the effect of career exploration on subsequent training performance
TRANSCRIPT
This article was downloaded by: [The Aga Khan University]On: 16 October 2014, At: 16:55Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK
Human Resource DevelopmentInternationalPublication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/rhrd20
The effect of career exploration onsubsequent training performanceDr. Jens Rowold aa Westfälische Wilhelms-Universitaet Muenster ,Published online: 28 Feb 2007.
To cite this article: Dr. Jens Rowold (2007) The effect of career exploration on subsequenttraining performance, Human Resource Development International, 10:1, 43-58, DOI:10.1080/13678860601170278
To link to this article: http://dx.doi.org/10.1080/13678860601170278
PLEASE SCROLL DOWN FOR ARTICLE
Taylor & Francis makes every effort to ensure the accuracy of all the information (the“Content”) contained in the publications on our platform. However, Taylor & Francis,our agents, and our licensors make no representations or warranties whatsoever as tothe accuracy, completeness, or suitability for any purpose of the Content. Any opinionsand views expressed in this publication are the opinions and views of the authors,and are not the views of or endorsed by Taylor & Francis. The accuracy of the Contentshould not be relied upon and should be independently verified with primary sourcesof information. Taylor and Francis shall not be liable for any losses, actions, claims,proceedings, demands, costs, expenses, damages, and other liabilities whatsoever orhowsoever caused arising directly or indirectly in connection with, in relation to or arisingout of the use of the Content.
This article may be used for research, teaching, and private study purposes. Anysubstantial or systematic reproduction, redistribution, reselling, loan, sub-licensing,systematic supply, or distribution in any form to anyone is expressly forbidden. Terms &Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions
The Effect of Career Explorationon Subsequent Training Performance
JENS ROWOLDWestfalische Wilhelms-Universitaet Muenster
ABSTRACT In recent models of training effectiveness, it has been proposed that careerexploration predicts training outcome variables such as training performance. Implementing theCareer Exploration Survey developed by Stumpf and colleagues (1983), the present studyexplored the impact of sixteen dimensions of career exploration on subsequent trainingperformance. A total of 145 call centre agents participated in the present study. Resultsdemonstrated that four dimensions of career exploration predicted subsequent trainingperformance. More specifically, trainees who (a) scored high on focused career exploration,(b) were more satisfied with information, (c) reported a higher internal search instrumentality,and (d) reported a lower external search instrumentality achieved higher training performancescores. Implications for theory, practice and future research are discussed.
KEY WORDS: Career exploration, training performance, call centre
Organizations rely on human resource development interventions to updateemployees’ knowledge, skills and abilities (Woodall, 2005). As the pace oftechnological development, environmental changes and global competition in-creases, it becomes more and more important for organizations to train theiremployees. Thus, for practitioners such as human resource development (HRD)professionals, it is important to understand factors that will ultimately lead tosuccessful training. Researchers are also interested in a thorough and comprehensivedescription of the process of training. In the last two decades, several factors thatimpact the effectiveness of development interventions such as training wereidentified. For example, in their classical review and critique of training research,Baldwin and Ford (1988) identified trainee characteristics (e.g. motivation to learn,cf. Bartlett and Kang, 2004), training design characteristics (e.g. role modelling) andwork environment factors (e.g. supportive training and development infrastructure,cf. Clarke, 2005) as three key determinants of effective training. Following Baldwinand Fords’ article, important advancements have been made as empirical researchclarified many of the mechanisms proposed to affect training outcomes (e.g. Clarke,
Correspondence Address: Dr. Jens Rowold, Psychologisches Institut II, Westfaelische Wilhelms-
UniversitaetMuenster Fliednerstrasse 21, 48149Muenster, Germany. Email: [email protected]
Human Resource Development International,Vol. 10, No. 1, 43 – 58, March 2007
ISSN 1367-8868 Print/1469-8374 Online/07/010043-16 � 2007 Taylor & Francis
DOI: 10.1080/13678860601170278
Dow
nloa
ded
by [
The
Aga
Kha
n U
nive
rsity
] at
16:
55 1
6 O
ctob
er 2
014
2002; Colquitt et al., 2000). However, several processes and factors that potentiallyinfluence training outcomes are not yet fully understood.
Among the factors that were hypothesized to influence training performance weretrainees’ career attitudes (Holton, 2005; McMahon and Merman, 1996). Careerattitudes encompass concepts such as career exploration, career planning, careercommitment and career motivation. This field of research has been of particularinterest due to recent development in the labour market. While in the past,organizations offered their employees relatively safe careers paths, recent organiza-tional trends such as increasing global competition and downsizing force employeesto take more responsibility for their own careers. For example, employees have toplan different career paths in order to be prepared for different tasks, jobs andorganizations (Sullivan, 1999). Employees are also forced to plan participation indevelopmental activities such as training in order to be prepared for their respectivecareer. The new ‘psychological contract’ (Atkinson, 2002) between employee andcompany emphasizes the self-initiated development of employees’ knowledge, skillsand abilities.
One of the career attitude concepts that has gained much attention from theresearch community is career exploration (Blustein, 1997). Career exploration refersto those purposeful activities that are directed toward enhancing self- andenvironment knowledge. People engage in career exploration in order to fosterprogress in their career development. Skill strengths and weaknesses are evaluated,as well as career values, interests, goals and plans (Jordaan, 1963; Stumpf andLockhart, 1987). This concept was proposed to influence outcomes of importantorganizational interventions such as training performance (Colquitt et al., 2000;Wolf et al., 1995). For example, employees who have a clear understanding of theircareer goals will be highly motivated to participate and to be successful in trainingprogrammes that support their respective career goals. Engaging in careerexploration helps employees to adapt to the current labour market situation witha decreasing level of job security and of career path stability. For both researchersand practitioners, it seems valuable to understand the relationship between careerexploration and training performance. From a theoretical perspective, this kind ofresearch will allow for a more thorough understanding of the training process. Forexample, which facets of trainees’ career exploration behaviours will help trainees tobe successful in training? Within organizations, HRD experts strive to adapt theirHRD programmes to the above-mentioned recent changes in the labour market.This kind of research will advance training needs analysis in organizations and willhelp HRD experts to prepare employees for their respective career and for theirparticipation in training programmes.
