Changes in achievement goals and competence perceptions across the college semester

Transcription

1 Motiv Emot (2010) 34: DOI /s x ORIGINAL PAPER Changes in achievement goals and competence perceptions across the college semester Carolyn M. Jagacinski Shamala Kumar Jan L. Boe Holly Lam Steven A. Miller Published online: 25 May 2010 Ó Springer Science+Business Media, LLC 2010 Abstract We investigated the relationship between changes in perceptions of competence and changes in achievement goals across a college semester for students enrolled in an introductory psychology course. Two types of competence perceptions were examined: self-efficacy for learning and normative perceived ability. Changes in normative perceived ability were predicted to relate to changes in performance goals, but not mastery goals. Because mastery goals rely on self-referent standards to evaluate ability, we predicted changes in self-efficacy for learning would relate to changes in mastery goals. We also expected changes in self-efficacy for learning to relate to changes in performance goals because learning can lead to the demonstration of superior competence. The predictions were supported for mastery and performance-approach goals, but not for performance-avoidance goals. Very little change in performance-avoidance goals was observed. Scores on the first course exam also predicted change in performance-approach goals, with this effect partially mediated by competence perceptions. C. M. Jagacinski (&) S. Kumar J. L. Boe H. Lam Department of Psychological Science, Purdue University, 703 Third Street, West Lafayette, IN , USA jag@psych.purdue.edu S. A. Miller Argosy University, Chicago, IL, USA Present Address: S. Kumar University of Peradeniya, Peradeniya, Sri Lanka Present Address: J. L. Boe H. Lam Valtera Corporation, Rolling Meadows, IL, USA Keywords Changes in achievement goals Perceived ability Self-efficacy Introduction Achievement goals (Ames and Archer 1987; Dweck 1986; Maehr and Nicholls 1980; Nicholls 1984) play an important role in determining students classroom attitudes, attributions, study strategies, and performance (e.g., Elliot et al. 1999; Harackiewicz et al. 1997; Meece et al. 1988). Originally two different types of achievement goals (i.e., mastery and performance goals) were identified that differ in terms of the criteria used to judge competence (Dweck 1986; Nicholls 1984). When individuals adopt mastery goals, they are concerned with developing their skills, learning, and mastering the task at hand. Feelings of competence derive from evidence of improvement, learning, or mastery. Thus, a self-referent standard is used to judge ability. In contrast, when individuals adopt performance goals, they are concerned with demonstrating that they are more competent than others and they derive feelings of competence from performing better than others (Nicholls 1984). In this case normative standards are used to judge ability. Thus, perceptions of competence are central to achievement goal theory. Classroom studies have demonstrated that the strength of endorsement of achievement goals can change across a school year or a semester (e.g., Fryer and Elliot 2007; Meece and Miller 2001; Seifert 1996; Senko and Harackiewicz 2005). Various factors are likely to influence these changes. One factor which has not been systematically investigated is changes in perceptions of competence. That is, the strength of endorsement of achievement goals may change based on changes in individuals confidence

2 192 Motiv Emot (2010) 34: that they can improve (mastery goals) or outperform others (performance goals). The present study investigated the relationship between changes in the endorsement of achievement goals and changes in perceptions of competence across a college semester. Two types of competence perceptions were examined: confidence in one s ability to learn the material and confidence about one s ability to outperform other students. Achievement goals 1 and competence assessments Achievement goals are concerned with the development and/or demonstration of competence and define the reasons for academic engagement (Nicholls 1984, 1989). An important outcome of achievement behaviors is feelings of competence. When individuals adopt mastery goals, they derive feelings of competence from improvement which signifies progress towards mastery. In contrast, individuals driven by performance goals are concerned with demonstrating competence in the normative sense, so feelings of competence derive from performing better than others. Hence, a crucial difference between mastery and performance goals concerns the conception of ability/competence that is employed to judge or evaluate one s competence (Elliot and McGregor 2001; Nicholls 1984, 1989). Nicholls (1984) proposed that when individuals adopt performance goals, their level of (normative) perceived ability, which he defined as indicating individuals evaluation of their ability relative to that of others (p. 334), will influence their behavior. As one s assessment of normative perceived ability declines, so does commitment to the goal of demonstrating superior competence. Nicholls and others (e.g., Miller et al. 1996) have referred to this construct as simply perceived ability. We will use the term normative perceived ability to highlight the fact that it involves a social comparison component. A few studies have measured normative perceived ability, including Duda and Nicholls (1992), Miller et al. (1996), and Greene and Miller (1996). The items on existing measures of normative perceived ability call for a coarse judgment of whether the individual s ability is better than most or worse than most (e.g., I am confident I can perform as well or better than others in this class, Compared with other students in this class my skills are weak ; from Miller et al. 1996). 1 Both Dweck (Dweck and Elliott 1983; Dweck 1986) and Nicholls (Maehr and Nicholls 1980; Nicholls 1984) view achievement goals as largely situational. However, they both recognized that the achievement goals adopted in a given situation can be partially a function of dispositional tendencies to favor one or more achievement goals. When achievement goals are viewed as dispositional tendencies they are referred to as orientations (see Nicholls 1989) and the items are written more generally. In the current study we focus on students goals in a specific situation, an introductory psychology course. Measures of normative perceived ability have been found to be positively related to both mastery and performance goals (Duda and Nicholls 1992; Miller et al. 1996) in crosssectional studies. According to Nicholls (1984), social comparison is irrelevant to individuals who endorse mastery goals and thus, normative perceived ability is not important in evaluating competence when mastery goals are adopted. Nicholls did not propose a specific measure of