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Inducing Maximal VersusTypical Learning Through theProvision of a Pretraining GoalOrientationJessica Mesmer-Magnus a & ChockalingamViswesvaran ba University of North Carolina Wilmingtonb Florida International UniversityPublished online: 05 Dec 2007.

To cite this article: Jessica Mesmer-Magnus & Chockalingam Viswesvaran (2007)Inducing Maximal Versus Typical Learning Through the Provision of a Pretraining GoalOrientation, Human Performance, 20:3, 205-222, DOI: 10.1080/08959280701333016

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Inducing Maximal Versus TypicalLearning Through the Provision of a

Pretraining Goal Orientation

Jessica Mesmer-MagnusUniversity of North Carolina Wilmington

Chockalingam ViswesvaranFlorida International University

Goal setting has been used in a variety of contexts in an effort to induce maximal ef-fort and to facilitate greater performance outcomes than would otherwise be achievedthrough an individual’s more typical efforts. Do pretraining goals induce trainees tomaximize learning efforts in training? Does the type of goal matter? Wemeta-analytically cumulated the results of 61 independent studies (N = 10,151) thatexamined the efficacy of pretraining goals. Results suggest pretraining goals (regard-less of type) yield higher performance on posttraining cognitive, skill, and affectivelearning assessments than “no-goal” conditions. Performance-oriented goals facili-tated better performance on measures of declarative knowledge, whereas mas-tery-oriented goals yielded greater learning on higher levels of cognitive learning andfor all levels of skill-based learning. Further, mastery-oriented goals fostered greaterposttraining self-efficacy, more positive attitudes toward training, and better inten-tions to transfer training material than performance-oriented goals and no-goal con-ditions. Implications for research and practice are discussed.

Goal setting has been used in a variety of contexts to facilitate greater performanceoutcomes than would otherwise be expected (cf. Kozlowski et al., 2001; Locke &Latham, 2002; Mento, Steel, & Karren, 1987). In organizational training contexts,trainers may use goals to inspire superior mastery/learning of training content(mastery/learning-oriented goals) and/or better performance on posttraining as-

HUMAN PERFORMANCE, 20(3), 205–222Copyright © 2007, Lawrence Erlbaum Associates, Inc.

Correspondence should be sent to Jessica Mesmer-Magnus, Department of Management, Univer-sity of North Carolina Wilmington, 601 South College Road, Wilmington, NC 28443. E-mail:magnusj@unc.edu

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sessments of learning (performance-oriented goals). Conceptually, pretraininggoals (whether mastery- or performance-oriented) are implemented in an effort toinduce trainees to maximize their efforts toward learning by appropriately direct-ing their attention and motivation during training (Kozlowski et al., 2001; Mento etal., 1987). Without goals, trainee learning will likely be a function of the trainee’saverage tendency toward learning, resulting in a typical level of learning and per-formance on posttraining assessments (e.g., Fisher & Ford, 1998; Kanfer &Ackerman, 1989; Kanfer, Ackerman, Murtha, Dugdale, & Nelson, 1994).

The purpose of this research is to extend the concepts of maximal and typicalperformance to learning from organizational training programs. Specifically, weexamine the potential pretraining goals to create a “maximal learning” condition,wherein trainees are induced to attend to training and learn at higher levels thanwould otherwise be expected (typical learning). Performance is conceptualized asa multiplicative function of ability and motivation. Motivation, in turn, is definedby the choice to expend effort, chosen level of effort, and willingness to persistwith effort (Campbell, 1990). In training programs, the presentation of goals pro-vides trainees with the direction to expend effort, guides their level of effort, andprovides incentive to persist with the effort (at least during the training evaluation).As such, pretraining goals should generate maximal learning performance. We usemeta-analytic methodology to explore whether pretraining goals, by inspiringtrainee attention and motivation to maximize learning, yield learning at a level su-perior to that which would be obtained in conditions where trainees were not pro-vided such a goal. In addition, we examine whether the type of goal provided (mas-tery/learning or performance) interacts to determine the results of maximalperformance with regards to trainee learning.