Thus, the purpose of the present study was to explore the effect of trainees’ careerexploration on subsequent training performance, one of the key indicators ofeffective training. We first turn our attention to recent theoretical models thatexplicate the role of career exploration in the training process. Second, the fewempirical studies that were conducted in this field of research are evaluated. Third, ina discussion of the limitations of this research, it is argued that a more differentiatedapproach to career exploration is needed in order to advance our understanding ofthe training process. Consequently, for a more sophisticated analysis of therelationship between career exploration and training performance, we focus on the
44 J. Rowold
Dow
nloa
ded
by [
The
Aga
Kha
n U
nive
rsity
] at
16:
55 1
6 O
ctob
er 2
014
theory of career exploration proposed by Stumpf and colleagues (Stumpf andColarelli, 1980; Stumpf et al., 1983a), which describes sixteen facets of careerexploration. Fourth, specific hypotheses are developed that relate these sixteendimensions of career exploration to training performance. Finally, results of anempirical study are presented and discussed in regard to their relevance for a morecomprehensive model of training effectiveness.
The Role of Trainees’ Career Exploration in Recent Models
of the Training Process
Over the last two decades, progress has been made in our understanding of thetraining process. Theoretical models that described the training process includedcareer exploration as a variable that was hypothesized to influence trainingperformance directly or indirectly (Colquitt et al., 2000; Holton, 1996; Noe, 1986;Ruona et al., 2002). The present study focused on two of these models because theywere among the most comprehensive models of the training process and havereceived considerable attention from the research community (Salas and Cannon-Bowers, 2001).
First, Holton and colleagues (Holton, 1996; Holton et al., 1997; Holton et al.,2000; Ruona et al., 2002) proposed a human resource development evaluationmodel. This model implied that motivational (e.g. motivation to learn), environ-mental (e.g. supervisory support), ability (e.g. opportunity to use), and secondaryinfluence factors affect outcomes of developmental interventions such as trainingperformance. With regard to secondary influences, job and career attitudes werehypothesized to impact subsequent training performance (Holton, 1996).
Second, a model of training effectiveness was developed by Cannon-Bowers andcolleagues (Cannon-Bowers et al., 1995, 1998). This model accounted for influencingfactors before (e.g. expectations), during (e.g. expectation fulfilment) and after (e.g.transfer motivation) training. On the side of trainees’ characteristics, job and careerattitudes were hypothesized to influence outcome criteria.
Both models included the three categories of variables that Baldwin and Ford(1988) hypothesized to influence training outcome variables (i.e. trainees’, trainingand environmental characteristics; cf. above). Trainees’ characteristics includedvariables such as career attitudes. Common to both models were the hypothesizedeffect of career attitudes on training performance. Because employees who score highon career exploration have a more differentiated understanding of their interests,strengths, and weaknesses and consequently understand the importance ofdevelopmental interventions such as training for their career (cf. Noe, 1986), careerexploration was hypothesized to influence training performance in these models.
Despite these theoretical contributions, only a few empirical studies tested thisproposition. For example, Facteau et al. (1995) explored the effect of careerexploration and other attitudes on perceived training transfer. It was found thatcareer exploration was positively related to perceived training transfer in a sample ofgovernment agencies’ supervisors. However, a major limitation of this study was thattransfer was rated by trainees (i.e. self-report data).
A second study tested effects of career exploration on learning and on trainingperformance in a sample of school principals (Noe and Schmitt, 1986). Contrary to
Career Exploration Training 45
Dow
nloa
ded
by [
The
Aga
Kha
n U
nive
rsity
] at
16:
55 1
6 O
ctob
er 2
014
the results obtained by Facteau et al., no significant associations between careerexploration and training outcome variables (i.e. learning, training performance, andjob performance) were observed.
Moreover, the dearth of empirical research was highlighted in Colquitt’s et al.(2000) work. Although in their theoretical analysis of the training process careerexploration was included as an important variable, there were not enough empiricalstudies to include the construct in their subsequent meta-analysis. As a result, one ofthe most up-to-date empirical path models of the training process which resultedfrom the meta-analysis did not include career exploration variables (Colquitt et al.,2000).
Another limitation of existing empirical studies was that only a limited number offacets of career exploration were tested with regard to their impact on trainingperformance. However, career exploration is a multi-faceted construct, as will bedescribed in the next section. Despite the fact that a complex set of relationshipsbetween facets of career exploration and training performance could be proposedfrom theory, only one combined career exploration scale was implemented in priorempirical research. This was also true for the above discussed studies conducted byFacteau et al. (1995) and Noe and Schmidt (1986). Finally, training studies weretypically based on a cross-sectional design, and relied on self-reports of trainingperformance (e.g. Facteau et al., 1995).
From this critique of the limited amount of empirical research, it seemed valuableto explore the effects of career exploration on training performance in greater detail.This kind of research could yield a more comprehensive understanding of the role ofdifferentiated aspects of career exploration in the training process. For each facet ofcareer exploration, relationships to training performance are hypothesized in thefollowing paragraphs. As a consequence of methodological deficiencies in priorresearch, the present study was conducted with methodological rigor. A researchdesign was implemented that included the assessment of data at multiple points-in-time and training performance was assessed by independent raters (trainers).
A Comprehensive Model of Career Exploration
Based on earlier work on career exploration (Greenhaus and Sklarew, 1981; Superand Hall, 1978), Stumpf and his colleagues (1983a, 1983b) developed a compre-hensive model of career exploration. Within this model, differentiated cognitive,affective, and behavioural aspects of career exploration were considered. Morespecifically, six aspects of beliefs about exploration (e.g. external search instrumen-tality), seven aspects of the exploration process (e.g. extent of environmentexploration), and three aspects of reactions to exploration (e.g. exploration stress)were included in their model. Based on this model, the Career Exploration Survey(CES) was developed for the assessment of 16 dimensions of career exploration.Table 1 provides a brief description of these dimensions as well as sample items.
