Journal of Applied Psychology 2000, Vol. 85, No. 5, 724-738
Copyright 2000 by the American Psychological Association, Inc. 0021-9010/00/$5.00 IX)I: 10.1037//0021-9010.85.5.724
Goal Orientation and Task Demand Effects on Motivation, Affect, and Performance Debra Steele-Johnson, Russell S. Beauregard, Paul B. Hoover, and Aaron M. Schmidt Wright State University Two studies tested the joint effects of goal orientation and task demands on motivation,affect, and performance, examiningdifferentfactors affectingtask demands. In Study 1 (N = 199), task difficulty was found to moderate the effect of goal orientationon performance and affect (i.e., satisfactionwith performance).In Study2 (N = 189),task consistencywas foundto moderatethe effect of goal orientation on self-efficacyand intrinsic motivation.Results are discussed in relation to self-regulatoryprocesses cued by goal orientations,attentionalresource demands, and the need to match goal orientationsto the nature of the task.
settings. Thus, one purpose of the present research was to examine goal orientation effects among adults performing a work-related task. Additionally, previous research has shown that a learning goal orientation in general has more beneficial effects on performance, motivation, and affect (e.g., Butler, 1987; Schraw, Horn, Thorndike-Christ, & Bruning, 1995; Treasure & Roberts, 1994), as compared with a performance goal orientation. However, this research has been conducted without considering whether goal orientation effects depend on task demands. Specifically, task demands could be an important boundary condition for goal orientation effects. Thus, a second purpose of the present study was to examine whether task demands influence goal orientation effects on performance, motivation, and affect and, furthermore, whether different factors influencing the level of task demands produce similar effects. The goal orientation construct has originated from the learned helplessness literature (Abramson, Seligman, & Teasdale, 1978; Seligman, 1990). Button, Mathieu, and Zajac (1996) characterized goal orientation as a "somewhat stable individual difference factor that may be influenced by situational characteristics" (p. 28). In general, research has identified two goal orientations, labeled variously as performance versus learning (e.g., Dweck & Leggett, 1988), ability focused versus mastery focused (e.g., Ames, 1984), performance versus mastery (e.g., Harackiewicz & Elliot, 1993), and ego oriented versus task oriented (e.g., Nicholls, 1984). Extensive research has examined the effects of goal orientations assessed as traits (e.g., Ames & Archer, 1988; Button et al., 1996; Duda, 1989; Duda & NichoUs, 1992; VandeWalle & Cummings, 1997) as well as the effects of goaI orientation manipulations (Butler, 1993; Harackiewicz & Elliot, 1993; Jagacinski & Nicholls, 1984; Licht & Dweck, 1984; Nicholls, t971, 1975, 1984). Originally conceived of as a unidimensional construct (e.g., Dweck, 1986, 1991; Nicholls, 1984), more recent research has examined goal orientation as a multidimensional construct (e.g., Ames & Archer, 1988; Bouffard, Boisvert, Vezeau, & Larouche, 1995; Duda, 1988; Hofmann & Strickland, 1995; Meece & Holt, 1993; Schraw et al., 1995; VandeWalle, 1997). Regardless of the conceptualization used (trait vs. situational, unidimensional vs. multidimensional), substantial research has suggested that learning and performance goal orientations have
Work in today's organizations is characterized by increasing complexity, rapid change, and increasingly competitive business environments (Cascio, 1998; Goldstein, 1993; Smith, Ford, & Kozlowski, 1997). Thus, a critical issue in work settings is how to help people perform well under conditions of varying task demands, including varying task difficulty or consistency. A theory from educational psychology, goal orientation, has emerged that has implications for facilitating individuals' performance under these conditions (Ames & Archer, 1988; Dweck, 1986; Nicholts, 1984). Goal orientation refers to two types of superordinate goals people can hold during task performance (Nicholls, 1984). A learning goal orientation cues an individual to believe competence can be improved, to evaluate competence in relation to previous competence, and to choose and persist on a challenging task (Dweck, 1986; Harackiewicz & Elliot, 1993; Nicholls, 1984). In contrast, a performance goal orientation cues an individual to believe competence is not likely to change, to evaluate his or her competence in relation to others, and to choose a task in which he or she can prove his or her competence and avoid failure. Goal orientation has been found to predict performance in educational environments (see Dweck, 1991, for a review), and researchers have found initial evidence that goal orientations have important implications for training and motivation in organizational contexts (e.g., Fisher & Ford, 1998; Ford, Smith, Weissbein, Gully, & Salas, 1998; Martocchio, 1994). However, much of the research to date has been conducted using children or in academic
Debra Steele-Johnson, Russell S. Beauregard, Paul B. Hoover, and Aaron M. Schmidt, Departmentof Psychology, Wright State University. Aaron M. Schmidt is now at the Departmentof Psychology, Michigan State University. This research was supportedby Research ChallengeGrant 663004 from Wright State University. A version of this article was presented at the annual conference of the Society for Industrial and OrganizationalPsychology, Dallas, Texas, April 1998. We thank Valerie Shalin for her insightful comments. Correspondence concerningthis article should be addressed to Debra Steele-Johnson,Departmentof Psychology,Wright State University,Dayton, Ohio 45435. Electronic mail may be sent to
[email protected]. 724
GOAL ORIENTATIONAND TASK DEMANDS differential effects on performance, motivation, and affect and that, in general, a learning goal orientation results in more beneficial effects (see Button et al., 1996, or Farr, Hofmaun, & Ringenbach, 1993, for reviews and further discussions of key issues). However, some researchers have observed that when individuals with a performance goal orientation perceive they have the ability to perform the task, they perform similarly to individuals with a learning orientation (e.g., Dweck, 1986; Vlachopoulos & Biddle, 1997). Furthermore, Bar-Eli et al. (1997) found that students given performance goal orientation instructions (or both performance and learning orientation instructions) outperformed students given learning orientation instructions alone. Thus, one goal orientation might not be superior in all circumstances; rather, other factors might play a role in the efficacy of different goal orientations. A clearer understanding is needed, then, of the mechanisms underlying goal orientation effects. Hence, we suggest that models addressing self-regulatory processes (e.g., Bandura, 1986, 1997) and attentional resources (e.g., Ackerman, 1987, 1989; Kahneman, 1973; Kanfer, 1987; Sweller, 1988) can increase our understanding of goal orientation effects. These models, in turn, can help clarify the role of boundary conditions such as task demands on goal orientation effects. Bandura (1986, 1997) discussed three important self-regulatory processes: self-monitoring, self-efficacy, and self-evaluation. All three processes are relevant to goal orientation effects; however, the role of self-monitoring is most central to the issues we examine. Self-monitoring refers to individuals attending to their performance. Whereas both goal orientations cue individuals to engage in self-monitoring, the focus (i.e., content) of self-monitoring differs depending on whether the individual has a performance or a learning goal orientation. For example, Fisher and Ford (1998) found that a performance goal orientation led to increased rehearsal of task strategies, whereas a learning goal orientation led to increased elaboration of task strategies. The notions of rehearsal of strategies and elaboration of task strategies are similar to two constructs proposed as major learning mechanisms in cognitive psychology: transfer from controlled to automatic processing and development of schemas. Sweller and his associates (Sweller, 1988; Sweller & Chandler, 1991, 1994) have suggested that learning occurs when individuals practice consistent task elements until they can be performed automatically-with little attention. Transferring the performance of task components to automatic processing then frees cognitive resources to develop more comprehensive schemas for performing the task. Therefore, we posit that to the extent that a performance goal orientation cues individuals to rehearse task strategies, individuals are more likely to rehearse familiar task components until they require little attention (i.e., automatic processing). Furthermore, we posit that to the extent that a learning goal orientation cues individuals to develop task strategies, individuals are more likely to develop and elaborate schemas for performing larger segments of a task. However, whether a learning or a performance goal orientation is more beneficial might depend on the attentional resource demands of the task. Key issues in our discussion are how attentional resource demands (i.e., cognitive load) vary with level of skill acquisition and task characteristics (e.g., task difficulty and task consistency). Models of attention (e.g., Kahneman, 1973; Norman & Bobrow, 1975; Schneider & Shiffrin, 1977; Shiffrin & Schnei-
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der, 1977) have suggested that individuals possess a fixed amount of attentional resources that can be allocated to various activities. However, researchers have suggested that the attentional demands associated with task performance can decline with task practice (Anderson, 1982, 1987, 1990; Fitts, 1964; Fitts & Posner, 1967). For example, Fitts (1964; Fitts & Posner, 1967) described three stages of skill acquisition: (a) a cognitive phase in which the individual learns the task requirements, memory and reasoning processes are required, and cognitive load is high; (b) a second, associative phase in which individuals begin to compile sequences of cognitive and motor processes; cognitive load declines; and (c) a third, autonomous phase in which skill becomes more rapid and automatic. Sweller (1988) has suggested that when cognitive load is high, a focus on practicing problems can interfere with learning. Individuals are able to practice task components until they are automatic, but they will have no resources to allocate to developing schemas for larger segments of the task. According to Sweller, the benefit of transferring the performance of task components to automatic processing is that it frees the attentional resources required for schema development. However, freeing attentional resources has little effect unless the individual redirects his or her attention to schema development--and away from the general problem-solving strategies (e.g., means-ends analysis) that are used to solve novel problems but have high cognitive resource requirements. Paas (1992) and Paas and Van Merrienboer (1994) have suggested also that the high cognitive load that occurs during learning (due to task novelty) should be controlled by using training strategies that appropriately direct attention to the task (i.e., to schema development). Thus, a goal orientation that cues an individual to focus his or her attention on transferring task components to automatic processing rather than on developing schema can be disruptive, particularly when cognitive load is high and the individual has to decide how to allocate his or her limited attentional resources. Ackerman (1987, 1989) has contended that the attentional resources available to devote to self-regulatory processes increase as the individual gains task experience (at least on consistent tasks) but that the attentional resource demands are initially higher for complex tasks. Furthermore, Kanfer and Ackerman (1989) have suggested that self-monitoring requires attentional resources. Thus, self-monitoring could disrupt learning on a complex task (a) if the task requires all of an individual's attentional resources or (b) if self-monitoring results in allocating attentional resources to activities unlikely to facilitate learning (Kanfer, 1987)--for example, to monitoring performance and using a rehearsal strategy (i.e., associated with a performance orientation) rather than developing and elaborating task strategies (i.e., associated with a learning orientation). Hofmann (1993) has discussed this issue in terms of cognitive interference, demonstrating that a performance goal orientation can cue the individual to devote limited 'attentional resources to thoughts unlikely to facilitate learning, such as how others are perceiving one's performance. Thus, a learning goal orientation might be more beneficial early in skill acquisition on a complex task (i.e., when cognitive load is highest), because it cues self-regulatory activities that are less disruptive to learning, and a performance goal orientation might be more beneficial later in skill acquisition or on simpler tasks, when attentional resource demands are lower.
