while affirming the implicit perception-basednature of the research instruments, for the sake of consistency of comparisonwith previous research and clarity, we do not explicitly refer to them as such.

Reio administered the four curiosity tests, the socialization-related learn-ing and job performance measures, and a demographic survey at the partici-pants’ places of work. The four companies all participated on the condition ofanonymity and were provided with a summary of the results. Employees wereinformed that their participation was voluntary and that their individualresponses would be completely confidential.

All of the instruments were fastened together into one booklet, with thedemographic survey on top, followed by the NES, STPI, WAQ, SSS, job per-formance instrument, and MCI. After the booklets were distributed, eachrespective instrument’s directions were discussed and clarified. The subjectswere then asked to complete the measures in the order in which they appearedin the booklet, and they were informed that they would not be timed.

The battery of instruments was administered at one sitting to the smallprinting company and to the small landscape company (to a group of twenty-one and twenty-five participants, respectively). Due to time and logistical con-siderations at the larger companies, groups of roughly twenty-five peoplecompleted the test battery at each particular company, once a week over aperiod of six weeks. Overall, the administration time for the test battery rangedfrom thirty to forty-five minutes per person.

Combination of the Sample. Kline (1993) and Tabachnick and Fidell(1989) recommended using caution when pooling results from diverse groups.Yet the benefit of using diverse groups is an increase in sample size. Accordingto Tabachnick and Fidell, if, for example, “men and women produce the samefactors, the sample should be combined and the results of the single FA [fac-tor analysis] reported” (p. 602). After factor analyzing the four curiosity instru-ments and then the Workplace Adaptation Questionnaire, we analyzed theresults of both analyses according to gender and produced the same factorswith almost identical loadings. Interestingly, we obtained similar results when


18 Reio, Wiswell

comparing the curiosity and Workplace Adaptation Questionnaire’s factorstructures of the two larger companies participating in the study. The twosmaller workplace samples were far too small for factor analysis work (Kline,1993); factor structure comparisons across occupational groups were not pos-sible for this reason as well, but we achieved similar factor loadings again whenexamining the one large occupational type, that is, service workers. In addi-tion, we performed one-way ANOVAs (1 � 4 [groups]), and examined thepatterns of correlations for each of the independent and dependent variables.On the basis of the lack of a significant difference between most of the mainvariables of interest, the resulting consistent patterns of correlations, and thestable factor structure by gender and company on the independent variables,we decided it would be appropriate to combine the individuals of this studyinto one large sample for further analysis. Nevertheless, the results of the studywould best be applied cautiously to similar research populations.

Data Analysis. The Statview 4.0 statistical package for the Macintosh wasused for all analyses except for determining the standardized path coefficients,for which EQS (pronounced “X”) for Windows, version 5.4, was used.

Results

Table 1 presents the means, standard deviations, alphas, and number of itemsfor each of the twelve curiosity subscales, the three socialization-related learn-ing subscales, and the two job performance subscales. Table 2 represents the

Table 1. Descriptive Statistics for Instrument Subscales

NumberScale Subscale M SD Alpha of Items

WAQ Job knowledge 33.3 4.4 .96 8WAQ Acculturation 19.0 3.5 .86 5WAQ Establishing relationships 21.2 3.0 .85 5MCI Melbourne state curiosity 58.5 11.5 .94 20MCI Melbourne trait curiosity 60.8 10.0 .92 20STPI State-trait personality-state 27.4 5.1 .79 10STPI State-trait personality-trait 28.1 5.1 .80 10NES External sensation 11.9 4.8 .85 20NES Internal cognitive 13.3 5.4 .90 20NES Internal sensation 10.9 4.5 .83 20NES External cognitive 11.0 4.7 .83 20SSS Disinhibition 4.5 2.4 .67 10SSS Boredom susceptibility 3.4 2.2 .60 10SSS Thrill and adventure seeking 6.2 2.7 .76 10SSS Experience seeking 5.2 1.9 .48 10TJP Technical job performance 7.1 2.1 .71 2IJP Interpersonal job performance 7.8 1.7 .71 2

Note: N � 233

correlational values between the variables of interest. At this stage of ourexploratory investigation, we decided not to use the results of our factor analy-sis work, to expedite comparison of the existing instruments. We were veryinterested, in other words, in examining the particular instruments in avery practical manner for their research utility.

