Researchers

OI Misato

Faculty	Department of Information and Computer Science
Researchmap	https://researchmap.jp/OI_Misato

Apr. 2022 - Today , Kindai University 産業理工学部情報学科准教授
Apr. 2018 - Mar. 2022 , Kyushu University Innovation Center for Educational Resources, Kyushu University Library Associate Professor
Jun. 2015 - Mar. 2018 , Kyushu University 基幹教育院学術研究員
Sep. 2007 - Mar. 2015 , Kinjo Gakuin University 非常勤講師
Apr. 2012 - Mar. 2014 , Tokai Gakuin University 非常勤講師
Apr. 2006 - Mar. 2010 , 岐阜市立第二看護専門学校非常勤講師
Apr. 2009 , Nagoya University 大学院・情報科学研究科協力研究員

Exploring Factors that Influence Collaborative Problem Solving Awareness in Science Education
Li Chen; Koichi Inoue; Yoshiko Goda; Fumiya Okubo; Yuta Taniguchi; Misato Oi; Shin’ichi Konomi; Hiroaki Ogata; Masanori Yamada
Technology, Knowledge and Learning 25 (2) , 337-366, 1, Jun. 2020 , Refereed
How Academic Organizations Support the Development of Online Educational Materials : Cases from the Innovation Center for Educational Resources of Kyushu University
OI Misato
名古屋高等教育研究 (20) , 51-60, Mar. 2020
Development and evaluation of a visualization system to support meaningful e-book learning
Jingyun Wang; Atsushi Shimada; Misato Oi; Hiroaki Ogata; Yoshiyuki Tabata
Interactive Learning Environments 2020 , Refereed

Emerging Trends in Learning Analytics: Leveraging the Power of Education Data , Okubo, F; Yamada, M; Oi, M; Shimada, A; Taniguchi, Y; Konomi, S , Learning Support Systems Based on Cohesive Learning Analytics , Learning Support Systems Based on Cohesive Learning Analytics , Apr. 2019
Smart Sensors at the IoT Frontier , Ogata, H; Oi, M; Mohri, K; Okubo, F; Shimada, A; Yamada, M; Wang, J; Hirokawa, S , Chapter12. Learning Analytics for e-Book Based Educational Big Data , Chapter12. Learning Analytics for e-Book Based Educational Big Data , Springer , May. 2017

オンライン教材の開発を組織はどう支援すべきか , 大井京 , 教育基盤連携本部高等教育システム開発部門シンポジウム：オンライン学習の可能性と課題 , 27, Sep. 2019
Integrating Multimodal Learning Analytics and Inclusive Learning Support Systems for People of All Ages. , Kaori Tamura; Min Lu; Shin'ichi Konomi; Kohei Hatano; Miyuki Inaba; Misato Oi; Tsuyoshi Okamoto; Fumiya Okubo; Atsushi Shimada; Jingyun Wang; Masanori Yamada; Yuki Yamada , Cross-Cultural Design. Culture and Society - 11th International Conference, CCD 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Orlando, FL, USA, July 26-31, 2019, Proceedings, Part II , 2019
Pilot Study to Estimate "Difficult" Area in e-Learning Material by Physiological Measurements. , Kaori Tamura; Tsuyoshi Okamoto; Misato Oi; Atsushi Shimada; Kohei Hatano; Masanori Yamada; Min Lu; Shin'ichi Konomi , Proceedings of the Sixth ACM Conference on Learning @ Scale, L@S 2019, Chicago, IL, USA, June 24-25, 2019. , 2019

Effects of varying physical exercises on working memory improvement , Misato Oi; Ryusei Udo , SARMAC 2023 , 99 , 99 , 12, Aug. 2023
Factors Affecting Judgments of Authenticity of Fake News , 大井京; 小野奨太 , 日本認知科学会大会発表論文集(CD-ROM) , 40th , 2023
学習中の生理応答同時計測による「学びのつまずき」推定システム開発 , 田村かおり; 岡本剛; 大井京; 島田敬士; 畑埜晃平; 山田政寛; LU Min; 木實新一 , 情報処理学会シンポジウムシリーズ(CD-ROM) , 2019 , 1 , ROMBUNNO.2F‐1 , 410 , 26, Jun. 2019
Summary:学習者が新規知識獲得時に感じる「学びのつまずき」を推定するために，学習ログデータと生体信号を活用した「マルチモーダル・ラーニングアナリティクス」が昨今注目されている．本研究では，学習中生体信号として脳波および視線計測を導入し，「学びのつまずき」推定のためのシステムを開発した．本開発システムを用いて学習中の状態を計測し，バイオマーカー候補を探索した．その結果，脳波ではベータ波振幅が，視線では視線停留時間および視線流入回数が，それぞれつまずき推定のマーカー候補になりうることを示した．本研究で得られた結果は，生体信号から「学びのつまずき」の詳細な推定を実現する上での基盤となりうる．

Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, Development of learning materials utilizing the facilitative effect of gestures in online second language learning , Kindai University
Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, Development of a feedback method based on learning log and brain activation analyses , Kyushu University
Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, Facilitaiton effect on speech production by gesture and its neural mechanism , Kyushu University