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Title: Exploring Temporal Study Patterns in eBook-based Learning
Authors: AKÇAPINAR, Gökhan
HASNINE, Nehal Mohammad
MAJUMDAR, Rwitajit
CHEN, Alice Mei-Rong
FLAGANAN, Brendan
OGATA, Hiroaki  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0001-5216-1576 (unconfirmed)
Author's alias: 緒方, 広明
Keywords: sequence mining
clustering
reading logs
eBook
educational data mining
learning analytics
Issue Date: 23-Nov-2020
Publisher: Asia-Pacific Society for Computers in Education (APSCE)
Journal title: 28th International Conference on Computers in Education Conference Proceedings
Volume: 1
Start page: 342
End page: 347
Abstract: In this study, approximately 2 million click-stream data of 1346 students in the eBook platform were analyzed aiming to explore the temporal study patterns of the students followed during the lectures. The data used in the study collected from Kyushu University, Japan with the help of a digital textbook reader called BookRoll. Students used BookRoll for reading learning materials in and out of the class. To analyze the data we first, converted reading sessions into the sequence data which represents student’s weekly reading behavior, then we clustered students based on their study patterns. Our results revealed that three groups of students can be extracted with similar study patterns. Most of the students in Cluster 1 viewed the learning materials only during the class, without previewing and reviewing them. Students in Cluster 2 previewed the learning materials before the class, viewed learning materials during the class, and also reviewed after the class. Students in Cluster 3 viewed the learning materials during the class in the beginning but they became inactive over the period of time (week by week). Our study also showed how learning analytics can be used to understand students' study patterns which are difficult to do with self-report data. These results can help instructors while designing their courses.
Description: 28th International Conference on Computers in Education, 23-27 November 2020, Web conference.
Rights: Copyright 2020 Asia-Pacific Society for Computers in Education.
許諾条件に基づいて掲載しています。
URI: http://hdl.handle.net/2433/259783
Appears in Collections:Journal Articles

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