perceived competence for mastery goals. We propose that an appropriate measure of competence for mastery goals would focus on confidence that one could learn or master the skills involved. In researching measures that assess confidence in one s ability to learn and master tasks, the selfefficacy for learning items of the Motivated Strategies for Learning Questionnaire (MSLQ, Pintrich et al. 1991; example item: I m certain I can master the skills being taught in this class ) seem to assess this construct as does the academic efficacy scale from the Patterns of Adaptive Learning Survey (PALS, Midgley et al. 1996; example item: Even if the work is hard, I can learn it ). Each of these measures captures an individual s perception of the extent to which he or she can learn and improve and invokes a self-referent standard. It is important to note that in examining this construct we are focusing on self-efficacy for learning, not self-efficacy in general. According to Nicholls et al. (1989), when individuals adopt mastery goals, learning is an end in itself. Progress towards mastery should engender feelings of competence. However, when individuals adopt performance goals, learning is a means to the end of demonstrating superior competence/ability. That is, progress in mastering the necessary skills is one route to demonstrating superior competence; however, learning and improvement will not necessarily result in performing better than others. To illustrate, if a student who has a mastery goal focus works hard and finds her homework grades consequently go from Ds to Cs, she should experience feelings of competence. That is, she has adopted the self-referent conception of ability and therefore judges her ability as superior to what it was when she was getting Ds on her homework. However, if instead the student had been more focused on performance goals, she would not have derived feelings competence from the change in grades, even though learning had occurred. Rather, she would have been employing a normative standard of ability and it is unlikely she would interpret the improvement as evidence she can perform better than other students. On the other hand, if the student s learning and improvement resulted in homework grades of As, she would derive feelings of competence based on both types of standard (i.e., self-referent and normative). This distinction would suggest that while selfefficacy for learning is fundamental to both types of goals,

3 Motiv Emot (2010) 34: normative perceived ability is only relevant for individuals with performance goals. Researchers have used a variety of measures of perceptions of one s competence or expectancy in the literature. These measures have included normative perceived ability, self-efficacy for learning, self-efficacy measures for task performance, and general questions of how well one expects to do. There are at least three different types of criteria embodied in these measures. First there is the selfreferent standard that occurs in the measure of self-efficacy for learning (e.g., Wolters et al. 1996) which involves a comparison with a person s own past performance. Second, there is a normative standard concerning how one s ability compares to that of a comparison group (e.g., Miller et al. 1996). In this case the comparison is with the performance of others, which is not directly under one s control. Finally, there are more absolute standards (e.g., Elliot and Church 1997) such as task-based measures (e.g., How many problems can you solve? ) and general assessments of performance (e.g., How well do you expect to do on this task? ). Results from all of these measures are likely to be positively correlated at a given point in time. However, performance feedback may lead to different patterns of change in these measures across time. For example, if a student receives a grade of C on her first exam in a course, her chances of performing better than most others are clearly not great. However, she could still believe she could learn and improve for the next exam. In general, researchers have tended to view different types of competence perceptions as similar and typically focus on one measure. The current research will distinguish between the self-referent and normative standards to test our predictions of how changes in the relevant conception of ability should influence changes in achievement goals. Recent expansion of the achievement goal types More recently, researchers have distinguished between two types of performance goals, performance approach and performance avoidance (Elliot and Church 1997; Middleton and Midgley 1997; Skaalvik 1997; VandeWalle 1997), both of which are concerned with the normative definition of competence. Performance-approach goals orient the individual towards demonstrating superior competence whereas performance-avoidance goals involve a concern with avoiding a demonstration of normative incompetence. According to Elliot and Church (1997) the two types of achievement goals have different antecedents. Performanceapproach goals are fueled by achievement motivation and high competence perceptions coupled with fear of failure. In contrast, performance-avoidance goals are primarily a function of fear of failure and low competence perceptions. Thus, individuals who endorse performance-avoidance goals already evaluate their competence as low. Elliot and Church (1997) measured competence expectations for a course (i.e., how well students expected to perform) and found the predicted pattern of relationships a positive correlation with performance-approach goal endorsement and a negative correlation with endorsement of performance-avoidance goals. Skaalvik (1997) and Wolters et al. (1996) found similar patterns of relationships using a measure of self-efficacy for learning. In addition, mastery goals were positively related to self-efficacy for learning in each study. Although the distinction between performance-approach and performance-avoidance goals is not made in Nicholls (1984) work, his writing does refer to two different orientations of performance goals that seem to correspond to the performance-approach/performance-avoidance distinction. Nicholls (1984) predicted that when performance goals are important and performance difficulties are encountered, the individuals confidence in their ability to outperform others is likely to decline. He further suggests that doubts about one s normative perceived ability would eventually lead to the abandonment of the goal of demonstrating superior competence and a switch to the goal of avoiding a demonstration of incompetence. In effect, Nicholls described a process through which performanceapproach goals can change to performance-avoidance goals due to declines in one s assessment of normative perceived ability. In partial support of this prediction, Kumar and Jagacinski (2009) manipulated normative perceived ability for