| Project/Area Number |
23K25156
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| Project/Area Number (Other) |
22H03902 (2022-2023)
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Multi-year Fund (2024)
Single-year Grants (2022-2023) |
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| Section | 一般 |
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| Review Section |
Basic Section 90020:Library and information science, humanistic and social informatics-related
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| Research Institution | Kumamoto University |
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Principal Investigator |
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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| Co-Investigator(Kenkyū-buntansha) |
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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| Project Period (FY) |
2022-04-01 – 2025-03-31
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| Project Status |
Granted (Fiscal Year 2024)
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| Budget Amount *help |
¥17,680,000 (Direct Cost: ¥13,600,000、Indirect Cost: ¥4,080,000)
Fiscal Year 2024: ¥5,590,000 (Direct Cost: ¥4,300,000、Indirect Cost: ¥1,290,000)
Fiscal Year 2023: ¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2022: ¥8,060,000 (Direct Cost: ¥6,200,000、Indirect Cost: ¥1,860,000)
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| Keywords | GOAL / Self Direction Skills / Learning Analytics / AI in Education / DAPER model / LAreflecT / Learning Habits / Collaborative learning / Quantified Self / DAPER |
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| Outline of Research at the Start |
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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| Outline of Annual Research Achievements |
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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| Current Status of Research Progress |
Current Status of Research Progress
1: Research has progressed more than it was originally planned.
Reason
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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| Strategy for Future Research Activity |
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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