Quantification of the Depth of Student Learning in Group Discussions to Support Active Learning Using Revised Taxonomy

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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: 電気学会論文誌C（電子・情報・システム部門誌） Vol.142 No.3 （2022） 特集Ⅰ：スマートシステムと計測・制御技術 －Withコロナ社会に向けて－ 特集Ⅱ：高機能化合物半導体エレクトロニクス技術と将来システムへの応用 特集Ⅲ：国際会議ICESS 2020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/ Show more