Finding traces of high and low achievers by analyzing undergraduates' e-book logs

Misato Oi, Masanori Yamada, Fumiya Okubo, Atsushi Shimada, Hiroaki Ogata

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)

Abstract

We investigated the learning behavior of undergraduates with e-book logs. E-book logs from 99 undergraduates taking an information science course were collected. First, we analyzed differences between nine high-achieving students and three low-achieving students. A log recorded before a class session in which the same e-book was used as a textbook was considered a preview log, and one recorded after a class session was considered a review log. The analysis of preview frequency indicates that the low achievers did not perform the previews, but many high achievers frequently did. The review frequency demonstrates that regardless of high and low achievements, students performed reviews. We added the logs of six relatively low achievers and analyzed more details of the preview logs of high and low achievers. The number of page flips and durations of preview logs revealed that relatively low achievers tried to perform previews, but they gave the endeavor up easily.

Original languageEnglish
Pages (from-to)15-22
Number of pages8
JournalCEUR Workshop Proceedings
Volume1828
Publication statusPublished - 2017
EventJoint 6th Multimodal Learning Analytics Workshop and the Second Cross-LAK Workshop, MMLA-CrossLAK 2017 - Vancouver, Canada
Duration: Mar 14 2017 → …

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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