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2022 Fiscal Year Final Research Report

System development for aggregating learners' expressive acts corresponding to mental states and feeding the results back to learners

Research Project

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Project/Area Number 18H01059
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypeSingle-year Grants
Section一般
Review Section Basic Section 09070:Educational technology-related
Research InstitutionThe Open University of Japan

Principal Investigator

Kato Hiroshi  放送大学, 教養学部, 教授 (80332146)

Co-Investigator(Kenkyū-buntansha) 寺田 努  神戸大学, 工学研究科, 教授 (70324861)
大西 鮎美  神戸大学, 工学研究科, 助教 (10869142)
葛岡 英明  東京大学, 大学院情報理工学系研究科, 教授 (10241796)
鈴木 栄幸  茨城大学, 人文社会科学部, 教授 (20323199)
久保田 善彦  玉川大学, 教育学研究科, 教授 (90432103)
Project Period (FY) 2018-04-01 – 2022-03-31
Keywords教育工学 / 教育評価 / HCI / ウェアラブルコンピューティング / 協調学習 / 生体情報
Outline of Final Research Achievements

The original goal was to record and collect situational assessments among learners in collaborative learning by using machine learning to automatically recognize expressions, but it was not possible to generate teacher data with good accuracy using real-time self-reporting or facial recognition. Therefore, we changed our direction to investigate how evaluative expressions affect the expressioner and the surrounding others. As a result, it was suggested that nodding has a function of increasing one’s concentration and arousal level from the change of an indicator called pNN50 obtained from heart rate information. However, when nodding was forced, no increase in concentration or arousal level was observed.

Free Research Field

教育工学

Academic Significance and Societal Importance of the Research Achievements

従来,教育場面における受講者のうなずきは,受講者が授業に集中して理解していることを表示していると捉えられてきた.本研究では,それ以外にも,うなずきによって受講者が高い集中度を持続させている可能性があることが明らかになった.これより,講義中にうなずきなどのリアクションの表出を促進することによって,講義に対する受講者の集中度を高く維持できる可能性が明らかになった.集中度が高まれば,ひいてはそれが学習効果を高めることにつながる可能性も示唆される.

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Published: 2024-01-30  

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