Project/Area Number |
20H01722
|
Research Category |
Grant-in-Aid for Scientific Research (B)
|
Allocation Type | Single-year Grants |
Section | 一般 |
Review Section |
Basic Section 09070:Educational technology-related
|
Research Institution | Kyoto University |
Principal Investigator |
|
Co-Investigator(Kenkyū-buntansha) |
緒方 広明 京都大学, 学術情報メディアセンター, 教授 (30274260)
Majumdar Rwito 京都大学, 学術情報メディアセンター, 特定講師 (30823348)
|
Project Period (FY) |
2020-04-01 – 2023-03-31
|
Project Status |
Completed (Fiscal Year 2022)
|
Budget Amount *help |
¥17,940,000 (Direct Cost: ¥13,800,000、Indirect Cost: ¥4,140,000)
Fiscal Year 2022: ¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2021: ¥5,070,000 (Direct Cost: ¥3,900,000、Indirect Cost: ¥1,170,000)
Fiscal Year 2020: ¥8,580,000 (Direct Cost: ¥6,600,000、Indirect Cost: ¥1,980,000)
|
Keywords | knowledge extraction / knowledge recommendation / human-in-the-loop system / automated labeling / Knowledge Map / Knowledge Extraction / Learning Analytics / Educational Data Mining / Smart Learning Systems / Knowledge map / Smart learning systems / Knowledge extraction / Learning analytics / Educational Informatics |
Outline of Research at the Start |
The study guidance code proposed by MEXT will standardize the representation of learning material knowledge structures, however a system to integrate teacher created materials with publisher contents and learning analytics systems is required to realize the full potential to support smart education and learning. This research investigates how meaningful analysis can be achieved by supporting the automated extraction, linking, management, and analysis of knowledge maps at scale.
|
Outline of Annual Research Achievements |
Research in this period focused on constructing systems to support teachers in the creation of knowledge maps of learning materials that have been uploaded to an e-book reading system. In particular we focused on the automated labeling of knowledge concepts in Mathematics taugh in Japanese, as it was previously identified as a problematic task. This resulted in a human-in-the-loop system for semi-automated labeling to support teachers. It was found that the system could both reduce the burden and increase the accuracy of the labeling task and results were disseminated as several articles in international journals. These labeled knowledge concepts were then used to provide recommendations in both Maths and English education contexts and presented at international conferences and disseminated as articles in jorunals. The results of this project have spawned several new projects and research themes. This demonstrates the impact and bredth of the results that were obtained during this project.
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Research Progress Status |
令和4年度が最終年度であるため、記入しない。
|
Strategy for Future Research Activity |
令和4年度が最終年度であるため、記入しない。
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