Because the CES reflected the complexity of the career exploration process in greatdetail, it has been used extensively in empirical research. For example, in a sampleof graduate business students, career exploration as assessed with the CES wassignificantly related to interview performance and outcomes (i.e. job offers; Stumpfet al., 1984). In a second study, career exploration two months prior to
46 J. Rowold
Dow
nloa
ded
by [
The
Aga
Kha
n U
nive
rsity
] at
16:
55 1
6 O
ctob
er 2
014
Table 1. Description of Career Exploration Survey (CES) dimensions
Dimension and definitionSample item, number of Items perscale, and response scale
Exploration ProcessEnvironment Exploration (EE). The extent of
career exploration regarding occupations,jobs and organizations within the last threemonths.
‘To what extent have you behaved inthe following ways over the lastthree months: Investigated careerpossibilities?’; 6; 1 – 5
Self-Exploration (SE). The extent of careerexploration involving self-assessment andretrospection within the last three months.
‘To what extent have you behaved inthe following ways over the lastthree months: Contemplated mypast?’; 5; 1 – 5
Number of Occupations Considered (NOC).The number of different occupational areason which one is acquiring information.
‘How many occupational areas areyou investigating?’; 1; open-ended
Intended-Systematic Exploration (ISE). Theextent to which one acquires information ononeself and the environment in an intendedor systematic manner.
‘To what extent have you behaved inthe following ways over the lastthree months: Tried specific workroles just to see if I liked them?’;3; 1 – 5
Frequency (FR). The average number of timesper week that one seeks career informationover a two-month period.
‘On average, how many times perweek have you specifically soughtinformation on careers within thelast few months?’; 1; 1 – 5
Amount of Information (AI). The amount ofinformation acquired on occupations, jobs,organizations and oneself.
‘How much information do you haveon what one does in the careerareas(s) you have investigated?’;4; 1 – 5
Focus (FO). How sure one feels in his/herpreference for a particular occupation, joband organization.
‘How sure are you that you knowexactly the occupation you want toenter?; 5; 1 – 5
Reactions to ExplorationSatisfaction with Information (SI). The
satisfaction one feels with the informationobtained regarding occupations, jobs, andorganizations relative to one’s interests,abilities and needs.
‘How satisfied are you with theamount of information you haveon jobs that are congruent withyour interests and abilities?’;6; 1 – 5
Explorational Stress (ES). The amount ofundesirable stress, relative to othersignificant life events, with which one has tocontend, felt as a function of the careerexploration process.
‘How much undesirable stress havethe following caused you relativeto other significant issues withwhich you have had to contend:Exploring specific jobs?’; 4; 1 – 7
Decisional Stress (DS). The amount ofundesirable stress, relative to othersignificant life events, with which one has tocontend, felt as a function of the careerdecision-making process.
‘How much undesirable stress havethe following caused you relativeto other significant issues withwhich you have had to contend:Deciding on an occupation?’;4; 1 – 7
BeliefsEmployment Outlook (EO). How favourable
the employment possibilities are in one’scareer area.
‘How do the employment possibilitieslook for the occupations youprefer?’; 3; 1 – 5
(continued)
Career Exploration Training 47
Dow
nloa
ded
by [
The
Aga
Kha
n U
nive
rsity
] at
16:
55 1
6 O
ctob
er 2
014
organizational entry predicted subsequent socialization variables (such as person-jobcongruence; Stumpf and Hartman, 1984). Among a sample of college students,vocational planning and commitment was significantly predicted by careerexploration (Blustein, 1989). These and other studies highlighted the importanceof career exploration for several fields of vocational psychology. However, to theauthor’s knowledge, no empirical research existed that tested the influence of allsixteen dimensions of career exploration as assessed by the CES on trainingperformance.
Development of Hypotheses
The main research question of the present study referred to the relationship betweenthe 16 dimensions of career exploration (as assessed by the CES) and trainingperformance. For each of these relationships, rationales were provided and specifichypotheses were developed. These hypotheses can be grouped in the three categoriesof career exploration variables that were outlined in Table 1 (i.e. exploration process,reactions and beliefs).
Table 1. (Continued)
Dimension and definitionSample item, number of Items perscale, and response scale
Certainty of Career Exploration Outcome(CCEO). The degree of certainty one feelsthat one will attain a desired position.
‘How certain are you that you willbegin work upon graduation at thespecific job you prefer (e.g. a CPAaccountant)?’; 3; 1 – 5
External Search Instrumentality (ESI). Theprobability that exploring the environmentfor career opportunities will lead toobtaining career goals.
‘What is the probability that each ofthe following activities will resultin obtaining your career goals:Initiating conversations withfriends and relatives aboutcareers?’; 4; 1 – 5
Internal Search Instrumentality (ISI). Theprobability that reflection on past careerbehaviour and retrospection will lead toobtaining career goals.
‘What is the probability that each ofthe following activities will resultin obtaining your career goals:Learning more about myself?’;4; 1 – 5
Method Instrumentality (MI). The probabilitythat being intended and systematic in one’scareer exploration will lead to obtainingcareer goals.
‘What is the probability that each ofthe following activities will resultin obtaining your career goals:Planning my job search in detail?’;4; 1 – 5
Importance of Obtaining Preferred Position(IOPP). The degree of importance placed onobtaining one’s career preference.
‘How important is it to you at thistime to work in the occupation youprefer?’; 5; 1 – 5
NoteReprinted from ‘Development of the Career Exploration Survey (CES)’ (Stumpf et al., 1983ap. 196); copyright (1983), with permission from Elsevier.
