@inproceedings{9a012c8e575a4e2f8100b9782c7fcc85,
title = "Analyzing the features of learning behaviors of students using e-Books",
abstract = "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.",
author = "Chengjiu Yin and Fumiya Okubo and Atsushi Shimada and Misato Oi and Sachio Hirokawa and Masanori Yamada and Kentaro Kojima and Hiroaki Ogata",
year = "2015",
language = "English",
series = "Workshop Proceedings of the 23rd International Conference on Computers in Education, ICCE 2015",
publisher = "Asia-Pacific Society for Computers in Education",
pages = "616--626",
editor = "Ying-Tien Wu and Tomoko Kojiri and Kong, {Siu Cheung} and Feiyue Qiu and Hiroaki Ogata and Thepchai Supnithi and Yonggu Wang and Weiqin Chen",
booktitle = "Workshop Proceedings of the 23rd International Conference on Computers in Education, ICCE 2015",
note = "23rd International Conference on Computers in Education, ICCE 2015 ; Conference date: 30-11-2015 Through 04-12-2015",
}