MAXIMAL VERSUS TYPICAL PERFORMANCE

The idea that individuals may perform at different levels (maximal versus typical)depending on individual differences and contextual constraints has been examinedby a number of researchers, as such a discrepancy has implications for the validityof performance appraisals, personnel selection decisions, job design, and work as-signments (e.g., DuBois, Sackett, Zedeck, & Fogli, 1993; Sackett, Zedeck, &Fogli, 1988). Maximal performance assessments are thought to capture what an in-dividual is capable of doing (“can do”), whereas typical performance assessmentscapture what an individual generally “will do” (DuBois et al., 1993). Maximal per-formance is thought to be stimulated by situations wherein individuals are encour-aged and motivated to maximize effort and that the results of such efforts will beexplicitly evaluated (Klehe & Anderson, 2005; Sackett et al., 1988). In a typicalperformance context, the individual determines the degree of effort, persistence,

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and time he or she will devote to a task (DuBois et al., 1993). Due to varying levelsof interest and motivation, the resulting output in a typical performance conditionis, on average, of lower quality/quantity than would be achieved when an individ-ual is motivated to perform at his or her peak (Kirk & Brown, 2003; Sackett et al.,1988).

Thus there are three primary differences between conditions promoting maxi-mal versus typical performance. For maximal performance, (a) the participantsknow they are being evaluated, (b) the evaluation is conducted over a short time,and (c) all individuals are highly motivated to direct their efforts toward the evalu-ated performance. In most training contexts, trainees are aware an evaluation willoccur at some point during (or after) training. Thus two of the conditions to ensuremaximal performance are present (known evaluation and evaluation within a spec-ified short time frame). The third condition for maximal performance requires par-ticipants’ efforts be directed; this condition is more likely to be met in training pro-grams where the participants are provided with a pretraining goal, as such goalsdirect effort and motivate participants. Unless trainees are motivated (whether in-trinsically or extrinsically) to maximize their training performance and outcomes,the amount of learning that results from training would be at a level more typicalfor the trainee rather than at the trainee’s maximum learning capacity. Further-more, depending on the type of goal set in training (see discussion next), maximalperformance may result in different learning outcomes.

USING A PRETRAINING GOAL TO INDUCEMAXIMAL LEARNING

Two types of goals may be set prior to training, each differentially impacting atrainee’s cognitive, affective, and motivational processes during training and prac-tice. Both goals are likely to induce maximal performance, though the type of goallikely interacts to determine the results of maximal performance. Mastery/learn-ing goals are used to focus the learner on mastering training material for long-termuse and increasing task competence. The focus is on maximizing trainee efforts as-sociated with true learning. Trainees provided with a mastery goal are encouragedto increase their competence at a task and focus on how learning will result inself-improvement (Fisher & Ford, 1998; Kozlowski et al., 2001). Performancegoals, on the other hand, focus trainees on maximizing their attention to salient as-pects of training material that will facilitate successful performance onposttraining tests. Because these trainees focus on performing well on training cri-teria, they likely devote less time and effort to developing the level of task profi-ciency that would indicate true/maximal learning. So, both goals are provided withthe hope of maximizing performance—one for maximizing learning performance

LEARNING GOALS 207

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and the other for maximizing posttraining test performance. Because the focus oftrainees’maximal efforts is directed to different aspects of the training curriculum,the maximal performance induced by each type of goal will result in enhanced per-formance on different outcomes (posttraining learning assessments). The differen-tial effect of goal type on level of learning likely provides guidelines for whethermaximal or typical performance is assessed.

ASSESSING TRAINEE LEARNING

In their 1993 monograph, Kraiger, Ford, and Salas proposed that evidence oftrainee learning could be found within three unique capacities: cognitive, skill, andaffective learning outcomes. The learning-oriented goals of organizational trainingprograms may target one or more of these outcomes. An important conclusiondrawn from the Kraiger et al. taxonomy is that learning occurs in stages, and thelevel of learning achieved at each stage is contingent on the quality of learning thatwas achieved at the previous stage.