48 J. Rowold
Dow
nloa
ded
by [
The
Aga
Kha
n U
nive
rsity
] at
16:
55 1
6 O
ctob
er 2
014
The Exploration Process (H1)
With regard to the exploration process, it was expected that persons who score highon Environment (H1a), Self (H1b), Intended-Systematic Exploration (H1c),Frequency of Exploration (H1d), Focused Exploration (H1e) and persons withhigh Amounts of Information (H1f) demonstrate higher training performance thanpersons that score low on these variables. All of these aspects of the explorationprocess yield extended knowledge about career paths and help to prepare for thecareer itself as well as for interventions included in the career. Consequently, futureemployees have more background information about training itself, importance oftraining, and the meaning of training for their respective career. Especiallyunderstanding the importance of training for the own career advancement helpsemployees to achieve high training performance scores.
Reactions to Career Exploration (H2)
As for reactions to career exploration, it was hypothesized that employees who arehighly satisfied with career exploration were prepared with exactly the kind ofinformation they need for their respective career. Moreover, their careers should bewith a higher probability congruent with their interests and abilities (cf. Table 1).Consequently, training is an intervention that will help employees to achieve careerand self-directed goals. Thus, employees who score high on Satisfaction withInformation are interested in performing well in training (H2a).
Beliefs (H3)
With regard to beliefs, it was expected that External Search (H3a), Internal Search(H3b), and Method Instrumentality (H3c) predict training performance. Inaccordance with the argument outlined above, employees that score high on theseinstrumentality variables will have more information about training itself and willunderstand the usefulness of training for their respective career. Likewise,Importance of Obtaining Preferred Position will signal employees the importanceof development interventions such as training for a successful career. Thus,employees scoring high on the subscale importance of obtaining preferred positionwould be highly motivated to perform well in training (H3d).
For the remaining five facets of career exploration (i.e. Number of OccupationsConsidered, Employment Outlook, Certainty of Career Exploration Outcomes,Explorational and Decisional Stress), it was hypothesized that these facets were notrelated to training performance (H4). More specifically, training performance shouldbe independent of the Number of Occupations Considered. Information acquiredthrough career exploration activity might be useful for several occupations, but willnot necessarily result in enhanced levels of training performance (H4a). As forEmployment Outlook, it might be assumed that a positive outlook will motivateemployees to higher levels of training performance. However, in labour markets withhigh probability for job loss, a negative outlook might motivate employees to achievehigh training scores, too. Performing well in training might prevent job loss. Fromthis argument, it becomes clear why a straightforward relationship between the two
Career Exploration Training 49
Dow
nloa
ded
by [
The
Aga
Kha
n U
nive
rsity
] at
16:
55 1
6 O
ctob
er 2
014
variables Employment Outlook and training performance could not be hypothesized(H4b). The same problem existed for the relationship between Certainty of CareerExploration Outcome and training performance. Several moderating variables forthis relationship could be proposed. For example, prior job-related experiences mightmoderate the relationship so that only employees who can ground their Certainty ofCareer Exploration Outcome on job-related experiences will perform well insubsequent trainings. Thus, it was hypothesized that Certainty of Career ExplorationOutcome is independent from training performance (H4c).
Finally, it was hypothesized that Explorational (H4d) and Decisional (H4e) Stresswere not related to training performance. The degree to which Explorational andDecisional Stress affect training performance might depend on several factors. Forexample, employees scoring high on dispositional characteristics such as hardiness orconscientiousness might perceive stress as a necessary condition of career explorationand thus, have enough resources to perform well in training. In contrast, employeeslow on these dispositional variables are ill-equipped for subsequent organizationalinterventions such as training and thus, demonstrate low performance.
Methods
Context
The present study was based on a sample drawn from 11 different in- and outboundcall centres. All of these call centres were located in Germany and hosted by a singleoutsourcing company. This company selected new employees utilizing an assessmentcentre. With the purpose of providing all newly selected call centre agents (CCA)with basic working knowledge and skills, the company offered a one-day trainingprogramme. Customer-oriented communication skills and knowledge, as well asspecific phrases and appropriate intonation were taught during this training.Trainers implemented a role-play exercise at the end of the training in order to assesstraining performance.
Study Design and Sample
The present study was conducted within the first four months of 2004. In this time,198 new employees were selected as CCA. At the end of the assessment centre, thestudy’s objective was communicated to the newly hired employees. A survey wasadministered to the participants, which included the CES and demographiccharacteristics. It was emphasized that participation in the study was voluntaryand open and honest answering was encouraged.
From the 198 newly selected employees, n¼ 155 returned the questionnaire,yielding a response rate of 78.3 per cent. Approximately two months after theassessment centre, the above-described training programme was offered to all newlyemployees on a voluntary basis. Because basic skills and knowledge were trained,93.6 per cent of the participants took part in the training programme, yielding a finalsample size of n¼ 145.
The mean age was 27.04 years (SD¼ 6.10). The sample consisted of 72 female(49.7 per cent) and 73 male (50.3 per cent) employees. Altogether, 25.5 per cent had a
50 J. Rowold
Dow
nloa
ded
by [
The
Aga
Kha
n U
nive
rsity
] at
16:
55 1
6 O
ctob
er 2
014
junior high school degree, and 74.5 per cent had passed their final high-schoolexaminations, qualifying them for university entrance. Forty-two percent of thesample worked part time, and 58 per cent were full-time employees; 78.7 per centwere inbound and 21.3 per cent outbound CCA.
Career Exploration Survey (CES)
The German version of the CES (Rowold, 2006) was implemented in the presentstudy to assess sixteen facets of career exploration. For descriptions of all sixteenscales and sample items, see Table 1. Recent empirical research demonstrated ade-quate psychometric properties of the German version of the CES (Rowold, 2006). Forexample, a sample of students reported similar levels of the sixteen facets of careerexploration over a three-month period (median of rtt¼ .52). In addition, results ofconfirmatory factor analyses that were based on several samples lend support for thenotion that the German version of the CES can be described best by the sixteen-factormodel that was articulated by Stumpf and colleagues (CFI¼ .981; RMSEA¼ .042; cf.Rowold, 2006). Within the same empirical study, the CES subscales showedsatisfactory levels of internal consistency (i.e. all Cronbach’s’ Alphas4.70).
