INDIVIDUAL AND SITUATIONAL INFLUENCES ON THE ...130.18.86.27/faculty/warkentin/SecurityPapers/Merrill/...that situational influences such as reinforcement and punishment contin-gencies,

PERSONNEL PSYCHOLOGY1993.46

INDIVIDUAL AND SITUATIONAL INFLUENCES ON THEDEVELOPMENT OF SELF-EFFICACY: IMPLICATIONSFOR TRAINING EFFECTIVENESS

JOHN E. MATHIEU, JENNIFER W. MARTINEAUPennsylvania State University

SCOTT I. TANNENBAUMState University of New York at Albany

We proposed a model that included individual and situational an-tecedents of self-efficacy development during training. Initial perfor-mance and self-efficacy levels, achievement motivation, and choicewere examined as individual variables. Constraints, operationalizedat both the individual and aggregate levels of analysis, were exam-ined as situational influences. Mid-course efficacy was hypothesizedto have positive linear relationships with training reactions and subse-quent performance, and an interactive relationship with performancewhen training reactions were considered as a moderator. Survey datawere gathered at two points in time from 215 students enrolled in 15eight-week long university bowling classes. All of the hypothesized an-tecedents of mid-course self-efficacy were significant except aggregateand individual situational constraints, although both constraints re-lated negatively to training reactions. Time 2 self-efficacy exhibited sig-nificant positive influences on training reactions and subsequent per-formance, but the hypothesized moderated relationship was not sup-ported.

Recent theorizitig and research concerning influences on training ef-fectiveness have moved beyond a focus on the training program andits attributes, and adopted a more global or systems perspective (Tkn-nenbaum & Yukl, 1992). For example, Campbell (1988) argued thatthe effects of individual and situational variables on training effective-ness should be considered. He noted that individual variables such astrainees' goals; their levels of self-efficacy before, during, and after train-ing; and the self-regulatory behaviors of trainees could all impact theultimate effectiveness of a program. Furthermore, Campbell suggestedthat situational influences such as reinforcement and punishment contin-gencies, socialization, and group processes that influence trainees' goals.

We thank three anonymous reviewers for their helpful comments on an earlier versionof this article.

Requests for reprints and other correspondence concerning this article should be sentto John Mathieu, 437 Moore Building, Department of Psychology, Pennsylvania StateUnivereity, University Park, PA 16802 or via BITNET to NI7 @ PSUVM.

COPYRIGHT © 1993 PERSONNEL PSYCHOLOGiY. INC.

125

126 PERSONNEL PSYCHOLOGY

self-efficacy, and instrumentality judgments should be incorporated intotraining effectiveness studies. In short, training research is expanding in-quiry beyond the method or learning techniques used by any particularprogram, and is beginning to consider the larger context within whichtraining programs reside. Accordingly, the purpose of the present studyis to examine more thoroughly the role of individual and situational an-tecedents of training effectiveness in a skills development program.

Previous work concerning the effects of individual variables on train-ing effectiveness has yielded many significant insights. In particular,studies have found significant correlations between various operational-izations of training related motivation and subsequent affective reac-tions (e.g., Mathieu, Tannenbaum & Salas, 1992; Tannenbaum, Math-ieu, Salas & Cannon-Bowers, 1991), learning (e.g., Baldwin, Magjuka &Loher, 1991; Clark, 1990; Mathieu et al., 1992), and performance (e.g..Hicks & Klimoski, 1987; Rails & Klein, 1991). One related constructthat has been receiving well-deserved attention in the training researchhterature is self-efficacy, or a trainee's perceived capability to performa specific task (Gist, 1987). In the current study, we present a model ofantecedents of self-efficacy development during training, and the subse-quent influence of self-efficacy on trainees' reactions and performanceimprovement. Below we review the existing research concerning self-efRcacy and its influence on various training outcomes in order to de-velop our hypothesized model.

Self-Efficacy and Training Effectiveness

Self-efficacy is ". . . defined as people's judgments of their capabilitiesto organize and execute courses of action required to attain designatedtypes of performances. It is concerned not with the skills one has butwith judgments of what one can do with whatever skills one possesses"(Bandura, 1986, p. 391). Self-efficacy has been shown to predict perfor-mance in computer software training (Gist, Schwoerer, & Rosen, 1989),interpersonal skills training (Gist, Stevens & Bavetta, 1991), and mili-tary training programs (Eden & Ravid, 1982; Tannenbaum et al., 1991).Furthermore, self-efficacy levels at the conclusion of training have ex-hibited significant correlations with post-training transfer and job per-formance measures. Ford, Quinones, Sego and Sorra (1992) found thatself-efficacy levels among Air Force mechanic trainees were related totask opportunities in their initial job assignment. Frayne and Latham(1987; Latham & Frayne, 1989) found that self-efficacy predicted jobattendance both during training and 9 months after the completion oftraining. In short, previous research has substantiated the important