completing cognitive problems in a laboratory setting. Changes in participants normative perceived ability were related to changes in the endorsement of performanceapproach goals. Elliot and McGregor (2001) have also introduced a measure of mastery-avoidance goals which they define as a concern over avoiding self-referential incompetence (see also Elliot 1999; Pintrich 2000). Some possible manifestations of this goal include a fear of not learning as much as one could or trying not to forget or lose what one has already learned. This goal was not considered in the early development of achievement goal theory. Instead, Nicholls (1984; Maehr and Nicholls 1980) assumed that: The two conceptions of ability have in common the notion that task mastery is improved by effort or learning and that mastery is not normally lost (p. 329, 1984). Elliot (2005) has pointed out that mastery-avoidance goals are less prevalent in typical achievement situations than the other three goals. In fact they were endorsed less than the other goals in the original Elliot and McGregor (2001) studies. Masteryavoidance goals are similar to performance-avoidance goals in terms of antecedents, but have not been found to relate to classroom grades. Given the lower endorsement of mastery-avoidance goals and the fact that they were not

4 194 Motiv Emot (2010) 34: considered in Nicholls original theory, we make no predictions about them. Based on the distinction proposed by Nicholls (1984) regarding the different conceptions of ability employed to evaluate competence for mastery and performance goals, it follows that changes in the relevant competences perceptions should be related to changes in the endorsement of achievement goals. That is, changes in normative perceived ability are predicted to be related to changes in both types of performance goals but not to changes in mastery goals. Further, it also follows that self-efficacy for learning is a more fundamental competence perception, and changes in this construct are predicted to be related to changes in mastery, performance-approach and performance-avoidance goals. It is likely that these different types of competence assessments will be highly correlated, particularly at a single point in time; however, that relationship does not preclude them from having differential impact on changes in achievement goals. To the extent that changes in competence perceptions reflect changes in students confidence in their ability to develop their skills (mastery goal) or to demonstrate superior performance (performance-approach goal), we expect to see changes in the endorsement of those achievement goals. Because the two types of competence perceptions are expected to be highly correlated at any given point in time, this predicted differential pattern of relationships would be most apparent when examining changes across time in competence perceptions and achievement goals. We expect increases in self-efficacy for learning to be related to increases in approach goals and to decreases in performance-avoidance goals. We predict increases in normative perceived ability to be related to increases in performance-approach goals and decreases in performance-avoidance goals. Changes in achievement goals across time There are numerous studies illustrating changes in the strength of endorsement of achievement goals across the school year despite fairly high correlations of the measures of the same goals across time (e.g., Meece and Miller 2001; Chouinard and Roy 2008; Seifert 1996). That is, the mean level of endorsement of a goal may be significantly lower at Time 2 compared to Time 1 even though the two assessments of the goal are highly correlated. In fact, Meece and Miller (2001) reported larger changes in goal endorsement across the school year rather than between school years for elementary school children. Shim et al. (2008) found a similar pattern for adolescents. Bong (2005) examined changes in self-efficacy for learning and achievement goals for a sample of Korean high school students across an entire school year. In this study self-efficacy for learning was measured before and after major exams and was found to significantly fluctuate across time. Bong reported a general pattern of changes in self-efficacy for learning preceding changes in achievement goals. In particular, increases in self-efficacy consistently predicted increases in mastery goals and the relationship was observed across different classes (e.g., English, math). Senko and Harackiewicz (2005) examined changes in achievement goals for an introductory psychology class, finding fairly strong correlations (i.e.,.53.66) between beginning and end of semester measures of mastery, performance-approach, and performance-avoidance goals. Even so, when the mean levels of goal endorsement were examined, there were significant declines in mastery and performance-approach goals, and a significant increase in performance-avoidance goals. Additionally, end of semester goals were partially predicted by grades on exams earlier in the semester. Students who did well on the early exams tended to have higher mastery and performanceapproach goals at the end of the semester. Poor performance on the early exams was associated with higher performance-avoidance goals. This pattern is consistent with Nicholls (1984) prediction of performance-approach goals being dropped in favor of performance-avoidance goals as normative perceived ability declines. Senko and Harackiewicz (2005) investigated the impact of exam grades on changes in achievement goals. It would make sense that the impact of exam grades on goals is through their effect on perceptions of competence. In fact, Senko and Harackiewicz (2005) suggested that goals should fluctuate with changes in perceived competence, but competence perceptions were not measured following the exam feedback in their study. Their study examined the influence of actual test scores but not of perceptions of competence. Exam scores are expected to correlate with perceptions of competence, but the student s interpretation of the exam score may be more predictive than the exam score itself. Thus, to the extent that a low grade on an early exam leads students to doubt their abilities, both competence perceptions and mastery or performance-approach goals may decline. However, if students do not feel the low grade accurately reflects on their ability to learn or to perform better than others, there may be no change in competence perceptions or achievement goals. The current study examines the effect of an early exam grade on changes in normative perceived ability and selfefficacy for learning, and additionally how any changes in these competence perceptions relate to changes in the endorsement of achievement goals. We predict that any influence of exam grades on changes in achievement goals will be partially mediated by competence perceptions.

