The effects of different metacognitive patterns on students' self-regulated learning in blended learning

Self-regulated learning has significant importance in blended learning, necessitating an exploration into the effects of metacognition on SRL. Furthermore, SRL exhibits interdependence, thus highlighting the urgent need for research that can capture the temporal processes of SRL in multi-task activities during blended learning. Over 18 weeks, 44 students participated in three SRL tasks designed for blended learning. Students completed a questionnaire assessing their metacognitive awareness at the end of the course. A two-step cluster analysis was employed to explore different metacognitive patterns among students: high metacognitive knowledge and regulation students and low metacognitive knowledge and regulation students. Furthermore, data from student's learning diaries were collected and coded based on the SRL model specific to blended learning. Epistemic Network Analysis, a computer-assisted learning analysis method, was employed to investigate the SRL process of students with different metacognitive patterns in various tasks of blended learning. First, the findings indicate that both types of students strive for performance achievement; however, students with high metacognitive knowledge and regulation primarily employ task strategies, while those with low metacognitive knowledge and regulation focus on time management. Moreover, a detailed centroid analysis conducted for each task revealed that students with high metacognitive knowledge and regulation initiate their SRL process in computer-assisted blended learning with self-efficacy and conclude it with goal setting. Conversely, students with low metacognitive knowledge and regulation commence their SRL process with self-efficacy and conclude it by employing strategies for self-evaluation. Finally, implications, limitations, and future research directions are discussed.