How to Cluster Students Based on Their Digital Competence for Learning?

Abstract

Finding the most relevant and effective teaching and learning methods is one of the core challenges in education. As the educational community is valuing personalized learning, student clustering for better outcomes is relevant. Therefore, the aim of the current study is to identify student clusters according to their level of digital competence for learning. 268 students (grades 3–8) from four schools in Estonia participated in the study and completed a test for assessing their digital competence for learning in ten dimensions. Four student clusters were identified using hierarchical cluster analysis: programmers, creators, casual users and beginners. The clusters were determined mainly by operational and programming skills. As all the students had rather positive attitudes towards using digital devices for learning, the levels of skills and knowledge ranged from very low to high. The results might be useful in designing long-term studies for monitoring the development of digital competence for learning throughout primary and lower secondary school. Furthermore, it is evidently clear from the findings that students do need tailored support in order to improve their digital competence for learning.