Self-regulated learning (SRL) can predict academic performance. Yet, it is difficult for
learners. The ability to self-regulate learning becomes even more important in emerging …

The ability to predict student performance in a course or program creates opportunities to
improve educational outcomes. With effective performance prediction approaches …

Adaptive e-learning is viewed as stimulation to support learning and improve student
engagement, so designing appropriate adaptive e-learning environments contributes to …

Several challenges are associated with e‐learning systems, the most significant of which is
the lack of student motivation in various course activities and for various course materials. In …

The use of analytic methods for extracting learning strategies from trace data has attracted
considerable attention in the literature. However, there is a paucity of research examining …

Background During the past decade, the increasingly heterogeneous field of learning
analytics has been critiqued for an over‐emphasis on data‐driven approaches at the …

This paper aims to identify self-regulation strategies from students' interactions with the
learning management system (LMS). We used learning analytics techniques to identify …

Research background: The COVID-19 pandemic has affected higher education globally and
disrupted its usual activities, according to differing perspectives. The ability to adapt to online …

Pre-class preparedness is critical to students' in-class learning and overall success in the
flipped classroom. This study used both trace data and self-report data to identify students' …

With the increased emphasis on the benefits of self-regulated learning (SRL), it is important
to make use of the huge amounts of educational data generated from online learning …