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STEELE-JOHNSON, BEAUREGARD,HOOVER, AND SCHMIDT
Finally, one remaining construct with important implications relating to attentional resources is task demands. As mentioned previously, task characteristics such as task difficulty and task consistency can influence cognitive load. On the basis of arguments made previously, we posit that a learning goat orientation is relatively more beneficial when cognitive load is high because of high levels of task difficulty or task inconsistency and that a performance goal orientation is relatively more beneficial when cognitive load is low. Anderson (1993) has described skill acquisition as a process in which knowledge starts in an initial declarative form that is interpreted to produce performance. Declarative knowledge becomes compiled into production-rule form. Newell (1990; Newell & Simon, 1972), who has not posited a declarative memory construct, has described problem-solving behavior as a process of searching a problem space by means of applying operators. Operating in the problem space requires knowledge that is used to implement operators and to guide the search (Newell, 1990). Such knowledge is held in long-term memory and accessed through knowledge search. Thus, in the present study we define task difficulty as the amount of declarative knowledge that must be learned and the number of productions that must be created to perform the task. This definition is consistent with Paas and Van Merrienboer's (1994) description of mental load in terms of the number and nature of component skills involved in task performance as well as with other researchers' suggestions that tasks vary in difficulty as a function of the number of acts, information cues, or paths to a goal and interactions among them (Campbell, 1988, 1991; Wood, 1986). Task consistency has been addressed extensively in research, particularly in terms of the effects and requirements of controlled versus automatic processing (Schneider, Dumais, & Shiffrirl, 1984; Schneider & Shiffrin, 1977; Shiffrin & Schneider, 1977). Controlled processing can be characterized as slow, serial, and effortful; its effectiveness is highly dependent on mental load. In contrast, automatic processing can be characterized as fast, parallel, and effortless; performance is insensitive to mental capacity limits (Paas & Van Merrienboer, 1994). The performance of tasks with consistent information-processing demands can be automatized with task practice (i.e., automatic processing), freeing attentional resources for other activities, such as monitoring performance. However, tasks with inconsistent information-processingdemands require continued high levels of attention to successfully perform the task (i.e., controlled processing). Because task demands are changing, one cannot automate processing of task information and free up attentional resources. Thus, we posit that a learning goal orientation should be relatively more beneficial when cognitive load is high, such as on tasks with inconsistent informationprocessing demands, and a performance goal orientation should be relatively more beneficial when cognitive load is lower, such as on tasks with consistent information-processing demands. By integrating these models and constructs, our research provides a clearer understanding of processes underlying goal orientation effects. This understanding is critical as we begin to examine the implications of goal orientations for adults in work settings. To summarize the underlying processes, we propose that goal orientations cue individuals to engage in self-regulatory processes. Specifically, goal orientations are likely to influence selfmonitoring, but the efficacy of self-monitoring depends on (a) the focus (i.e., content) of self-monitoring and (b) the attentional
resources available to perform that process. Thus, the purpose of Studies 1 and 2 was to examine the role of task difficulty and task consistency, respectively, in goal orientation effects on performance, motivation, and affect during early skill acquisition. Study 1 In this study, we examined the role of task difficulty in goal orientation effects on performance, motivation, and affect during initial skill acquisition. The goal orientation construct has been particularly appealing in the context of continual learning, and a number of researchers have examined its effects in training contexts (e.g., Ford et al., 1998; Martocchio, 1994; Phillips & Gully, 1997; Wood & Bandura, 1989). Research has shown that a learning goal orientation results in higher self-monitoring (Greene & Miller, 1996; Miller, Behrens, Greene, & Newman, 1993), deeper level processing (Greene & Miller, 1996; Ford et al., 1998), more effective strategy search and development (Fisher & Ford, 1998; Wood & Bandura, 1989), and more attentional resources devoted to the task (Fisher & Ford, 1998). In addition, indirect evidence from research on goal setting has shown that specific, difficult goals administered early in skill acquisition on complex tasks have dysfunctional effects on strategy search and development and performance (Earley, Connolly, & Ekegren, 1989; Kanfer & Ackerman, 1989). Clearly, a learning goal orientation has beneficial effects in the context of learning a task. Furthermore, previous research (e.g., Ackerman, 1987, 1989; Kanfer & Ackerman, 1989) has suggested that a learning goal orientation is most beneficial when the attentional demands are highest (i.e., early in skill acquisition on difficult tasks). However, a performance goal orientation could be similarly beneficial later in skill acquisition and on simpler, consistent tasks. Although research showing that a performance orientation can be beneficial is sparse (see Bar-Eli et al., 1997, for an exception), we offer three pieces of indirect evidence supporting our contention that the efficacy of different goal orientations depends on skill acquisition and task difficulty. Winters and Latham (1996) observed that although specific learning goals (i.e., number of task strategies) resulted in higher performance on the complex task, specific performance goals (i.e., number of class schedules) and specific learning goals had similar effects on the simple version of the task. In addition, research on goal setting has shown that specific, difficult task goals enhance performance, although the effects are stronger for simple than for complex tasks (see Locke & Latham, 1990, for a summary). Finally, Licht and Dweck (1984) found that goal orientations and task conditions (i.e., confusion vs. no confusion) interacted in their effects. That is, whereas children with a helpless orientation demonstrated poorer performance relative to children with a mastery orientation in the confusion task condition, children with helpless versus mastery orientations demonstrated similar performance in the no-confusion task condition. Thus, we predict that when the task is simple (or well learned, although this is beyond the scope of the current research), rehearsing task strategies (Anderson, 1990) rather than elaborating strategies might have beneficial effects on performance. In contrast, when the task is difficult (particularly early in skill acquisition), devoting cognitive resources to exploring and mastering a task might have more beneficial effects than rehearsing known but suboptimal task strategies.
GOAL ORIENTATION AND TASK DEMANDS
Hypothesis I: Goal orientation and task difficulty interact in their effects on performance. In addition, previous research has observed more beneficial effects for a learning goal orientation than for a performance orientation on motivation variables such as self-efficacy (e.g., Colquitt & Simmering, 1998, expectancies; Ford et al., 1998; Martocchio, 1994; Phillips & Gully, 1997; Wood & Bandura, 1989), self-set goals (e.g., Miller et al., 1993), and intrinsic motivation (e.g., Butler, 1987; Heyman & Dweck, 1992; Koestner, Zuckerman, & Koestner, 1987; Plant & Ryan, 1985). However, no research has examined whether these effects are influenced by task difficulty. We posited that individuals with a learning goal orientation would be more motivated by a difficult task, whereas individuals with a performance goal orientation would be more motivated by a simple task. In Study 1, we focus on intrinsic motivation as an index of motivation. Specifically, needs for competence and self-determination (Deci, 1971, 1975; Deci & Ryan, 1980, 1987) should be important issues, particularly for individuals with a learning goal orientation. We posit that individuals with a learning goal orientation should perceive that they have a greater opportunity to satisfy their needs for self-determination and competence in tasks requiring greater attentional resources and greater strategy development--that is, in difficult tasks. In contrast, individuals with a performance goal orientation tend to believe they have less control (Duda, 1992; Dweck, 1986; Nicholls, 1975) and less ability to change their performance. These individuals should perceive that they have a greater opportunity to satisfy their needs for self-determination and competence in tasks with lower attentional resource demands and requiring less strategy development that is, on simple tasks.
