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.
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Acknowledgements
We would like to thank the ICT class students who cooperated in this questionnaire. Without their participation this paper would not have been possible. Further, we would also like to express our gratitude to our faculty who took the time from their busy schedule to participate in the questionnaire survey.
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Taniguchi, T., Maruyama, Y., Kurita, D., Tanaka, M. (2019). Classification of University Students Attending Computing Classes Using a Self-assessment Questionnaire. In: Uskov, V., Howlett, R., Jain, L. (eds) Smart Education and e-Learning 2019. Smart Innovation, Systems and Technologies, vol 144. Springer, Singapore. https://doi.org/10.1007/978-981-13-8260-4_3
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DOI: https://doi.org/10.1007/978-981-13-8260-4_3
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