JOHN E. MATHIEU ET AL. 127

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Model of the Role of Self-Efficacy on Training Effectiveness

Bandura (1986) argued that self-efficacy develops gradually throughrepeated task-related experiences. Elsewhere, he (Bandura, 1989,1991)and Gist and Mitchell (1992) have outlined several antecedents of effi-cacy development. Gist and Mitchell classify these antecedents as ei-ther intemal (i.e., individual) or extemal (i.e., situational). Mathieu etal. (1992) advanced a similar framework when discussing antecedentsof a valence-instrumentality-expectancy training motivation compositeas either individual or situational. Included in Gist and Mitchell's in-ternal category are individual attributes such as knowledge, skills andabilities, performance-related strategies, personality factors, and moodstates. For example, Bandura (1991) argued that individuals monitortheir experiences and base subsequent efficacy judgments, in part, onthe extent to which they perceive their performances were attributableto their abilities and effort. Further, he argued that personality needs,such as achievement motivation, exert indirect influence on performanceby impacting efficacy perceptions (Bandura, 1989). In the current study,we examine previous performance, the extent to which individuals choseto participate in the program, and achievement motivation as individualinfluences on efficacy development during training.

Gist and Mitchell's (1992) extemal category includes influences suchas task attributes (e.g., difficulty, complexity), distractions, and norma-tive information (e.g., models, persuasion). For example, Bandura andWood (1989) found that individuals' efficacy levels decreased when theywere placed in a constrained situation where they were led to believe thatthey had little control. In the current study, we consider different typesof situational constraints as extemal influences on efficacy developmentduring training.

One factor that cannot be neatly classified as either intemal or exter-nal is enactive mastery; which is defined as individuals' previous experi-ences in the same or similar situations (Bandura, 1986). While primarilyan individual variable, the relative difficulty, complexity, and other at-tributes of previous task experiences will also influence individuals' per-ceptions of enactive mastery. Thus, while enactive mastery varies perindividual, it is partly determined by extemal characteristics such as, thetask assignments, resource availability, or the experimental conditionsto which subjects have been previously assigned. For sake of discussion,however, we consider enactive mastery experiences as an individual vari-able.


Hypothesized Antecedents of Self-Efficacy Development

Initial self-efficacy. Participants' initial levels of self-efficacy (i.e., self-efficacy-1), as assessed at the beginning of training, were hypothesizedto relate positively to later levels of self-efficacy (i.e., self-efficacy-2).Gist et al. (1991), Latham and Frayne (1989), and Tiinnenbaum et al.(1991) have provided evidence that individuals' efficacy levels exhibitsome consistency over time. That is, self-efficacy levels are iikely tobe somewhat stable yet are also somewhat malleable over time (Gist &Mitchell, 1992). The path from self-efficacy-1 to seIf-efficacy-2 assessesthe degree of efficacy stability over time. Therefore, the other pathsleading to self-efficacy-2 predict the residual variance in efficacy, or thechanges that occur from one time to another.

Initial performance. Initial performance is represented by partici-pants' scores on the first of approximately 13 games they bowled through-out the course. In effect, this represents a baseline measure that playstwo critical roles in the current model. First, participants' scores at thebeginning of training may act as a surrogate measure of enactive masterythat reflects not only their first experience in this class, but also experi-ences that they had prior to the course. Thus, we anticipated that individ-uals who initially experienced greater success in the program would ev-idence greater self-efficacy development than would those who initiallyperformed poorly. Initial performance in the program was also includedin the equation predicting performance during the latter portion of thecourse to control for initial individual differences, and thereby, to isolatevariance in performance improvement during training.

Achievement motivation. Achievement motivation, defined as a de-sire "... to overcome obstacles, to exercise power, to strive to do some-thing difficult as well and as quickly as possible" (Murray, 1938, pp. 80-81), was also hypothesized to exhibit a positive influence on the de-velopment of self-efficacy. Achievement motivation is a relatively sta-ble individual attribute that predisposes individuals to approach situa-tions in a particular manner. High achievement motivated individualsgenerally prefer challenging tasks and perceive a stronger relationshipbetween their abilities and efforts and their performance, than do lessachievement motivated individuals (see Heckhausen, Schmalt & Schnei-der, 1985; Weiner, 1984). This pattern of relations led Meyer (1987) tohypothesize that differences in achievement motivation would lead todifferences in task specific ability perceptions, and by extension In thepresent context, to differences in self-efficacy. He reviewed previous re-search and found support for this contention in 8 of 13 studies (Meyer,1987). Therefore, we hypothesized that achievement motivation wouldrelate positively to the development of self-efficacy during training.