5 Motiv Emot (2010) 34: The current study In the current study, we examine the relationships of changes in both normative perceived ability and self-efficacy for learning to changes in achievement goals for college students enrolled in an introductory psychology class. In contrast to most prior studies, we examine the dynamic relationship between changes in competence perceptions (measured early in the term and after the first course exam) and changes in achievement goals across the semester. There have been two prior studies which have examined change in achievement goals for an introductory psychology class across a semester. Senko and Harackiewicz (2005) reported a decline in mastery goals and performance-approach goals and an increase in performance-avoidance goals. A similar pattern was reported by Fryer and Elliot (2007) although in their studies there were no significant changes in performance-approach goals. We will test for changes in the level of endorsement of the achievement goals and then examine to what extent statistically significant changes in achievement goals can be accounted for by changes in competence perceptions. We make the following predictions: Hypothesis 1: Changes in normative perceived ability will be positively related to changes in performanceapproach goals and negatively related to changes in performance-avoidance goals. We do not expect changes in normative perceived ability to relate to changes in mastery goals. Hypothesis 2: Changes in self-efficacy for learning will be positively related to changes in mastery and performance-approach goals and negatively related to changes in performance-avoidance goals. Hypothesis 3: Changes in both self-efficacy for learning and normative perceived ability will be related to the grade earned on the first exam. Hypothesis 4: Any influence of Exam 1 grades on changes in achievement goals will be partially mediated by changes in self-efficacy for learning and normative perceived ability. Finally, given that much research has focused on the prediction of grades and course interest using achievement goals (e.g., Elliot et al. 1999; Harackiewicz et al. 1997), we examined the extent to which changes in achievement goals might relate to students interest and performance in the course. That is, we examined the contribution of endof-semester achievement goals to the prediction of final course interest and final exam grades after accounting for initial achievement goals and SAT scores. Prior research (e.g., Elliot and Church 1997; Elliot and McGregor 2001; Harackiewicz et al. 1997) has generally found that performance-approach goals are consistent positive predictors of course grades, but they do not consistently relate to course interest. Performance-avoidance goals sometimes relate negatively to course grades and interest, but the relationships have not been consistent across studies. Finally, mastery goals are typically not predictive of grades but relate strongly to course interest. We will explore the influence of achievement goals measured early in the term on final exam grades and course interest. We will then see if the achievement goals measured at the end of the semester make an additional contribution to the prediction of final exam grades and course interest. Method Participants One hundred sixty-two introductory psychology students (41% men) participated in the study in partial fulfillment of a course requirement. The vast majority of the students were White (89%). The median age was 19 with 53% of the students being first-year students in their first semester of college. The course fulfills a requirement for most majors, so a variety of students enroll in the course. The participants in this study represented 13 different colleges within the university. Students were enrolled in six different sections of the course, each taught in a large lecture format with multiple choice exams. Instructors were not aware of which students participated in the study and had no access to the data. Typical enrollments are around 400 per section, limiting the opportunity for in-class interaction with the professor. Three of the sections determined grades based solely on multiple choice exams. Two additional sections based 90% of the grade on multiple choice exams and 10% on surprise attendance quizzes based on the lecture that day. The last section included homework and labs and only attributed 51% of the grade to the multiple choice exams. All sections used cutoff scores to determine final grades which were not based on a curve. Four students did not complete Time 2 and Time 3 surveys, three of the students dropped the course, and SAT scores were not available for six students. Procedures Students came to our lab to complete the first survey during weeks 4 6 of the fall semester. This survey (Time 1) contained the initial assessments of achievement goals, self-efficacy for learning, and normative perceived ability. At this meeting the students signed consent forms and gave us permission to obtain their grades from their introductory psychology instructors and their SAT scores from the registrar. We collected SAT scores as a control variable

6 196 Motiv Emot (2010) 34: and as an indicator of ability. Students also provided us with their addresses so we could notify them about the next two surveys which were completed electronically. The second survey (Time 2), which was completed in October (weeks 9 10 of the semester), contained the second assessment of self-efficacy for learning and normative perceived ability. The second survey occurred after the first course exam. Finally, the last survey (Time 3) was completed at the end of November (weeks of the semester) and again assessed achievement goals for the course as well as intrinsic interest in the course. The separation of the second assessment of competence perceptions (Time 2) from the second assessment of the achievement goals (Time 3) was intended to reduce the effect of common method bias. Each survey included several measures that are not relevant to the current research questions and therefore will not be discussed. Measures All of the measures attained adequate internal consistency reliability, which is reported in Table 1. Achievement goals were assessed at the beginning (Time 1) and end (Time 3) of the semester using the three-item scales 2 developed by Elliot and McGregor (2001). Example items include: I want to learn as