Conceptualization of IMS that estimates learners’ mental states from learners’ physiological information using deep neural network algorithm

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationIntelligent Tutoring Systems - 15th International Conference, ITS 2019, Proceedings
EditorsMaiga Chang, Andre Coy, Yugo Hayashi
PublisherSpringer-Verlag
Pages63-71
Number of pages9
ISBN (Print)9783030222437
DOIs
Publication statusPublished - 2019 Jan 1
Event15th International Conference on Intelligent Tutoring Systems, ITS 2019 - Kingston, Jamaica
Duration: 2019 Jun 32019 Jun 7

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11528 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Intelligent Tutoring Systems, ITS 2019
CountryJamaica
CityKingston
Period19/6/319/6/7

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Keywords

  • Deep neural network
  • Intelligent mentoring system
  • Physiological information

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Matsui, T., Tawatsuji, Y., Fang, S., & Uno, T. (2019). Conceptualization of IMS that estimates learners’ mental states from learners’ physiological information using deep neural network algorithm. In M. Chang, A. Coy, & Y. Hayashi (Eds.), Intelligent Tutoring Systems - 15th International Conference, ITS 2019, Proceedings (pp. 63-71). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11528 LNCS). Springer-Verlag. https://doi.org/10.1007/978-3-030-22244-4_9