Choice. Hicks and Klimoski (1987) conducted a field experiment inwhich they manipulated trainees' choices conceming whether to attenda training program. Their results showed that participants who weregiven a choice reported greater satisfaction with the program, highermotivation to leam, more positive reactions, and performed better onan achievement test, as compared to individuals who were not givena choice of whether to attend the program. Similar results have beenobtained by Ryman and Biersner (1975), Mathieu et al. (1992), andBaldwin et al. (1991). In the present setting, the university required allundergraduates to eam three credits in P.E. to graduate, although theydid not need to enroll in a bowling class. Consequently, many studentsenroll in P.E. courses not because they wish to learn a particular skill, butsimply to fulfill a requirement. In short, some students want to be in thecourse, whereas others are simply "getting their tickets punched."

We hypothesized that students who chose, or wanted, to be in thecourse would report more positive training reactions. Furthermore, weassumed that individuals who intentionally enrolled in a bowling classwould do so, in part, because they believed that they could perform well.Indeed, Bandura (1982,1989,1991) argued that individuals' self-efficacywould influence their choices concerning the situations in which they arewilling to participate. Extending this reasoning to the present setting,we hypothesized that individuals who wanted to participate in bowlingwould do so, in part, because they felt that they could develop the neces-sary skills and perform well in the class. Further, to the extent that par-ticipants did not wish to be in the course, we expected that they wouldlikely experience reactance, psychologically disengage from the activity,and would be less likely to develop self-efficacy than would those whowanted to be there. Bandura (1989, 1991) has summarized previous re-search which has suggested that when individuals do not care about theirperformance in a given situation, they do not engage in self-regulatoryprocesses. Thus, we anticipated a positive influence of choice on thedevelopment of efficacy.

Situational constraints. The final two antecedents depicted in Fig-ure 1 are individual and aggregate situational constraints. Situationalconstraints can be defined as characteristics of the environment that in-terfere with or restrict employees' performance (Peters & O'Connor,1980; Peters, O'Connor & Eulberg, 1985). Although typically conceivedof as aspects of the situation, previous research has yet to differentiatethe level(s) of analysis at which constraints operate. In the current study,we distinguish constraints that exist at different levels of analysis. Specif-ically, situational constraints can covary at individual or aggregate levels.At the individual level of analysis, situational constraints refer to otherobligations or pressures placed on individuals that may differ from one


person to another. In the current setting, these may include the num-ber of other classes different students are taking, their extracurricularactivities, part-time jobs, and so forth. In work settings, individual-levelconstraints could refer to any inhibitor that differs from one person toanother (e.g., specific job tasks, time pressures, nonwork or family diver-sions, lack of feedback, etc.).

Aggregate situational constraints refer to environmental featuresthat are common to a set or group of employees and hinder or limitperformance. Examples of such constraints in the training environmentwould include, but not be limited to, differences in training sessions,classes, or group influences that interfere with leaming processes. Inthe current setting, 15 different bowling classes were sampled. The pri-mary factors that differed from one class to another were the instruc-tors and their teaching styles, but other features such as time and equip-ment availability also differed somewhat. In more traditional trainingsettings, aggregate constraints in the training environment could includethe trainer, equipment, facilities, training methods, and so forth; namely,any inhibitor that may differ from one training group to another.

We hypothesized that both individual and aggregate constraintswould relate negatively both to the development of self-efficacy andto training reactions. Phillips and Freedman (1984) found support fora negative relationship between individuals' perceptions of situationalconstraints and their work motivation. Mathieu et al. (1992) founda negative relationship between perceived situational constraints andan index of training-related motivation. Further, Peters et al. (1985)reviewed several studies that have obtained negative relationships be-tween individuals' perceptions of constraints and their affective reac-tions. Gist and Mitchell (1992) argued that when individuals are focusedupon formidable aspects of a task they report lower levels of self-efficacy.

What is not clear from the research summarized above, however, isthe extent to which the detrimental effects of situational constraints areattributable to individual or aggregate processes. The effects emanat-ing from individual situationai constraints in the current study repre-sent individual-level processes, whereas the effects from aggregate sit-uational constraints represent cross-level processes (see Mathieu, 1991,and Rousseau, 1985 for more discussion of these designs). Because pre-vious theory and research has yet to disentangle these two constmcts, wehypothesized negative paths from both types of constraints to the devel-opment of efficacy and reactions to the program.


