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).