Cognitive outcomes of training include the development of verbal knowledge,knowledge organization, and cognitive strategies. Verbal knowledge, which mayinclude declarative, factual, procedural, strategic, and tacit knowledge (e.g., An-derson, 1982; Kraiger et al., 1993), lays the foundation for higher levels of cogni-tive learning (i.e., meaningful knowledge organization and strategic knowledge re-garding when/how to use training material). Knowledge organization andcognitive strategy development signal higher levels of learning because they repre-sent the integration of declarative knowledge into the trainee’s repertoire (Gagne,Briggs, & Wager, 1992; Kraiger et al., 1993). Skill-based outcomes refer to the de-velopment of motor or technical skills and involve three distinguishable stages:skill acquisition, compilation, and automaticity (Anderson, 1982; Gagne et al.,1992). Initial skill acquisition is measured by development of procedure-relateddeclarative knowledge (Day, Arthur, & Gettman, 2001). As with cognitive learn-ing, skill/task-related declarative knowledge lays the foundation for higher levelsof skill-based learning (i.e., integration of specific skill-related steps into a coher-ent whole and error-free task/skill performance; compilation and automaticity). Inthe final category of learning outcomes, affective learning, Kraiger et al. (1993) in-cluded all noncognitive and non-skill-based learning outcomes that also have im-portant implications for the success of training (e.g., attitude change, posttrainingself-efficacy, etc.). For example, a person’s self-efficacy for training material at theconclusion of training may have serious implications for the potential for transferto the work environment, as well as subsequent performance on the job (Noe,1986; Wood & Locke, 1987).

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SUMMARY AND HYPOTHESES

When no pretraining goals are provided (i.e., when no encouragement is providedto attain a specific level of learning), it is probably safe to assume that traineelearning performance will be representative of their average or typical learningtendencies (cf. Seijts, Latham, Tasa, & Latham, 2004). Specifically, trainees whotypically do well in learning contexts will likely do well in training; trainees whotypically perform poorly in learning contexts will probably perform consistently intraining. In either case, however, it is unlikely that the trainee will learn to his or hermaximum potential. In this context, the trainer has comparatively less control inexacting the desired learning than in a training context wherein a goal is set. So,consistent with past research, we would expect a main effect for pretraining goalsin inducing maximal learning performance during training.

H1: Trainees provided with a pretraining goal (whether mastery or perfor-mance) will have greater learning performance than trainees not providedwith a pretraining goal.

However, the type of pretraining goal may interact to determine the results ofmaximal performance. Specifically, pretraining goals may induce maximal learn-ing performance in two ways: (a) A performance goal could be set, wherein thetrainee is encouraged to do what is necessary to perform well on training tasks andposttraining learning assessments but may not give maximal performance in theactual learning of training concepts, or (b) a mastery goal is provided, wherein thetrainee is encouraged to master training content for long-term use.1 It could be ar-gued that each goal induces a maximal performance condition, but do these goalsproduce equivalent levels of learning? It seems that a goal to maximize perfor-mance on posttraining assessments (performance goal) would certainly yieldhigher scores on measures of the most basic levels of learning (e.g., declarativeknowledge and skill acquisition). Here, the assessment of training content is rela-tively straightforward (e.g., “What are the steps involved in this task?” “What arethe key concepts involved in this task?”). A trainee who is oriented toward per-forming well on this assessment would have concerned himself during training

LEARNING GOALS 209

1The use of the terms performance goal and mastery goal can be confusing when discussed in thecontext of maximal and typical performance. Those familiar with the literature on maximal versus typi-cal performance would likely expect that a performance goal would yield maximal performance acrossthe board (and over that which results from a mastery goal), because the focus of such a goal is in fact onmaximizing performance. Although this is true, when it comes to the level and type of learning whichresults from a training intervention, a performance goal may indeed maximize efforts in training, but itwill not focus trainee attention on the aspects of training curriculum that will promote the greatest levelsof learning (and therefore the greatest performance on learning assessments).

