A Review of Learners' Self-Regulated Learning Behavior Analysis Using Log-Data Traces
Penulis/Author
ANINDYA DAMAYANTI (1); Prof. Dr. Ir. Sri Suning Kusumawardani, S.T, M.T. (2); Dr.Eng. Ir. Sunu Wibirama, S.T., M.Eng., IPM. (3)
Tanggal/Date
2023
Kata Kunci/Keyword
Abstrak/Abstract
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.
