Student rules: exploring patterns of students\u27 computer-efficacy and engagement with digital technologies in learning

Teachers\u27 beliefs about students\u27 engagement in and knowledge of digital technologies will affect technologically integrated learning designs. Over the past few decades, teachers have tended to feel that students were confident and engaged users of digital technologies, but there is a growing body of research challenging this assumption. Given this disparity, it is necessary to examine students\u27 confidence and engagement using digital technologies to understand how differences may affect experiences in technologically integrated learning. However, the complexity of teaching and learning can make it difficult to isolate and study multiple factors and their effects. This paper proposes the use of data mining techniques to examine unique patterns among key factors of students\u27 technology use and experiences related to learning, as a way to inform teachers\u27 practice and learning design. To do this, association rules mining and fuzzy representations are used to analyze a large student questionnaire dataset (N = 8817). Results reveal substantially different patterns among school engagement and computer-efficacy factors between students with positive and negative engagement with digital technologies. Findings suggest implications for learning design and how teachers may attend to different experiences in technologically integrated learning and future research in this area