Hypothesis 2: Goal orientation and task difficulty interact in their effects on intrinsic motivation. Finally, previous research has observed beneficial effects for a learning goal orientation on affect (i.e., satisfaction with performance; Jagacinski & Nicholls, 1984; Treasure & Roberts, 1994). However, no research has examined the role of task difficulty in those effects. W e suggest that satisfaction with performance can be understood in terms of individuals' superordinate goals (i.e., to master the task or demonstrate ability). Individuals with a learning orientation are likely to base their satisfaction on the extent to which the task enables them to gain mastery. These individuals are likely to perceive greater opportunities to gain mastery and in turn express greater satisfaction on difficult tasks. In contrast, those with a performance goal orientation are likely to base their satisfaction on the extent to which they can demonstrate ability. Given a belief that performance is difficult to change, individuals with a performance orientation are likely to perceive greater opportunities to demonstrate ability and in turn express greater satisfaction on simple tasks.
Hypothesis 3: Goal orientation and task difficulty interact in their effects on satisfaction with performance.
Method Participants Participants were 202 undergraduate students from a midwestern university. One participant was removed from the analyses for failure to
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follow task instructions, and 2 others were removed because their performance was extreme enough (more than 6 standard deviations above the mean) to alter the results; therefore, there were 199 participants available for analyses (men, n = 79; women, n = 120). A 2 (simple vs. difficult task) × 2 (learning vs. performance goal orientation) × 4 (trial blocks) design was used. Participants were randomly assigned to task difficulty and goal orientation conditions and completed four performance blocks, each consisting of two 10-rain trials.
Task Overview and Task Difficulty Manipulation The participants performed a computerized class scheduling task adapted from Earley and Kanfer (1985) and Wright (1991, 1992). They selected courses from a database and conformed to assigned rules to create class schedules for hypothetical students. Participants received points for each schedule completed and lost points for each error. Those in the simple task condition were provided with five task rules (e.g., classes must not overlap in time). Those in the difficult task condition were provided with the same five rules plus two additional task rules (e.g., assign lab sections for courses requiring a lab). The task difficulty manipulation altered the amount of declarative knowledge and the number of productions required.
Goal Orientation Manipulation The goal orientation manipulation was derived from Nicholls (1984). Goal orientation was manipulated using task instructions. In the performance goal orientation condition, the task instructions were designed to create the perception that cognitive ability was stable and difficult to improve through effort and to focus the subject on achievement (i.e., scoring well). Participants were instructed that performance on problemsolving tasks like the class scheduling task reflects basic cognitive capabilities and that the higher their underlying cognitive capacities are, the better their problem solving is. Participants were informed that this task provides a vehicle for gauging underlying cognitive capacities. In the learning goal orientation condition, the task instructions were designed to create the perception that cognitive ability is changeable and easy to improve through effort and to focus the participants on exploring and mastering the task. Participants were instructed that "skills on problem solving tasks like the class scheduling task are developed through practice.., the more people practice, the more capable they become.., you can expect to make some mistakes.., you should see your performance improve with practice."
Measures Perceived task difficulty. Six items were used to assess perceived task difficulty (e.g., "How difficult is performing this task?"). Participants responded on a 7-point Likert-type scale ranging from 1 (not at all) to 7 (very). Internal consistency reliabilities were .77, .76, .76, and .71 in Blocks 1 to 4, respectively. Perceived goal orientation. Six items were used to assess perceptions regarding goal orientation (e.g., "An important part of being a good task performer is continually improving your skills;" a = .69). Participants responded on a 5-point Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree). Performance. Performance was operationalized as the number of class schedules completed and was averaged across the two 10-min trials in each block. Intrinsic motivation. Intrinsic motivation was measured using a 21item scale (McAuley, Wraith, & Duncan, 1991). McAuley et al. expanded on the original 9-item inventory developed by Ryan (1982; 1981/1982). The scale includes items addressing different aspects of intrinsic motivation such as interest/enjoyment (e.g., "I enjoy participating in this task very much"), competence (e.g., "I think I am pretty good at this task"), and
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STEELE-JOHNSON, BEAUREGARD, HOOVER, AND SCHMIDT
effort/importance (e.g., "I put a lot of effort into this task"). Participants responded using a 7-point Likert-type scale ranging from 1 (strongly disagree) to 7 (strongly agree). Internal consistency reliabilities were .84, .82, .79, and .76 in Blocks t to 4, respectively. Affect: Satisfaction with performance. Affect was assessed using a two-item scale (e.g., "How satisfied were you with your overall performance on the previous trial.'?"). Participants responded on a 7-point Likerttype scale ranging from t (not at all) to 7 (very). Internal consistency reliabilities were .71, .56, .72, and .72 in Blocks 1 through 4, respectively.
Procedure Following provision of informed consent, participants received general task instructions and goal orientation instructions. They reported their perceptions regarding goal orientation immediately following the goal orientation instructions. They then performed four trial blocks, each with two 10-rain trials. Following each block, participants reported their levels of perceived task difficulty, intrinsic motivation, and affect toward the task. Participants were then debriefed.
Results Means and standard deviations by condition are shown in Table 1 for performance, intrinsic motivation, and satisfaction with performance for Trial Blocks 1 through 4.
Manipulation Checks A 2 (task difficulty) x 2 (goal orientation) x 4 (trial blocks) repeated measures analysis of variance (ANOVA) was used to
examine whether participants in the difficult condition perceived the task as more difficult. Results indicated main effects for task difficulty, F(1, 186) = 9.13, p < .01, and trial block, F(3, 184) = 21.09, p < .001, Wilks's lambda = .74. Participants in the difficult condition (M = 3.03, SD = 0.87) perceived the task as more difficult, as compared with those in the simple task condition (M = 2.65, SD = 0.90). Also, participants perceived the task as less difficult over blocks (Block 1, M = 3.22, SD = 1.06; Block 4, M = 2.78, SD = 1.08). A 2 (task difficulty) X 2 (goal orientation) A N O V A was used to examine whether participants in the learning and performance goal orientation conditions differed in their perceptions regarding goal orientation. Results indicated a main effect for goal orientation, F(1, 186) = 4.39, p < .05. Participants in the learning goal orientation condition reported a stronger belief that they could improve their performance (M = 4.03, SD = 0.46), as compared with those in the performance goal orientation condition (M = 3.87, SD = 0.49).
Effects o f Task Difficulty and Goal Orientation on Performance A 2 (task difficulty) x 2 (goal orientation) x 4 (trial blocks) repeated measures A N O V A was used to examine whether task difficulty and goal orientation interacted in their effects on performance (Hypothesis 1). In support of Hypothesis 1, results revealed a significant Task Difficulty × Goal Orientation x Trial Block interaction effect, F(3, 193) = 3.35, p < .05, Wilks's lambda =
Table 1
Means and Standard Deviations of Variables in Study 1 Goal orientation Learning Dependent variable Performance
Task difficulty Simple
Difficult
Satisfaction with performance
Simple
Difficult
Intrinsic motivation
Simple
Difficult
Performance
Trial block
M
SD
M
SD
1 2 3 4 1 2 3 4 1 2 3 4
4.99 9.75 12.08 13.89 3.10 6.35 7.93 8.34 4.29 4.92 5.03 4.80
2.55 4.60 5.21 6.78 1.65 2.57 2.71 3.17 1.47 1.57 1.64 1.74
5.23 11.94 15.86 17.61 3.26 6.45 8.62 9.41 5.05 5.27 5.11 5.25
2.94 5,63 6.64 7.09 t.75 3.14 4.05 3.99 1.46 t .51 1.75 1.77
1
4.51
1.80
3,64
1.42
2 3 4 1 2 3 4 1 2 3 4
5.07 5.23 4.96 4.36 4.24 4.12 4.14 4.46 4.40 4.28 4.33
1.41 1.64 1.70 0.68 0.76 0.70 0.60 0.84 0.83 0.86 0.81
4.79 4.81 4.72 4.46 4.24 4.07 4.09 4.40 4.38 4.30 4.21
1.31 1.14 1.39 0.71 0.66 0.71 0.72 0.85 0.72 0.64 0.62
Note. For performance, N = 199; for satisfaction and intrinsic motivation, N = 190 because of missing data.
