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Conceptualization of IMS that Estimates Learners’ Mental States from Learners’ Physiological Information Using Deep Neural Network Algorithm

  • Tatsunori MatsuiEmail author
  • Yoshimasa Tawatsuji
  • Siyuan Fang
  • Tatsuro Uno
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11528)

Abstract

To improve the efficiency of teaching and learning, it is substantially important to know learners’ mental states during their learning processes. In this study, we tried to extract the relationships between the learner’s mental states and the learner’s physiological information complemented by the teacher’s speech acts using machine learning. The results of the system simulation showed that the system could estimate the learner’s mental states in high accuracy. Based on the construction of the system, we further discussed the concept of IMS and the necessary future work for IMS development.

Keywords

Intelligent mentoring system Physiological information Deep neural network 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Tatsunori Matsui
    • 1
    Email author
  • Yoshimasa Tawatsuji
    • 1
  • Siyuan Fang
    • 2
  • Tatsuro Uno
    • 3
  1. 1.Faculty of Human SciencesWaseda UniversityTokorozawaJapan
  2. 2.Global Education CenterWaseda UniversityShinjukuJapan
  3. 3.School of Human SciencesWaseda UniversityTokorozawaJapan

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