Effects of Self-Efficacy on Training Outcomes

Gist (1987; Gist & Mitchell, 1992) argued that trainees' self-efficacyrepresents a critical mediating variable in the effectiveness of trainingprograms. For example, Frayne and Latham (1987) found that trainees'self-efficacy levels mediated the influence of a self-management trainingprogram on work attendance levels during training. Given the demon-strated pervasive effects of self-efficacy on performance in a variety ofsettings (cf. Bandura, 1989, 1991; Gist, 1987), we hypothesized that ef-ficacy assessed at the mid-point of the course would relate significantlyto performance during the latter half of the program, after controllingfor initial performance levels. Further, we hypothesized that mid-courseself-efficacy would relate positively with participants' training reactions.Bandura and Schunk (1981) argued that when individuals experience asense of self-efficacy in a situation, they are more likely to develop aninterest in the activity than are those who fail to develop such efficacy.Thus, we hypothesized that individuals who develop greater levels ofself-efficacy by mid-way through the course would report greater interestin bowling and react more positively to the course.

Besides the effects discussed above, reactions and self-efficacy werehypothesized to interact as related to performance during the latter por-tion of the course. Alliger and Janak (1989) conducted a meta-analysisof studies that included two or more measures of Kirkpatrick's (1976)4-fold typology of training outcomes: (1) reactions, (2) learning, (3) be-havior change, and (4) results. TTiey concluded that although significantpositive relationships are generally found between learning, behavior,and results, training reactions tend to be unrelated to other outcomes.Mathieu et al. (1992) argued that Alliger and Janak's (1989) results donot preclude other forms of relationships between training reactions andother outcome measures. Mathieu et al. suggested and found support fora moderated relationship between training motivation and training re-actions, as related to a measure of learning due to training. The form ofthe interaction was such that training motivation was more strongly re-lated (i.e., exhibited a steeper positive slope) to learning if participantsreacted positively to the program. Training motivation was still relatedpositively to learning among individuals who reacted negatively to theprogram, but to a lesser degree.

Applied to the present context, the moderated relationship obtainedby Mathieu et al. (1992) would suggest that trainees' mid-course self-efficacy might interact with their training reactions, so that efficacy wouldexhibit a more positive relationship with subsequent performance amongparticipants who reacted positively to the program. Finally, although a

JOHN E. MATHIEU ETAL. 133

path from training reactions to performance is included in the hypothe-sized model, based on Alliger and Janak's (1989) meta-analysis findings,we did not expect it to be significant. The path is included in the modelsimply to permit the test of the hypothesized moderated relationships.

Method

Participants/Program

The training program was an 8-week long introductory bowling courseat Pennsylvania State University in which students were instmcted ontechniques and were able to practice almost every class during the semes-ter. Five hundred six students were enrolled in 15 classes. Classes metfor either 50 minutes, three times a week, or 75 minutes, twice a week.

Obviously a University bowling class is markedly different from most"real" training settings. Nevertheless, this setting provides a valuableopportunity for examining the processes in question. First, because stu-dents had to take at least three credits of P.E. classes in order to graduate(but not necessarily a bowling class), we expected a wide range of atti-tudes concerning participation. Second, because the classes were taughtby several different instmctors, we anticipated that some between-classeffects could emerge. Third, a significant limitation of conducting re-search in most corporate training environments is the lack of meaningful,objective, quantifiable criterion measures (Saari, Johnson, McLaugh-lin & Zimmerle, 1988). The current setting does not suffer this short-coming. Bowling scores are directly quantifiable and objective, and canbe compared from one time to another and from one course to an-other. When gathered longitudinally, they provide a fairly uncontami-nated measure of skill acquisition. TTius, although the extemal validity,or generalizability to "real world" settings is naturally a concem here,the current setting offers many protections against threats to intemaland statistical conclusion validities and offers a "strong test" of the hy-pothesized relationships (Cook & Campbell, 1979).

Surveys were distributed during the first and fourth weeks of classes,and contained the measures described below. Students were asked tocomplete the surveys outside of class time and to retum them within aweek. Although 280 students completed the first survey, only 215 alsoreturned usable second surveys. This sample was 58% male and had anaverage age of 20.33 years. Statistical contrasts were performed betweenthose who did and did not retum the second survey, using demographicindices and other measures available from the first survey (see below).No significant (p >.O5) differences were obtained. Furthermore, therewere no significant differences between the performance levels of class


members who participated in the study and those who did not. Thus, dif-ferential mortality is not a threat to intemal validity (Cook & Campbell,1979).

Survey Measures

The first survey, administered on the first day of class, assessed par-ticipants' demographics, initial self-efficacy, achievement motivation,choice, and other measures not pertinent here (e.g., course expecta-tions). The second survey included measures of individual and aggregatesituational constraints, self-efficacy, and reactions to training, and wasadministered during the middle week of the course. Except for the de-mographic items, all responses were made on 7-point Likert-type scales,with higher values representing greater amounts of each variable. Scalescores were computed for each variable by averaging the items to whicha participant responded.