much as possible from this class for the mastery goal; My goal in this class is to get a better grade than most of the students for the performance-approach goal; and I just want to avoid doing poorly in this class for the performance-avoidance goal. A 7-point response scale was used with the following anchors: 1 = not at all true of me and 7 = very true of me. In order to capture the construct self-efficacy for learning, we selected the learning items from the selfefficacy for learning and performance scale of the Motivated Strategies for Learning Questionnaire (MSLQ; Pintrich et al. 1991). The eight-item scale was developed for college students and the five items we used focus on learning and mastery of course content consistent with mastery goals. Some example items include: I m confident I can understand the basic concepts taught in this course, I m certain I can understand the most difficult material presented in the readings in this course, and I m certain I can master the skills being taught in this class. 2 We also measured mastery-avoidance goals. The average level of endorsement of these goals was below the scale midpoint (Time 1 M = 3.6, Time 3 M = 3.4), there was not a significant change in mastery avoidance across the semester, and these goals did not predict any outcomes examined. Consequently we decided to omit a discussion of the null results of mastery-avoidance goals as we did not have any formal hypotheses about them. These items were evaluated on the same 7-point response scale as the achievement goals. We constructed a new normative perceived ability scale which would allow for greater differentiation of responses than currently available scales. Items on existing scales simply distinguish performing better than most from performing worse than most. The items on the new scale ask students to evaluate the likelihood that they could perform better than a specified percentage of the other students in the course. The first item was: Thinking about all the students taking Introductory Psychology, how likely is it that your overall course performance could be better than 10% of them? An 11-point response scale was used with the following anchors: 0 = definitely could not ; 5 = 50/50 chance I could ; and 10 = definitely could. Other items on the scale were identical except for the percentage of other students mentioned. There were 10 items with the percentage of other students mentioned incrementing by 10 (e.g., could be better than 20, 30%), except for the last percentage which was 99%. The 10 responses were averaged to create a single normative perceived ability score. As the percentage of students one could perform better than increases, the likelihood of doing so should decrease monotonically. Twelve students misinterpreted the response scale (i.e., had monotonically increasing responses) and were thus eliminated from the analyses. The final sample size was 142. We also used four items from Miller et al. s (1996) normative perceived ability scale in the Time 1 survey. Example items from this scale include: Compared to other student in this class, my skills are weak ; I am confident I can perform as well or better than others in this class. This less detailed measure of normative perceived ability had a coefficient alpha of.75 and correlated.61 with the new normative perceived ability measure administered as part of the Time 1 survey, supporting the validity of the new measure. Our analyses will use the new measure because it results in a more differentiated estimate of normative perceived ability. The Time 3 survey included a measure of intrinsic interest in the class. Items were taken from Harackiewicz et al. (2000). The scale consisted of 9 items (e.g., I think what we are learning in this class is interesting ) evaluated on a 1 = strongly disagree to 7 = strongly agree scale. Results Table 1 presents descriptive statistics, internal consistency measures, and the correlations among the major variables. The achievement goals were relatively stable across time with correlations ranging from.51 to.64. Self-efficacy for learning and normative perceived ability also demonstrated

7 Motiv Emot (2010) 34: Table 1 Descriptive statistics, internal consistency reliability, and correlations among the primary variables Measure (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (1) SAT (2) T1 Perf. Approach (3) T1 Perf. -.32** Avoidance (4) T1 Mastery **.83 (5) T3 Perf. Approach.19*.51** (6) T3 Perf. Avoidance -.21**.08.51** *.76 (7) T3 Mastery *.64**.23** (8) T1 Self-Eff. for.46** **.31**.27** -.25** learning (9) T1 N. Perc.ability.45**.18* -.23**.11.30** -.30**.03.60**.94 (10) T2 Self-Eff. for.55** **.20*.36** -.21*.15.72**.59**.91 learning (11) T2 N. Perc..46*.17* -.25**.22**.42** -.19*.12.58**.72**.70**.96 Ability (12) Exam 1 Grade.49** ** -.18*.16.41**.43**.63**.63** (13) T3 Course Interest ** ** **.22**.22**.94 (14) Final Exam Grade.41** **.26** *.25**.15.40**.32**.49**.17* Means Standard Deviation Note: T1, T2, and T3 denote Time 1, Time 2, and Time 3 respectively; Perf. = Performance; Self-Eff. = Self-Efficacy; N. Perc. = Normative Perceived. Numbers on the diagonal are reliability coefficients * p \.05; ** p \.01 stability with a correlation across administrations of.72 for both. Competence perceptions and exam grades were significantly correlated with SAT scores as expected (see Table 1). To determine whether there were significant differences among the six sections of the course on the major variables, we conducted one-way analyses of variance, following up statistically significant effects with Tukey pairwise comparison tests. Three statistically significant differences were found, each involving the course section which included homework and labs. The section with homework and labs scored higher than one other section on Exam 1 and higher than another section on Time 3 mastery goals. Students in the homework/labs section also had higher Time 2 normative perceived ability scores compared to two other sections. When the homework/labs section, which included 14 students, was omitted, no significant differences among the remaining sections were found. To deal with these differences, we created five dummy variables through contrast coding to distinguish the sections and entered these variables as controls in all regression analyses. We also reanalyzed the data leaving out the discrepant homework/lab section and the dummy