Applying learning analytics to explore the influence of online learners\' motivation on their online learning behavioral patterns

Abstract

This study aims to apply sequential analysis to explore the effect of learning motivation on online learning behavioral patterns. The study participants were 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 revealed that highly motivated learners exhibited a relatively serious learning pattern in a multi-tasking learning environment, and that online reading duration was a significant indicator of seriousness in taking an online course. Finally, relevant recommendations were made to instructors and researchers based on the results of the present study.