IMPLICIT THEORIES, GOAL ORIENTATIONS, AND PERCEIVED COMPETENCE: IMPACT ON STUDENTS ACHIEVEMENT BEHAVIOR

Psychology in the Schools, Vol. 39(3), 2002 Published online in Wiley InterScience (www.interscience.wiley.com). 2002 Wiley Periodicals, Inc. DOI: 10.1002/pits.10035 IMPLICIT THEORIES, GOAL ORIENTATIONS, AND PERCEIVED COMPETENCE: IMPACT ON STUDENTS ACHIEVEMENT BEHAVIOR ANGELIKI LEONDARI University of Thessaly VASILIOS GIALAMAS Athens University The present study was designed to explore relations between implicit theories of intelligence, goal orientations, perceived competence, and school achievement. It was assumed that implicit theories of intelligence orient individuals toward particular goals, which in turn influence achievement behavior. Perceived competence was hypothesized to moderate the relationship between implicit theories, goal orientations and actual achievement. Subjects were 451 elementary and junior high school students. The results of Pearson product moment correlations and Path analysis show theoretically important intercorrelations that replicated previous research. Implicit theories were not related to academic achievement. Goal orientations had an indirect effect on achievement, which was mediated through perceived competence. Educational implications of these findings are discussed. 2002 Wiley Periodicals, Inc. Previous research has shown that students beliefs about themselves and their academic competence affect classroom achievement. The findings of these studies have stressed the role of self-concept, self-efficacy, causal attributions, self-regulation, and self-determination (Deci, Vallerand, Pelletier, & Ryan, 1991; Schunk, 1989; Zimmerman, 1990). More recently, the emerging research on the cognitive and motivational factors influencing learning has stressed the role of two motivational factors that are related to students achievement beliefs and approaches to learning: implicit theories of intelligence and academic goal orientations (Ames, 1992; Dweck & Leggett, 1988). One of the best articulated models in this respect is that of Dweck (1986, Dweck & Leggett, 1988), who postulated that student engagement, persistence, and course achievement, can be explained by different academic goal orientations, which in turn, are due to implicit theories students hold about intellectual ability. Implicit theories of intelligence are beliefs about the fundamental nature of intelligence, specifically whether intelligence is a fixed entity that cannot be changed (an entity theory) or a malleable quality that can be increased through one s efforts (an incremental theory). These theories create a framework for processing information, constructing representations of events and making inferences (Dweck, Chiu, & Hong, 1995; Gervey, Chiu, Hong, & Dweck, 1999). Research has shown (Dweck & Leggett, 1988; Faria, 1996) that students entity vs. incremental conceptions of intelligence have a definite impact on cognition and behavior in academic situations. The importance of implicit theories of intelligence is their link to effort and preference for challenge. It seems that students with an incremental view of intelligence tend to increase their effort as task difficulty increases with the primary intent to understand the task and ultimately to increase knowledge. On the other hand, students with an entity view, being more concerned with the success of their performance, they often avoid challenging tasks that involve a high degree of risk for poor performance and subsequent evaluations of incompetence (Dweck & Leggett, 1988). The second motivational factor related to students achievement beliefs, is achievement goals. Weiner (1990) has pointed to goal orientation theory as a major new direction, one pulling Correspondence to: A. Leondari, Irinis 89, Agia Paraskevi 15342, Athens, Greece. E-mail: leontari@ece.uth.gr 279

280 Leondari and Gialamas together different aspects of achievement research (p. 629). Achievement goals, have been described by Ames (1992, p. 261) as an integrated pattern of beliefs, attributions, and affect that produces the intentions of behavior... represented by different ways of approaching, engaging in, and responding to achievement-type activities. Two achievement goals have received the most attention: the goal to develop and improve ability (referred to in this study as a task goal orientation) and the goal to demonstrate and prove ability (referred to in this study as a performance-approach goal orientation). These two achievement goals are conceptualized as approach motivational tendencies (Middleton & Midgley, 1997). Traditionally, however, theorists have described motivation in terms of approach and avoidance tendencies (e.g., Atkinson, 1957; McClelland, 1951). For some people the goal of avoiding negative judgments from others or avoiding looking stupid may be dominant. However, the goal to avoid the demonstration of lack of ability has not played a major role in studies using a goal theory framework (Middleton & Midgley, 1997). More recently, researchers have started to turn their attention to this goal which is conceptualized as striving to avoid incompetence (Elliot & Harackiewicz, 1996, p. 461). In this study, we examine both the approach and avoidance components of achievement goals. Therefore, three goal orientations were considered: a task goal (directed towards acquiring new skills or improving knowledge), a performance-approach goal (directed towards the demonstration of competence), and a performanceavoidance goal (aimed at avoiding the demonstration of incompetence). Goal orientation research suggests that a task goal orientation is associated with positive achievement beliefs that lead to adaptive educational outcomes, whereas performance goals are associated with negative achievement beliefs that often lead to maladaptive behaviors including low task engagement, less persistence, and the occasional adoption of a helpless response (Ames & Archer, 1988, Elliot & Dweck, 1988). In most of these studies no distinction is made between performance-approach and performance-avoidance goal orientation. In this study, we were interested with documenting the differential effects of performance-approach and performanceavoidance goals on achievement. One achievement belief that has received a great deal of attention in the literature is perceived competence. Perceived competence seems to be a powerful motivational construct that has been linked to both implicit theories and achievement goals (Dweck & Leggett, 1988). Findings suggest that individuals with either a task or a performance-approach goal orientation, who are confident in their ability to succeed at a task, show quite similar behavior. They accept the reasonable challenge of the task and will persist in an effort to successfully complete it. However, individuals with performance-avoidance goals who doubt their ability, try to avoid tasks perceived to be challenging, show decreased performance, negative affect, and low persistence when they encounter difficulties (Ames & Archer, 1988; Elliot & Dweck, 1988; Nolen, 1988). Although previous research has provided empirical support for these predictions, the distinction between the performance-approach and performance-avoidance goal orientations and their interaction with implicit theories and perceived ability has not been adequately tested. This study attempted to do that by examining whether there can be a meaningful distinction between the two performance orientations, namely performance-approach and performance-avoidance goal orientations. An additional purpose of the present study was to test a causal model that examines the relationships between students implicit theories of intelligence, goal orientations, perceived competence, and actual achievement. Specific goals of the study were to explore if there were age and gender-related differences. Based on previous theoretical and research literature we made the following hypotheses: (a) task, performance-approach, and performance-avoidance scales will factor separately; (b) incremental theory will be positively correlated with task and performanceapproach goal orientations and negatively with performance-avoidance goal orientation; (c) incremental theory and approach goal orientations (task and performance-approach) would be positive

Implicit Theories, Goal Orientations, and Perceived Competence 281 predictors of academic achievement; and (d) perceived competence would moderate the relationship between implicit theories, goal orientations and academic achievement. METHOD Participants Participants were 451 students (M 204, F 247) from four elementary (n 221) and three junior high schools (n 230), from an ethnically and economically homogeneous school district, in a big city in Northern Greece. The sample was representative of the school district, which was predominantly middle class, White, with a small minority population (6%). Students socioeconomic status was operationalized in terms of the mean education level of parents, and coded into two categories: working class (less than high school completion) and middle class (college completion or higher). Parental education as an index of social class was selected because recent data suggest that indices of class based on composite measures of occupation, income, and education fluctuate frequently over the course of an individual child s lifetime because of parental job changes and fluctuations of family finances (Featherman, Spenner, & Tsunematsu, 1988). Parental education is probably the most stable component of the family s social class. Approximately 36% of the students fathers and 34% of the mothers had a university degree. The percentages for high school completion were 49% for fathers and 47% for mothers, respectively. Most students (89%) came from intact families. Of the remaining students 10% lived in divorced, single-parent families, and 1% had a deceased parent. The age range was 10 years 5 months to 13 years 8 months. Classrooms ranged in size from 16 to 28 (M 21.1, SD 6.2). Procedure Questionnaires were administered to intact classes during class hours by one of the authors. Students were informed that their participation was voluntary and that their responses would be confidential should they choose to participate. Measures All participants completed a booklet containing three separate inventories. The booklet contained: 1. A four-item self-report inventory measuring students implicit theories of intelligence (Stipek & Gralinski, 1996). The original questionnaire consists of two subscales one measuring beliefs about the effect of ability on performance (Entity beliefs), and the second measuring beliefs about the positive effects of effort on performance (Incremental beliefs). In this study only the incremental statements were presented (intelligence as malleable) because research in the achievement domain (Erdley, Cain, Loomis, Duman- Hines, & Dweck, 1997) has shown that when both the entity and incremental options are included, children tend to endorse incremental statements. The four items assessed the beliefs that effort is a cause of academic performance (e.g., Everyone could do well in school if they worked hard ); and that effort increases intelligence (e.g., You can get smart by working hard in school ). Stipek and Gralinski (1996) report reliability coefficients for the Effort-Related scale ranging from.50 to.63. The responses to the four items were added and then averaged. High values indicate that the students had high incremental beliefs, that is, the higher the score the less one believes that intelligence is a fixed entity. The Cronbach alpha reliability coefficient in this study was.73. 