2021 Fiscal Year Final Research Report
Construction of Learning Support AI Platform based on Prediction Model of Skill Acquirement
| Project/Area Number |
19H04157
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Review Section |
Basic Section 61020:Human interface and interaction-related
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| Research Institution | Future University-Hakodate |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
平田 圭二 公立はこだて未来大学, システム情報科学部, 教授 (30396121)
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| Project Period (FY) |
2019-04-01 – 2022-03-31
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| Keywords | 学習支援 / インタラクション / 情報デザイン / 機械学習 |
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| Outline of Final Research Achievements |
The purpose of this study is to construct a predictive model for skill acquisition that integrates human-computer interaction (HCI) technology and machine learning, and to build an AI infrastructure to support learning. Learning physical skills such as piano, calligraphy, and illustration takes a great deal of time and effort. Learners do not know when they will be able to master a skill, and must continue to practice basic skills while feeling anxious and impatient. Therefore, this study constructs a predictive model of skill acquisition for beginners. The solution is to construct a learning support AI infrastructure that checks, monitors, and diagnoses the learner's skills, and constructs a learning plan that takes into account the learner's needs (amount of practice, degree of difficulty, desired date of completion, etc.).
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| Free Research Field |
ヒューマンコンピュータインタラクション
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| Academic Significance and Societal Importance of the Research Achievements |
技能習得予測技術は，従来の学習支援システムを躍進させる革新的な成果になり，インタラクション・教育工学・認知心理学分野への学術的貢献ができる．また，本研究の成果は，身体を活用したゲーム開発や，新たな知育教材・情操教育用教材・生涯学習教材などの開発に直接的に応用できるだけでなく，人間の教師が生徒に指導する場合や，親が子供に技能を教える場合に，例えば，自立を促すためには何をどこまで指導するべきかなどの指導方法の検討においても応用でき，教育現場にも貢献できる．
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