Self-regulated learning strategies and student video engagement trajectory in a video-based asynchronous online course: a Bayesian latent growth modeling approach
- 주제(키워드) Asynchronous online learning , Bayesian latent growth modeling , Self-regulated learning , Video-based learning
- 등재 SSCI, SCOPUS, KCI등재
- 발행기관 Springer Science and Business Media B.V.
- 발행년도 2021
- 총서유형 Journal
- URI http://www.dcollection.net/handler/ewha/000000181810
- 본문언어 영어
- Published As http://dx.doi.org/10.1007/s12564-021-09690-0
초록/요약
The self-paced nature of asynchronous online learning (AOL) is recognized as an obstacle that disrupts student success in the learning environment. Without on-time interventions provided by instructors, students find it challenging to use learning strategies tailored to the learning environment, and their use of self-regulated learning (SRL) strategies has been regarded one of the key indicators of success in AOL. To examine how student SRL strategies are associated with their video engagement trajectory and learning outcomes, we used student video engagement data collected at multiple time points. Participants were 159 students who were taking a self-paced asynchronous online statistics course. Results revealed that student video engagement was found to increase over time and student management strategies contributed to the upward change. We also found that the growth of engagement predicted student achievement in the course. Our findings shed light on instructional strategies to support students in AOL contexts. © 2021, Education Research Institute, Seoul National University, Seoul, Korea.
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