2. An 18-item inventory measuring three goal orientations: a task goal orientation, a performance-approach goal orientation, and a performance-avoidance goal orientation. The original instrument consists of 22 items designed to measure four dimensions of goal orientation. For the purposes of the present study only the items corresponding to the three goal orientations were used. Task goal orientation was defined as representing a

282 Leondari and Gialamas desire to learn something new, to master a task, or to improve one s competence. The scale had an alpha coefficient of.72. The scale measuring performance-approach goal orientation (a.70) included items tapping students desire to be best, to demonstrate superior ability. The performance-avoidance goal orientation scale (a.74) was composed of items representing a desire to avoid looking stupid, avoid negative reactions from others. Answers were rated on a four-point Likert scale ranging from mostly true to mostly false. The responses to the items of each scale were added and then averaged. 3. A seven-item subscale assessing students confidence in their own ability (Harter, 1982). Self-Perception Profile for Children (SPPC) is a measure of children s self-evaluations of personal competence. This self-report inventory contains six subscales (a global selfworth scale, and five competence scales). Only the Scholastic Competence scale was used in the current study. It is based on a collection of items that refer to a general feeling of doing well or poorly in school. Four response options are presented in a format involving two decision points. First, children select which of the two descriptions is most like themselves. Second, they indicate if the selected description is very characteristic of them ( really true ) or somewhat characteristic of them ( sort of true ). The responses are scored on a scale from 1 to 4, with higher scores reflecting greater competence. The subscales have good internal consistency (Cronbach s alphas range from.75 to.82; Harter, 1985). Three-month test retest reliabilities were also high (.70 to.87; Harter, 1982). Furthermore, the SPPC showed a highly interpretable factor structure (Harter, 1985). Cronbach s alpha for the Scholastic Competence subscale in this study was.79. 4. An academic performance measure which was based on the students official school records. Students grades in math and language were coded on a 10-point scale, and were averaged across these two subject areas. Exploratory Factor Analysis RESULTS To test the factor structure of the goals inventory that has been validated in a specific cultural setting, and to determine the extent to which it can be applied intact with other cultural groups, a factor analysis was performed on 18 items using oblique rotation. Oblique rotation was chosen because the factors were expected to correlate with each other (Tabachnick & Fidell, 1996). Principal components extraction was used prior to principal factor extraction to estimate number of factors, presence of outliers, and factorability of the correlation matrices. With an a.001 cutoff level, 20 of 451 subjects produced scores that identified them as outliers. These cases were deleted from principal factor extraction. Although there were five eigenvalues greater than 1, both the scree plot method and parallel analysis supported the existence of three factors. The eigenvalues for random data were estimated using the regression equation developed by Allen and Hubbard (1986). The minimum loading used to identify items to factors was.45. The cutoff point of.45 was decided because of a gap in loadings across the factors (Tabachnick & Fidell, 1996). Besides, as Comrey and Lee (1992) suggest, loadings in excess.71 are considered excellent,.63 very good,.55 good,.45 fair, and.32 poor. In each case the items designed to measure the three goal orientations loaded significantly on the appropriate factors. All items had high factor loadings (above.45) on the predicted factor. Moreover, all items had lower factor loadings, on the other two factors than the predicted one. Four of the items were discarded as having loadings less than.45. Therefore, the final instrument was reduced to 14 items. Table 1 presents the final set of items for each of the three factors and the factor loadings. The estimates of internal consistency for each of the scales were calculated utilizing Cronbach coefficient alpha. The reliability coefficients for the three factors (Task, Performanceapproach, and Performance-avoidance) were.72,.70, and.74, respectively. The three factors combined accounted for 40.06% of the variance in the sample.

