2023 Fiscal Year Final Research Report
Development of Self-Regulated Learning Support System in Continuous Learning along Knowledge Body
| Project/Area Number |
20K12111
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 62030:Learning support system-related
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| Research Institution | Chitose Institute of Science and Technology |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
今井 順一 公立千歳科学技術大学, 理工学部, 教授 (60458148)
山川 広人 公立千歳科学技術大学, 理工学部, 講師 (90724732)
上野 春毅 公立千歳科学技術大学, 理工学部, 助手 (40948337)
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| Project Period (FY) |
2020-04-01 – 2024-03-31
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| Keywords | 適応型システム / CBT / 数理データサイエンス教育 / 学習アドバイジング |
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| Outline of Final Research Achievements |
To promote self-regulated learning, we have implemented a fully online flipped classroom design. This system manages CBT activities for pre-study, lecture video viewing, assignment submission, and pre- and post-class reflections in a unified manner. We validated this approach across multiple data science courses and confirmed that it encourages active learning, allowing students to determine their own learning order. Additionally, we utilized machine learning algorithms to identify features that lead to successful learning outcomes from a series of digitized learning performance data. Using these features, we conducted clustering to categorize learners into 21 groups. For each category, we defined learning support messages and developed a system that provides automated learning support.
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| Free Research Field |
教育工学
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| Academic Significance and Societal Importance of the Research Achievements |
(1) 数理データサイエンス・AI教育を想定したCBT教材群を知識体系の中で構築した．当該CBT教材は，大学eラーニング協議会を通じて広く公開しており，山梨大学・創価大学で既に授業で活用され始めている．(2)(1)の体系的な教材群を活用した，フルオンラインで実施できる反転型の授業設計を図り，その有用性を示した．本授業設計に基づく授業実践は，公立千歳科学技術大学の中の複数科目で実施されている．(3)(1)及び(2)で構成される適応型学習支援システムと，ChatGPTをAPI接続することで，学習者特性を踏まえた学習指導アドバイジングの自動化を実現した．これは教育のDX化の有用事例といえる．
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