Predicting Roles of Achievement Goals in Students' Self-Regulated Learning

Friday, March 16, 2012
Poster Area 1 (Foyer Outside Exhibit Hall C) (Convention Center)
Xiaoxia Su, Ping Xiang, Ron E. McBride and Jaeyoung Yang, Texas A&M University, College Station, TX

Background/Purpose Self-regulated learning (SRL) and achievement goals are both critical to student achievement in academic and physical education settings. Few studies have simultaneously explored both SRL and achievement goals, and these studies used regression analysis only and results were mixed. The purpose of the current study is to clarify the predictive roles of achievement goals (mastery-approach, mastery-avoidance, performance-approach, and performance-avoidance) in SRL using Structural Equation Modeling (SEM).

Method Participants were 361 students (155 males; M age = 19.98 years, SD = 1.71; 74.0% Caucasian) enrolled in physical activity classes at a large southern university. Participants completed two well-established questionnaires assessing achievement goals and SRL during their regularly scheduled physical activity classes.

Analysis/Results SEM analysis following a two-step modeling process (Kline, 2011) examined the relationship between achievement goals and SRL. The final model showed a good fit to the data: Chi-Square=134.844, DF=67, CMIN/DF=2.01, CFI=.966, TLI=.954, RMSEA=.053. Only the mastery approach goals appeared to be a significant predictor of autonomous regulation.

Conclusions That mastery approach goals were predictive of students' autonomous regulation in this study suggests students who endorsed mastery approach goals had higher degree of self-regulated learning than students who did not endorse these goals. This finding supports the view that mastery approach goals were more adaptive for learning. To enhance students' self-regulated learning, we recommend that instructors structure the learning environment that supports a mastery approach to learning.

Handouts
  • Predicting Roles of Achievement Goals in Students' Self-Regulated Learning.doc (73.5 kB)