Implicit Theories, Goal Orientations, and Perceived Competence 283 Table 1 Summary of Items and Factor Loadings for a Three-Factor Solution (Oblimin Rotation) for the Goal Orientation Questionnaire (N 431) Factor Loadings Items 1 2 3 Communality 1. Task goal orientation Concerned improving skills.68.05.22.55 Like to learn interesting things at school.57.12.09.45 Important to learn new things at school.50.02.15.42 Want to learn more.49.09.22.31 2. Performance-avoidance goal orientation Concerned about what classmates think.11.72.26.53 Concerned when answering questions.07.65.16.44 Anxious when doing exercise on blackboard.16.65.23.42 Worry over mistakes.03.55.27.29 Try not to appear stupid.04.49.06.24 3. Performance-approach goal orientation Try to attain higher grades than others.32.21.72.52 Try to do better than others.36.18.68.50 Feel successful if one s own work is better.07.15.48.24 Manage tasks than others don t.08.14.48.22 Answer questions to show more knowledge.11.21.47.22 Eigenvalues a 3.39 2.19 1.64 Variance explained (%) a 18.83 12.14 9.09 a Eigenvalues and variance percentages from the unrotated Principal Component Analysis. Correlations Among the Goal Orientation Scales Task orientation was positively correlated with performance-approach (.27) goal orientation. The correlation between the two performance scales was.24 (Table 2). Positive correlations between task and performance-approach goals as well as between the two performance goal orientation scales were found previously in similar studies (Elliott & Church, 1997; Midgley, Anderman, & Hicks, 1995; Midgley & Urdan, 1995; Skaalvik, 1997). Although these correlations indicate that there is some overlap between the three scales, they are low enough to permit the conclusion that the three goal orientations form distinct factors. School Level and Gender Differences in Relation to Implicit Theories of Intelligence and Goal Orientations Multivariate analysis of variance followed by univariate F-tests was used to test for differences by school level and gender on each of the three goal orientation scales and theories of intelligence. The scales measuring task goal orientation and theories of intelligence were negatively skewed; thus, scores were transformed by using inverse transformation. According to Bradley (1982), the inverse is the best of several alternatives for J-shaped distributions. Despite the fact that the transformation did not render the distribution normal, there were no outliers and the assumptions of homogeneity were met (Box s M-test was not significant at p.001). Moreover, the ratio of largest to smallest sample size was not greater than 4:1, and the ratio between largest

284 Leondari and Gialamas Table 2 Pearson Product-Moment Correlations 1 2 3 4 5 1. Inc. 2. Task.16* 3. Perf.-Approach.12*.27* 4. Per.-Avoid.04.09.24* 5. P.C..03.30*.25*.18 6. Ach.09.23*.17*.09.52* *p.01. P.C. Perceived Competence; Inc. Incremental beliefs; Task Task goal orientation; Perf.-approach Performance-approach goal orientation; Perf.-avoid Performance-avoidance goal orientation; Ach Academic Achievement. and smallest variance was no greater than 10:1 for each of the dependent variables (Tabachnick & Fidell, 1996). There were significant school-level differences on all the dependent variables (Table 3). School level was related to views of intelligence, F(1,427) 9.70, p.01. High school students had more of a stability view than the younger group of students. Similarly, high school students obtained lower scores on the task goal orientation scale, F(1,427) 51.68, p.01, the performanceapproach goal orientation scale, F(1,427) 34.92, p.01, and the performance-avoidance goal orientation scale, F(1,427) 15.32, p.01. Effects for gender were not significant. Relationships Among the Variables The second stage of analysis was an exploration of the relationships among the