Criterion Measure
Training performance was assessed at the end of training via a role-play exercise, whichfocused on several aspects of customer-oriented behaviours. The respective trainer ratedtrainees’ behaviour during the role-play on a company-designed performance-assessmentsurvey. The survey included eleven behaviourally anchored ratings scales. For example,courtesy, an aspect of customer-oriented communication skill, was assessed with the item‘Courteous verbal communication’ (5-point rating scale, ‘Uses courteous expressions’,1¼ never, 2¼ seldom, 3¼ sometimes, 4¼ often, 5¼ always). Only final scores for traineeswere available from the training department. Thus, with regard to the internalconsistency estimate of this scale, the author relied on information provided by thecompany. Prior validation study that was conducted by the company’s personneldepartment led to the conclusion that the training performance scale exhibited sufficientinternal consistency (i.e. Cronbach’s Alpha¼ .88).
Results
Table 2 reports descriptive statistics, intercorrelations, and reliability estimates(Cronbach’s Alpha) of study variables. With the exception of Explorational Stress(Cronbach’s’ Alpha¼ .51), the reliability estimates of the CES scales can be judgedas satisfactory (i.e. Cronbach’s Alpha� .70). Cortina (1993) demonstrated thatscales with few items can be judged as reliable even if their Cronbach’s Alpha isslightly below the commonly accepted standard of .70. From this perspective, theExternal Search Instrumentality scale exhibited sufficient internal consistency(Cronbach’s’ Alpha¼ .69).
Simultaneous regression analysis is an appropriate method for detectingsignificant influences of several rivaling independent variables (i.e. CES) on onesingle dependent measure (i.e. training performance). Results are presented in
Career Exploration Training 51
Dow
nloa
ded
by [
The
Aga
Kha
n U
nive
rsity
] at
16:
55 1
6 O
ctob
er 2
014
Table
2.DescriptiveStatistics,InternalConsistency
Estim
ates(C
ronbach’sAlpha),andIntercorrelationsofStudyVariables(N¼145)
MSD
12
34
56
78
910
11
12
13
14
15
16
17
1.EE
3.32
0.72
(.77)
2.SE
3.66
0.70
.39
(.82)
3.NOC
2.61
0.96
.13
.13
–4.ISE
2.55
0.90
.39
.21
.15
(.71)
5.FR
2.21
1.24
.47
.27
.09
.15
–6.AI
3.23
0.68
.47
.28
.01
.13
.29
(.79)
7.FO
3.41
0.99
.24
.15
7.08
.25
.19
.12
(.78)
8.SI
3.47
0.53
.38
.06
7.08
.07
.19
.32
.16
(.80)
9.ES
4.07
0.93
.14
.23
7.01
.16
.15
.06
.07
.01
(.51)
10.DS
3.76
1.22
7.07
.17
.20
.05
7.10
.02
7.16
7.02
.55
(.84)
11.EO
3.21
0.84
7.02
.00
7.21
.06
7.18
.12
.16
.20
7.10
7.15
(.92)
12.CCEO
3.24
0.82
.07
7.06
7.21
.14
7.03
.08
.30
.35
7.19
7.29
.51
(.81)
13.ESI
3.68
1.43
.10
.13
.01
.07
.13
.06
.17
.23
7.05
7.08
.20
.15
(.69)
14.ISI
3.66
0.67
.13
.33
.07
.23
.14
.16
.22
.17
.00
.02
.18
.31
.18
(.77)
15.MI
3.70
0.62
.04
.17
7.08
.17
.18
7.01
.23
.28
7.01
7.07
.22
.41
.18
.51
(.77)
16.IO
PP
4.02
0.56
.11
.13
7.09
.20
7.05
.06
.16
.06
.03
7.09
.41
.33
.13
.28
.28
(.79)
17.TP
0.00
1.00
7.07
7.06
7.02
7.10
7.05
.03
.12
.17
.02
.13
.15
.08
7.10
.20
.10
.13
(.89)
Note
EE¼EnvironmentExploration;SE¼Self-Exploration;NOC¼Number
ofOccupationsConsidered;ISE¼Intended
System
aticExploration;
FR¼Frequency;AI¼AmountofInform
ation;FO¼Focus;SI¼SatisfactionwithInform
ation;ES¼ExplorationalStress;DS¼DecisionalStress;
EO¼EmploymentOutlook;CCEO¼Certainty
ofCareer
Exploration
Outcome;
ESI¼ExternalSearch
Instrumentality;ISI¼InternalSearch
Instrumentality;MI¼Method
Instrumentality;IO
PP¼Im
portance
ofObtainingPreferred
Position;TP¼Trainingperform
ance;all
r’s4.14:
p5
.05(one-tailed);allr’s4.19:p5
.01(one-tailed);values
atthediagonalrepresentinternalconsistency
estimates.
52 J. Rowold
Dow
nloa
ded
by [
The
Aga
Kha
n U
nive
rsity
] at
16:
55 1
6 O
ctob
er 2
014
Table 3. It should be noted that the CES subscales Focus, Satisfaction withInformation, and Internal Search Instrumentality were significantly and positivelyrelated to training performance, lending support for hypotheses H1e, H2a, and H3b,respectively. However, none of the other facets of career exploration was related totraining performance. As Number of Occupations Considered, EmploymentOutlook, Certainty of Career Exploration Outcomes, Explorational and DecisionalStress were hypothesized to be independent from training performance, H4a-ereceived support from the data, respectively. Interestingly, External SearchInstrumentality was related negatively to training performance. In sum, theindependent variables explained 19.3 per cent of variance in training performance(R2
adj¼ 9.2 per cent). Thus, career exploration, as assessed with the CES atorganizational entry, seems a valuable predictor of subsequent training performance,as assessed by trainers.