On three of the four measures of curiosity used in this study (excludingthe SSS-V), a positive relationship with the socialization-related learning andjob performance measures was found, as expected. Two of the three positiverelationships were significant at the p � .001 level, carrying a low to moder-ately pronounced relationship of .23 to .43. The other positive correlation (theNES) was significant at the p � .02 level; this lower relationship was also antic-ipated because the instrument is a combination of two cognitive and two sen-sation subscales. Separately, a combination of the NES’s cognitive subscalescorrelated positively and significantly with the socialization-related learningand job performance variables .23 and .26 (p � .001), respectively. In con-trast, the NES’s sensation scale combination lacked a statistically significantrelationship with either the socialization-related learning or job performancevariables. Thus, Hypotheses 1 and 2 are supported, because there is a positivestatistically significant relationship among all the measures of adult state andtrait epistemic curiosity, socialization-related learning, and the job performancevariables.

The SSS-V was also examined because it represents a major type of curios-ity reported in the research literature. This type of curiosity—sensation seekingor sensory, as mentioned previously—is not an epistemic or knowledge-seekingkind of curiosity per se, but it was of research interest because of our desire toinvestigate fully the curiosity construct in a heretofore untouched venue, theworkplace. As predicted, there was a negative correlation between the SSS-Vand the other variables of interest. Nevertheless, due in part to the measure’s lowsubscale reliabilities and lack of immediate practical relevance to answering theresearch hypotheses, we will not investigate the instrument further in this article.


Table 2. Research Variable Total Score Intercorrelations

MCI-T NES-T STPI-T SSS-T WAQ-T JP-T

1 —— .36 .60 �.02 .40 .432 —— —— .29 .21 .16* .233 —— —— —— �.04 .33 .324 —— —— —— —— �.20 �.245 —— —— —— —— —— .586 —— —— —— —— —— ——

Note: N � 233; * p < .02.

The numbers on the left margin correspond to labels for the column headings: 1 � MCI-T; 2 �NES-T; 3 � STPI-T; 4 � SSS-T; 5 � WAQ-T; 6 � JP-T.

20 Reio, Wiswell

We will mention, however, that this sensation-seeking variety of adult curiositymight prove to be fertile ground for future research.

To further analyze the hypothesized relationships of this research and toassess Hypothesis 3, we employed a structural modeling approach. We evalu-ated three structural models (henceforth called path models) with observedvariables (Kline, 1998). Figures 1, 2, and 3 represent these three theoreticalpath models.

According to Cohen and Cohen (1983), “Learning causal analysis is muchlike learning to sail. About half the task involves learning the constructs andvocabulary of its practitioners. Most of the other learning requires that onecome aboard and try it” (p. 353). We tried to keep this wisdom in mind whenexplaining the following. In Kline’s (1998) timely examination of structuralmodeling techniques, he recommends their use because they allow evaluationof entire models, thus introducing a macrolevel perspective to the analysis.

Figure 1. Curiosity to Job Performance Path Model

MelbourneCuriosityInventory

Socialization-Related Learning

Job Performance.40*** .58***

E2 E3

*** p � .001

Figure 2. Curiosity to Job Performance, Revised


Job Performance

MelbourneCuriosityInventory

E2

E3

.40***

.23***.49***

*** p � .001

Moreover, he further stressed their utility by citing their flexibility as tools foranalyzing both experimental and nonexperimental data, because they can beevaluated across multiple groups and provide the researcher with an opportu-nity to analyze means of either observed or latent variables (or factors). Thoughwe did not utilize latent variables in our exploratory research, these same struc-tural models could be tested further using latent variables derived fromexploratory and confirmatory factor analysis inquiry.

