A Review of Learners' Self-Regulated Learning Behavior Analysis Using Log-Data Traces

• المؤلفون الرئيسيون: Damayanti, Anindya, Kusumawardani, Sri Suning, Wibirama, Sunu
• التنسيق: Conference or Workshop Item PeerReviewed
• اللغة: English
• منشور في: Institute of Electrical and Electronics Engineers Inc. 2023
• الموضوعات: Electrical and Electronic Engineering not elsewhere classified; Electrical and Electronic Engineering; Engineering
• الوصول للمادة أونلاين: https://repository.ugm.ac.id/285839/1/A%20Review%20of%20Learners%20Self-Regulated.pdf; https://repository.ugm.ac.id/285839/; https://ieeexplore.ieee.org/document/10264050
• المؤسسة: Universitas Gadjah Mada

There is a recent trend of investigating self-regulated learning (SRL) using trace-based methodologies. The result of the SRL analysis can be used to provide appropriate interventions to maintain participation during online learning. There are many analytical methods that can be used to analyze the SRL process in various online learning settings. However, to the best knowledge of the authors, little attention has been paid to the literature study on SRL using trace-based methodologies. Here, we conducted a literature review to provide more insight into the investigation of the SRL process using trace data collected by an online learning system. This study reviewed relevant literature from three databases: ScienceDirect, IEEE Xplore, and Scopus from 2018 to 2022. We chose 33 articles to be reviewed and analyzed. The results show that the combination of two or more analytical methods can provide a wider insight into the SRL process. Different learning modalities use an online learning system with many features that activate different behaviors. Therefore, challenges are explored for future research.