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Classification of University Students Attending Computing Classes Using a Self-assessment Questionnaire

Authors :
Yukiko Maruyama
Tadanari Taniguchi
Makoto Tanaka
Daisaku Kurita
Source :
Smart Education and e-Learning 2019 ISBN: 9789811382598
Publication Year :
2019
Publisher :
Springer Singapore, 2019.

Abstract

The aim of the present paper is to analyze the results of a self-assessment questionnaire meant to classify students attending ICT classes using clustering methods. The questionnaire survey consisted of 25 educational skills and was conducted in Tokai University using a computer-assisted web-interviewing technique both before and after participants attended ICT classes. The questionnaire results were analyzed using an agglomerative hierarchical clustering based on Ward’s method and a self-organizing map. The findings of the present paper show that students attending ICT classes could be classified into several groups based on the classes they attended and their respective academic faculties.

Details

Database :
OpenAIRE
Journal :
Smart Education and e-Learning 2019 ISBN: 9789811382598
Accession number :
edsair.doi...........23fac1eec702261f0c46cc670b2d2527
Full Text :
https://doi.org/10.1007/978-981-13-8260-4_3