Latent Profiles of Online Self-Regulated Learning: Relationships with Predicted and Final Course Grades

  • Diana Mindrila University of West Georgia
  • Li Cao University of West Georgia
Keywords: online self-regulated learning, latent profile analysis, person-centered approach, variable-centered approach, higher education


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.


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How to Cite
Mindrila, D., & Cao, L. (2022). Latent Profiles of Online Self-Regulated Learning: Relationships with Predicted and Final Course Grades. The International Review of Research in Open and Distributed Learning, 23(3), 212-239.
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