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

doi:10.1145/3330430.3333648

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

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.

Original language	English
Title of host publication	Proceedings of the 6th 2019 ACM Conference on Learning at Scale, L@S 2019
Publisher	Association for Computing Machinery, Inc
ISBN (Electronic)	9781450368049
DOIs	https://doi.org/10.1145/3330430.3333648
Publication status	Published - Jun 24 2019
Event	6th ACM Conference on Learning at Scale, L@S 2019 - Chicago, United States Duration: Jun 24 2019 → Jun 25 2019

Publication series

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

Conference

Conference	6th ACM Conference on Learning at Scale, L@S 2019
Country/Territory	United States
City	Chicago
Period	6/24/19 → 6/25/19

All Science Journal Classification (ASJC) codes

Software
Computer Science Applications
Computer Networks and Communications
Education

Access to Document

10.1145/3330430.3333648

Cite this

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. In 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

Pilot study to estimate “difficult” area in e-learning material by physiological measurements. / Tamura, Kaori; Okamoto, Tsuyoshi; Oi, Misato et al.
Proceedings of the 6th 2019 ACM Conference on Learning at Scale, L@S 2019. Association for Computing Machinery, Inc, 2019. (Proceedings of the 6th 2019 ACM Conference on Learning at Scale, L@S 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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. in 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, 6th ACM Conference on Learning at Scale, L@S 2019, Chicago, United States, 6/24/19. https://doi.org/10.1145/3330430.3333648

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

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abstract = "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.",

author = "Kaori Tamura and Tsuyoshi Okamoto and Misato Oi and Atsushi Shimada and Kohei Hatano and Masanori Yamada and Min Lu and Shin'ichi Konomi",

note = "Funding Information: This work was supported by JST Mirai Grant Number 17-171024547, Japan. Publisher Copyright: {\textcopyright} 2019 Copyright is held by the owner/author(s).; 6th ACM Conference on Learning at Scale, L@S 2019 ; Conference date: 24-06-2019 Through 25-06-2019",

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AU - Yamada, Masanori

AU - Lu, Min

AU - Konomi, Shin'ichi

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

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