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Utilizing clickstream data to reveal the time management of self-regulated learning in a higher education online learning environment
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Type
Article
Citation
Cao, T., Zhang, Z., Chen, W., & Shu, J. (2023). Utilizing clickstream data to reveal the time management of self-regulated learning in a higher education online learning environment. Interactive Learning Environments, 31(10), 6555-6572. https://doi.org/10.1080/10494820.2022.2042031
Abstract
Online learning with the characteristics of flexibility and autonomy has become a widespread and popular mode of higher education in which students need to engage in self-regulated learning (SRL) to achieve success. The purpose of this study is to utilize clickstream data to reveal the time management of SRL. This study adopts learning analytics to investigate the differences in time management (time investment and time use patterns) in a large-scale authentic online learning environment based on 8019 students’ clickstream data of over one term recorded by the starC system log. This study quantitatively reveals the SRL process in a higher education online learning environment, which presents the detailed differences in time management among students with different academic performance categories. These research results will have inspirations in the design of SRL interventions for optimizing students’ learning processes and overall achievement.
Publisher
Taylor & Francis
Journal
Interactive Learning Environments
Grant ID
62077020
202006770012
2020YBZZ009
Funding Agency
National Natural Science Foundation of China
Fund of China Scholarship Council
Fundamental Research Funds for the Central Universities of China