GOAL ORIENTATION AND TASK DEMANDS .95. Post hoc repeated measures ANOVAs were conducted to examine goal orientation and trial block effects within task difficulty conditions. In the simple condition, results revealed significant effects for trial block, F(3, 83) = 120.28, p < .001, Wilks's lambda = .19, and goal orientation, F(1, 85) = 5.83, p < .05, and a Trial Block X Goal Orientation interaction, F(3, 83) = 4.43, p < .01, Wilks's lambda = .86. In the difficult task condition, results indicated a significant effect only for trial block, F(3, 108) = 172.03, p < .001, Wilks's lambda = .17. Thus, participants in the performance goal orientation condition performed better than those in the learning orientation condition, and the goal orientation effect increased in size across blocks, but. only for participants in the simple task condition (see Figure 1). Participants in the performance and learning orientation conditions performed similarly and more poorly in the difficult task condition. Results from the repeated measures A N O V A on performance also revealed a significant effect for trial block, F(3, 193) = 280.12, p < .001, Wilks's lambda = .19, and significant Trial Block × Task Difficulty, F(3, 193) = 23.98, p < .001, Wilks's lambda = .73, and Trial Block x Goal Orientation, F(3, 193) = 5.33, p < .01, Wilks's lambda = .92, interaction effects. Consistent with the results displayed in Figure 1, performance improved over blocks and task difficulty and goal orientation effects increased in size over trial blocks (Block 1 simple vs. difficult task, Ms = 5.09 vs. 3.18, SDs = 2.71 and 1.70; Block 4 simple vs. difficult, Ms = 15.47 vs. 8.87, SDs = 7.12 vs. 3.62; Block 1 learning vs. performance orientation, Ms = 3.98 vs. 4.05, SDs = 2.32 vs. 2.49; Block 4 learning vs. performance, Ms = 10.93 vs. 12.71, SDs = 5.85 vs. 6.76).
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Effects of Task Difficulty and Goal Orientation on Intrinsic Motivation A 2 (task difficulty) x 2 (goal orientation) × 4 (trial blocks) repeated measures ANOVA was used to examine whether task difficulty and goal orientation interacted in their effects on intrinsic motivation (Hypothesis 2). Results revealed only a significant trial block effect, F(3, 184) = 11.73, p < .001, Wilks's lambda = .84. Participants' intrinsic motivation declined from Block 1 (M = 4.42, SD = 0.78) to Block 4 (M = 4.20, SD = 0.69). Thus, this hypothesis was unsupported.
Effects of Task Difficulty and Goal Orientation on Affect A 2 (task difficulty) x 2 (goal orientation) x 4 (trial blocks) repeated measures A N O V A was used to examine whether task difficulty and goal orientation interacted in their effects on affect (i.e., satisfaction with performance; Hypothesis 3). Results revealed a significant Task Difficulty X Goal Orientation interaction effect, F(1, 186) = 5.14, p < .05, providing support for Hypothesis 3. Participants in the learning orientation condition were similarly satisfied whether working on the simple (M = 4.76, SD = 1.18) or difficult (M = 4.89, SD = 1.37) task. However, in the performance orientation condition, participants working on the simple task (M = 5.17, SD = 1.32) were more satisfied with their performance, as compared with those in the difficult task (M = 4.50, SD = .93) condition (see Figure 2). A significant effect on satisfaction with performance was also observed for trial block, F(3, 184) = 11.72, p < .001, Wilks's
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Effects of goal orientation, task difficulty, and trial block on performance in Study 1.
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STEELE-JOHNSON, BEAUREGARD, HOOVER, AND SCHMIDT
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The interaction effect of task difficulty and goal orientation on satisfaction with performance in
lambda = .84. Participants' satisfaction with their performance increased over blocks (Block 1, M = 4.29, SD = 1.61; Block 4, M = 4.91, SD = 1.64). Discussion
We examined whether goal orientation interacted with task difficulty in its effects on performance, satisfaction with performance, and intrinsic motivation. In partial support of Hypothesis 1, our results indicate that individuals with a performance goal orientation outperformed those with a learning orientation on a simple task, but no goal orientation effects were observed in the difficult task condition. In partial support of Hypothesis 2, our results show that individuals with a performance goal orientation were more satisfied with their performance on a simple than on a difficult task, but those with a learning goal orientation were unaffected by task difficulty. However, contrary to Hypothesis 3, we failed to observe any goal orientation or task difficulty effects on intrinsic motivation. Study 2 One purpose of the present research was to examine whether task demands influence goal orientation effects on performance, motivation, and affect and, furthermore, whether different factors influencing the level of task demands produce similar effects. In
Study 1, we influenced task demands by manipulating task difficulty. Results revealed beneficial effects for individuals with a performance goal orientation on performance and satisfaction with performance in a simple task. An important question in Study 2, then, was whether a similar pattern of results would be observed when we influenced task demands by manipulating a different task factor. Thus, in Study 2, we examined the role of task consistency in goal orientation effects on performance, motivation, and affect during initial skill acquisition. We posited that different goal orientations would be beneficial depending on cognitive load and that cognitive load would be influenced by task consistency. Previous research (e.g., Schneider & Shiffrin, 1977) has shown that tasks with consistent information-processing demands can be automatized with task practice (automatic processing) but tasks with inconsistent information-processing demands require continued high levels of attention (controlled processing). Furthermore, in Study 2, we examined two additional motivational variables: selfefficacy and self-set goals. These variables enabled us to examine a wider array of motivation variables and to determine whether goal orientations had effects on aspects of motivation other than intrinsic motivation. On the basis of the arguments made in Study 1, we posited that a learning goal orientation is relatively more beneficial when cognitive load is high (i.e., on an inconsistent task) and that a performance goal orientation is relatively more beneficial when cognitive load is lower (i.e., on a consistent task).
GOAL ORIENTATION AND TASK DEMANDS
Hypothesis 1: Goal orientation and task consistency interact in their
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Method
effects on performance.
Participants As we mentioned above, previous research has observed generally more beneficial effects for a learning goal orientation than for a performance orientation on motivation variables such as self-efficacy (e.g., Ford etal., 1998), self-set goals (e.g., Miller et al., 1993), and intrinsic motivation (e.g., Butler, 1987). However, no research has examined whether these effects are influenced by task consistency. In general, we posited that individuals with a learning goal orientation are more motivated by an inconsistent task, whereas individuals with a performance goal orientation are more motivated by a consistent task. Specifically, a learning goal orientation focuses individuals on developing and elaborating task strategies to help them master the task. As elaborated strategies are developed, the individual's belief in his or her capability to perform the task (self-efficacy) should increase. Similarly, as elaborated strategies are developed, individuals should set new, more challenging goals for themselves to help them increase their mastery of the task. A learning orientation, then, should have particularly beneficial effects on motivation in tasks in which strategy development is more important--that is, on inconsistent tasks. In contrast, a performance goal orientation focuses individuals on rehearsing. Efficiency in strategy use should most increase the individual's confidence in his or her capability to perform the task when there are fewer strategies needed for effective perform a n c e - t h a t is, on consistent tasks. As efficiency in strategy use increases, individuals should begin also to set new, more challenging goals that help them further demonstrate their abilities. On the basis of the arguments made in Study 1, we posited that individuals with a learning goal orientation should perceive that they have a greater opportunity to satisfy their needs for selfdetermination and competence (intrinsic motivation) in tasks requiring greater attentional resources (i.e., in inconsistent tasks). In contrast, individuals with a performance goal orientation should perceive that they have a greater opportunity to satisfy their needs for self-determination and competence in tasks with lower attentional resource demands (i.e., on consistent tasks).
Hypothesis 2: Goal orientation and task consistency interact in their effects on self-efficacy, self-set goals, and intrinsic motivation. Finally, as we mentioned in Study 1, previous research has observed beneficial effects for a learning goal orientation on affect (i.e., satisfaction with performance; Jagacinski & Nicholls, 1984; Treasure & Roberts, 1994). However, no research has been conducted examining whether satisfaction with performance varies as a function of task consistency. On the basis of arguments made in Study 1, we posited that individuals with a learning goal orientation are likely to perceive greater opportunities to gain mastery and in turn express greater satisfaction on inconsistent tasks. In contrast, individuals with a performance goal orientation are likely to perceive that they have performed well (i.e., demonstrated their ability) and in turn express greater satisfaction on a consistent task than on an inconsistent task.
Hypothesis 3: Goal orientation and task consistency interact in their effects on satisfaction with performance.
Participants were 193 undergraduate students from a midwestern university. Four outliers were removed from the analyses because of their extxeme performance (more than 3.5 standard deviations above the mean), resulting in 189 participants available for analysis (men, n = 67, women, n = 122). A 2 (consistent vs. inconsistent task) × 2 (learning vs. performance goal orientation) × 4 (trial blocks) design was used. Participants were randomly assigned to task complexity and goal orientation conditions. They completed four blocks, each consisting of two 10-min trials.
