Pilot study to estimate “difficult” area in e-learning material by physiological measurements

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抜粋

To improve designs of e-learning materials, it is necessary to know which word or figure a learner felt "difficult" in the materials. In this pilot study, we measured electroencephalography (EEG) and eye gaze data of learners and analyzed to estimate which area they had difficulty to learn. The developed system realized simultaneous measurements of physiological data and subjective evaluations during learning. Using this system, we observed specific EEG activity in difficult pages. Integrating of eye gaze and EEG measurements raised a possibility to determine where a learner felt “difficult” in a page of learning materials. From these results, we could suggest that the multimodal measurements of EEG and eye gaze would lead to effective improvement of learning materials. For future study, more data collection using various materials and learners with different backgrounds is necessary. This study could lead to establishing a method to improve e-learning materials based on learners' mental states.

元の言語英語
ホスト出版物のタイトルProceedings of the 6th 2019 ACM Conference on Learning at Scale, L@S 2019
出版者Association for Computing Machinery, Inc
ISBN(電子版)9781450368049
DOI
出版物ステータス出版済み - 6 24 2019
イベント6th ACM Conference on Learning at Scale, L@S 2019 - Chicago, 米国
継続期間: 6 24 20196 25 2019

出版物シリーズ

名前Proceedings of the 6th 2019 ACM Conference on Learning at Scale, L@S 2019

会議

会議6th ACM Conference on Learning at Scale, L@S 2019
米国
Chicago
期間6/24/196/25/19

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Education

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  • これを引用

    Tamura, K., Okamoto, T., Oi, M., Shimada, A., Hatano, K., Yamada, M., Lu, M., & Konomi, S. (2019). Pilot study to estimate “difficult” area in e-learning material by physiological measurements. : Proceedings of the 6th 2019 ACM Conference on Learning at Scale, L@S 2019 (Proceedings of the 6th 2019 ACM Conference on Learning at Scale, L@S 2019). Association for Computing Machinery, Inc. https://doi.org/10.1145/3330430.3333648