Discussion
The significant relationships between several aspects of career exploration andtraining performance stand out as the most important contribution of this study. Aconsiderable portion of variance in training performance was predicted by facets ofcareer exploration, a construct that has generally been neglected in prior trainingperformance research. The assessment of data in multiple points-in-time implemen-ted in the present study allows for a more causal interpretation of results.
Three aspects of career exploration were related positively to training perfor-mance. More specifically, future employees who were (a) highly satisfied withinformation obtained, (b) engaged in highly focused career exploration, and
Table 3. Summary of Simultaneous Regression Analysis for Variables Predicting TrainingPerformance (n¼ 145)
Independent Variable B SE B b
1. Environment Exploration 7.12 .17 7.082. Self-Exploration 7.18 .14 7.133. Number of Occupations Considered .02 .09 .024. Intended Systematic Exploration 7.18 .11 7.165. Frequency .02 .08 .036. Amount of Information 7.02 .14 7.017. Focus .19 .09 .18*8. Satisfaction with Information .43 .20 .22*9. Explorational Stress 7.07 .11 7.0610. Decisional Stress .16 .09 .1911. Employment Outlook .15 .12 .1312. Certainty of Career Exploration Outcome 7.15 .14 7.1213. External Search Instrumentality 7.13 .06 7.19*14. Internal Search Instrumentality .36 .15 .23*15. Method Instrumentality 7.08 .17 7.0516. Importance of Obtaining Preferred Position .23 .17 .13
NoteR2¼ 19.3 per cent; R2
adj¼ 9.2 per cent; *p5 .05.
Career Exploration Training 53
Dow
nloa
ded
by [
The
Aga
Kha
n U
nive
rsity
] at
16:
55 1
6 O
ctob
er 2
014
(c) reported a highly useful internal search strategy performed better in a subsequenttraining programme. While Internal Search Instrumentality was positively associatedwith subsequent training performance, External Search Instrumentality showed anegative relationship. This result warrants further discussion. A possible explanationfor the negative relationship between External Search Instrumentality and trainingperformance might be that although career-related information that has beenacquired externally has been judged as highly useful by the future employee, theinformation was either not accurate or not up-to-date when the training programmeoccurred. For example, conversations with friends and relatives are externalexploration strategies. Future employees might have acquired information that theythemselves judged as highly useful, although the information was imprecise, biased,or gossip-like, and thus, to a larger degree inaccurate and misleading.
The distinction between Internal and External Search Instrumentality reminds usof the concepts of internal versus external locus of control (Rotter, 1966). From atheoretical perspective, it is reasonable to assume that persons with an internal locusof control score high on Internal Search Instrumentality, and persons with an externallocus of control score high on External Search Instrumentality (Stumpf et al., 1983a;cf. Table 1). It was demonstrated by a meta-analysis (Colquitt et al., 2000) thatemployees with an internal locus of control have higher motivation to learn thanemployees with an external locus of control. In turn, motivation to learn was relatedpositively to training performance. As a speculation, both the positive effect ofInternal Search Instrumentality and the negative effect of External Search Instru-mentality on training performance that were observed in the present study could beredundant to the underlying dispositional construct of locus of control (cf. Blustein,1988). Within the same line of thought, it might be interesting to compare the CESsubscale of Focus with general meta-learning capabilities (Lubinski and Davis, 1992).
As hypothesized, no relationship between five aspects of career exploration (i.e.Number of Occupations Considered, Employment Outlook, Certainty of CareerExploration Outcomes, Explorational and Decisional Stress) and training perfor-mance was observed. These aspects were important within the theory of careerexploration, as outlined by Stumpf and his colleagues (1983a). With regard to theresults of the present study, the hypothesized independence of these five aspects ofcareer exploration and training performance was supported. As outlined in theTheory section, the relationship between these aspects of career exploration andtraining performance could be further clarified by exploring the role of moderatingvariables such as personality (cf. Reed et al., 2004).
Implications for Theory
The results obtained in the present study extend our understanding of the effects ofcareer exploration on training outcome criteria. Prior research provided inconsistentsupport for the positive relationship between career exploration and trainingoutcome variables. One possible explanation for this inconsistency might be theimplementation of a combined scale of career exploration in prior research. Forexample, Noe and Schmidt (1986) combined five subscales of career exploration (i.e.Self, Environment, and Intended-Systematic Exploration, Amount of Information,and Focus), into a single measure and found no relationship with training
54 J. Rowold
Dow
nloa
ded
by [
The
Aga
Kha
n U
nive
rsity
] at
16:
55 1
6 O
ctob
er 2
014
performance. Of these five subscales of career exploration, only Focus was related totraining performance in the present study. Facteau et al. (1995), who reported apositive relationship between a combined scale of career exploration and trainingperformance, did not explicate which subscales of the CES were implemented in theirstudy. Consequently, it was not possible to conclude which specific aspect of careerexploration was responsible for the results obtained in their study. This resultunderlines the importance of a differentiated assessment of career exploration in thefield of training research. Only if that is the case, a comprehensive understanding ofvarious influences of facets of career exploration on the training process seemsfeasible. By the implementation of all sixteen CES subscales, the present studyaccounted for the complexity of the construct of career exploration andconsequently, allowed for a more thorough understanding of the effects of trainees’individual career attitudes on the training process.
The present study points to an interesting expansion of recent models of thetraining process (Cannon-Bowers et al., 1995; Colquitt et al., 2000; Holton, 1996). Sofar, these models included career exploration as a one-dimensional construct.However, the theory of Stumpf and colleagues (1983a) allows for a moredifferentiated assessment of facets of career exploration. For the advancement ofour theoretical understanding of the training process, specific relationships betweenseveral of these sixteen dimensions of career exploration and training outcomevariables such as training performance, transfer performance, etc., should beproposed and, consequently, tested empirically. The present study is a first attemptin this direction, demonstrating how constructs of career theory can help to expandthe theoretical understanding of the training process.