Loehlin (1992) viewed path diagrams as easy and convenient ways torepresent the relationships among research variables; therefore, they can besimple and clear descriptive devices, and much more. With empirical data,for example, one can explain or solve for the numerical values associated witheach path arrow, consequently indicating the causal influence of each. How-ever, as with the use of almost any analytic method, if proper steps are nottaken to ensure the integrity of the data and the specific hypotheses, thereexists the very real possibility of misinterpreting the data. To avoid this prob-lem, Kline (1998) advises specifying the path model by using psychologicallysound measures and theoretically plausible associations, carefully screeningdata for outliers and normality, and avoiding believing that a robust analyticmethod such as structural modeling will compensate for poor research ideasor inadequate study design. In a very real sense, the value of path analysiscan be limited to the extent that the theoretical model is based on a sound


Figure 3. Curiosity to Dimensions of Job Performance Path Model


State Curiosity

Trait Curiosity

Technical JobPerformance

Interpersonal JobPerformance

.79***

.23***

.20***

.45***

E3

.49***

E5

E4

*** p � .001

22 Reio, Wiswell

research method, especially when applied to the issue of implying causalitybetween variables.

In a path model, one-way arrows indicate the presumed primary causaldirection flowing from the observed variable on the left to the one on the rightof the arrowhead, while the curved, doubleheaded arrow indicates an unana-lyzed association, in which two variables (such as state and trait curiosity, theexogenous variables) are assumed to covary, with no specific hypothesis abouthow this correlation arises (Kline, 1998; Loehlin, 1992). Endogenous variables,conversely, are causally dependent on the other variables in the model, andtheir causal source is internal.

Three a priori-determined recursive path models (see Figures 1, 2, and 3)suggesting the causal influence of adult curiosity on socialization-related learn-ing and then job performance were tested. Recursive path models have nofeedback loops; consequently, all causal effects are unidirectional. Standard-ized path coefficients (a measure of to what extent a change on the variable atthe tail of the arrow is transmitted to the variable at the head of the arrow,holding all other variables constant; Loehlin, 1992) were calculated by EQSfrom a combination of the correlational matrix containing the three main studyvariables (curiosity, socialization-related learning, and job performance—seeTable 2), their covariances, and their standard deviations (see Table 1) using amaximum likelihood criterion for estimation. Acknowledging that the para-meters of our recursive path models could be computed with similar results inlarge samples (N > 200) by either multiple regression or other procedures suchas the maximum likelihood criterion (Kline, 1998), we chose the latter pri-marily because of the advantage of the availability of several overall fit indexesand the automatic derivation of direct and indirect effects.

Although each of the cognitive curiosity measures (MCI state and trait,STPI state and trait, and NES internal and external cognitive subscales) hadsimilar, somewhat moderate, statistically significant relationships with theendogenous variables, the MCI subscales demonstrated the most robust inter-relationships with the research variables and were used for subsequent calcu-lations of standardized path coefficients. All of the following path coefficientsare significant at the p � .001 level.

In the initial, simple model (Figure 1), adult epistemic curiosity is repre-sented as a single construct (MCI total score used). The standardized pathcoefficient for the path between curiosity and socialization-related learning(WAQ total score used) is .40, while the socialization-related learning-to-job-performance (total job performance score used) standardized path coefficientis .58. This model is an overidentified path model because it has fewer parame-ters or statistical effects than observations (Kline, 1998). When interpreting thismodel, one would say that curiosity has solely an indirect influence on job per-formance, mediated through the socialization-related learning variable. To eval-uate the overall path model, fit indexes are computed by EQS and most othermodel-fitting computer programs. Basically, fit indexes indicate the overall fit

of a path model to the data. One of the more widely cited indexes, the Com-parative Fit Index (CFI; Bentler, 1990; Kline, 1998), was .89 for this theoreti-cal model (values > .90 are conventionally acceptable); thus the model did notadequately fit the data. In structural modeling terms, the data disconfirmedthe model (Cliff, 1983), suggesting the need for an additional path to explainmore fully the hypothesized relationship between curiosity and job perfor-mance. Indeed, all but one of the other fit indexes did not support the fit of thedata to the theoretical model (see Table 3 for the values of fit for multipleindices as recommended by Kline, 1998).

