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IJIET 2021 Vol.11(7): 313-318 ISSN: 2010-3689
doi: 10.18178/ijiet.2021.11.7.1528

Classification of Educational Skills for University Students in Computer Programming Classes

Tadanari Taniguchi

Abstract—This paper analyzes the relationship of educational skills that students should achieve for each computer programming class using a student self-assessment questionnaire. The questionnaire survey, containing 25 educational skills, was conducted in computer programming classes in my university using a computer-assisted web-interviewing technique. The questionnaire results are analyzed using an agglomerative hierarchical clustering based on Ward’s method and a self-organizing map, which is a machine learning method. This study shows that the students can be classified into four clusters: highly skilled students, students with high learning and thinking skills but low executing skills, students with high leaning and executing skills but low thinking skills, and students with lower skills.

Index Terms—Educational skills, machine learning, questionnaire survey, self-organizing map.

T. Taniguchi is with IT Education Center, Tokai University, Hiratsuka, Kanagawa 2591292, Japan (e-mail: taniguchi@tokai-u.jp).


Cite: Tadanari Taniguchi, "Classification of Educational Skills for University Students in Computer Programming Classes," International Journal of Information and Education Technology vol. 11, no. 7, pp. 313-318, 2021.

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).

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 (Since 2019), INSPEC (IET), UGC-CARE List (India), EBSCO, Electronic Journals Library, Google Scholar, Crossref, etc.
  • E-mail: ijiet@ejournal.net

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