Learning Style Analysis on an Online Course by Structural Equation Modeling

Authors

  • Keisuke Nakagawa Japan Advanced Institute of Science and Technology
  • Koichi Ota
  • Wen Gu
  • Shinobu Hasegawa Japan Advanced Institute of Science and Technology

DOI:

https://doi.org/10.52731/liir.v003.063

Keywords:

learning style, online lectures, structural equation modeling

Abstract

This study analyzes learning styles for an online course with flipped learning employing structural equation modeling. First, we discuss the definition of learning style in this study and design a structural equation model of the learning style. Next, we obtain data via LMS for 94 students (53 Japanese and 41 International students) attending the machine learning course offered in Japanese and evaluate the validity of the structural equation model. Furthermore, we compare the structural equation models in terms of groups for students' language abilities, prior knowledge of the course, and learning motivation to compare the characteristics of each group.

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Published

2023-02-17