Application of computational intelligence based clustering algorithms on educational data

Abstract

Contemporary research, especially in the academic community, focuses on the increasingly frequent application of artificial intelligence (AI) in learning and teaching processes, but also on all the benefits and disadvantages that it brings with it. This study was conducted in order to examine the application of computational intelligence (CI) methods on educational data. The main goal of the paper is to group students according to similarity with the aim to analyse each group in details. Data was collected via questionnaire among students enrolled at three universities in three different countries. It represents students' opinion on the use of AI in education. Using k-medoids, self-organized maps (SOM) and fuzzy C means (FCM), two groups of students were identified according to the use of AI in learning process as the most important attribute.