To assess self-efficacy, students were asked to rate the extent to whichthey believed that they could score at least each of eight bowling scores(i.e., 141,131,121, etc.) that corresponded to the grade levels they couldeam (i.e.. A, A-, B+, etc.). They responded to each level using a 7-pointscale that ranged from (1) "Almost no possibility" to (4) "About a 50/50chance" to (7) "Complete certainty." This scale exhibited high intemalconsistencies both at time 1 (a = .85) and at time 2 (a = .87). Further,participants'self-efficacy improved significantly (i(214)= 8.17,p < .001)between the first and second surveys (M = 4.23, SD = 1.22 and M = 4.86,SD = 1.15, respectively).

Achievement motivation was assessed using a 10-item scale (a = .74)adapted from Mehrabian and Banks (1978). Six items on this scale areworded negatively, and were reverse coded prior to analyses. This scalehas demonstrated acceptable reliability and predictive validity in previ-ous research (e.g., Mathieu, 1988). The scale measures the extent towhich participants (a) prefer challenging situations, (b) are comfortablewith making decisions or being in high-pressure situations, and (c) wouldwork hard rather than take it easy.

The university requires students to participate in three credits of P.E.to graduate. Two items were used to assess participants' choice of, orpreference for, their enrollment: "If the University did not require me totake P.E. courses, I would not take any during my undergraduate career"(reverse coded) and "I would take as many P.E. courses as I could fit intomy schedule during a given semester." These two items exhibited a =.62.

Individual and a^egate situational constraints were each assessed us-ing items included in the second survey. This timing was adopted so that

JOHN H. MATHIEU ETAL. 135

participants would have sufficient time and experience to evaluate theextent to which their class provided certain opportunities, and the otherdemands placed upon them during the semester. The 3-item individualconstraints scale assessed the extent to which extracurricular activitiesand other classes' workloads interfered with the amount of time partici-pants had to practice their bowling skills (a = .63).

The aggregate situational constraints, or those experienced by all par-ticipants in a given class, were assessed using a 3-item scale that mea-sured the extent to which adequate equipment, time, and encourage-ment were given to students. It is important to emphasize that althoughsurvey responses were collected from individual students, these itemsreferred to an aggregate class attribute. Thus, as discussed by Sirotnik(1980), the psychometric properties of this scale should be examined atthe aggregate level of analysis using a between groups matrix that con-tains item averages computed within groups. In order to justify aggre-gating students' responses within classes, however, it is first necessary todemonstrate that individuals within each class exhibit reasonably highlevels of agreement. James, Demaree and Wolf (1984) advanced an in-terrater reliability index (IRR) for such purposes. James et al.'s multi-item IRR formula contrasts the average observed item variance acrossresfjondents within a group, against that which might be expected from arandom response pattern. Low IRR values indicate a lack of agreementbetween individuals in a group, whereas high IRRs suggest that individ-uals within a group agree on some target variable (Kozlowski & Hattrup,1992). The 15 class IRRs ranged from .65 to .89 with a median value of.82. Thus, students within each class evidenced high agreement and theirresponses/wr item were averaged within each class. Finally, to calculatea reliability for the aggregate situational constraints, Cronbach's alphawas computed based on the item averages per class and was .67. Meanclass scores were then assigned to all students in the class (see Mathieu,1991 and Rousseau, 1985 for more discussion on this procedure).

Outcome Measures

Training reactions. Participants' affective reactions to the course weremeasured using a 4-item scale included in the second survey that assessedthe extent to which students enjoyed the class (a = .88). Two exampleitems are "I have had a good time in bowling so far this semester" and"I am happy that I am taking bowling this semester."

Performance. Students' course grades were determined, in large part,by how well they performed on a series of games bowled during the 8-week course. The exact number of games bowled per student varied


somewhat across the 15 classes because of class schedules and instruc-tion styles. On average, students bowled 13.5 games during the course.So as to maintain the temporal order of processes depicted in Figure 1,each participant's performance score was calculated as the average of thegames he or she bowled after retuming the second survey. Applying theSpearman-Brown prophecy formula using the average number of gamesplayed after survey 2 was retumed (i.e., 8.8), and the average weightedgame-to-game correlation (i.e., r = .34, p < .05), yields a stability coef-ficient of .82 for the performance measure. Finally, to control for initialindividual performance differences, we used participants' scores on theflrst games they bowled (which occurred after survey 1 and before survey2 was returned) as an initial performance, or baseline measure. Individ-uals improved significantly (t(214) = 5.90, p


and therefore should be interpreted cautiously. It is useful, however, fortesting the relative fit of nested models. We employed a p value of .05for determining the significance of competing models, and the individualmodel paths. GFI represents an index of the relative amount of the co-variances among the latent variables that are collectively accounted forby the hypothesized model. Generally, GFIs above .90 are consideredindicative of a good fit. RMSR is a measure of the average of the fittedresiduals, and when working in covariance metric, must be interpretedrelative to the magnitude of variables' variances and covariances.