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with memorizing and attending to salient concepts. However, this trainee may nothave devoted the same level of effort to understanding conceptual interrelation-ships, hierarchies, and applications, which are required for true learning gains athigher levels and which would be visible in assessments of higher levels of learn-ing (e.g., knowledge organization, cognitive strategies, skill compilation). On theother hand, trainees whose motivation has been directed toward learning/master-ing training material (mastery-oriented trainees) would probably have focused lesseffort on simply memorizing concepts and more on understanding conceptual im-plications, applications, and interrelations, so they would be prepared to utilizetraining content later. These trainees’maximal performance would yield more suc-cess in learning and retaining training material and therefore would facilitate en-hanced performance on learning assessments of higher levels of learning. After all,mastery of new knowledge or a new skill requires far more than memorization ofconcepts or task sequences; it requires conceptual understanding, retention, andthe ability to apply new material to novel circumstances. Thus, although the per-formance-oriented trainee would outperform the mastery-oriented trainee on as-sessments of lower levels of learning, the mastery-oriented trainee would be betterprepared for assessments evaluating higher levels of learning. Although both train-ees were oriented toward maximal training performance, the focus of their motiva-tion led them to attend to different aspects of training and yielded performance dif-ferences on posttraining assessments of learning.

In sum, we expect the type of pretraining goal will have implications for the re-sults of trainee maximal learning efforts. Specifically, we hypothesize that perfor-mance goals will yield maximal performance, the effects of which will be reflectedin enhanced performance on all learning assessments but which will be strongestin lower levels of learning (e.g., declarative knowledge, skill acquisition). We ex-pect mastery goals will also induce maximal performance, the effects of which willbe reflected in enhancements across all posttraining learning assessments butwhich will be strongest in higher levels of learning (e.g., knowledge organization,skill compilation). Further, we would expect the strongest effect of maximal per-formance brought about by pretraining goals will be seen in mastery goal condi-tions at higher levels of learning. Table 1 depicts the hypothesized relationships be-tween the type of pretraining goal used to induce maximal learning and itsdifferential effects on learning.

H2: Trainees provided with a performance goal will have superior learning per-formance at lower levels of learning than trainees provided with a masterygoal.

H3: Trainees provided with a mastery goal will have superior learning perfor-mance at higher levels of learning than trainees provided with a perfor-mance goal.

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METHOD

To address these questions and to make use of the wealth of existing research thathas explored related questions, we employed meta-analytic methodology. A com-prehensive search of the extant literature was conducted using (a) a computerizedsearch of the PsycInfo, ABI Inform, and ERIC databases using appropriatekeywords and phrases (i.e., pretraining goals, goal orientation, mastery/perfor-mance orientation/goals, AND learning/training); (b) a manual search of refer-ences cited in recently published reviews (e.g., Cannon-Bowers, Rhodenizer,Salas, & Bowers, 1998) and in studies included in this meta-analysis; and (c) con-ference programs for recent meetings of the Society of Industrial and Organiza-tional Psychology, the Academy of Management, and the American PsychologicalAssociation. Studies were included in the database if they administered apretraining goal, measured at least one type of learning outcome (related to cogni-tive, skill, or affective outcomes), and reported sufficient information to facilitatethe computation of relevant effect sizes. In sum, 61 independent studies (N =10,151) reported in journal articles, dissertations, and conference presentationswere included in this study. Of these 61 independent studies, 21 provided a mas-tery/learning goal, 28 provided a performance goal, and 9 compared learning out-comes resulting from mastery goals versus performance goals. The studies in-

LEARNING GOALS 211

TABLE 1Hypothesized Relationships Between the Type of Goal

(Mastery vs. Performance) Used to Induce Maximal Learningand Learning Performance

Learning Outcomes (Posttraining Assessments)

Maximal LearningGoal Condition

Lower Levelsof Learning

Effect SizeComparison

>, = , <Higher Levelsof Learning

Pretraining goal vs. no goal + = +Mastery/learning goal vs. no goal + < +

(Strongest effectof pretraining goals)

Perf. goal vs. no goal +(2nd strongest effectof pretraining goals)

> +

Perf. goal vs. mastery/learning goal +Perf. > mastery

+Perf. < mastery

Note. Positive effects are indicated by +; negative effects are indicated by –. Perf. = performance.

