Abstract—The present research aims to explore the relationships between self-regulated learning (SRL) awareness, online behaviors and achievement by investigating whether SRL awareness measured at the beginning of the semester can predict online learning behaviors and achievement in the flipped classroom model. Psychometric data about SRL awareness and log data were collected and analyzed using multiple linear regression. Motivated Strategies for Learning Questionnaire (MSLQ) and a Moodle platform were used as data collection tools. Five flipped courses with a total of 93 undergraduates of a university in Taiwan were included in the present study. The results indicated that 1) task value, intrinsic motivation, control of learning beliefs and metacognition predict achievement, 2) SRL awareness predicts online behaviors to a limited extent, 3) combination of SRL awareness and online behaviors predicts achievement better than either one of the single-domain models. Theoretical contributions and implications for education and practice, and future research of the present study are discussed.
Index Terms—Flipped classroom, learning management system, online behavioral engagement, self-regulated learning.
F. H. Wang is with the Department of Computer Science and Information Engineering, Ming Chuan University, Taiwan (e-mail: firstname.lastname@example.org).
Cite: Feng Hsu Wang, "On Prediction of Online Behaviors and Achievement Using Self-regulated Learning Awareness in Flipped Classrooms," International Journal of Information and Education Technology vol. 9, no. 12, pp. 874-879, 2019.Copyright © 2019 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).