In the second theoretical model (Figure 2), we added a direct curiosity-to-job-performance path. This is a just-identified path model because it has thesame number of parameters as observations; because of this, none of the stan-dard indexes of fit are generated (Kline, 1998). The standardized path coeffi-cient for the new curiosity-to-job-performance path is .23, the one for thecuriosity-to-socialization-related path is .40, and the one for the socialization-related learning-to-job-performance path is .49. The multiple R of the directcuriosity path to job performance is .16, while that of the path mediated bysocialization-related learning is .38. Consequently, according to this model,curiosity directly explains 16 percent of the variance of the dependent variableand also has an indirect relationship to the dependent variable that accountsfor 38 percent of the variance. The observed mediated relationship betweencuriosity and job performance partially supports the third hypothesis. Althoughthis model fits the data in some rather interesting ways, further clarification isnecessary to denote the extent of the meaningful relationship between the inde-pendent variables and the two dimensions of job performance.

Last, the final model (Figure 3) is an overidentified path model in whichjob performance, the dependent variable, is split into its two dimensions, tech-nical (task) and interpersonal (contextual) performance. Adult curiosity, theindependent variable, is also split into its state and trait components. With aCFI of .96, the data failed to disconfirm the model, and there was no directinfluence of state or trait curiosity on either of the job performance dimensions.All but one of the other fit indexes fully support this interpretation, but cautionis in order. When the standardized root mean-square residual (SRMR) isaround .10 or less, the model is generally considered to be acceptable (Kline,1998); yet there is some controversy over this issue because some researchers


Table 3. Summary of Fit Indexes for the Models Examined

Model CFI AGFI MFI IFI SRMR

Initial .89 .74 .97 .89 .08Final .96 .99 .97 .96 .07

Note: CFI � Comparative Fit Index; AGFI � Adjusted Goodness of Fit Index; MFI � McDonald’s FitIndex; IFI � Bollen’s Incremental Fit Index; SRMR � Standardized Root Mean-Square Residual.

24 Reio, Wiswell

believe that a value around .05 is really the acceptable convention for appro-priate model fit (Hancock, 1997). Our final model yielded a value of .067.A logical step in such situations is to consider the 90 percent confidence inter-val of the Root Mean-Square Error of Approximation, which ranged between.064 and .167. Because the SRMR for our model fell within this range, it canbe assumed with reasonable confidence that the data still do not disconfirmthe theoretical model. Hence, the influence of state and trait curiosity on tech-nical and interpersonal job performance was solely through the mediation ofthe socialization-related learning variable. This finding supports the thirdhypothesis.

According to the theoretical models, therefore, adult state and traitepistemic curiosity directly influence socialization-related learning and indi-rectly but significantly influence both dimensions of job performance. Second,socialization-related learning moderately influences both of the job performancevariables. The relationship between curiosity and learning was expected due tosupport in the literature, which describes curiosity as a primary motivator anddirector of learning (see, for example, Berlyne, 1960). Socialization-relatedlearning was expected to have an important influence on task mastery and thuson technical job performance (see, for instance, Ostroff and Kozlowski, 1992).

Technically speaking, based on our path analysis work, it could be saidthat a standard-deviation increase in state or trait curiosity, holding all else con-stant, would directly lead to .20 or .22 standard deviation increases, respec-tively, in socialization-related learning, which in turn would result in .49 or.45 standard deviation increases in technical and interpersonal job perfor-mance. The practical significance of this result is that if one could somehowadvance the state curiosity of an individual, such as a trainee in a formal train-ing setting or a new employee in an informal learning setting, one coulddirectly influence their socialization-related learning and indirectly affect theirtechnical and interpersonal job performance (stimulating curiosity could rea-sonably be done by a competent trainer). This study demonstrates support forthis notion. Moreover, the same may hold true for trait curiosity, that is, thatholding all else constant, increasing a work group’s or business unit’s overalllevel of trait curiosity by a standard deviation (perhaps by hiring more curiousemployees) could facilitate socialization-related learning and job performanceas well (at least in companies similar to the ones investigated in this study).It would be interesting to test these notions with further research, becausethere would be obvious limitations to these findings. To be able even to thinkthat these path-analytic results indicate a causal relationship between the vari-ables, however, Kline (1998) recommends that the following three conventionsbe followed: replicating the model across independent samples, obtainingsubstantiating evidence from experimental studies involving the variables ofinterest, and accurately predicting the effects of various interventions on themodel. We believe that this additional evidence would be essential for the fullsupport of our final theoretical model.

