Applying Learning Analytics to Explore the Effects of Motivation on Online Students' Reading Behavioral Patterns

Keywords: learning analytics, motivation, sequential analysis, online learning, behavioral pattern

Abstract

This study aims to apply a sequential analysis to explore the effect of learning motivation on online reading behavioral patterns. The study’s 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.

Published
2018-05-01
How to Cite
Sun, J. C.-Y., 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). https://doi.org/10.19173/irrodl.v19i2.2853
Section
Research Articles