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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.

Classification of Educational Skills for University Students in Computer Programming Classes