Nonetheless, the results of this exploratory study provide preliminaryempirical evidence that adult state and trait curiosity is a reflection, at least inpart, of the importance of curiosity or information seeking and learning in theacquisition of job knowledge and the attainment of higher technical and inter-personal job performance.

Discussion and Implications

Although researchers have acknowledged that curiosity plays some rolein adult learning, little effort has been made to incorporate curiosity into exist-ing adult learning theory. Knowles’s andragogical model (Knowles, Holton, andSwanson, 1998) deserves special note. The sixth assumption underlying themodel is the notion that intrinsic and extrinsic motivators are important con-siderations for adult learning; overall, internal motivators are viewed as themost potent motivators for fostering adult learning.

It is interesting to note that curiosity is not identified specifically as animportant internal learning motivator. Based on the results of our research, wethink it might be useful to acknowledge curiosity clearly in the argument sup-porting the continued relevance of the andragogical model. This study pro-vides empirical evidence that curiosity plays a significant role in workplacelearning, which is an important part of the adult learning arena.

Another attractive possibility for extending adult learning theory throughunderstanding of curiosity would be in the area of situated cognition. Wilson(1993) informs us that the situated cognitive view, based significantly onVygotsky’s (1986) notions about cognitive development, stresses the vital roleof understanding the context in which thinking and learning occur. In essence,everyday thinking and learning are most often social activities, mediated bysituationally available tools, which in turn are affected by one’s interaction witha particular environment. Thus, thinking, learning, and knowing are all medi-ated by the context in which they are situated. Rather than simply focusing onlearners’ acquisition of knowledge, Wilson advocates that the most meaning-ful adult learning occurs when “modeling, coaching, and practice approachesto learning” are employed (p. 78). Nevertheless, this perspective (see, forexample, Lave, 1997) pays little attention to the motivational aspects relatedto these activities in which curiosity arguably plays a role.

Although no particular motivational model was tested in this research, ourfindings nevertheless promote the idea that fostering curiosity may be animportant strategy to include in instructional models of motivational learning.Both state and trait curiosity were found to influence directly the learning asso-ciated with the socialization process; thus it would be logical to infer that bysomehow increasing curiosity in the workplace (by designing exercises topromote it in formal learning endeavors and by fostering it in informal learn-ing contexts through supportive organizational policies and procedures), indi-vidual learning could be facilitated and adaptation could become more


26 Reio, Wiswell

probable because of the likely increases in levels of information and knowl-edge seeking (such as self-directed learning) as well as in creative thinkingand problem solving. As Confessore and Kops (1998) suggested, these indi-vidual learning activities might in turn promote the continuous developmentof the learning organization’s capacity to manage change.

Further, the significant relationship between state and trait curiosity andsocialization-related learning demonstrated in this research becomes even moreinteresting when one considers that workers in the service industry, such asthe subjects in this study, are generally expected to possess lower curiosity lev-els than workers in many other occupations (Naylor, 1981). Naylor comparedcuriosity levels established by scores on the MCI with realistic, investigative,artistic, social, enterprising, and conventional (RIASEC; Holland, 1973) workinterests as assessed by the Strong-Campbell Interest Inventory. Positive sta-tistically significant relationships (p � .001) were found with the investigative,artistic, and social categories, in which service-industry employees would notbe expected to be represented greatly. Conversely, it would be expected thatresearch scientists, for instance, would possess higher trait curiosity levelsaccording to the RIASEC classification (investigative), and Tucker (1986)indeed found this to be true. Thus the findings that curiosity directly influ-ences socialization-related learning even among service industry employeeswho were not expected to be terribly curious suggest that additional researchwith other occupational groups is warranted.

