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

Jerry Chih-Yuan Sun; Che-Tsun Lin; Chien Chou

doi:10.19173/irrodl.v19i2.2853

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

Authors

Jerry Chih-Yuan Sun National Chiao Tung University http://orcid.org/0000-0002-7892-4313
Che-Tsun Lin National Chiao Tung University
Chien Chou National Chiao Tung University

DOI:

https://doi.org/10.19173/irrodl.v19i2.2853

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.

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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

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Issue

Vol. 19 No. 2 (2018)

Section

Research Articles

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