Real-time estimation of learners' mental states from learners' physiological information using deep learning

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

It is important to know the mental states of learners during the learning process to improve the effectiveness of teaching and learning. In this study, we first extracted the relationships between learners' mental states and teachers' speech acts, as well as learners' physiological information, by constructing a deep learning system. The physiological indexes were near infrared spectroscopy (NIRS), electroencephalography (EEG), respiration intensity, skin conductance, and pulse volume. Learners' mental states were divided into nine categories in accordance with the Achievement Emotions Questionnaire. In our experiment, the system achieved a high accuracy in predicting the learner's mental states from the teacher's speech acts and the learner's physiological information. A mock-up experiment was then conducted, which revealed that the system's interface was able to support teaching and learning in real time.

本文言語English
ホスト出版物のタイトルICCE 2018 - 26th International Conference on Computers in Education, Main Conference Proceedings
編集者Ma. Mercedes T. Rodrigo, Jie-Chi Yang, Lung-Hsiang Wong, Maiga Chang
出版社Asia-Pacific Society for Computers in Education
ページ107-109
ページ数3
ISBN(電子版)9789869401289
出版ステータスPublished - 2018 11 24
イベント26th International Conference on Computers in Education, ICCE 2018 - Metro Manila, Philippines
継続期間: 2018 11 262018 11 30

出版物シリーズ

名前ICCE 2018 - 26th International Conference on Computers in Education, Main Conference Proceedings

Other

Other26th International Conference on Computers in Education, ICCE 2018
CountryPhilippines
CityMetro Manila
Period18/11/2618/11/30

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computer Science Applications
  • Education

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