Task Overview and Task Consistency The participants performed the same computerized class scheduling task used in Study 1, selecting courses from a database and conforming to assigned rules to create class schedules for hypothetical students. As in Study 1, they received points for each schedule completed and lost points for each error. However, in Study 2, task consistency was manipulated by exposing participants to either changing (i.e., inconsistent) or unchanging (i.e., consistent) task rules. More specifically, participants in both task versions were exposed to five unchanging task rules in each of the four performance blocks (e.g., classes must not overlap in time). Four variations of a sixth rule were used to manipulate task consistency (e.g., must schedule a break after every hour of lecture). Thus, participants in the consistent task condition were exposed to the same variation of the.sixth rule in each performance block (with 25% of the participants being exposed to each of the four rule variations). Participants in the inconsistent task condition were exposed to all four variations of the sixth rule, a different rule in each of the four performance blocks. (Rule variations were provided in different orders for different participants.)
Goal Orientation Manipulation The goal orientation manipulation was the same as that used in Study 1, in which task instructions were manipulated either to create the perception that cognitive ability was stable and difficult to improve through effort and to focus the participant on achievement (performance goal orientation) or to create the perception that cognitive ability was changeable and easy to improve through effort and to focus the participants on exploring and mastering the task (learning goal orientation).
Measures Perceived task difficulty. The six-item scale used in Study 1 was used to assess perceived task difficulty. Cronbach's alphas were .77, .71, .72, and .72 in Blocks 1 through 4, respectively. Perceived goal orientation. The six-item scale assessing perceptions regarding goal orientation was used again in Study 2, although the reliability was somewhat lower (tx = .52). Performance. Performance was operationalized as the number of class schedules completed and was averaged across the two 10-min trials in each block. Intrinsic motivation. Intrinsic motivation was measured using the same scale as in Study 1. Coefficient alphas were .83, .80, .81, and .77, following Blocks 1 through 4. Self-efficacy. Self-efficacy magnitude and certainty were assessed using a questionnaire derived from Locke, Frederick, Lee, and Bobko (1984). At each of 11 performance levels, the questionnaire asked the participants (a) whether they could perform at that performance level (magnitude; yes/no) and (b) how certain they were that they could perform at that level (certainty; 1 = not at all certain, 10 = very certain). Correlations between self-efficacy magnitude and certainty ranged from .51 to .58 in Blocks 2 through 4. Self-efficacy magnitude and self-efficacy certainty scores were
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STEELE-JOHNSON, BEAUREGARD, HOOVER, AND SCHMIDT
standardized and summed to form a composite self-efficacy score. Selfefficacy was assessed prior to Blocks 2, 3, and 4, after receiving task experience in Block 1. Self-set goals. Participants selected a performance goal to work toward prior to Blocks 2, 3, and 4; they had no experience on which to base goals prior to Block 1. Participants selected their goal from 1 of 10 response categories (0 = 0 - 7 9 performance points to 9 = 400 or more points, with 40-point increments in intervening categories). Goal commitment. Goal commitment was assessed using an eight-item scale adapted from Hollenbeck, Williams, and Klein (1989). The measure was administered prior to Blocks 2, 3, and 4 (coefficient as = .81, .88, and .90, respectively). Participants responded using a 7-point Likert-type scale ranging from 1 (not at all) to 7 (very). This measure was administered to confirm that individuals possessed moderate to high levels of commitment to the goals they set for themselves. Affect: Satisfaction with performance. Affect was assessed using the same two-item scale as we used in Study 1. Coefficient alphas were moderate in Blocks 1 through 4 (rs = .67, .67, .69, and .65, respectively).
Procedure Participants followed the same procedure as in Study 1. They reported perceived goal orientation following the goal orientation instructions. Following each performance block, they reported their levels of perceived task difficulty, intrinsic motivation, and affect toward the task as well as their self-efficacy, goal level, and goal commitment for the next block. Because of the nature of the task consistency manipulation, the first opportunity for participants to detect a change in rules was during Block 2. Therefore, the dependent measures of interest in this study were those obtained from the second, third, and fourth blocks. Following Blocks 2, 3, and 4, participants completed measures of perceived task difficulty and intrinsic motivation. Following Blocks 2 and 3, participants reported their self-efficacy and self-set goals for the subsequent performance block.
Results M e a n s a n d standard deviations by condition are s h o w n in Table 2 for p e r f o r m a n c e , intrinsic motivation, self-efficacy, self-set goals, a n d satisfaction with p e r f o r m a n c e for Blocks 1 to 4.
Table 2
Means and Standard Deviations o f Variables in Study 2 Goal orientation Learning Dependent variable Performance
Task consistency Consistent
Inconsistent
Intrinsic motivation
Consistent
Inconsistent
Self-efficacy
Consistent
Inconsistent
Self-set goals
Consistent
Inconsistent
Satisfaction with performance
Consistent
Inconsistent
Note. N = 189.
Performance
Trial block
M
SD
M
SD
1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 2 3 4 2 3 4 2 3 4 2 3 4 1 2 3 4 1 2 3 4
3.97 8.34 10.70 12.20 4.21 8.60 9.97 11.47 4.29 4.03 3.87 3.90 4.47 4.38 4.27 4.26 0.07 -0.33 -0.21 0.18 0.50 0.42 2.73 3.06 3.44 3.22 3.56 3.69 4.43 5.19 5.50 5.31 4.57 4.97 5.02 4.97
2.33 2.94 4.12 4.83 2.37 2.85 3.81 5.43 0.78 0.66 0.58 0.69 0.89 0.79 0.79 0.69 2.04 1.87 2.04 1.67 1.57 1.47 2.53 2.19 2.34 2.28 1.93 2.25 1.74 1.48 1.28 1.50 1.63 1.47 1.59 1.62
3.88 8.13 11.26 13.20 3.41 7.44 8.81 10.18 4.26 4.15 4.14 4.20 4.20 4.10 3.96 4.01 0.12 0.17 0.36 -0.39 -0.55 -0.72 2.79 3.17 3.44 2.17 2.50 2.81 4.33 5.13 5.55 5.46 4.20 5.18 4.87 4.67
2.05 3.49 4.43 5.56 2.05 3.08 4.77 4.82 0.63 0.74 0.84 0.73 0.81 0.67 0.81 0.76 1.67 1.59 1.66 1.65 1.81 1.85 2.30 2.18 2.48 2.18 2.02 2.17 1.63 1.46 1.31 1.61 1.75 1.21 1.42 1.49
GOAL ORIENTATION AND TASK DEMANDS
Manipulation Checks A 2 (task consistency) X 2 (goal orientation) X 4 (trial blocks) repeated measures ANOVA was used to examine whether participants in the inconsistent task condition perceived the task as more difficult. Results revealed a significant Task Consistency x Trial Block interaction effect, F(3, 183) = 2.91, p < .05, Wilks's lambda = .95. Post hoc analyses revealed a significant effect for task consistency across Blocks 2 through 4, F(1,185) = 5.92, p < .05, but not in Block 1, F(1, 185) = .32, ns. Participants' perceptions of task difficulty were similar in Block 1 (consistent, M = 3.29, SD = 1.16; inconsistent, M = 3.19, SD = 1.11) and diverged in later blocks (consistent, M = 2.97, SD = 1.02 vs. inconsistent, M = 3.32, SD = 0.89). Thus, after participants in the inconsistent task condition were exposed to rule variations, they began to perceive the task as more difficult, as compared with those in the consistent task condition. A 2 (task consistency) x 2 (goal orientation) ANOVA was used to examine whether participants in the learning and performance goal orientation conditions differed in their perceptions regarding goal orientation. The results revealed a goal orientation effect, although the effect was smaller, F(1, 185) = 3.53, p = .06, than that observed in Study 1. Participants in the learning goal orientation condition reported a stronger belief that they could improve their performance (M = 3.87, SD = 0.47), as compared with those in the performance goal orientation condition (M = 3.75, SD = 0.40),
Effects of Task Consistency and Goal Orientation on Performance A 2 (task consistency) x 2 (goal orientation) x 3 (trial blocks) repeated measures ANOVA was used to examine whether task consistency and goal orientation interacted in their effects on performance (Hypothesis 1). Results revealed significant effects for task consistency, F(1, 185) = 4.52, p < .05, trial block, F(2, 184) = 97.17, p < .001, Wilks's lambda = .49, and the Task Consistency x Trial Block interaction, F(2, 184) = 6.62, p < .01, Wilks's lambda = .93. Performance improved more rapidly for participants in the consistent task than for participants in the inconsistent task condition (see Table 2). The hypothesized interaction effect was not observed.
