| 研究課題/領域番号 |
23K25156
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| 補助金の研究課題番号 |
22H03902 (2022-2023)
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| 研究種目 |
基盤研究(B)
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| 配分区分 | 基金 (2024)
補助金 (2022-2023) |
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| 応募区分 | 一般 |
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| 審査区分 |
小区分90020:図書館情報学および人文社会情報学関連
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| 研究機関 | 熊本大学 |
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研究代表者 |
Majumdar Rwito 熊本大学, 半導体・デジタル研究教育機構, 准教授 (30823348)
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| 研究分担者 |
Flanagan Brendan 京都大学, 国際高等教育院, 特定准教授 (00807612)
緒方 広明 京都大学, 学術情報メディアセンター, 教授 (30274260)
李 慧勇 九州大学, 情報基盤研究開発センター, 助教 (60913910)
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| 研究期間 (年度) |
2022-04-01 – 2025-03-31
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| 研究課題ステータス |
交付 (2024年度)
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| 配分額 *注記 |
17,680千円 (直接経費: 13,600千円、間接経費: 4,080千円)
2024年度: 5,590千円 (直接経費: 4,300千円、間接経費: 1,290千円)
2023年度: 4,030千円 (直接経費: 3,100千円、間接経費: 930千円)
2022年度: 8,060千円 (直接経費: 6,200千円、間接経費: 1,860千円)
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| キーワード | GOAL / Self Direction Skills / Learning Analytics / AI in Education / DAPER model / LAreflecT / Learning Habits / Collaborative learning / Quantified Self / DAPER |
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| 研究開始時の研究の概要 |
Learners need to be trained to be self-directed in their learning and daily activities. This research focuses on developing digital learning environments that trace learners' behaviors and provide them functionalities to develop such self-direction skills by analysis of those data.
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| 研究実績の概要 |
This research aims to design and support student’s self-directedness by data-informed approaches in everyday learning context. As part of the research we built online system, GOAL which synchronizes the students' online learning logs and assists them to analyze, plan, monitor and reflect on their self-directed learning activities. The system was used in a junior high and high school in Japan and continued to collect students interaction logs, plans and self-reflection notes. The students engaged in learning activities such as extensive reading and reflecting on their weekly mathematics learning
This year the research could progress in investigations related to self-directed activity profiler. Empirical studies were conducted in learning habit building, group learning in a data-rich environment and analysis of the data collected in the GOAL system in the actual school scenario over the last year. It helped to conceptualize more of the personalized feedback generator features. The development involved GOAL v2.0 and LAreflecT, a new system for supporting teachers to author reflective micro-learning tasks. LAreflecT was introduced to students and teachers in 2 international conferences and at 2 institutes in India and Taiwan.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
1: 当初の計画以上に進展している
理由
Along with emperical studies, a new system LAreflecT was developed, which also had capabilities of data-driven reflection for teachers and students. The system was then used in classrooms in India, Taiwan and Japan. It also provided opportunities of international joint research.
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| 今後の研究の推進方策 |
The work this year involves
1. Analysis of GOAL data to understand weekly test preparation strategies of junior high school students.
2. Design prototyping a habit dashboard for the students.
3. Understanding cross activity self-directedness of the students.
4. Updating the LAreflecT authoring tool with integration of generative AI API.
5. Developing further analysis modules in the LAreflecT dashbaord.
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