Quantification of the Depth of Student Learning in Group Discussions to Support Active Learning Using Revised Taxonomy
Quantification of the Depth of Student Learning in Group Discussions to Support Active Learning Using Revised Taxonomy
カテゴリ: 論文誌(論文単位)
グループ名: 【C】電子・情報・システム部門
発行日: 2022/03/01
タイトル(英語): Quantification of the Depth of Student Learning in Group Discussions to Support Active Learning Using Revised Taxonomy
著者名: Asako Ohno (Osaka Sangyo University), Yuka Nakagawa (Osaka Sangyo University), Yoshiro Imai (Kagawa University)
著者名(英語): Asako Ohno (Osaka Sangyo University), Yuka Nakagawa (Osaka Sangyo University), Yoshiro Imai (Kagawa University)
キーワード: learning depth,revision of bloom's taxonomy,Word2vec,TF-IDF,group discussion,active learning
要約(英語): The Ministry of Education, Culture, Sports, Science and Technology (MEXT) has called for educational institutions to realize “independent, interactive, and deep learning” in order to develop the qualities and abilities necessary for children to live in the human-centered society (Society 5.0) that Japan aims to establish in the future. As a result, active learning, such as group discussions, is becoming more common in school education. However, quantitative evaluation indicators and methods have not been established to show whether “deep learning” has been achieved or not. In this study, we propose a method to quantify the depth of learning based on the features extracted from the content of the students' comments in group discussions using the Revised Taxonomy, and to present the results to the teacher.
本誌掲載ページ: 382-388 p
原稿種別: 論文/英語
電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/142/3/142_382/_article/-char/ja/
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