The T-L index compares the relative fit and degrees of freedomfor a given structural model against a baseline model. One T-L indexwas calculated comparing the hypothesized model against a model thatspecified zero correlations among the latent variables (i.e., a null latentmodel). Values > .90 for this version T-L index are generally consideredas indicative of a good fit. Sobel and Bohrnstedt (1985) have argued thata null latent baseline model is too restrictive and recommended the useof "informed baseline models" for comparative purposes. Thus, we useda "null structural model," which hypothesized that none of the paths de-picted in Figure 1 would be significant, as a second baseline model.

Results

Descriptive statistics and observed correlations among all study vari-ables, and correlations among the latent variables, are presented in Tk-ble 1. However, the sample covariance matrix was used for all modeltests. The results of the hypothesized model, with and without the mod-erator term, are presented in Figure 1 and a summary of the model fitindices is presented in T^ble 2. The hypothesized model represented asignificant improvement over the null structural model that predicts nosignificant paths [x^-difference (14) = 228.56, p < .01], and exhibitedhigh fit indices [(x^(22) = 52.40 p < .01; GFI =.956; RMSR = .062;T-L vs. Null Latent = .988, T-L vs. Null Structural = .797]. However,some hypothesized relationships were not statistically significant. Specif-ically, aggregate situational constraints did not have a significant impacton self-efficacy-2, and the influence of individual situationai constraintswas only marginal {0 = - .141, p < .10). Further, choice did not have asignificant effect on reactions to training. Finally, as hypothesized, thelinear relationship between training reactions and perfonnance was notsignificant.

In order to assess the hypothesized moderated relationship betweenself-efiicacy-2 and training reactions, as related to performance, we per-formed a x^ difference test between models including and excluding the


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TABLE 2Summary of liirious Structural Model Fit Indices

Model fit indicesT-L vs.

null nullModels df X GFI RMSR latent structural

1. Hypothesizedwith interaction" 22 52.40* .956 .062 .988 .797

2. Hypothesizedwithout interaction" 23 52.79* .956 .063 .989 .810

3. Null structural 36 280.98* .797 .175 NA NA4. Null latent 55 6526.23* .196 .196 NA NA

Notes: dS= degrees of freedom; T-L = TUcker-Lewis incremental fit index; GF1=goodness of fit index; RMSR= root mean square residual.

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Antecedents of Self-Efficacy Development

Individual variables. Several individual-level variables influenced thedevelopment of self-efficacy, including initial performance, achievementmotivation, and trainee choice. Trainees' initial self-efficacy levels alsoexhibited a strong positive relationship with mid-course self-efficacy.That is, as in previous research, efficacy levels were somewhat consis-tent over time (Gist et al., 1991; Latham & Frayne, 1989; Tannenbaumet al., 1991). Alone, initial self-efficacy accounted for 39.06% of the vari-ance of mid-course efficacy. However, after controlling for time 1 self-efficacy, the other hypothesized antecedents accounted for a significantadditional 12.47% of time 2 self-efficacy variance.

Achievement motivation was positively related to the developmentof self-efficacy. Tt"ainees who entered the course with a predispositionfor challenging situations and hard work were more likely to exhibitincreased self-efficacy during training. However, achievement motiva-tion only appears to influence training effectiveness as mediated by self-efficacy, as an examination of the bivariate correlations revealed no di-rect relationships between it and either performance or training reac-tions. Thus, the relatively stable personality variable shaped trainees'cognitions about more specific instances (i.e., self-efficacy), which in turnhad an influence on training effectiveness. These findings are consistentwith Bandura's (1989) conception of the linkage between personal needsand self-efficacy development.

As hypothesized, trainees who chose to take this course were morelikely to develop increased self-efficacy during training. Perhaps traineeswho wanted to take the course entered more motivated to learn (e.g.,Baldwin et al., 1991), exerted more effort, and thus, correctly believedthat they would learn to bowl better than before. However, traineechoice was unrelated to training reactions. It is somewhat surprising thattrainees who wanted to attend did not report greater satisfaction thantrainees who had not wanted to be there. We can only speculate whythis occurred. Perhaps those trainees who wanted to attend this courseentered it with higher expectations than those who merely wanted their"ticket punched." There is some evidence that trainee desires and expec-tations are correlated and that a failure to meet trainee expectations canlead to reduced satisfaction (Tannenbaum et al., 1991). Perhaps sometrainees who wanted to take this course had false expectations, washingout any positive effect of choice on reactions.

