2019 Fiscal Year Final Research Report
Visualization of learning states during watching online video class by developing feature space of brain activity
| Project/Area Number |
17K20016
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| Research Category |
Grant-in-Aid for Challenging Research (Exploratory)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Human informatics and related fields
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| Research Institution | Meiji University |
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Principal Investigator |
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| Project Period (FY) |
2017-06-30 – 2020-03-31
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| Keywords | オンライン授業 / 脳活動計測 / 被験者間相関 / 近赤外分光法 / 脳波 |
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| Outline of Final Research Achievements |
In this study, we conducted experiments to measure brain activities of a teacher and a student who underwent online video class or of two individuals performing a cooperative work by using near-infrared spectroscopy (NIRS) or electroencephalography (EEG), and found similar brain activities among participants during the tasks. Based on these results, we developed a technique to map brain activity of an individual during watching a video class on a brain-activity-based feature space, by employing the principal component analysis (PCA) that maximizes inter-subject correlation (ISC) of participants’ brain activities.
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| Free Research Field |
認知脳科学
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| Academic Significance and Societal Importance of the Research Achievements |
近年の情報技術の発展により教育コンテンツのオンライン化（オープンエデュケーション）が進み、また現在のコロナ禍の影響も重なって、世界的にもオンライン授業の重要性が高まっている。本研究では、同一の授業内容が再現性を持って提供されるオンライン動画授業を主眼として、学習に関する脳活動を特徴空間にマッピングする技術の開発を行った。これによって学習状態のより的確な把握と、これに基づいたテーラーメイド教育への可能性を示すことができた。
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