variables. The pattern of relationships between the different variables was examined first by Pearson productmoment correlations and then by path analysis. Believing that ability is modifiable was positively related to task (.16) and performance-approach (.12) goal orientations. Perceived competence was also positively related to task (.30) and performance-approach (.25) goal orientations and negatively to performance-avoidance goal orientation (.18). Academic achievement was positively Table 3 Analysis of Variance on Differences Between Elementary and Junior High School Students Elementary School Students High School Students Variable M SD M SD F 2 Test (F) a Levene s Inc.96.10.92.13 9.70*.022 12.24* Task.89.16.77.18 51.68*.108 1.57 Perf.-approach 3.17.66 2.80.65 34.92*.076 2.68 Perf.-avoid 2.75.83 2.44.84 15.32*.035.65 *p.01. a Levene s Test of Equality of Error Variances (from two-way Manova). Inc Incremental beliefs; Task Task goal orientation; Perf.-approach Performance-approach goal orientation; Perf.- avoid Performance-avoidance goal orientation.

Implicit Theories, Goal Orientations, and Perceived Competence 285 associated with perceived competence (.52), task (.23), and performance-approach (.17) goal orientations. To further examine the relations between the variables used in this study, Maximum Likelihood estimation was used and all analyses were conducted on covariance matrices. The assumptions of multivariate normality and linearity were evaluated through SPSS and AMOS. Two measures (the task goal orientation scale and the scale measuring incremental beliefs) showed extreme skeweness and kurtosis ( p.001). Despite that, and the fact that some of the variables were categorical, we decided to choose Maximum Likelihood Estimation after using bootstrapping to estimate robust standard errors and to evaluate different estimation methods (Efron, 1982). Relatively few studies have attempted to test causal models that combine students implicit theories, goal orientations, perceptions of competence, and actual achievement. In this study, we attempted to test a causal model derived from the theoretical and research literature. The model examines how students implicit theories and goal orientation are related to perceived competence and how they influence academic achievement. The model depicts implicit theories and goal orientations as related, but in a noncausal fashion. In evaluating the fit of the model we followed recent recommendations (Hoyle & Panter, 1995; Hu & Bentler, 1995) and used multiple indexes of fit. Specifically, in addition to reporting the chi-square test statistic, we report the Normed fit index (NFI), the Comparative fit index (CFI), the Tucker-Lewis index (TLI), and the Root Mean Square of Error Approximation (RMSEA). Each of these indexes evaluates the fit of the model slightly differently (Hu & Bentler, 1995), and therefore, an indication of good fit from these various indexes increases the confidence in the model. The critical value that is recommended for the first three indexes is.90. Under that value a model is considered to have a questionable fit. A value lower than.08 of the RMSEA is considered to indicate an adequate fit whereas values lower than.05 indicate a good fit (Browne & Cudeck, 1993). Figure 1 presents the measurement model. The fit for this model was: 2 (12, N 431) 17.76, p 0.12, NFI.96, CFI.99, TLI.97, RMSEA.03 with P (0.05).79. All indexes indicated a good fit to the data (Table 4). Parameter estimates in Figure 1 indicate that the belief that ability is modifiable is not a direct predictor of academic achievement. Achievement is directly affected by perceived competence, gender, and school level. The effects of the three goal orien- Figure 1. Path model predicting academic achievement from implicit theories, goal orientations, and perceived competence (Maximum Likelihood method).