Situational variables. We hypothesized that situational constraintswould relate negatively to the development of self-efficacy during train-ing. Previous research has shown the potentially debilitating effects of


situational constraints on employee performance (e.g., Peters & O'Con-nor, 1980). However, this study was the first to test whether constraintsoperate at different levels as related to training effectiveness. We exam-ined individual- or trainee-level constraints and aggregate- or course-level constraints. In addition, the correlation between the two types ofconstraints was non-significant (r = .085, n.s.) suggesting that they weretapping different phenomena. Furthermore, the two levels of constraintsexhibited different relationships with other variables.

Individual-level constraints exhibited a marginally significant (p <.10) negative impact on seIf-efficacy-2 in the hypothesized model. Thissame relationship became significant (p < .05), however, when the non-significant path from aggregate situational constraints to self-efficacy-2was trimmed from the model. Trainees who felt they had more individ-ual constraints (e.g., competing demands for their time) were less likelyto develop a belief that they could master the skills being trained. Thisis an important finding as it shows that events outside of training (i.e.,non-training demands) can have a debilitating influence on training ef-fectiveness. It suggests that managers must give careful attention to theobligations and pressures that their employees need to balance while at-tending training. Training does not occur in isolation from other job andpersonal obligations, and merely providing release time to attend train-ing may not be sufficient to maximize training effectiveness.

Trainees who reported the presence of constraints, whether individ-ual or course related, responded less favorably to the training. That is,whatever the source of the constraints, trainees translated any limita-tions in their environment into negative reactions to the training. Thus,it appears that constraints can have a negative influence on trainees' re-actions as well as on their self-efficacy. Many organizations rely on reac-tion forms to evaluate their training programs, yet most reaction formsdo not ask trainees anything about non-training issues (e.g., time con-straints). Therefore, organizations that use standard reaction measuresto revise their training may make fruitless "improvements" to a train-ing program if the actual source of discontent lies outside the trainingcontext.

In contrast to individual constraints, training environment constraintswere not related to the development of self-efficacy. Because the aggre-gate-level measure was significantly related to training reactions, it is un-likely that the non-significant finding for self-efficacy can be attributablestrictly to statistical power or to measurement issues. However, it is pos-sible that in this training context the constraints were not severe enoughto interfere with actual performance and thus, did not interfere with thedevelopment of self-efficacy.


Overall, these findings highlight the importance of identifying andminimizing constraints within the entire training system—not just in thetraining program. In addition, they suggest the need to treat and di-agnose different types of constraints separately. In the current context,individual-level and training-level constraints both had a negative influ-ence on trainee reactions, but more importantly, individual constraintshad a debilitating effect on trainee self-efficacy. Researchers may wantto examine how altemative methods of "freeing" employees to attendtraining can influence trainee self-efficacy, motivation to learn, and sub-sequent training outcomes. For example, in one study that reportedhigh training effectiveness, managers performed their subordinates' jobswhile the employees were attending training (Lee, 1991). While that ap-proach may not always be feasible, researchers should begin to examinedifferent ways to balance training needs with other job obligations andstresses.

We should also note that the aggregate-level constraints examinedin this study dealt specifically with the training program. Yet, aggregatesituational constraints are also likely to be present in the work environ-ment and could include different work technologies; rules, procedures,or policies; supervisor behaviors; or any other features that are commonto more than one employee. Work environment constraints are likelyto be most detrimental to transfer processes. For example, Rouiller andGoldstein (1991) found that aggregate aspects of the work environment(called climate for transfer) related significantly to subsequent trans-fer behavior even after controlling for individual difTerences in learning.Supportive climates enhanced transfer processes, whereas nonsupport-ive climates limited transfer. Thus, researchers and practitioners shouldtry to identify and to minimize aspects of individuals' jobs, the training,and the work environment, that constrain the learning process and ul-timately limit performance improvements. In a similar vein, attentionshould be directed at identifying features of the work and training envi-ronments that facilitate such processes (i.e., act as enhancers).

Self-Efficacy —* Performance Improvement

Linear effect. As hypothesized, self-efficacy assessed midway throughthe course contributed to subsequent performance improvement andwas positively related to training reactions. This is consistent with pre-vious research and further confirms the central role that self-efficacyplays in understanding and enhancing training effectiveness. Initial self-efficacy was also related to subsequent self-efficacy, and initial perfor-mance levels were associated with subsequent performance levels. Other


studies have shown how successful performance enhances the subse-quent development of self-efficacy (cf. Bandura, 1982, 1991). This sug-gests that there may be a form of positive, reinforcing feedback cycle thatoccurs between self-efficacy and perfomiance (Gist & Mitchell, 1992).Perhaps initial self-efficacy enhances skill acquisition and performancewhich in turn fosters subsequent self-efficacy. It is also conceivable thatthis phenomenon may carry over to related courses (cf. Gist, Bavetta,& Stevens, 1990), and over time could contribute to the establishmentof a "continuous leaming environment" within an organization. Indeed,this process may account for the pervasive effects of enactive mastery ex-periences on efficacy levels that has been observed in previous research.Future research should examine the longitudinal efFects of self-efficacyand performance over a sequence of training experiences.

