A Comparison of General v. Specific Measures of Achievement Goal Orientation Lisa Baranik, Kenneth Barron, Sara Finney, and Donna Sundre Motivation Research.

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A Comparison of General v. Specific Measures of Achievement Goal Orientation Lisa Baranik, Kenneth Barron, Sara Finney, and Donna Sundre Motivation Research Institute, James Madison University Background The Current Study Results The purpose of the current study was to address the lack of research comparing and contrasting the use of general v. specific measures of goals, and to report the results of two studies varying slightly in methodology. To evaluate how similar or variable students’ specific goals for one particular class were to their general goals for the semester, we conducted a series of correlations and dependent t-tests in each study. To determine which goal measures (specific or general) have better criterion-related validity in predicting specific or general outcomes, we conducted a series of regression analyses in each study. For example: Recently Elliot and McGregor (2001) proposed a 2 x 2 model of goal orientation: Achievement Goal Theory has emerged as an important framework for understanding student motivation, however the specificity level at which achievement goals should be assessed is an important measurement issue to resolve. The current research compared specific vs. general measures of achievement goals for a 2 x 2 model of goal orientation. Matching the specificity between achievement goals and outcomes may be an important consideration for goal researchers when trying to better understand when goals have been (or have not been) related to important educational outcomes. Abstract Method Study college-aged students participated. The majority of the sample was White and female. At the beginning of the semester, students completed a general measure of achievement goals using a general version of the Achievement Goal Questionnaire (AGQ). Then, one month later, students completed a specific measure of the AGQ for a particular class. Upon completion of the semester students’ specific grade for their one particular class and overall GPA for all their classes were collected. Study college-aged students participated. The majority of the sample was White and female. One month into the semester, students completed both a general and specific version of the AGQ simultaneously. Later in the semester, students completed a measure of interest in their specific course as well as a measure of general interest in all of their courses. Again, specific grade and overall GPA were collected. Researchers (Elliot & McGregor, 2001; Finney, Pieper, & Barron, 2004) have found the 2 x 2 model to fit data in a general academic context (e.g., “My goal this semester is to learn as much as I can in the classes that I’m taking”) and in a specific academic context (e.g., “My goal in this class is to learn as much as I can”). Although a call for measuring goals at different levels of specificity has been made (VandeWalle, 1997), the merits of using general v. specific measures have not been investigated. Researchers (Bandura, 1986; DeVellis, 2003; Pajares, 1996 ) have suggested matching the situational specificity level of a predictor variable with the situational specificity level of a criterion variable may improve criterion validity. For example, using specific goals (e.g., “my goal in this class…”) to predict specific outcome variables (e.g., course grade) may explain more variance than using general goals (e.g., “my goal this semester…”) to predict specific outcomes and vice versa. All correlations from Study 1 (shown in top diagonal) suggested that general and specific goals were distinct, yet related. In Study 2 (shown in bottom diagonal), Mastery-Approach and Mastery-Avoidance appeared to be distinct yet related, as well. However, Performance-Approach and Performance-Avoidance goals may not be as distinct. Differential magnitudes of correlations across Study 1 and Study 2 may reflect the timing of when measures were assessed. Specifically, goal orientations in Study 1 (when specific and general goals were measured one month apart) were not as highly correlated as goal orientations in Study 2 (when specific and general goals were measured at the same time). Note: G represents a general goal and S represents a specific goal. MAP- Mastery-Approach, MAV- Mastery- Avoidance, PAP- Performance-Approach, PAV- Performance-Avoidance. G Grade was measured with semester GPA and S Grade was measured with course grade. G Interest was a measure of general interest in classes. S Interest was a measure of specific interest in a particular class. Table 3. Average goal adoption depending on specificity of measurement. Goals were assessed on a 1 (not at all) to 7 (very true of me) response scale Study 1 results using dependent t-tests indicated that all four general goal orientations were significantly higher than specific goal orientations. Study 2 replicated this pattern with general Mastery-Approach and Mastery-Avoidance goals higher than their specific measurements. However, Performance-Approach and Performance-Avoidance goals were not significantly different from one another at the general v. specific level. Study 1 Study 2 Table 4. Average goal adoption depending on specificity of measurement. Goals were assessed on a 1 (not at all) to 7 (very true of me) response scale Specific Mastery-Approach Specific Mastery-Avoid Specific Performance-Approach Specific Performance-Avoid Specific Course Grade General Mastery-Approach General Mastery-Avoid General Performance-Approach General Performance-Avoid Specific Course Grade Table 5: Regression Results Using General and Specific Interest as Criterion Variables Results from the four regression analyses indicated that specific goals were a much better predictor of specific interest in psychology than general goals. In addition, general goals were a better predictor of general goals in psychology than specific goals. Study 1Study 2 The four regression analyses conducted in Study 1 did not show higher R 2 values when matching specific goals with specific course grades than when using general goals The four regression analyses conducted in Study 2 show that matching specific goals with specific course grades did result in higher values than when using general goals. However, it must be noted that the R 2 value was minimal. Study 2 Conclusion and Implications Correlations and t-tests offered some support that general v. specific measures of the same goal orientation are distinct constructs. Across Study 1 and Study 2, distinctiveness was clear for Mastery-Approach and Mastery- Avoidance goals. However, across the two studies, the distinctiveness between general v. specific Performance-Approach and Performance- Avoidance goals was less clear. This lack of replication could be due to other important measurement issues (e.g., the time measures were assessed), or reflect the fact that performance orientations are more stable and generalizable across multiple settings. In addition, results indicated that specificity does affect R 2 values. In both Study 1 and Study 2, using specific goals to predict specific grades resulted in slightly higher R 2 values than when using general goals. General grades, however, were better predicted by specific goals, not general goals, across both studies. In Study 2 when interest outcomes were also collected, using specific goals to predict specific interest resulted in higher R 2 values than when using general goals. Matching general goals with general interest also resulted in slightly higher R 2 values than using specific goals to predict general interest. In sum, matching specificity to improve R 2 values may depend on the outcome variable that is being investigated. Future studies should investigate how specificity of measurement affects R 2 values on variables other than grades and interest. Table 1. Definitions of the 4 goal orientations proposed in the 2 x 2 model of goal orientation Table 2. Zero-order correlations from Study 1 (top diagonal) and Study 2 (bottom diagonal). Table 5: Regression Results Using GPA / Course Grades as Criterion Variables