286 Leondari and Gialamas Table 4 Path Analysis Results: Standardized Parameters with Bootstrap Standard Errors Dependent Variables Independent Standardised parameters Bootstrap SE Path coefficients Ach PC.47*.037 Ach Gender.15*.038 Ach School Level.36*.037 PC Task.26*.046 PC Perf.-approach.24*.047 PC Perf.-avoid.26*.043 Variable correlations Inc Task.16*.053 School level Inc.15*.044 School level Task.33*.044 School level Perf.-avoid.18*.047 Task Perf.-avoid.08.049 Perf.-avoid Perf.-approach.25*.044 Task Perf.-approach.27*.041 Gender Perf.-approach.11*.046 School Level Perf.-approach.27*.045 Inc Perf.-approach.11*.044 Squared multiple correlations Ach.40*.036 PC.18*.034 *p.01; two-tailed significance levels based on bias corrected confidence interval. Inc Incremental beliefs; Task Task goal orientation; Perf.-approach Performanceapproach goal orientation; Perf.-avoid Performance-avoidance goal orientation. tations on achievement were indirect, operating through perceived competence. The picture painted by this model suggests that the adoption of task and performance-approach goals has a positive, indirect effect on academic achievement, whereas the adoption of performance-avoidance goal orientation has a negative, indirect effect on achievement. In the model, gender was a positive predictor of academic achievement and school level a negative one. Girls (M 8.16, SD 1.38) outperformed boys (M 7.68, SD 1.50) and elementary school students (M 8.59, SD 1.29) outperformed high school students (M 7.32, SD 1.34). Incremental beliefs were positively correlated with task and performance-approach goal orientations only. DISCUSSION Although both approach and avoidance tendencies have traditionally been described by motivation theorists, the goal of avoiding the demonstration of lack of ability has not been included in most studies using a goal orientation framework. Consistent with the current understanding that achievement goals include both approach and avoidance components (Elliot & Church, 1997; Skaalvik, 1997), in this study, we used scales to assess task, performance-approach and performance-

Implicit Theories, Goal Orientations, and Perceived Competence 287 avoidance goals. The results support previous findings about the existence of two independent dimensions of performance orientation. Factor analysis distinguished clearly between these two dimensions, thus supporting the usefulness of the theoretical framework that emphasizes the existence of two ego or performance orientations. However, the correlations between the two subscales suggest that it is possible for individuals to have a mixture of different goals that they are pursuing at the same time (Elliot & Church, 1997; Midgley et al., 1998). In relation to school level, the results of the study show that elementary school students were more likely to espouse all three kinds of achievement goals more than the older group of students. Previous research has found that middle school students endorse performance goals more, and task goals less, than do elementary school students (Midgley et al. 1995). The results of our study show that students academic motivation declines during the early adolescent period and so does their academic achievement (Eccles et al., 1993). A number of studies have indicated that the early adolescent years are characterized by a negative change in motivational orientation and a decline in academic performance for a number of children (Eccles & Midgley, 1989). This general disengagement from school, as regards high school students, have been linked to the transition from elementary to high school level, and the fact that students experience secondary schools as both frustrating academically and unsupportive interpersonally (Eccles & Midgley, 1989; Roeser, Midgley, & Urdan, 1996). In support of prior research (Ablard & Mills, 1996), this study found that younger students adopted more than older ones an incremental view of intelligence (intelligence as modifiable). As Nicholls and Miller (1983) have shown, during early adolescence, children s conception of the nature of ability becomes more differentiated and more like that of an adult. The difference in beliefs of elementary and high school students may be a reflection of this developmental change. It may also be due to the fact that as children grow older and obtain more experience with society s increasing emphasis on intelligence as stable, they tend to adopt this view. Hypothesis 2 stated that incremental beliefs (the belief that intelligence is modifiable) would be positively correlated with approach goals (task and performance-approach) and negatively with performance-avoidance goals. The findings of the study show that, in line with Dwecks (1986) assumptions, incremental beliefs were positively related to task orientation. There was no association between incremental beliefs and the two performance goal orientations. In other words, the implicit belief that ability is increasable seemed to orient individuals toward pursuing the learning goal of developing that