Researchers and practitioners should also consider the use of main-tenance interventions, such as self-management or goal-setting applica-tions designed to maintain efficacy levels (cf. Gist et al., 1990; Gist etal., 1991). For example. Gist et al. (1991) found that post-training self-management interventions were effective maintenance strategies for in-dividuals who left training with low or moderate efficacy levels. In con-trast, goal-setting interventions proved more successful for individualswho left training with high efficacy levels. Clearly the interplay betweentrainees' efficacy levels, both during and after training, and factors out-side of the training environment need to be understood better to maxi-mize the effectiveness of training programs.

Training reactions as moderators. We found no support for a moder-ated relationship between reactions and mid-course self-efficacy, as re-lated to performance improvement. This is in contrast with the resultsfrom the Mathieu et al. (1992) study that reported a moderated effect be-tween motivation and reactions. However, there are several differencesbetween the two tests of moderation that may explain the seemingly con-flicting results. First, the Mathieu et al. study used a VIE measure oftrainee motivation rather than a self-efficacy construct. Although self-efficacy and motivation are similar constructs they are not synonymous(see Gist, 1987; Gist & Mitchell, 1992). Efficacy is similar to the effort -»perfomiance expectancy component of VIE theory, although the formeris a more encompassing concept that includes individuals' considerationsof task and situational attributes, and their ability to mobilize resourcesto accomplish the task. The instrumentality and valence componentsof VIE theory deal with linkages between performance and differentlyvalued outcomes. Thus, it may be that the moderating influence of train-ing reactions found in Mathieu et al. may be more attributable to theircombination with instrumentalities and valences than with effort —* per-fomiance expectancies. This represents a question for future research.


A second difference between the Mathieu et al. (1992) study and thisone is that the former used a leaming measure as the criterion for the testof interaction, whereas the current study used a performance measure.As noted earlier, a traditional leaming measure was not as applicable inthe current setting that focused on physical skill acquisition. Finally, thenature of the two samples differed markedly, which could account forthe different findings. In summary, although we failed to find a non-linear relationship among training criteria in the current context, webelieve that future researchers should continue to examine moderatedrelationships among training outcomes. It would be most informative tocollect both efficacy and VIE measures from a sample of trainees so asto test some of these altemative explanations directly.

Study Limitations

Although significant effects stemmed from individuals' choice, indi-vidual-level constraints, and aggregate constraints, these variables weremeasured with only a few items each and exhibited relatively low relia-bilities. We recommend that future researchers develop more compre-hensive scales for measuring these variables. Second, we believe that acomment on sampling decisions, as related to various validity inferences,is in order (Cook & Campbell, 1979). Traditionally, laboratory studiesare thought to yield greater intemal validity whereas field studies pro-vide more extemal validity. We chose our sample as a "middle ground"in order to balance the two competing demands. We wanted a researchsite that would enable us to control or to test for various threats to inter-nal validity (e.g., instrumentation, differential mortality), yet still sam-ple from an actual leaming environment with real consequences (albeit,simply a course grade). We also desired a setting that would minimizethreats to statistical conclusion validity (e.g., minimize range restriction,provide sufficient power). As part of this decision, we recognize thatsome compromises are inevitable. In particular, we acknowledge that auniversity bowling class is inherently different from a company trainingcourse on computer programming, engine repair, interpersonal skills,and so forth. Nevertheless, effective training depends, in part, on skillacquisition processes, whatever those skills may be.

In the current context we were able to study processes associated withthe acquisition of a physical skill (i.e., average improvement in bowlingscore was approximately 10%) in an environment that allowed for thecollection of objective perfonnance indicators and enhanced internaland statistical conclusion validity. Task attributes such as the nature, dif-ficulty, and complexity of activities, are likely to influence the magnitude


of effects that are observed (Gist & Mitchell, 1992) and the generalizabil-ity of findings. Therefore, these findings are probably most generalizableto jobs that require repetitive use of physical skills such as machine oper-ators, cashiers, pressors, or assembly line work. The nature of the train-ing program itself may also operate as an important boundary condition.For example, the bowling classes were conducted in a group setting andentailed primarily verbal and written instruction with some demonstra-tions. Other training methods, such as the use of video-taped feedback,extensive modeling efforts, and individually designed and paced pro-grams might influence the nature of the processes underlying effectiveprograms. As part of a programmatic effort to better understand theinfluences on training effectiveness, we encourage the extension of thisresearch into more traditional organizational settings where issues suchas the role of work environment constraints on trainees' efficacy and mo-tivation, and also transfer processes may be more thoroughly examined.

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