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Title: Toward Precision Education: Educational Data Mining and Learning Analytics for Identifying Students’ Learning Patterns with Ebook Systems
Authors: Yang, C. Y. Christopher
Chen, L. Y. Irene
Ogata, Hiroaki  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0001-5216-1576 (unconfirmed)
Author's alias: 緒方, 広明
Keywords: Precision education
Learning analytics
Educational data mining
Learning pattern
Ebook learning log
Issue Date: 2021
Publisher: International Forum of Educational Technology & Society
Journal title: Educational Technology & Society
Volume: 24
Issue: 1
Start page: 152
End page: 163
Abstract: Precision education is now recognized as a new challenge of applying artificial intelligence, machine learning, and learning analytics to improve both learning performance and teaching quality. To promote precision education, digital learning platforms have been widely used to collect educational records of students’ behavior, performance, and other types of interaction. On the other hand, the increasing volume of students’ learning behavioral data in virtual learning environments provides opportunities for mining data on these students’ learning patterns. Accordingly, identifying students’ online learning patterns on various digital learning platforms has drawn the interest of the learning analytics and educational data mining research communities. In this study, the authors applied data analytics methods to examine the learning patterns of students using an ebook system for one semester in an undergraduate course. The authors used a clustering approach to identify subgroups of students with different learning patterns. Several subgroups were identified, and the students’ learning patterns in each subgroup were determined accordingly. In addition, the association between these students’ learning patterns and their learning outcomes from the course was investigated. The findings of this study provide educators opportunities to predict students’ learning outcomes by analyzing their online learning behaviors and providing timely intervention for improving their learning experience, which achieves one of the goals of learning analytics as part of precision education.
Rights: This article of the journal of Educational Technology & Society is available under Creative Commons CC-BY-NC-ND 3.0 license (https://creativecommons.org/licenses/by-nc-nd/3.0/). For further queries, please contact Journal Editors at ets.editors@gmail.com.
URI: http://hdl.handle.net/2433/261247
Related Link: https://www.j-ets.net/collection/published-issues/24_1
Appears in Collections:Journal Articles

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