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

IF 8.9 1区 教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Xingyu Geng, Yu-Sheng Su
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引用次数: 0

Abstract

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.
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来源期刊
Computers & Education
Computers & Education 工程技术-计算机:跨学科应用
CiteScore
27.10
自引率
5.80%
发文量
204
审稿时长
42 days
期刊介绍: Computers & Education seeks to advance understanding of how digital technology can improve education by publishing high-quality research that expands both theory and practice. The journal welcomes research papers exploring the pedagogical applications of digital technology, with a focus broad enough to appeal to the wider education community.
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