Analyzing the Features of Learning Behaviors of Students using e-Books

Chengjiu Yin, Fumiya Okubo, Atsushi Shimada, Misato Oi, Sachio Hirokawa, Masanori Yamada, Kentaro Kojima, Hiroaki Ogata

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

The analysis of learning behavior and identification of learning style from learning logs are expected to benefit instructors and learners. This study describes methods for processing learning logs, such as data collection, integration, and cleansing, developed in Kyushu University. The research aims to analyze learning behavior and identify students' learning style using student's learning logs. Students were clustered into four groups using k-means clustering, and features of their learning behavior were analyzed in detail. We found that Digital Backtrack Learning style is better than Digital Sequential Learning style.

本文言語英語
ホスト出版物のタイトルDoctoral Student Consortium (DSC) - Proceedings of the 23rd International Conference on Computers in Education, ICCE 2015
出版社Asia-Pacific Society for Computers in Education
ページ617-626
ページ数10
ISBN(電子版)9784990801496
出版ステータス出版済み - 2015
イベント23rd International Conference on Computers in Education, ICCE 2015 - Hangzhou, 中国
継続期間: 11 30 201512 4 2015

その他

その他23rd International Conference on Computers in Education, ICCE 2015
国/地域中国
CityHangzhou
Period11/30/1512/4/15

All Science Journal Classification (ASJC) codes

  • コンピュータ サイエンス(その他)
  • 教育

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