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cluded in the meta-analytic database are available upon request from JessicaMesmer-Magnus.

Coding Procedures

Jessica Mesmer-Magnus undertook an independent effort to code studies that metthe criteria for inclusion in this meta-analysis. A random subset of the studies wascoded by a graduate-level research assistant, who was unfamiliar with the study’shypotheses, so that coder reliability could be determined. Intercoder agreementwas very high (97%), likely due to the objective nature of the data coded. Datacoded included the study sample size, the type of pretraining goal provided, mea-sures of learning outcomes, and reliability (if available) for criterion measures. Tobe included, the primary study’s pretraining goals must have been provided as anexplicit goal or as a goal imposed by or within the training environment prior to thecommencement of a training program or session. These goals may orient thetrainee toward mastering training content (mastery goals) or toward performingwell on posttraining assessments (performance goals). Either goal presumably in-spires trainee performance/learning in training at levels superior to that whichwould be obtained via a “typical” learning condition. That is, either goal by direct-ing form and level of effort attempts to keep motivational levels constant acrossindividuals.

However, the direction of trainee efforts will differ depending on the criteria oflearning assessed as elaborated in our earlier hypotheses (H2 and H3). The primarystudies provided data that facilitates an examination of the impact of pretraininggoals on learning by: (a) comparing the provision of a goal prior to training (re-gardless of goal type) to a “no-goal” condition, (b) comparing a mastery goal witha “no-goal” condition, (c) comparing a performance goal with a “no-goal” condi-tion, and (d) comparing a performance goal with a mastery goal. A positive corre-lation between performance and mastery goals and a learning outcome would indi-cate that the mastery goal was superior to a performance goal in promoting thattype of learning (i.e., effects were coded such that higher numbers indicated a mas-tery goal condition; lower numbers indicated a performance goal condition).

Coding of learning outcomes. Learning outcomes were coded using theKraiger et al. (1993) learning taxonomy as a guide. According to this taxonomy,cognitive learning may be assessed at any of three stages of learning: verbal knowl-edge (level of declarative, factual, procedural, or strategic knowledge attained),knowledge organization (accuracy of cognitive organization of declarative knowl-edge), and cognitive strategies (strategic knowledge of how/when to use trainedknowledge). Skill-based learning is also assessed at any of three stages of learning:skill acquisition (declarative skill-based knowledge), skill compilation (traineeability to perform discrete skill-related behaviors under conditions of maximal

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performance or ability to generalize skill-related behaviors to novel problems orcontexts), and skill automaticity (fluid, effortless, error-free, and invariant perfor-mance of skills). Finally, affective learning outcomes included attitudinal out-comes (most of which evaluated trainee assessment of the training program),posttraining self-efficacy, and disposition (typically trainee intention to use/trans-fer trained material).

Coding of study design. The design of each study was coded so that corre-lations collected from different designs, which would be reflective of different ef-fects, could be meta-analyzed separately. Approximately half of the studies uti-lized a between-subjects design, and sufficient data were reported to facilitate thecomputation of effect sizes representative of the differences between the posttestscores of experimental and control groups. Of the 61 studies coded, 30 studies uti-lized a correlational design (e.g., Seifriz, Duda & Likang, 1992). Here, participantperceptions of the goal orientation of the learning environment (performance vs.mastery) were assessed and then correlated with relevant learning outcomes. Be-cause the goal/learning correlations that result from these studies represent a dif-ferent type of effect than that which would be obtained from a “posttest only/con-trol group” design, these studies were examined separately.

