Examination of Online Learning Strategies With Cluster Analysis

ABSTRACT

The aim of this study is to identify the learning strategies of students taking e‐courses in e‐learning environments using clustering algorithms, a data mining technique and to determine how these strategies are distributed according to the variables gender, class, faculty, computer and Internet usage level, and Internet usage time. The survey model was used in the study conducted in accordance with this objective. The data were collected using the Learning Strategies Scale designed for students taking distance education courses. The scale consists of 23 items and 5 sub‐dimensions: management of time and effort, use of complex cognitive strategies, use of simple cognitive strategies, contact with others, and academic thinking. The study involved 518 students taking online courses at a university. The data obtained were analysed and interpreted using descriptive statistics and cluster analysis. The study's results revealed that distance‐education students' learning strategies were generally inadequate. It was also found that those who used the Internet less, who owned a computer and who had a higher level of computer skills, as well as those who used web pages, tests, assignments, animation, and video tools, had more advanced distance‐ learning strategies.