Résumés
Abstract
This study used a combined person- and variable-centered approach to identify self-regulated online learning latent profiles and examine their relationships with the predicted and earned course grades. College students (N=177) at a Southeastern U.S. university responded to the Online Self-Regulated Learning Questionnaire. Exploratory structural equation modeling revealed four self-regulation factors: goal setting, environment management, peer help-seeking, and task strategies. Latent profile analysis yielded four latent profiles: Below Average Self-Regulation (BASR), Average Self-Regulation (ASR), Above Average Self-Regulation (AASR), and Low Peer Help-Seeking (LPHS). Compared with the AASR group, when students anticipated obtaining a higher course grade, they were less likely to engage in peer help-seeking and task strategies and more likely to adopt the LPHS self-regulation profile. Relating to LPHS, membership to all other groups predicted significantly lower course grades. AASR and LPHS predicted their performance most accurately, with non-significant differences between the predicted and the final course grades.
Keywords:
- online self-regulated learning,
- latent profile analysis,
- person-centered approach,
- variable-centered approach,
- higher education
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