Secondary students’ online self-regulated learning during flipped learning: A latent profile analysis

Abstract

Flipped learning (FL) makes greater use of students' self-regulated learning (SRL) skills when they regulate their online learning behavior. Previous research has shown the value of SRL support during FL to enhance students' SRL and learning outcomes. However, as previous studies have indicated that SRL behavior varies, should SRL support be tailored to these differences in SRL? We applied latent profile analysis to identify subgroups in 150 eighth-graders during FL. We used practically relevant online behavioral data to represent students’ online SRL activities, which we gathered unobtrusively in an ecologically valid secondary educational classroom setting. We found five distinct SRL profiles from low completion and no activity to full completion and very high activity. In addition, students in the profile who showed low SRL activity achieved significantly worse learning outcomes than students in the three profiles with higher SRL activity. Finally, we explored whether SRL activity profile membership can be explained by student characteristics (i.e., self-reported SRL, motivation, and prior knowledge). None of the student-level variables predicted profile membership, but our approach offers leads for future research to further investigate the potential of tailored SRL support.