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.