GENERATING EXPLANATORY TEXTS ON RELATIONSHIPS BETWEEN SUBJECTS AND THEIR POSITIONS IN A CURRICULUM USING GENERATIVE AI

Ryusei Munemura, Fumiya Okubo, Tsubasa Minematsu, Yuta Taniguchi, Atsushi Shimada

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

抄録

Course planning is essential for academic success and the achievement of personal goals. Although universities provide course syllabi and curriculum maps for course planning, integrating and understanding these resources by the learners themselves for effective course planning is time-consuming and difficult. To address this issue, this study proposes a method that uses generative AI to classify relationships between subjects and generate explanatory texts describing the connections of subjects and positions of subjects within the curriculum based on subject and curriculum information. An evaluation experiment involving learners demonstrated a classification accuracy of approximately 70% for inter-subject relationships. Furthermore, our experimental results confirm that that the generated explanatory texts significantly enhance the understanding of relationships between subjects, and are thus effective for course planning.

本文言語英語
ホスト出版物のタイトルProceedings of the 21st International Conference on Cognition and Exploratory Learning in the Digital Age, CELDA 2024
編集者Demetrios G. Sampson, Dirk Ifenthaler, Dirk Ifenthaler, Pedro Isaias, Pedro Isaias, Luis Rodrigues
出版社IADIS Press
ページ159-166
ページ数8
ISBN(電子版)9789898704610
出版ステータス出版済み - 2024
イベント21st International Conference on Cognition and Exploratory Learning in the Digital Age, CELDA 2024 - Zagreb, クロアチア
継続期間: 10月 26 202410月 28 2024

出版物シリーズ

名前Proceedings of the 21st International Conference on Cognition and Exploratory Learning in the Digital Age, CELDA 2024

会議

会議21st International Conference on Cognition and Exploratory Learning in the Digital Age, CELDA 2024
国/地域クロアチア
CityZagreb
Period10/26/2410/28/24

!!!All Science Journal Classification (ASJC) codes

  • 人工知能
  • 教育

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