Exploring the Relationships between Reading Behavior Patterns and Learning Outcomes Based on Log Data from E-Books: A Human Factor Approach

ABSTRACT

Online learning environments presently accumulate large amounts of log data. Analysis of learning behaviors from these log data is expected to benefit instructors and learners. This study was intended to identify effective measures from e-book materials used at Kyushu University and to employ these measures for analyzing learning behavioral patterns. In an evaluation, students were grouped into four clusters using k-means clustering, and their learning behavioral patterns were analyzed. We examined whether the learning behavioral patterns exhibited relations with the learning outcomes. The results reveal that the learning behavior of “backtrack” style reading exerts a significant positive influence on learning effectiveness, which can aid students to learn more efficiently.

Notes

1. More information is available at http://www.kccs.co.jp/ict/cloud-booklooper/ (in Japanese).

2. https://moodle.org/.

Additional information

Funding

A part of this research work was supported by the Grant-in-Aid for Scientific Research No. 16H03078 and No. 16H06304 from the Ministry of Education, Culture, Sports, Science and Technology (MEXT) in Japan.

Notes on contributors

Chengjiu Yin

Chengjiu Yin is an associate professor of the Information Science and Technology Center, Kobe University, Japan. He received his PhD degree in Computer Science and Information Engineering from Tokushima University in Japan. His current research interests focuses on Educational Data Mining. He is a member of IEEE, JSET, and IPSJ.

Masanori Yamada

Masanori Yamada is an associate professor in Faculty of arts and science, Kyushu University. He received PhD in Human System Science from Tokyo Institute of Technology in 2008. He is engaged in research and development of CSCL for project-based learning, based on social and educational psychology theories.

Misato Oi

Misato Oi is a research fellow at Faculty of Arts and Science, Kyushu University, Japan. She received her Doctor of Philosophy from Nagoya University in 2010. Her research includes Computer Supported Ubiquitous and Mobile Learning, bilingualism, and non-verbal communication.

Atsushi Shimada

Atsushi Shimada received the DE degrees from Kyushu University in 2007. He is an associate professor of Faculty of Information Science and Electrical Engineering, Kyushu University. He also works as a JST-PRESTO researcher since 2015. His current research interests focused on image processing, pattern recognition, and learning analytics.

Fumiya Okubo

Fumiya Okubo is an assistant professor at Faculty of Arts and Science, Kyushu University, Japan. He received his PhD in Science from Waseda University in 2014. His research includes formal language theory, automata theory, and computation theory.

Kentaro Kojima

Kentaro Kojima is an associate professor in Faculty of arts and science, Kyushu University. He received MS and PhD from Kyushu University in 2005 and 2008, respectively. His recent research interests are Physics education research and development of CSCL.

Hiroaki Ogata

Hiroaki Ogata is a full professor at Faculty of Academic Center for Computing, Kyoto University, Japan. He was a visiting researcher of Center of Lifelong Learning and Design, the University of Colorado at Boulder, USA from 2001 through 2003. His research includes CSUML, CSCL, CSCW, CALL, and Learning Analytics.