Analysis

The meta-analytic methods outlined by Hunter and Schmidt (2004) were em-ployed to analyze the data. Effect sizes were compiled and transformed into a uni-versal measure of effect, r, using formulas provided in Hunter and Schmidt. Sam-ple sizes in the experimental and control groups were approximately the same inall studies. We weighted effect sizes by sample size to compute a sample-sizeweighted estimate of the observed effect size. The standard deviation of this effectsize (which is composed of true variation as well as variation due to artifacts likesampling and measurement error) across the multiple studies was also computed toprovide a sample-size weighted estimate of variability. Next, sample-sizeweighted mean observed correlations and standard deviations were corrected forunreliability in measures using artifact-distribution meta-analysis (Hunter &Schmidt, 2004). Artifact distribution meta-analysis uses a weighted mean reliabil-ity estimate (drawn from those studies that reported sufficient reliability informa-tion) to correct for unreliability in the measures. In this study, sufficient data wereavailable to correct only for unreliability within criterion (learning outcome)measures.

Information provided in the results table includes the number of correlationscompiled (k), the total sample size across all estimates (N), the sample-sizeweighted mean observed correlation (r), the sample-size weighted standard devi-ation (Sdr), the reliability-corrected correlation (ρ), the standard deviation of the

LEARNING GOALS 213

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reliability-corrected correlation (SDρ), the percentage of observed variance at-tributable to sampling error (%SEV), the percent variance attributable to all arti-facts (%ART), the 80% credibility interval around the reliability-corrected corre-lation, and a file-drawer analysis (FD k; Hunter & Schmidt, 2004; Rosenthal,1979) estimating the number of studies reporting null findings that would havebeen required to reverse any substantive conclusions (i.e., by reducing the re-ported reliability-corrected correlation to r = .10). When there were fewer thanthree primary studies examining a particular relationship, a meta-analysis wasnot conducted.

RESULTS

Hypothesis 1 proposed a main effect for pretraining goals wherein trainees pro-vided with a goal, regardless of type, would have greater learning performance(presumably because they maximized efforts in training) than trainees not pro-vided with a goal. Results provide support for this hypothesis (see Table 2). Spe-cifically, the provision of a pretraining goal (compared with a no-goal condition)explained up to about 8% of the variance in cognitive learning, up to approxi-mately 18% of the variance in skill-based learning, and up to about 10% of thevariance in affective learning. It is important to note that the impact of pretraininggoals appears to be strongest in higher levels of learning, suggesting thatpretraining goals improve not only performance in training but also the potentialthat trained knowledge/skills will be transferred to performance on the job.

In addition to the hypothesized main effect for pretraining goals inducing maxi-mal performance, we also hypothesized the type of pretraining goal may interact todetermine the results of maximal performance, such that (a) trainees provided witha performance-oriented goal would have superior learning performance at lowerlevels of learning than trainees provided with a mastery-oriented goal (Hypothesis2), and (b) trainees provided with a mastery-oriented goal would have superior per-formance at higher levels of learning than trainees provided with a performanceorientation (Hypothesis 3). Results provide support for Hypothesis 3 and partialsupport for Hypothesis 2. Pretraining goals, regardless of whether they were per-formance or mastery oriented, yielded higher learning outcomes (across all learn-ing types and levels) than no-goal conditions. Although performance-orientedgoals fostered better scores on measures of verbal knowledge acquisition (the firststage of cognitive learning) than did mastery-oriented goals (ρ = .25 vs. ρ = .15;compared with no-goal conditions; providing partial support for Hypothesis 2),this same effect was not seen with skill-based learning. Specifically, mas-tery-oriented goals yielded better learning performance on both lower and higherlevels of skill-based learning, though (consistent with these hypotheses) the differ-ence between goal types appears to increase with level of skill learning (comparing

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215

TAB

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performance with mastery goals, ρ = .12 for skill acquisition and ρ = .22 for skillcompilation).

With regard to higher levels of cognitive learning (knowledge organization andcognitive strategies), mastery-oriented goals appear to facilitate greater learning.Although it was not possible to compare performance and mastery goals directlyfor the criterion of knowledge organization, when the effect for mastery goals iscompared with the average impact of goals on knowledge organization, it is appar-ent mastery goals foster better knowledge organization (ρ = .29 vs. ρ = .22). Forcognitive strategies, a direct comparison between performance and mastery goalsyielded a ρ of .05, suggesting mastery goals were superior.