Effects of Task Consistency and Goal Orientation on Motivational Variables Next, 2 (task consistency) x 2 (goal orientation) X 3 (trial blocks) repeated measures ANOVAs were used to examine whether task consistency and goal orientation interacted in their effects on three motivational variables: intrinsic motivation, selfefficacy, and self-set goals (Hypothesis 2). Results revealed a significant Task Consistency × Goal Orientation interaction effect for intrinsic motivation, F(1, 185) = 5.91, p < .05, providing support for our prediction. Post hoc analyses indicated that task consistency had an effect on intrinsic motivation for participants in the learning orientation, t(91) = -2.55, p < .05, but not in the performance orientation condition, t(94) = .91, ns. As shown in the top panel of Figure 3, participants in the learning orientation condition reported higher intrinsic motivation for the inconsistent
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than for the consistent task. Significant effects for block were also obtained, F(2, 184) = 6.91, p < .001, Wilks's lambda = .93. Similarly, the results provided support for our prediction for self-efficacy, revealing a significant Task Consistency x Goal Orientation interaction effect, F(1, 185) = 11.69, p < .001. (It is important to note that analyses used the self-efficacy measures preceding Blocks 3 and 4 because participants had not yet experienced the task consistency manipulation when they responded to the self-efficacy measure prior to Block 2.) Post hoc analyses indicated that task consistency had opposite effects on selfefficacy in the learning goal orientation, t(91) = -1.98, p = .05, and in the performance goal orientation condition, t(94) = 2.69, p < .01. Participants in the learning orientation condition reported higher self-efficacy in the inconsistent task condition, but participants in the performance orientation condition reported higher self-efficacy in the consistent task condition (bottom panel of Figure 3). No significant task consistency or goal orientation effects were observed for self-set goals. Rather, results indicated a significant effect only for block, F(1, 185) = 5.11, p < .05, with self-set goals increasing across blocks (see Table 2) and reported commitment to those goals uniformly high across conditions and blocks (M = 5.14, SD = 1.27).
Effects of Task Consistency and Goal Orientation on Affect Finally, a 2 (task consistency) X 2 (goal orientation) x 3 (trial blocks) repeated measures ANOVA was used to examine whether task consistency and goal orientation interacted in their effects on affect (i.e., satisfaction with performance; Hypothesis 3). Results revealed a significant effect only for task consistency, F(1, 185) = 5.66, p < .05. Participants' satisfaction with their performance was higher for those in the consistent (M = 5.36, SD = 1.23) than in the inconsistent (M = 4.95, SD = 1.10) task condition. Thus, Hypothesis 3 was not supported.
Discussion We examined whether goal orientation interacted with task consistency in its effects on performance, motivation, and sarisfaction with performance. In support of our hypotheses, our results indicate that individuals with a learning goal orientation reported higher levels of motivation in terms of self-efficacy and intrinsic motivation on an inconsistent task, and those with a performance goal orientation reported higher levels of self-efficacy on a consistent task. However, contrary to our predictions, we failed to observe Goal Orientation X Task Consistency interaction effects on performance or satisfaction with performance. General Discussion The two purposes of the present research are to examine (a) goal orientation effects among adults on a work-related task and (b) task demands as a boundary condition of goal orientation effects. As we expected, we observed that goal orientation and task demands interacted in their effects on performance, motivation, and affect. We found that a performance orientation had beneficial effects on performance on a simple task. Furthermore, goal orien-
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STEELE-JOHNSON, BEAUREGARD, HOOVER, AND SCHMIDT
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The interaction effect of task consistency and goal orientation on intrinsic motivation (top panel of figure) and self-efficacy (bottom panel of figure) in Study 2. Figure 3.
tations had more beneficial effects on motivation and affect when matched with appropriate task contexts: a learning goal orientation under high task demands or a performance goal orientation under low task demands. Our research contributes to the literature by highlighting the relevance of task features to goal orientation effects. It is interesting to note that the pattern of results differed depending on the task characteristic used to influence task demands. With respect to performance, we observed that goal ori-
entation and task difficulty interacted in their effects on performance in Study 1, but no interaction was observed between goal orientation and task consistency in Study 2. One explanation for this result is that the task version used in Study 2 was sufficiently demanding that cuing participants to focus on rehearsing strategies had no immediate benefits on overall performance in the consistent task. Comparing performance on the task versions used in Studies 1 and 2 revealed that performance on the consistent and inconsistent task versions (with six rules) fell between that ob-
GOAL ORIENTATIONAND TASK DEMANDS served for the simple (five rules) and difficult (seven rules) task versions in Study 1. Moreover, the small goal orientation effect within the difficult task condition in Study 1 was similar in magnitude to that observed in the consistent task condition in Study 2. Thus, a simpler consistent task version might have been needed to reveal goal orientation effects in Study 2. In addition, the different results observed for intrinsic motivation in Studies 1 and 2 might be explained by the nature of task demands. That is, intrinsic motivation declined across blocks in Study 1, regardless of goal orientation or task difficulty condition. In contrast, results revealed an interaction between goal orientation and task consistency in Study 2. Study 2 revealed that participants in the performance orientation condition reported similar levels of intrinsic motivation regardless of task consistency condition. In contrast, participants in the learning goal orientation reported much higher levels of intrinsic motivation in the inconsistent than in the consistent task condition. We offer the conjecture that for individuals with alearning goal orientation, task consistency might be a more important factor in intrinsic motivation than task difficulty. Support for this conjecture is provided by the observation that perceived task difficulty declined across blocks for all three consistent task versions (simple and difficult in Study 1; consistent in Study 2). Continued high task challenge was experienced only in the inconsistent task version. Thus, perceived task challenge and perceived opportunities for increasing competence appear to be an important aspect of intrinsic motivation for individuals with a learning goal orientation. The results for self-efficacy in Study 2 further support the notion that a greater challenge and a greater resulting opportunity to increase competence are obtained in the inconsistent task for participants with a learning goal orientation. Results from Study 2 reveal that whereas participants with a performance goal orientation reported higher self-efficacy in the consistent task condition, participants with a learning goal orientation reported higher selfefficacy in the inconsistent task. Thus, results for motivational variables in Study 2 were consistent with previous goal orientation research. Similar effects on performance might have been observed later in skills acquisition. Finally, apparent differences in the results obtained for performance satisfaction might be explained by task characteristics. Specifically, participants with a performance goal orientation were more satisfied with their performance on the simple task, which offered the greater opportunity for demonstrating their ability. In contrast, participants with a learning goal orientation were more satisfied with their performance on the difficult task, which we posit offered the greater opportunity to master the task, although no performance benefits were observed yet at this early stage of skill acquisition. Study 2, however, revealed an effect only for task consistency on performance satisfaction. It is interesting to note that a closer examination of the data suggests that task difficulty plays a more important rote in performance satisfaction for participants with a performance goal orientation, as compared with participants with a learning goal orientation. Thus, in Study 2, if both task consistency versions were too demanding to allow participants with a performance goal orientation to feel satisfied with their demonstration of ability, no goal orientation effects on satisfaction would be expected. These results raise several issues. Most important, our results have revealed beneficial effects for a performance goal orientation
735
