Applying Learning Analytics to Explore the Effects of Motivation on Online Students' Reading Behavioral Patterns ARTICLE
Jerry Sun, Che-Tsun Lin, Chien Chou, National Chiao Tung University
IRRODL Volume 19, Number 2, ISSN 1492-3831 Publisher: Athabasca University Press
This study aims to apply a sequential analysis to explore the effect of learning motivation on online reading behavioral patterns. The study\u2019s participants consisted of 160 graduate students who were classified into three group types: low reading duration with low motivation, low reading duration with high motivation, and high reading duration based on a second-order cluster analysis. After performing a sequential analysis, this study reveals that highly motivated students exhibited a relatively serious reading pattern in a multi-tasking learning environment, and that online reading duration was a significant indicator of motivation in taking an online course. Finally, recommendations were provided to instructors and researchers based on the results of the study.
Sun, J., Lin, C.T. & Chou, C. (2018). Applying Learning Analytics to Explore the Effects of Motivation on Online Students' Reading Behavioral Patterns. The International Review of Research in Open and Distributed Learning, 19(2),. Athabasca University Press. Retrieved May 22, 2018 from https://www.learntechlib.org/p/183602/.
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