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IJIET 2022 Vol.12(3): 194-202 ISSN: 2010-3689
doi: 10.18178/ijiet.2022.12.3.1604

Development of Online Learning Materials for Tensor Data Processing Exercises

Shota Abe, Akio Ishida, Jun Murakami, and Naoki Yamamoto

Abstract—Tensor decomposition is used in a wide range of research fields; however, its theory is difficult to understand. Therefore, basic education is essential when using it in programming. Currently, there are few Japanese universities that provide education on tensor decomposition; however, some overseas universities have already conducted it, and online learning materials are also substantial. Therefore, in this paper, we have developed online learning materials for basics and programming exercises of higher-order singular value decomposition (HOSVD), which is one of tensor decomposition, for the purpose of increasing the learning materials for tensor decomposition education. Our learning material is created on Microsoft Teams, and students can access this material channel and work on exercises on demand while watching explanatory videos including CG animation. As a result of the trial of this learning material, it was found that the students who used it can generally understand the processes related to tensor decomposition and can perform basic programming of them.

Index Terms—Tensor decomposition, online learning materials, HOSVD, 3D puzzle, R language.

S. Abe is with Kumamoto College, National Institute of Technology, Koshi, Japan (e-mail: ae21abe@g.kumamoto-nct.ac.jp).
A. Ishida is with the Faculty of Liberal Arts, Kumamoto College, National Institute of Technology, Koshi, Japan (e-mail: ishida@kumamoto-nct.ac.jp).
J. Murakami and N. Yamamoto are with the Faculty of Electronics and Information Systems Engineering, Kumamoto College, National Institute of Technology, Koshi, Japan (e-mail: jun@kumamoto-nct.ac.jp, naoki@kumamoto-nct.ac.jp).

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Cite: Shota Abe, Akio Ishida, Jun Murakami, and Naoki Yamamoto, "Development of Online Learning Materials for Tensor Data Processing Exercises," International Journal of Information and Education Technology vol. 12, no. 3, pp. 194-202, 2022.

Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • ISSN: 2010-3689 (Online)
  • Abbreviated Title: Int. J. Inf. Educ. Technol.
  • Frequency: Monthly
  • DOI: 10.18178/IJIET
  • Editor-in-Chief: Prof. Dr. Steve Thatcher
  • Executive Editor: Ms. Nancy Y. Liu
  • Abstracting/ Indexing: Scopus (CiteScore 2021: 1.3), INSPEC (IET), UGC-CARE List (India), CNKI, EBSCO, Google Scholar
  • E-mail: ijiet@ejournal.net


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