As with the other forms of learning, a pretraining goal also elevates affectivelearning outcomes, though the benefit of providing a specific type of goal is lessclear. Specifically, a direct comparison between performance and mastery goalssuggests mastery goals are better for inducing posttraining self-efficacy (ρ = .03)and a positive disposition regarding subsequent use of training material (ρ = .14),but training attitudes and overall affective outcomes appear to be more greatly in-fluenced by performance goals (ρ = –.02 and –.03, respectively). These conclu-sions become somewhat less clear when performance and mastery goals are eachcompared with no-goal conditions. Here, performance goals yield stronger effectsfor self-efficacy variables (ρ = .23), and mastery goals yield slightly stronger ef-fects for attitudes toward training (ρ = .09 vs. .04).

DISCUSSION

In this study, we sought to extend the concepts of maximal and typical perfor-mance to learning from organizational training programs. We examined the poten-tial pretraining goals create a “maximal learning” condition, wherein trainees areinduced to attend to training and learn at greater levels than would otherwise be ex-pected (typical learning). Meta-analytic results suggest goals may indeed create amaximal learning context wherein learning from training is enhanced at all levels.It is important to note that the benefits of such enhanced motivation and attentionto learning induced by pretraining goals appear to increase with the levels of learn-ing. Because higher levels of learning (e.g., expertlike knowledge organization,valid cognitive strategies, and skill compilation) are more likely to foster the main-tenance and generalization (transfer) of training material (Baldwin & Ford, 1988;Kraiger et al., 1993), the benefits of creating a maximal learning condition likelyextend far beyond the training context.

Further, our results suggest goals that encourage trainees to maximize effort to-ward truly learning training content (mastery goals), as compared with those thatencourage maximal performance on training assessments (performance goals), ap-pear to facilitate the greatest gains in learning performance. Although performance

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goals yielded superior performance on assessments of lower levels of cognitivelearning (declarative/verbal knowledge), mastery goals yielded better perfor-mance on assessments of higher levels of cognitive learning (knowledge organiza-tion and cognitive strategies) and for all levels of skill-based learning. Althoughboth goals create a “maximal learning condition,” the focus of the goal fosters mo-tivation to attend to different aspects of training and thus yields performance dif-ferences on posttraining assessments of learning. Specifically, trainees motivatedto perform well on posttraining assessments would maximize efforts during train-ing on memorizing and attending to salient concepts rather than on developingstrategies for understanding and retaining conceptual interrelationships, hierar-chies, and applications. On the other hand, mastery-oriented trainees, who havebeen directed to maximize learning/mastering training material, would be moti-vated less to simply memorize concepts and more to understand conceptual impli-cations, applications, and interrelations. These trainees would focus performanceduring training toward mastering training material so it could be utilized later.

Our finding that performance goals yielded greater performance on declarativeknowledge but not on skill acquisition (both of which are indicative of learning atlower levels) may be consistent with past research. Winters and Latham (1996)found that performance goals often led to deleterious performance (compared tono goal conditions or to “do your best” goals) when the task was novel, complex, orotherwise required some initial learning prior to being able to perform well. Here,the task cannot be performed better simply by increasing/maximizing motivation/performance, but rather some ability (resulting from learning) is a prerequisite (cf.Kanfer & Ackerman, 1989; Locke, 2000; Seijts et al., 2004). It is important to notethat our results suggest pretraining goals (especially those encouraging maximalmastery/learning) also benefit attitudes toward training, assessments of the utilityof training content, and posttraining self-efficacy. Because evaluations of trainingprogram utility and posttraining self-efficacy are important predictors of transfer(Alliger, Tannenbaum, Bennett, Traver, & Shotland, 1997; Kraiger et al., 1993),this provides further evidence for the importance of fostering maximal learningduring training.

