Designing a Learning Condition Diagnosing System Using Mental and Physical Health Information

Brief Paper (Asynchronous) ID: 62219
  1. aaa
    Masahiro Nagai
    Tokyo Metropolitan University
  2. aaa
    Noriyuki Matsunami
    Teikyo University

Abstract: Guidance for living considers problems such as moral or ethical issues and pro- or antisocial behaviors. Due to COVID-19, an increasing number of students cannot adapt to their new lifestyles and complain of mental stress and physical ailments. Therefore, we are developing and evaluating the “E-health Observation System” to quickly and easily grasp the students’ physical and mental conditions to use in the Guidance for living. In this research, we will develop the “Learning Condition Diagnosing System” (LCDS), which includes an E-health system and diagnoses learning conditions based on data such as mental and physical conditions and results provided by E-health observations. Students’ data will be statistically processed by multi-regression analysis or machine learning using artificial intelligence (AI), and students can obtain their learning conditions diagnoses. In this paper, we discuss the design of the LCDS and the results of a preliminary experiment to create the learning condition indicators.

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