Recent trends in the labour market force employees to utilize career exploration inorder to be prepared for new jobs, employees, or career paths. Thus, it is likely thatthe construct of career exploration will become more important in the near future. Inthe past two decades, training effectiveness research (Colquitt et al., 2000) focused onvariables such as organizational commitment that were most relevant in times ofstable careers. However, it might be speculated that the recent trends in the labourmarket will turn the attention of the research community to the role of career atti-tudes within the training process. Thus, in contrast to organizational commitment,concepts such as career commitment and – as demonstrated in the present study –career exploration seem valuable fields of future research.
Implications for Practice
In the past, the assessment of employees’ career exploration was used primarily forcareer counselling and career planning interventions (Blustein, 1989; Super and Hall,1978). However, the results of the present study demonstrate the usefulness of theconstruct of career exploration for practitioners in additional areas of humanresource activities. More specifically, several aspects of career exploration might beutilized for a) employee selection and b) subsequent training. For example, applicantswho have engaged in focused career exploration before entering the organizationspossess more information about their future work and aspired career and they arelikely to perform well in subsequent training interventions. Thus, with regard to theresults of the present study, in order to enhance learning (Woodall, 2005) and human
Career Exploration Training 55
Dow
nloa
ded
by [
The
Aga
Kha
n U
nive
rsity
] at
16:
55 1
6 O
ctob
er 2
014
capital (Rowold andMonninghoff, 2005), organizations will be interested in assessingapplicants’ career exploration and in including several subscales of the CES in theirrespective selection batteries. The results of the present study have also implicationsfor the work of HRD experts. For example, organizational career guidanceinterventions (Kim, 2005) could help to a) improve employees’ internal searchstrategy and b) to have a clear focus with regard to their respective career goals. Theseinterventions would ultimately result in higher training performance.
Limitations and Directions for Future Research
Several limitations and recommendations for future research should be noted. First,the present study was located in a call centre context. Future research should test theproposed relationships in different contexts. Second, while the present study focusedon direct effects of facets of career exploration on training performance, future studiescould test mediating mechanisms proposed by theory. For example, Colquitt’s et al.(2000) meta-analytic path analysis revealed the importance of motivation to learn as amediating construct between individual (e.g. conscientiousness) variables and train-ing performance. Consequently, future research could test if motivation to learnmediates the effect of certain facets of career exploration on training performance.This would be consistent with earlier research that found relationships betweenmotivational processes and career exploration (Blustein, 1988). This type of researchwould allow for a more comprehensive understanding of the training process.
Next, while the present study assessed career exploration prior to organizationalentry, future studies could focus on the assessment of this construct after theorganizational entry. It might be speculated that within the first months of tenure,organizational socialization has an effect on career exploration. Thus, it would beinteresting to test the effect of career exploration on training performance in a settingwhere career exploration is assessed after a few months of tenure. From a theoreticalperspective, this research would help to understand the temporal dynamics of careerexploration and the effect of career exploration on performance.
Third, additional research is needed that compares and contrasts previouslyestablished constructs with subscales of career exploration in order to arrive at amore parsimonious description of the phenomenon. For example, it was speculatedabove that the CES subscales of Internal and External Search Instrumentality arerelated to the well-known constructs of internal vs. external locus of control. Futureresearch has to provide evidence for these relationships and thus should includemeasures for career exploration and locus of control. It was argued that in general,individual dispositions such as locus of control and other personality characteristicsshould be related to individual levels of career exploration (Kracke, 2002; cf. Reedet al., 2004). Within applied fields such as career counselling, this type of researchwould help to select appropriate career exploration and career guidance programmesfor different personalities.
References
Atkinson, C. (2002) Career management and the changing psychological contract, Career Development
International, 7, pp. 14 – 23.
56 J. Rowold
Dow
nloa
ded
by [
The
Aga
Kha
n U
nive
rsity
] at
16:
55 1
6 O
ctob
er 2
014
Baldwin, T. T. and Ford, J. K. (1988) Transfer of training: A review and directions for future research,
Personnel Psychology, 41, pp. 63 – 105.
Bartlett, K. and Kang, D. S. (2004) Training and organizational commitment among nurses following
industry and organizational change in New Zealand and the United States, Human Resource
Development International, 7, pp. 423 – 40.
Blustein, D. L. (1988) The relationship between motivational processes and career exploration, Journal of
Vocational Behaviour, 32, pp. 345 – 57.
Blustein, D. L. (1989) The role of career exploration in the career decision making of college students,
Journal of College Student Development, 30, pp. 111 – 17.
Blustein, D. L. (1997) A context-rich perspective of career exploration across the life-roles, Career
Development Quarterly, 45, 260 – 74.
Cannon-Bowers, J. A., Rhodenizer, L., Salas, F. and Bowers, C. A. (1998) A framework for understanding
pre-practice conditions and their impact on learning, Personnel Psychology, 51, pp. 291 – 320.
Cannon-Bowers, J. A., Salas, E., Tannenbaum, S. I. and Mathieu, J. E. (1995) Toward theoretically based
principles of training effectiveness: A model and initial empirical investigation, Military Psychology, 7,
pp. 141 – 64.
Clarke, N. (2002) Job/work environment factors influencing training transfer within a human service
agency: Some indicative support for Baldwin and Ford’s transfer climate construct, International
Journal of Training and Development, 6, pp. 146 – 62.
Clarke, N. (2005) Workplace learning environment and its relationship with learning outcomes in
healthcare organizations, Human Resource Development International, 8, pp. 185 – 205.
Colquitt, J. A., LePine, J. A. and Noe, R. A. (2000) Toward an integrative theory of training
motivation: A meta-analytic path analysis of 20 years of research, Journal of Applied Psychology, 85,
pp. 678 – 707.
Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications, Journal of
Applied Psychology, 78, pp. 98 – 104.