Limitations and Directions for Future Research

A potential limitation of this research relates to the relatively small number of pri-mary studies located relevant to a few of the reported meta-analyses. Althoughanalyses of the more general relationships (i.e., between goal/no-goal conditionsand learning averages) incorporated a relatively large number of studies, the morefocused analyses (e.g., between specific goal types and specific learning out-comes, particularly higher-level learning outcomes) were at times based on a lim-ited number of studies. In these cases, although the k was smaller, the actual sam-ple sizes were in the hundreds and often in the thousands, signifying some

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generalizability of the conclusions. Furthermore, by integrating findings over mul-tiple research domains (i.e., business, psychology, education), this study providesa comprehensive investigation of the role of pretraining goals in the enrichment oflearning from training. Thus, although conclusions regarding certain goal formatsor specific learning outcomes would benefit from further investigation, this studywas successful in providing a snapshot of what we know about the utility ofpretraining goals in maximizing learning. Another concern relates to the lack of re-liability data available in many of the studies included in this meta-analysis. Allmeasures are affected by measurement error, and thus the correlates reported heremay underestimate true relationships. In an attempt to address this potential con-cern, artifact distribution meta-analysis was employed. This technique utilizes thereported reliability estimates to make reliability corrections to the reported correla-tions using a weighted reliability estimate.

An avenue for future research is to test our assumption that trainees who re-ceived a pretraining goal (whether performance oriented or mastery/learning ori-ented) operated at peak performance to meet these goals. Specifically, although aspecific goal was set prior to training, it may be a leap of faith to assume all traineesactually maximized their performance. To make this assumption, we must be con-fident that pretraining goals were adopted by all trainees and the rewards for maxi-mal learning were valuable enough to trainees to sustain maximal effort in trainingto meet them. This level of goal commitment cannot be readily inferred from thismethodology. However, this limitation is also true of primary research. Fortu-nately, a majority of the studies included in this meta-analysis employed manipula-tion checks to ensure their manipulations were recognized/adopted by partici-pants. Another way we sought to address this concern is by including studies thatassessed participant perceptions of goals in the learning environment (i.e.,“correlational studies”). In these studies, participants actually rated their percep-tions of the strength of and attraction to the goals placed on them during training.With such ratings, we may be more confident that these trainees were actually in-fluenced by learning/performance goals. Regardless, it is clear that pretraininggoals yield learning at levels higher than that obtained by “typical” learning condi-tions, even if trainee effort is not maximized by these goals. Our results represent aconservative estimate of the power of goals to maximize learning performance.

Another interesting direction for future research would be to examine the ef-fects of maximal learning over time. Specifically, if pretraining goals indeed createa maximal learning condition during training, what are the implications for traineeperformance over time? Assuming that maximal performance conditions are timelimited (at some point, performance reverts back to typical levels), will the greaterlearning achieved during training as a function of pretraining goals facilitate betterperformance over time (e.g., during typical performance conditions)? Ifpretraining goals indeed facilitate greater learning from training, then even if per-formance reverts back to typical levels, the relative increase in knowledge (com-

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pared with that gained in typical learning conditions) should facilitate superiorperformance. Some support for this proposition is evident with the stronger effectsfound for pretraining goals at higher levels of learning; performance on these as-sessments require a greater mastery of training content than would be gained bytrainees focused only on performing well on posttraining assessments. In otherwords, whereas maximal performance could explain better scores on initial learn-ing assessments (e.g., declarative knowledge), performance on assessments athigher learning levels requires a superior grasp of training content and an integra-tion of this content into existing knowledge structures (a degree of learning that isunlikely to result from lesser learning/performance efforts). In sum, future re-search should examine the role of pretraining goals (maximal learning) over time.

CONCLUSION

Goal setting has been used in a variety of contexts in an effort to induce maximaleffort and to facilitate greater performance outcomes than would otherwise beachieved through an individual’s more typical efforts. We sought determinewhether pretraining goals induce trainees to maximize learning efforts in training.In general, we found pretraining goals yield higher performance on posttrainingcognitive, skill, and affective learning assessments than no-goal conditions. Fur-ther, performance-oriented goals facilitated better performance on measures of de-clarative knowledge; mastery-oriented goals yielded greater learning on higherlevels of cognitive learning and for all levels of skill-based learning. Our results re-flect the power of pretraining goals to enhance learning outcomes beyond atrainee’s typical learning tendencies.

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