in the simpler or consistent task version, whereas much previous research (see Button et al., 1996; Dweck, 1991; or Farr et al., 1993, for reviews) has demonstrated the beneficial effects for a learning goal orientation in more difficult tasks. These results can be explained using two learning mechanisms from cognitive psychology: transfer from controlled to automatic processing and development of schemas (Sweller, 1988). That is, on simpler consistent tasks there are fewer task strategies to learn, and schema development plays a relatively less important role in performance. In this situation, the individual can develop a strategy for completing the task and then rehearse relevant production rules involving task components until they can be applied with little attention. This should result in immediate beneficial effects on performance. However, on more difficult or inconsistent tasks, a larger number of task strategies must be learned before one can perform the task effectively, or effective task strategies might change with task changes. In turn, rehearsing productions that are not related to effective task strategies has little effect on performance. In a related issue, we suggest that one might not see immediate beneficial effects on performance resulting from schema development. Rather, benefits to performance may not be observed until the individual has had sufficient time to explore and evaluate task strategies in the process of developing schema. This explanation is consistent with research suggesting time-lagged effects for goal setting on difficult tasks (e.g., Locke & Latham, 1990). Hence, our study makes an important contribution to the literature, identifying circumstances in which a performance goal orientation has beneficial effects early in skill acquisition and linking those effects to learning mechanisms. Specifically, our study has revealed that when the task is simpler and consistent, one can expect to observe immediate beneficial effects for a performance goal orientation as individuals shift task components to automatic processing. Furthermore, shifting task components to automatic processing has the important function of freeing attentional resources for schema development. Moreover, schema development is more important and more difficult to complete on difficult or inconsistent tasks in which there are a larger number of relevant task strategies or in which task strategies are changing. The implication for managers and trainers is that seeing immediate benefits to performance can indicate transfer of task components to automatic processing without effective schema development. Whether performance improvements are beneficial in the long run depends on whether the trainee is rehearsing an optimal task strategy. Indeed, Sweller (1988) has noted that novices using general problem-solving strategies (e.g., means-ends analysis) experience a higher cognitive load that can prevent more effective schema development. Thus, in difficult tasks, the managers or trainers need to structure the situation to encourage schema development or provide optimal task strategies (if known) rather than reward possibly short-term performance gains. One limitation of our study is that it was conducted using undergraduates in a laboratory setting. On the other hand, as Kanfer (1994) has noted, the use of increasingly realistic and complex tasks in laboratory settings has begun to blur the distinction between field and laboratory research. Much evidence relating to goal orientation effects for adults has come from research examining goal orientation effects for undergraduate or graduate students performing complex, work-related task simulations (Bouffard et al., 1995; Fisher & Ford, 1998; Ford et al., 1998;
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Hofmann & Strickland, 1995; Wood & Bandura, 1989). Similarly, in the current research, undergraduates performed a complex task simulation that is similar to administrative tasks performed by employees in work settings, and the content of the task was relevant and realistic for students. Nevertheless, an important contribution of our research is that it highlights the relevance of task features to purportedly general constructs such as goal orientation. Thus, more research of the present kind is needed examining the generalizability of our findings to employees in work settings. In conclusion, our results provide evidence relating to several important issues in the goal orientation literature. First, our results show that task demands are an important boundary condition in assessing goal orientation effects and that different approaches to influencing task demands can produce different patterns of results. In addition, we highlight the important role of cuing effects in goal orientations and suggest that whether the focus of attention has beneficial effects depends on the cognitive resource demands of the task. Finally, we conclude that it is important to match goal orientations with task contexts. Much of the previous research on goal orientation (e.g., Greene & Miller, 1996) suggests that a learning orientation is superior (for exceptions, Hall, 1990). However, our results show that the benefits of a given goal orientation depends on the specific task context. References Abramson, L. Y., Seligman, M. E. P., & Teasdale, J. D. (1978). Learned helplessness in humans: Critique and reformulation. Journal of Abnormal Psychology, 87, 49-74. Ackerman, P. L. (1987). Individual differences in skill learning: An integration of psychometric and information processing perspectives. Psychological Bulletin, 102, 3-27. Ackerman, P. L. (1989). Individual differences in skill acquisition. In P. L. Ackerman, R. J. Sternberg, & R. Glaser (Eds.), Learning and individual differences: Advances in theory and research (pp. 165-217). New York: Freeman. Ames, C. (1984). Competitive, cooperative, and individualistic goal structures: A cognitive motivational analysis. In R. Ames & C. Ames (Eds.), Research on motivation in education (Vol. 1, pp. 177-208). New York: Academic Press. Ames, C., & Archer, J. (1988). Achievement goals in the classroom: Students' learning strategies and motivation processes. Journal of Education Psychology, 80, 260-267. Anderson, J. R. (1982). Acquisition of cognitive skill. Psychological Review, 89, 369-406. Anderson, J. R. (1987). Skill acquisition: Compilation of weak-method problem solutions. Psychological Review, 94, 192-210. Anderson, J. R. (1990). Cognitive psychology and its implications. New York: Freeman. Anderson, J. R. (1993). Rules of the mind. Hillsdale, NJ: Erlbaum. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman. Bar-Eli, M., Tenenbaum, G., Pie, J. S., Kudar, K., Weinberg, R., & Barak, Y. (1997). Aerobic performance under different goal orientations and different goal conditions. Journal of Sport Behavior, 20, 3-15. Bouffard, T., Boisvert, J., Vezeau, C., & Larouche, C. (1995). The impact of goal orientation on self-regulation and performance among college students. British Journal of Educational Psychology, 65, 317-329.
Butler, R. (1987). Task-involving and ego-involving properties of evaluation: Effects of different feedback conditions on motivational perceptions, interest, and performance. Journal of Educational Psychology, 79, 474-482. Butler, R. (1993). Effects of task- and ego-achievement goals on information seeking during task engagement. Journal of Personality and Social Psychology, 65, 18-31. Button, S. B., Mathieu, J. E., & Zajac, D. M. (1996). Goal orientation in organizational research: A conceptual and empirical foundation. Organizational Behavior & Human Decision Processes, 67, 26-48. Campbell, D. J. (1988). Task complexity: A review and analysis. Academy of Management Review, 13, 40-52. Campbell, D. J. (1991). Goal levels, complex tasks, and strategy development: A review and analysis. Human Performance, 4, 1-31. Cascio, W. F. (1998). Applied psychology in human resource management. Upper Saddle River, NJ: Prentice Hall. Colquitt, J. A., & Simmering, M. J. (1998). Conscientiousness, goal orientation, and motivation to learn during the learning process: A longitudinal study. Journal of Applied Psychology, 83, 654-665. Deci, E. L. (1971). Effects of externally mediated rewards on intrinsic motivation. Journal of Personality and Social Psychology, 18, 105-115. Deci, E. L. (1975). Intrinsic motivation. New York: Plenum. Deci, E. L., & Ryan, R. M. (1980). The empirical exploration of intrinsic motivational processes. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 13, pp. 39-80). New York: Academic Press. Deci, E. L., & Ryan, R. M. (1987). The support of autonomy and the control of behavior. Journal of Personality and Social Psychology, 53, 1024-1037. Duda, J. L. (1988). The relationship between goal perspectives, persistence and behavioral intensity among male and female recreational sport participants. Leisure Sciences, 10, 95-106. Duda, J. L. (1989). Relationship between task and ego orientation and the perceived purpose of sport among high school athletes. Journal of Sport & Exercise Psychology, 11, 318-335. Duda, J. L. (1992). Motivation in sport settings: A goal perspective approach. In G. C. Roberts (Ed.), Motivation in sport and exercise (pp. 57-91). Champaign, IL: Human Kinetics Books. Duda, J. L., & Nicholls, J. G. (1992). Dimensions of achievement motivation in schoolwork and sport. Journal of Educational Psychology, 84, 290 -299. Dweck, C. S. (1986). Motivational processes affecting learning. American Psychologist, 41, 1040-1048. Dweck, C. S. (1991). Self-theories and goals: Their role in motivation, personality, and development. In R. Dienstbier (Ed.), Perspectives on motivation: Nebraska symposium on motivation 1990 (Vol. 38, pp. 199-235). Lincoln, NE: University of Nebraska Press. Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95, 256-273. Earley, P. C., Connolly, T., & Ekegren, G. (1989). Goals, strategy development, and task performance: Some limits on the efficacy of goal setting. Journal of Applied Psychology, 74, 24-33. Earley, P. C., & Kanfer, R. (1985). The influence of component participation and role models on goal acceptance, goal satisfaction, and performance. Organizational Performance and Human Decision Processes, 36, 378-390. Farr, J. L., Hofmann, D. A., & Ringenbach, K. L. (1993). Goal orientation and action control theory: Implications for industrial and organizational psychology. In C. L. Cooper & I. T. Robertson (Eds.), International review of industrial and organizational psychology (Vol. 8, pp. 191232). New York: Wiley. Fisher, S. L., & Ford, J. K. (1998). Differential effects of learner effort and goal orientation on two learning outcomes. Personnel Psychology, 5l, 397-420.