Facteau, J. D., Dobbins, G. H., Russell, J. E. A., Ladd, R. T. and Kudisch, J. D. (1995) The influence of
general perceptions of the training environment on pretraining motivation and perceived training
transfer, Journal of Management, 21, pp. 1 – 25.
Greenhaus, J. H. and Sklarew, N. D. (1981) Some sources and consequences of career exploration, Journal
of Vocational Behavior, 18, pp. 1 – 12.
Holton, E. F. (1996) The flawed four-level evaluation model, Human Resource Development Quarterly, 7,
pp. 13 – 19.
Holton, E. F. (2005) Holton’s evaluation model: New Evidence and construct elaborations, Advances in
Developing Human Resources, 7, pp. 37 – 54.
Holton, E. F., Bates, R. A. and Ruona, W. E. (2000) Development of a generalized learning transfer
system inventory, Human Resource Development Quarterly, 11, pp. 333 – 60.
Holton, E. F., Bates, R. A. and Syler, D. L. (1997) Toward construct validation of a transfer climate
instrument, Human Resource Development Quarterly, 8, pp. 95 – 113.
Jordaan, J. P. (1963) Exploratory behavior: The formation of self and occupational concepts, in:
D. E. Super, R. Stratishersky, N. Mattin and J. P. Jordaan (Eds) Career development self-concept theory
(New York: College Examination Board).
Kim, N. (2005) Organizational interventions influencing employee career development preferred
by different career success orientations, International Journal of Training and Development, 9, pp. 47 – 61.
Kracke, B. (2002) The role of personality, parents and peers in adolescents’ career exploration, Journal of
Adolescence, 25, pp. 19 – 30.
Lubinski, D. and Davis, R. V. (1992). Aptitudes, skills and proficiencies, in: M. Dunnette and
L. M. Hough (Eds) Handbook of Industrial and Organizational Psychology, Vol. 3 (2nd edn), pp. 1 – 59
(Palo Alto, CA: Consulting Psychologists Press, Inc.).
McMahon, J. E. and Merman, S. K. (1996) Career development, in: R. L. Craig (Ed.) Training and
Development Handbook. A Guide to Human Resource Development (4th edn), pp. 756 – 70 (New York:
McGraw-Hill Trade).
Noe, R. A. and Schmitt, N. (1986) The influence of trainee attitudes in training effectiveness: Test of a
model, Personnel Psychology, 39, pp. 497 – 523.
Noe, R. A. (1986). Trainee’s attributes and attitudes: Neglected influences on training effectiveness,
Academy of Management Review, 11, pp. 736 – 49.
Career Exploration Training 57
Dow
nloa
ded
by [
The
Aga
Kha
n U
nive
rsity
] at
16:
55 1
6 O
ctob
er 2
014
Reed, M. B., Bruch, M. A. and Hasse, R. F. (2004) Five-factor model of personality and career
exploration, Journal of Career Assessment, 12(3), pp. 223 – 38.
Rotter, J. B. (1966) Generalized expectancies for internal versus external control of reinforcement,
Psychological Monographs, 80, pp. 600 – 9.
Rowold, J. (2006). Questionnaire for the assessment of career exploration – Validity of a German version
of the Career Exploration Survey (CES-D) [Fragebogen zur Laufbahnerkundung – Zur Validitat einer
deutschen Version des Career Exploration Survey (CES-D)]. Manuscript submitted for publication.
Rowold, J. and Monninghoff, M. (2005) Strategic human resource utility analysis, Journal of Human
Resource Costing and Accounting, 9, pp. 10 – 25.
Ruona, W. E., Leimbach, M., Holton, E. F. and Bates, R. (2002) The relationship between learner utility
reactions and predicted learning transfer among trainees, International Journal of Training and
Development, 6, pp. 218 – 28.
Salas, E. and Cannon-Bowers, J. A. (2001) The science of training: A decade of progress, Annual Review of
Psychology, 52, pp. 471 – 99.
Stumpf, S. A. and Colarelli, S. M. (1980) Career exploration: development of dimensions and some
preliminary findings, Psychological Reports, 47, pp. 979 – 88.
Stumpf, S. A. and Hartman, K. (1984) Individual exploration to organizational commitment or
withdrawal, Academy of Management Journal, 27, pp. 308 – 29.
Stumpf, S. A. and Lockhart, M. C. (1987) Career Exploration: Work-role salience, work preferences,
beliefs, and behavior, Journal of Vocational Behavior, 30, pp. 258 – 69.
Stumpf, S. A., Austin, E. J. and Hartmann, K. (1984) The impact of career exploration and interview
readiness on interview performance and outcomes, Journal of Vocational Behavior, 24, pp. 221 – 35.
Stumpf, S. A., Colarelli, S. M. and Hartmann, K. (1983a) Development of the Career Exploration Survey
(CES), Journal of Vocational Behavior, 22, pp. 191 – 226.
Stumpf, S. A., Colarelli, S. M. and Hartmann, K. (1983b) The Career Exploration Survey: A summary of
its dimensionality, reliability, and validity, Psychological Reports, 51, pp. 117 – 18.
Sullivan, S. E. (1999). The changing nature of careers: A review and research agenda, Journal of
Management, 25, pp. 457 – 84.
Super, D. E. and Hall, D. T. (1978) Career development: exploration and planning, Annual Review of
Psychology, 29, pp. 333 – 72.
Wolf, G., London, M., Casey, J. and Pufahl, J. (1995) Career experience and motivation as predictors of
training behaviors and outcomes for displaced engineers, Journal of Vocational Behavior, 47, pp. 316 –
31.
Woodall, J. (2005) International management development, in: T. Edwards and C. Rees (Eds)
International HRM: A Critical Introduction, pp. 34 – 58 (London: Pearson).
58 J. Rowold
Dow
nloa
ded
by [
The
Aga
Kha
n U
nive
rsity
] at
16:
55 1
6 O
ctob
er 2
014