ability further. An interesting result of the present study was that incremental beliefs were not related to academic achievement as stated in Hypothesis 3 and as would be predicted by prior research (Dweck & Leggett, 1988). An explanation for this finding might be that incremental beliefs influence achievement indirectly through the adoption of a specific goal orientation. The results demonstrate that the three goal orientations were effective in predicting variations in perceived competence. In line with previous findings significant positive correlations were found between task goal orientation, performance-approach goal orientation and perceived competence (Meece, Blumenfeld, & Hoyle, 1988; Nicholls, 1989; Skaalvik, 1997). Performanceavoidance goal orientation was also a significant but negative predictor of perceived competence. In other words, students who had a strong performance-avoidance orientation tended to perceive themselves as less competent academically. Our findings suggest that achievement goals and perceived competence are important in explaining school achievement. Perceived competence moderated the relationship between achievement goals and achievement. In most previous studies task goals were positively correlated with academic achievement (Meece & Holt, 1993; Midgley & Urdan, 1995). However, perfromanceapproach goals were sometimes positively related (Archer, 1994; Butler, 1992; Harackiewicz,

288 Leondari and Gialamas Barron, Elliot, Carter, & Lehto, 1997; Harackiewicz & Elliot, 1993; Midgley & Urdan, 1995; Pintrich & Garcia, 1991), and sometimes were either unrelated or negatively related to academic achievement (Meece et al., 1988; Schraw, Horn, Thornkike-Christ, & Bruning, 1995). These contradictory results may be due to the fact that performance goal orientation has been defined in different ways: the attempt to gain a favorable judgement of competence or avoid an unfavorable judgement of competence (Dweck & Leggett, 1988), a desire to be superior to others (Nicholls, Cobb, Wood, Yackel, & Patashnick, 1990), or to achieve an extrinsic reward, such as a high grade (Pintrich & Garcia, 1991). Although it may be the case that each of these definitions coexist within an individual, as the results of this study show, it might be useful to make a distinction between the two performance goal orientations and examine the implications of adopting one or the other for students academic learning. In conclusion, this study shows that implicit theories of intelligence are related to students achievement goals and that students with different goal orientations differed in respect to achievement. Students with dominant approach goal orientations and high perceived competence attained higher achievement. According to Dweck (Dweck and Leggett, 1988) a consistent predictor of children s goal orientation is their theory of intelligence. These implicit beliefs about ability would predict whether individuals will be oriented toward developing that ability or toward documenting the adequacy of their ability. In other words, goal orientations based on implicit theories of intelligence may be the root of adaptive of maladaptive patterns. In achievement situations, task orientation is presumed to result in behaviors conductive to long-term accomplishment and investment. It has been suggested that task oriented students invest more time and effort in mastering course material because they are motivated to improve their knowledge. In addition, task-oriented students seem to engage in deep cognitive processing, to use more strategies, or use strategies more efficiently (Ames & Archer, 1988; Elliot & Dweck, 1988; Nolen, 1988). Further, task orientation seems to enhance the probability that individuals feel competent when engaged in achievement activities. In short, it is assumed that a task orientation establishes the basis for maximal motivation and adaptive behaviors (Nolen, 1988; Pintrich & Garcia, 1991). The results of our study lead to the conclusion that both task and performance-approach goals are facilitative for academic achievement, a result that was evident in several other studies (Elliot & Harackiewicz, 1996). Wentzel (1991) maintains that students need to pursue both task and performance goals if they are to succeed. Additionally, it must be stressed that students do not have either on goal orientation or another (Middleton & Midgley, 1997), but various levels of different goal orientations. Previous research has indicated that the most facilitative pattern for learning is high task and low performance-approach goals (Meece & Holt, 1993). It will be important to further examine these patterns and interactions in relation to educationally relevant outcomes in future studies. An educational implication of these findings concerns the question of how we can translate an approach goal orientation into actual classroom processes. It seems that situational factors and instructional demands can influence the salience of a particular achievement goal and, hence, its adoption (Ames, 1990; Ames & Archer, 1988). Recent studies suggest that the psychological environment of the classroom may have a strong influence on the goals that students adopt (Anderman & Young, 1994; Maehr, 1991). When environments are marked by interpersonal competition, social evaluation, and normative-based testing, performance orientation is more likely to result. Situations characterized by an emphasis on learning from one s mistakes, personal skill mastery, and the importance of exerting effort, tend to lead to a task orientation. If we want to enhance the quality of students involvement in learning, increase the likelihood that they will opt for and persevere in challenging learning activities, and develop an interest in learning, we may have to

