Sanal Öğrenme Ortamlarındaki Öğrenci Davranışlarının Kümeleme Yöntemi İle Analiz Edilmesi

Abstract

Virtual learning environments offer a wide range of opportunities for educators and students, providing the appropriate tools for managing the learning process and ensuring that students are responsible for their own learning. Despite all these opportunities, even within the same educational institution, it is seen that virtual learning environments are not used effectively. In this experimental research, in Atilim University, Ankara where Moodle is used as a virtual learning environment, the use of the environment by the users is analyzed by data mining techniques using clustering algorithms, and it is determined which are preferred or less preferred components in the environment. The research was conducted on 131 students who attended the Introduction to Computers and Information Systems course at a university in Ankara. During the practicing process, the students took a face to face course per week and the rest of the course in the Moodle virtual learning environment at the same time by the blended learning approach. In the analysis of the data, it was determined how the students were distributed according to their satisfaction with the virtual learning environment, computer anxiety and academic achievement by using k-means analysis from clustering algorithms. In addition, according to this distribution, the use of activity in the virtual learning environment is evaluated whether there is a difference between them.