variables. The pattern of results was quite similar across these analyses, so we will present the data with all students included. However, we will discuss any differences that occurred in the analyses when the one section was removed. Changes in achievement goals and competence perceptions We next examined the extent to which achievement goals changed across the semester (See Table 1 for means.) Despite relatively strong correlations across time for the achievement goals, there were significant changes in the mean levels of endorsement of the goals. There was a significant increase in performance-approach goals (t(141) = 4.91, p \.001, d =.42) and a decline in mastery goals (t(141) =-3.34, p \.001, d =-.28) across the semester. There was not a statistically significant change in performance-avoidance goals, t(141) = 1.31, p [.05, d =.11. Given that mastery and performanceapproach goals changed across the semester, we will investigate the extent to which these changes are related to changes in competence perceptions. Analyses will also be conducted on the performance-avoidance goals; however,

8 198 Motiv Emot (2010) 34: given that there is not a reliable change across time, it will be difficult to predict this change. First we examine changes in competence perceptions. Interestingly there was not a statistically significant change in self-efficacy for learning from Time 1 to Time 2, t(141) = 1.58, p [.05, d =.13. However, the measure of normative perceived ability showed a significant decline, t(141) =-4.28, p \.001, d =-.36. The difference in this pattern suggests that self-efficacy for learning and normative perceived ability do assess somewhat different aspects of competence perceptions. Predicting change in achievement goals We used hierarchical regression to test the significance of predictors of change in achievement goals across the semester. We used the Time 3 measure of the goal as the dependent variable and first included the Time 1 measure of the goal as a predictor. This procedure effectively allows us to examine predictors of change in the achievement goal. We also added the five dummy variables representing the different course sections in the first block. In the second block we added the change in self-efficacy for learning and finally in the third block change in normative perceived ability. We also checked to see how much variance would be accounted for by change in normative perceived ability if it were added in block 2 alone. Table 2 summarizes the results of these analyses. To form a predictor variable to represent the change in competence perceptions, we subtracted the Time 1 score from the Time 2 score. Thus, positive scores on the change variable represent an increase in competence perceptions and negative scores represent a decline. Difference scores have been criticized in the literature in part because they are typically less reliable than the scores that make them up. However, Rogosa (1995) has pointed out that the difference score is an unbiased estimate of the true difference. We calculated the reliabilities of our difference scores. In fact they were lower than the reliabilities of the individual scores making up each difference, but they were marginally acceptable (.68 for selfefficacy for learning and.84 for normative perceived ability). Hypothesis 1 predicted that changes in normative perceived ability would be related to changes in performanceapproach and performance-avoidance goals, but not to changes in mastery goals. As can be seen in Table 2, when normative perceived ability was added in Block 2 it did account for a significant amount of variance in the performance goals, but not in the mastery goals. The pattern is generally consistent with our prediction except that increases in normative perceived ability were associated with increases in performance avoidance goals, whereas we had predicted a negative relationship. Hypothesis 2 predicted that changes in self-efficacy for learning would be positively related to changes in mastery and performance-approach goals, but negatively related to changes in performance-avoidance goals. When self-efficacy for learning was added in Block 2, it did account for a significant amount of variance in the changes in mastery and performance-approach goals consistent with our Table 2 Standardized regression coefficients and change in R 2 for predicting Time 3 mastery, performance-approach and performanceavoidance goals from changes in self-efficacy for learning and normative perceived ability controlling for Time 1 goal endorsement and section Predictors Time 3 Mastery goal Time 3 Performance-approach goal Time 3 Performance-avoidance goal b DR 2 b DR 2 b DR 2 Block 1.440***.246***.321*** T1 Goal; Course section a.611***.494***.499*** Block 2.032**.035*.000 T1 Goal; Course section a.637***.520***.499*** Change in self-efficacy for learning.182**.191*.009 Block **.020* T1 Goal; Course section a.650***.508***.521*** Change in self-efficacy for learning.199** Change in normative perceived ability **.155* Total R 2.474***.325***.342*** Block 2 with normative perceived ability ***.020* T1 Goal; Course section a.609***.494***.518*** Change in normative perceived ability ***.144* a Five dummy variables represented course section. Regression coefficients for these variables are omitted T1 denotes Time 1 * p \.05, ** p \.01, *** p \.001

9 Motiv Emot (2010) 34: prediction. However, change in self-efficacy for learning had no relationship with changes in performance-avoidance goals. It is also notable that when changes in both self-efficacy for learning and normative perceived ability were in the prediction equation, self-efficacy for learning was no longer statistically significant in predicting changes in performance-approach goals. This suggests that changes in normative perceived ability have a stronger relationship to changes in performance-approach goals than do changes in self-efficacy for learning. Because the regression analyses involved the observed variables which were measured with error, we decided to conduct a latent difference score analysis using structural equation modeling which could estimate the relationships between the change variables controlling for error. A structural equation model which specified five separate latent difference score models (see McArdle 2001) was estimated using Mplus Version The latent difference score models estimated change in competence