Implicit Theories, Goal Orientations, and Perceived Competence 289 consider modified teacher roles and different instructional strategies (Brophy, 1983). Ames (1992) suggests that a task goal orientation becomes evident when the teachers instructional approach is designed to promote meaningful, rather than rote learning, is adapted to students interests, promotes positive peer relationships, and emphasizes the intrinsic value of learning. It is interesting that as research findings show those children who may be the most likely to benefit from an enhanced task orientation climate are those who are often considered as at risk (Ames, 1992). There are a number of limitations to this study. The data were collected at one point in time and, therefore, no causal links can be firmly established. Longitudinal studies that follow children from elementary to high school and assess changes in implicit theories and in achievement goals, are needed. Another point concerns the domain specifity of implicit theories and goal orientations. In this study it was assumed, following Nicholls s suggestion (Duda & Nicholls, 1992) that implicit theories and goal orientations cut across specific domains. However, there is evidence that seems to suggest that an approach that allows for domain specifity may be more fruitful in understanding student behavior. Even when individuals do hold similar theories and goals across domains, they may have different confidence levels, and therefore, may display different behavior patterns. References Ablard, K.E., & Mills, C.J. (1996). Implicit theories of intelligence and self-perceptions of academically talented adolescents and children. Journal of Youth and Adolescence, 25, 137 148. Allen, S.J., & Hubbard, R. (1986). Regression equation of the latent roots or random data correlation matrices with unities on the diagonal. Multivariate Behavioral Research, 21, 393 398. Anderman, E.M., & Midgley, C. (1997). Changes in achievement goal orientations and perceived classroom goal structures across the transition to middle level schools. Contemporary Educational Psychology, 22, 269 298. Anderman, E.M., & Young, A.J. (1994). Motivation and strategy use in science: Individual differences and classroom effects. Journal of Research in Science Teaching, 31, 811 831. Ames, C. (1990). What teachers need to know. Teachers College Record, 91, 409 421. Ames, C. (1992). Achievement goals and classroom motivational climate. In J. Meece & D. Schunk (Eds.). Students perceptions in the classroom (pp. 327 348). Hillsdale, NJ: Erlbaum. Ames, C., & Archer, J. (1987). Mothers beliefs about the role of ability and effort in school learning. Journal of Educational Psychology, 79, 409 414. Ames, C., & Archer, J. (1988). Achievement goals in the classroom: Students learning strategies and motivation processes. Journal of Educational Psychology, 80, 260 267. Archer, J. (1994). Achievement goals as a measure of motivation in university students. Contemporary Educational Psychology, 19, 430 446. Atkinson, J.W. (1957). Motivational determinants of risk-taking behavior. Psychological Review, 6, 359 372. Bradley, I.V. (1982). The insidious L-shaped distribution. Bulletin of the Psychonomic Society, 20 (2), 85 88. Brophy, J. (1983). Conceptualizing student motivation. Educational Psychologist, 18, 200 215. Browne, M.W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. Bollen & J. Long (Eds.), Testing structural equation models (pp. 136 162). Newbury Park, CA: Sage. Butler, R. (1992). What young people want to know when: Effects of mastery and ability goals on interest in different kinds of social comparisons. Journal of Personality and Social Psychology, 62, 934 945. Comrey, A.L., & Lee, H.B. (1992). A first course in factor analysis (2nd ed.). Hillsdale, NJ: Erlbaum. Deci, E.L., Vallerand, R.J., Pelletier, L.G., & Ryan, R.M. (1991). Motivation and education: The self-determination perspective. Educational Psychologist, 26, 325 346. 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., & Leggett, E. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95, 256 273. Dweck, C.S., Chiu, C., & Hong, Y. (1995). Implicit theories and their role in judgements and reactions. A world from two perspectives. Psychological Inquiry, 6, 267 285.

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