Project/Area Number |
23H01001
|
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) |
Majumdar Rwito 京都大学, 学術情報メディアセンター, 特定講師 (30823348)
戴 憶菱 京都大学, 学術情報メディアセンター, 特定研究員 (90912254)
高見 享佑 国立教育政策研究所, 教育データサイエンスセンター, 主任研究官 (70912252)
|
Project Period (FY) |
2023-04-01 – 2026-03-31
|
Project Status |
Granted (Fiscal Year 2023)
|
Budget Amount *help |
¥18,850,000 (Direct Cost: ¥14,500,000、Indirect Cost: ¥4,350,000)
Fiscal Year 2023: ¥8,840,000 (Direct Cost: ¥6,800,000、Indirect Cost: ¥2,040,000)
|
Keywords | Educational AI / Explainability / Transferability |
Outline of Research at the Start |
AI models are increasingly being used in education. To explain AI model decisions and support their transfer to new or low resource classes, we aim to identify and extract highly explainable and transferable indicators and investigate their application in machine learning in education.
|