doi: 10.18178/ijiet.2021.11.4.1505
Development of Online Learning Material for Data Science Programming Using 3D Puzzle
Naoki Yamamoto
,
Akio Ishida ,
Kazuki Ogitsuka ,
Nobuhiro Oishi ,
Jun Murakami
- Kumamoto College, National Institute of Technology, Koshi, Japan
Abstract
In multidimensional data processing, one of the important data structures is a higher-order tensor or a multidimensional array. In general, the processing related to the higher-order tensor is so complicated that we have been developing understanding support tools for it using 3D puzzles from the viewpoint of making students interested. However, although these tools have been tried by students in graduation studies and other some occasions, their introduction into lectures was one issue. Therefore, in this study, we developed a new programming exercise material for the higher-order tensor, which is supposed to be used in data science subjects, by using a 3D puzzle. This learning material is also composed of Microsoft Teams, and students can access the material remotely to learn programming. In this paper, several students actually tried this material. As a result, it was found that the students themselves could create and submit assignment reports by viewing explanatory videos and performing exercises. From this, it is expected that this material will be able to introduce to data science courses, including online use.
Keywords
- Higher-order tensor
- 3D puzzle
- data science education
- R
- programing materials
- remote exercise
How to Cite
Naoki Yamamoto, Akio Ishida, Kazuki Ogitsuka, Nobuhiro Oishi, and Jun Murakami, "Development of Online Learning Material for Data Science Programming Using 3D Puzzle," International Journal of Information and Education Technology, vol. 11, no. 4, pp. 154-163, 2021. https://doi.org/10.18178/ijiet.2021.11.4.1505
Copyright & License
Copyright © 2021 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).