Data models built for analyzing student data often obfuscate temporal relationships for reasons of simplicity, or to aid in generalization. We present a model based on temporal relationships of heterogeneous data as the basis for building predictive models. We show how within- and between-semester temporal patterns can provide insight into the…

Programming is a complex learning activity that involves coordination of cognitive processes and affective states. These aspects are often considered individually in computing education research, demonstrating limited understanding of how and when students learn best. This issue confines researchers to contextualize evidence-driven outcomes when…

This study investigates how multimodal user-generated data can be used to reinforce learner reflection, improve teaching practices, and close the learning analytics loop. In particular, the aim of the study is to utilize user gaze and action-based data to examine the role of a mirroring tool (i.e., Exercise View in Eclipse) in orchestrating basic…

Lecture videos are amongst the most widely used instructional methods within present Massive Open Online Courses (MOOCs) and other digital educational platforms. As the main form of instruction, student engagement behaviour, including interaction with videos, directly impacts the student success or failure and accordingly, in-video dropouts…