GOAL ORIENTATION AND TASK DEMANDS Fitts, P. M. (1964). Perceptual-motor skill learning. In A. W. Melton (Ed.), Categories of human learning (pp. 243-285). New York: Academic Press. Fitts, P. M., & Posner, M. I. (1967). Human performance. Belmont, CA: Brooks/Cole. Ford, J. K., Smith, E. M., Weissbein, D. A., Gully, S. M., & Salas, E. (1998). Relationship of goal orientation, metacognitive activity, and practice strategies with learning outcomes and transfer. Journal of Applied Psychology, 83, 218-233. Goldstein, I. L. (1993). Training in organizations: Need assessment, development, and evaluation. Pacific Grove, CA: Brooks/Cole. Greene, B. A., & Miller, R. B. (1996). Influences on achievement: Goals, perceived ability, and cognitive engagement. Contemporary Educational Psychology, 21, 181-192. Hall, H. K. (1990). A social-cognitive approach to goal setting: The mediating effects of achievement goals and perceived ability. Unpublished doctoral dissertation, University of Illinois at Urbana-Champaign. Harackiewicz, J. M., & Elliot, A. J. (1993). Achievement goals and intrinsic motivation. Journal of Personality and Social Psychology, 65, 904-915. Heyman, G. D., & Dweck, C. S. (1992). Achievement goals and intrinsic motivation: Their relation and their role in adaptive motivation. Motivation and Emotion, 16, 231-247. Hofmann, D. A. (1993). The influence of goal orientation on task performance: A substantively meaningful suppressor variable. Journal of Applied Social Psychology, 23, 1827-1846. Hofmann, D. A., & Strickland, O. J. (1995). Task performance and sarisfaction: Evidence for a task- by ego-orientation interaction. Journal of Applied Social Psychology, 25, 495-511. Hollenbeck, J. R., Williams, C. R., & Klein, H. J. (1989). An empirical examination of the antecedents of commitment to difficult goals. Journal of Applied Psychology, 74, 18-23. Jagacinski, C. M., & Nicholls, J. G. (1984). Conceptions of ability and related affects in task involvement and ego involvement. Journal of Educational Psychology, 76, 909-919. Kahneman, D. (1973). Attention and effort. Englewood Cliffs, NJ: prentice-Hall. Kanfer, R. (1987). Task-specific motivation: An integrative approach to issues of measurement, mechanisms, processes and determinants. Journal of Social and Clinical Psychology, 5, 237-264. Kanfer, R. (1994). Work motivation: New directions in theory and research. In C. L. Cooper & I. T. Robertson (Eds.), Key reviews in managerial psychology: Concepts and research for practice (pp. 1-53). Chichester, England: Wiley. Kanfer, R., & Ackerman, P. L. (1989). Motivation and cognitive abilities: An integrative/aptitude-treatment interaction approach to skill acquisition. Journal of Applied Psychology, 74, 657-690. Koestner, R., Zuckerman, M., & Koestner, J. (1987). Praise, involvement, and intrinsic motivation. Journal of Personality and Social Psychology, 53, 383-390. Licht, B. G., & Dweck, C. S. (1984). Determinants of academic achievement: The interaction of children's achievement orientations with skill area. Developmental Psychology, 20, 628-636. Locke, E. A., Frederick, E., Lee, C., & Bobko, P. (1984). Effect of self-efficacy, goals, and task strategies on task performance. Journal of Applied Psychology, 69, 241-251. Locke, E. A., & Latham, G. P. (1990). A theory of goal setting and task performance. Englewood Cliffs, NJ: Prentice Hall. Martocchio, J. J. (1994). Effects of conceptions of ability on anxiety, self-efficacy, and learning in training. Journal of Applied Psychology, 79, 819-825. McAuley, E., Wraith, S., & Duncan, T. E. (1991). Self-efficacy, percep-
737
tions of success, and intrinsic motivation for exercise. Journal of Applied Social Psychology, 21, 139-155. Meece, J. L., & Holt, K. (1993). A pattern analysis of students' achievement goals. Journal of Educational Psychology, 85, 582-590. Miller, R. B., Behrens, J. T., Greene, B. A., & Newman, D. (1993). Goals and perceived ability: Impact on student valuing, self-regulation, and persistence. Contemporary Educational Psychology, 18, 2-14. Newell, A. (1990). Unified theories of cognition. Cambridge, MA: Harvard University Press. Newell, A., & Simon, H. A. (1972). Human problem solving. Englewood Cliffs, NJ: Prentice-Hall. Nicholls, J. G. (1971). Some effects of testing procedure on divergent thinking. Child Development, 42, 1647-1651. Nicholls, J. G. (1975). Causal attributions and other achievement-related cognitions: Effects of task outcome, attainment value, and sex. Journal of Personality and Social Psychology, 31, 379-389. Nicholls, J. G. (1984). Achievement motivation: Conceptions of ability, subjective experience, task choice, and performance. Psychological Review, 91, 328-346. Norman, D. A., & Bobrow, D. G. (1975). On data-limited and resourcelimited processes. Cognitive Psychology, 7, 44-64. Paas, F. G. W. C. (1992). Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach. Journal of Educational Psychology, 84, 429-434. Paas, F. G. W. C., & Van Merfienboer, J. J. G. (1994). Instructional control of cognitive load in the training of complex tasks. Educational Psychology Review, 6, 351-371. Phillips, J. M., & Gully, S. M. (1997). Role of goal orientation, ability, need for achievement, and locus of control in the self-efficacy and goal-setting process. Journal of Applied Psychology, 82, 792-802. Plant, R. W., & Ryan, R. M. (1985). Intrinsic motivation and the effects of self-consciousness, self-awareness, and ego-involvement: An investigation of internally controlling styles. Journal of Personality, 53, 435-449. Ryan, R. M. (1982). Control and information in the intrapersonal sphere: An extension of cognitive evaluation theory. Journal of Personality and Social Psychology, 43, 450-461. Ryan, R. M. (1982). Self versus other evaluation: An extension of cognitive evaluation theory to intrapersonal processes. (Doctoral dissertation, University of Rochester, 1981). Dissertation Abstracts International,
42(8-B), 3440. Schneider, W., Dumais, S. T., & Shiffrin, R. M. (1984). Automatic and control processing and attention. In R. Parasuraman & D. R. Davies (Eds.), Varieties of attention (pp. 1-27). New York: Academic Press. Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information processing: I. Detection, search, and attention. Psychological Review, 84, 1-66. Schraw, G., Horn, C., Thorndike-Christ, T., & Bruning, R. (1995). Academic goal orientations and student classroom achievement. Contemporary Educational Psychology, 20, 359-368. Seligman, M. E. P. (1990). Learned optimism. New York: Pocket Books. Shiffrin, R. M., & Schneider, W. (1977). Controlled and automatic human information processing: II. Perceptual learning, automatic attending, and a general theory. Psychological Review, 84, 127-190. Smith, E. M., Ford, J. K., & Kozlowski, S. W. J. (1997). Building adaptive expertise: Implications for training design. In M. A. Quinones & A. Duda (Eds.), Training for a rapidly changing workplace: Applications of psychological research (pp. 89-118). Washington DC: American Psychological Association. Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12, 257-285. Sweller, J., & Chandler, P. (1991). Evidence for cognitive load theory. Cognition and Instruction, 8, 351-362. Sweller, J., & Chandler, P. (1994). Why some material is difficult to learn. Cognition and Instruction, 12, 185-233.
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Treasure, D., & Roberts, G. C. (1994). Cognitive and affective concomitants of task and ego goal orientations during the middle school years. Journal of Sport and Exercise Psychology, 16, 15-28. VandeWalle, D. (1997). Development and validation of a work domain goal orientation instrument. Educational & Psychological Measurement, 57, 995-1015. VandeWalle, D., & Cummings, L. L. (1997). A test of the influence of goal orientation on the feedback-seeking process. Journal of Applied Psychology. 82, 390-400. Vlachopoulos, S., & Biddle, S. J. H. (1997). Modeling the relation of goal orientations to achievement-related affect in physical education: Does perceived ability matter? Journal of Sport and Exercise Psychology, 19, 169-187. Winters, D., & Latham, G. P. (1996). The effect of learning versus outcome goals on a simple versus a complex task. Group and Organization Management, 21, 236-250.
Wood, R. E. (1986). Task complexity: Definition of the construct. Organizational Behavior and Human Decision Processes, 37, 60-82. Wood, R., & Bandura, A. (1989), Impact of conceptions of ability on self-regulatory mechanisms and complex decision making. Journal of Personality and Social Psychology, 56, 407-415. Wright, P. M. (1991). Goals as moderators of the relationship between monetary incentives and performance: A review and NPI theory examination. Human Resource Management Review, 1, 1-22. Wright, P. M. (1992). An examination of the relationships among monetary incentives, goal level, goal commitment, and performance. Journal of Management, 18, 677-693. Received January 19, 1999 Revision received October 12, 1999 Accepted October 14, 1999 []
Members of Underrepresented Groups: Reviewers for Journal Manuscripts Wanted If you are interested in reviewing manuscripts for A P A journals, the A P A Publications and Communications Board would like to invite your participation. Manuscript reviewers are vital to the publications process. As a reviewer, you would gain valuable experience in publishing. The P & C Board is particularly interested in encouraging members o f underrepresented groups to participate more in this process. If you are interested in reviewing manuscripts, please write to Demarie Jackson at the address below. Please note the following important points: •
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To be selected as a reviewer, you must have published articles in peer-reviewed journals. The experience of publishing provides a reviewer with the basis for preparing a thorough, objective review. To be selected, it is critical to be a regular reader o f the five to six empirical journals that are most central to the area or journal for which you would like to review. Current knowledge o f recently published research provides a reviewer with the knowledge base to evaluate a new submission within the context o f existing research. To select the appropriate reviewers for each manuscript, the editor needs detailed information. Please include with your letter your vita. In your letter, please identify which A P A journal(s) you are interested in, and describe your area of expertise. Be as specific as possible. For example, "social psychology" is not suffic i e n t - y o u would need to specify "social cognition" or "attitude change" as well. Reviewing a manuscript takes time ( 1 - 4 hours per manuscript reviewed). If you are selected to review a manuscript, be prepared to invest the necessary time to evaluate the manuscript thoroughly.
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