Perhaps what is more engaging here is the idea that adult epistemic curios-ity appears to be partly involved in workplace learning, such as the socializa-tion process, despite Naylor’s (1981) finding that curiosity is not related to therealistic, conventional, and enterprising work-interest types. Thus curiosityand the information-seeking behaviors it elicits (such as question asking,thinking, and reflecting) seem to have a role in adult learning and in adult-learning contexts, such as the workplace, and not just in children’s classrooms.

These results also lend empirical support to research (for instance, Ostroffand Kozlowski, 1992) that advocates meaningfully viewing the socializationprocess as an information-seeking process (which includes curiosity) or alearning process. Employees may thus need some level of curiosity to seektechnical and interpersonal information productively from organizational lit-erature, coworkers, and supervisors; to adapt to a constantly changing workenvironment; and finally to perform their jobs well.

In conclusion, the findings of this study indicate that adult curiositydirectly influences the ever-important learning associated with the socializationprocess and indirectly influences both the technical and interpersonal dimen-sions of job performance. Accommodating curiosity in instructional designs bystimulating it in training endeavors may facilitate the necessary acquisition andapplication of learning by increasing learner arousal and promoting deeperexploration of workplace problems. Hiring more curious employees might alsobe an attractive way to assist with the development of a learning organization,

especially in emerging businesses and industries where high levels of curiosityand creativity are absolutely necessary for remaining ahead of the competition.Including curiosity in adult learning theory also seems appropriate.

By fostering a safe workplace environment in which curiosity is positivelystimulated and acknowledged through evaluation, career development, andreward and compensation procedures, curiosity could be promoted, learningcould be increased, and the learning organization could surely benefit.

Limitations and Recommendations for Future Research

The generalizability of the research findings is limited to the particular occu-pational groups examined in this research and to the self-report nature of theresearch measures. Further research employing alternative occupational groupsfrom different industries and more objective learning and job performancemeasures (such as formal supervisor ratings) would be useful in efforts to val-idate our final theoretical model. Indeed, if the results of this study were repli-cated in other types of organizations with diverse samples, there would ofcourse be additional evidence to support our major conclusions.

Some consideration should also be extended to the curiosity instrumen-tation that is presently available. Despite the rather positive evaluation of allthe measures used in this study, the construct validity of each measure maybe unnecessarily limited due to the apparent transparency of the test items.Inasmuch as we recommend the use of the MCI because of its high internalreliability, substantial overlap with the STPI (r � .60), and overall utility asa research measure, this issue should be weighed carefully by the researcher.The construction of more empirically rigorous measures in which the obvi-ous purpose of the instrument is not obvious could only contribute toincreased construct validation efforts, and assist in guiding and interpretingfuture research.

Additional research is recommended to evaluate more clearly the role ofBerlyne’s (1960) collative motivational variables (that is, conflict, uncertainty,surprisingness, complexity, contradiction, and so on) in workplace learningsettings. According to Berlyne, these variables all stimulate states of curiosity;it would thus be beneficial to ascertain the extent of the contributions of thesevariables to adult learning facilitation in various formal and informal instruc-tional contexts. This information would be especially relevant for the refine-ment and development of viable instructional models.

Finally, even though this exploratory research has primarily focused oncognitive curiosity, another promising area of investigation might be the explo-ration of sensation-seeking curiosity and its associated behaviors in the work-place. For a more complete understanding of the possible influences of adultcuriosity on workplace learning, it might be fruitful to determine what role thesensation-seeking kind of curiosity plays in inducing or perhaps deterringworkplace learning and adaptation to change, in which contexts, and why.


28 Reio, Wiswell

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Thomas G. Reio Jr. is a lecturer in the Department of Human Development at theUniversity of Maryland, College Park.

Albert Wiswell is associate professor of adult learning and human resource developmentin the Department of Human Development at Virginia Polytechnic Institute and StateUniversity, Falls Church.

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