2020 Fiscal Year Final Research Report
Development of a Design Framework for Learning Support Agents based on a Teaching Strategy Model using Insights from Neuroscience
| Project/Area Number |
18K11584
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 62030:Learning support system-related
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| Research Institution | Waseda University |
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Principal Investigator |
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Keywords | 学習者の心的状態の推定 / 学習支援エージェント / 神経科学的知見 / 生体計測と機械学習 / 脳機能モデリング / 感情制御 / マインドフルネス状態 / インタラクション |
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| Outline of Final Research Achievements |
In order to achieve a better learning effect in a computer-assisted learning system, it is important to realize an appropriate interaction between the system and the learner. Since this interaction is often carried out through computer agents, the design method of these agents is an important issue. In particular, it is necessary for the agent to understand not only the learner's state of knowledge comprehension but also the learner's mental state in order to realize the optimal interaction. In this study, we attempted to construct a model for understanding the learner's mental state based on the findings of neuroscience. As a result, , although it is limited in scope, we were able to obtain some knowledge that can be used as a guideline for designing agents.
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| Free Research Field |
感性情報科学，知識情報科学，学習支援システム
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| Academic Significance and Societal Importance of the Research Achievements |
本研究では，優れた人間教師の教授活動をシステムによって実現することを重要なコンセプトとしている．特に，教授行為による学習者の知識理解状態のみならず心的状態変化への影響を予測・評価するプロセスの足掛かりとなるモデルを構築することを目指してきている．これらの課題に対して，認知心理，生体計測と機械学習，神経科学の知見に基づき学際的手法によってモデル構築を実現した点は学術的意義が大きいものと考えられる．また，生体計測によって学習者の心的状態の推定を，比較的少ないサンプル数でも高精度に推定可能な手法を実現できた点は，今後の学習支援システムの新しい方向性を示すという点で社会的意義も大きいものと考えられる．
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