perceptions (self-efficacy for learning and normative perceived ability) from Time 1 to Time 2, as well as differences in each of the achievement goals (mastery, performance-approach and performance-avoidance) from Time 1 to Time 3. Latent difference score models address the short-comings commonly associated with using difference scores between observed variables (see Burr and Nesselroade 1990). Once specified, latent variables which modeled differences were used as predictors and outcomes in order to assess how changes in both types of competence perceptions related to changes in achievement goals. The results were consistent with the original regression analyses. Changes in normative perceived ability were positively related to changes in performance-approach goals (b =.215, p \.01), were marginally positively related to changes in performanceavoidance goals (b =.134, p \.10), and were not significantly related to changes in mastery goals (b =-.057, p [.10). Changes in self-efficacy for learning were positively related to changes in performance-approach goals (b =.262, p \.05) and changes in mastery goals (b =.336, p \.01), but were unrelated to changes in performance-avoidance goals (b =-.040, p [.10). Changes in competence perceptions as a function of exam 1 grades We next examined how much influence the Exam 1 grades had on changes in competence perceptions. Hypothesis 3 predicted that changes in both types of competence perceptions would be influenced by Exam 1 grades. We conducted hierarchical regression to see how much variance in the Time 2 competence perceptions could be accounted for by the Exam 1 grades after controlling for the Time 1 competence perceptions, SAT scores and course section. The SAT scores were included as a measure of ability. For self-efficacy for learning, Exam 1 grades accounted for an additional 8.4% of the variance in change, b =.371, p \.001 after SAT scores and course section were controlled. The regression coefficient for SAT scores was no longer statistically significant with Exam 1 grades in the prediction equation (total R 2 =.68). A similar pattern was observed for change in normative perceived ability. The Exam 1 grades accounted for an additional 6.6% of the variance in the change in normative perceived ability, b =.329, p \.001, after accounting for SAT scores and course section (total R 2 =.67). The addition of the Exam 1 grades made the SAT scores no longer statistically significant in predicting change in normative perceived ability. The results of these analyses provide support for Hypothesis 3. Feedback from Exam 1 had an impact on changes in both self-efficacy for learning and normative perceived ability. Competence perceptions as mediators of the influence of exam 1 grades on changes in achievement goals Hypothesis 4 predicted that any impact of Exam 1 grades on changes in achievement goals would be partially mediated by competence perceptions. In order to test this hypothesis, we first determined if the Exam 1 grades had a direct effect on changes in achievement goals. We conducted hierarchical regressions in which the Time 3 goals were predicted by the Time 1 goals and course section. We then added the Exam 1 grades to the prediction equation. The Exam 1 grades did not account for a significant percentage of variance in changes in mastery goals or performance-avoidance goals. However, Exam 1 grades did account for 12.5% of the variance in change in performance-approach goals. Therefore we conducted additional analyses to see if changes in perceptions of competence mediated the effect of the Exam 1 grades on changes in performance-approach goals. Our first assessment of competence perceptions occurred early in the semester and may have contributed to Exam 1 grades. Therefore, we controlled for the Time 1 competence perceptions and examined whether or not the Time 2 competence perceptions mediated the effect of Exam 1 grades on changes in performance-approach goals. The results of these analyses are displayed in Table 3. Using hierarchical regression, we predicted Time 3 performance-approach goals with Time 1 performanceapproach goals, course section, Time 1 self-efficacy for learning and Exam 1 grades. We then added in Time 2 selfefficacy for learning to see if it would account for additional variance and reduce the influence of the Exam 1

10 200 Motiv Emot (2010) 34: Table 3 Standardized regression coefficients and change in R 2 for predicting change in performance-approach goals from exam 1 grades, selfefficacy for learning and normative perceived ability Predictors Time 3 Performanceapproach goal Predictors Time 3 Performanceapproach goal Self-efficacy analysis b DR 2 Perceived ability analysis b DR 2 Block 1.390*** Block 1.393*** T1 Performance approach; Course section a.469*** T1 Performance approach; Course section a.463*** T1 Self-efficacy for learning.057 T1 Normative perceived ability.088 Exam 1.351*** Exam 1.338*** Block Block 2.025* T1 Performance approach; Course section a.487*** T1 Performance approach; Course section a.459*** T1 Self-efficacy for learning T1 Normative perceived ability Exam 1.254** Exam 1.239** T2 Self-efficacy for learning.228 T2 Normative perceived ability.268* Total R 2.406***.418*** a Five dummy variables represented course section. Regression coefficients for these variables are omitted T1 and T2 denote Time 1 and Time 2 respectively * p \.05, ** p \.01, *** p \.001 grades. Adding Time 2 self-efficacy for learning accounted for an additional 1.6% of the variance which was not statistically significant (p =.06). The regression coefficient for Exam 1 grades was somewhat reduced, however a Sobel test for mediation was not statistically significant (Z = 1.85, p \.07). 3 A similar analysis was conducted to see if the Time 2 normative perceived ability mediated the effect of Exam 1 grades on changes in performance-approach goals. As can be seen in Table 3, the addition of the Time 2 normative perceived ability measure accounted for an additional 2.5% of the variance which was statistically significant and the regression coefficient for Exam 1 grades was reduced from b =.338, p \.001 to b =.239, p \.01, suggesting partial mediation. In addition, the Sobel test for mediation was statistically significant (Z = 2.24, p \.05). Thus, the influence of Exam 1 grades on changes in performance-approach goals was partially mediated by normative perceived ability. Exam 1 grades did not have a direct effect on change in mastery goals or performanceavoidance goals. 