Educational data mining is a developing research trend for exploring hidden patterns and natural associations among a set of student, teacher or school related variables. Discovering profiles of preservice science teachers using data mining methods would give important information about quality of teacher education programs and future science…

For decades, self-report instruments -- which rely heavily on students' perceptions and beliefs -- have been the dominant way of measuring motivation and strategy use. Event-based measures based on online trace data arguably has the potential to remove analytical restrictions of self-report measures. The purpose of this study is therefore to…

This study has two central purposes: First, it examines not only the roles of gender and persistence in undergraduate computing majors' learning self-efficacy, computer self-efficacy, and programming self-efficacy but also Bandura's hypothesized sources of self-efficacy; second, it examines the influence of sources of efficacy on the three…

Self-regulated learning theories are used to understand the reasons for different levels of university student academic performance. Similarly, learning analytics research proposes the combination of detailed data traces derived from technology-mediated tasks with a variety of algorithms to predict student academic performance. The former approach…