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Pilot Study to Estimate "Difficult" Area in e-Learning Material by Physiological Measurements

Published:24 June 2019Publication History

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.

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  1. Pilot Study to Estimate "Difficult" Area in e-Learning Material by Physiological Measurements

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      • Published in

        cover image ACM Other conferences
        L@S '19: Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale
        June 2019
        386 pages
        ISBN:9781450368049
        DOI:10.1145/3330430

        Copyright © 2019 Owner/Author

        Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 24 June 2019

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        • poster
        • Research
        • Refereed limited

        Acceptance Rates

        L@S '19 Paper Acceptance Rate24of70submissions,34%Overall Acceptance Rate117of440submissions,27%

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