3 This was the only analysis that led to different results when the section with homework and labs was removed. When the analysis was conducted again omitting the section with homework/labs and the dummy variables for section, the Time 2 self-efficacy for learning account for an additional 2.8% of the variance which was statistically significant. In addition the regression coefficient for Exam 1 grades was reduced from b =.321, p \.001 to b =.206, p \.05, suggesting partial mediation. Furthermore, the Sobel test for mediation was statistically significant (Z = 2.01, p \.05). Changes in achievement goals and course interest and performance Finally, we examined the extent to which the changes in achievement goals related to final course interest and the final exam grades. We predicted Time 3 course interest with the Time 1 goals, course section, and SAT scores in the first block. Then we added Time 3 goals in the second block. The results of these analyses are displayed in Table 4. For the analysis of course interest, the first block accounted for 40% of the variance with mastery (b =.546, p \.001) and performance-approach goals (b =-.210, p \.01) having significant regression coefficients. When the Time 3 goals were added in block 2, they accounted for an additional 11% of the variance. However, only Time 3 mastery goals had a statistically significant regression coefficient (b =.371, p \.001), suggesting that increases in mastery goals were associated with greater course interest. Both Time 1 mastery and performance-approach goals were still statistically significant predictors of course interest with the Time 3 goals in the equation. We also examined the impact of the Time 3 goals on the final exam grades. The first block accounted for 24% of the variance with significant coefficients for SAT scores (b =.412, p \.001) and mastery goals (b =.217, p \.05). The addition of the Time 3 goals accounted for an additional 4% of the variance. Time 3 performanceapproach goals significantly predicted final exam grades (b =.202, p \.05), but Time 1 mastery goals were no longer statistically significant (b =.176, p [.09). This suggests that the increase in performance-approach goals was related to better performance on the final exam.

11 Motiv Emot (2010) 34: Table 4 Standardized regression coefficients and change in R 2 for predicting Time 3 course interest and final exam grades from Time 1 and Time 3 achievement goals controlling for SAT scores and course section Predictors Time 3 course interest Final exam grade b DR 2 b DR 2 Block 1.398***.241*** SAT Math? Verbal; Course section a *** T1 Performance-approach goals -.210**.039 T1 Performance-avoidance goals T1 Mastery goals.546***.217* Block 2.109***.043 SAT Math? Verbal; Course section a *** T1 Performance-approach goals -.273*** T1 Performance-avoidance goals T1 Mastery goals.322***.176 T3 Performance-approach goals * T3 Performance-avoidance goals T3 Mastery goals.371***.067 Total R 2.507***.284*** a Five dummy variables represented course section. Regression coefficients for these variables are omitted p \.06 * p \.05, ** p \.01, *** p \.001 Discussion In this study we examined naturally occurring dynamic changes in achievement goals and competence perceptions. Building on Nicholls (1984) contention that mastery and performance achievement goals involve different standards for judging competence, we reasoned that different types of competence perceptions would be most important for judging the likelihood of attaining the achievement goals. Nicholls had suggested that normative perceived ability would be most relevant to performance goals and not for mastery goals. However, he did not propose a specific competence perception which would influence commitment to mastery goals. We propose that a relevant competence perception for mastery goals is self-efficacy for learning. We expected that variation in competence perceptions would be related to changes in the strength of endorsement of achievement goals. That is, if one s normative perceived ability increases, we should also see an increase in commitment to performance-approach goals. If one s self-efficacy for learning declines, we might also observe a decline in commitment to mastery goals. Basically, we are proposing that changes in the two types of competence perceptions have implications for the likelihood of goal achievement, and consequently, should be related to changes in commitment to the relevant achievement goals. The results of the study are generally consistent with our predictions. Changes in normative perceived ability were related to changes in performance goals but not to changes in mastery goals. Changes in selfefficacy for learning were related to changes in mastery and performance-approach goals, but not to performanceavoidance goals. The pattern of results for performance-avoidance goals was not consistent with predictions in that increases in normative perceived ability were associated with increases in performance-avoidances goals and changes in self-efficacy for learning were not related to changes in performance-avoidance goals. However, there was not a statistically significant change in performance-avoidance goals across the semester so finding predictors of that change would be difficult and perhaps unreliable. Other studies of changes in achievement goals across the semester of a college course have noted increases in performance-avoidance goals (e.g., Fryer and Elliot 2007; Senko and Harackiewicz 2005). The fact that we did not see an increase in performance-avoidance goals may reflect the grading policies and/or classroom climate. The students in the Senko and Harackiewicz (2005) study were graded on a curve. None of our instructors graded on a curve and in fact, the average grades were around a B suggesting the course was not too difficult for those participating in this study. When instructors grade on a curve, a certain percentage of the students will definitely get Ds and Fs. This type of policy calls attention to normative standards and can contribute to a perception of harsh evaluation which tends to foster performance-avoidance goals (see Church et al. 2001). This also raises the issue of the importance of context in field studies. If a classroom is particularly egoinvolving or task-involving, the context may influence