We present a systematic literature review of data-driven self-regulated learning (SRL) that
emphasises the methodological importance of temporality and sequence, as opposed to …

Self-regulated learning (SRL) is a cyclical process through which individuals plan their
objectives, execute them and self-evaluate their own behavior so as to obtain their proposed …

Most work in the design of learning technology uses click-streams as their primary data
source for modelling & predicting learning behaviour. In this paper we set out to quantify …

Contemporary research that looks at self-regulated learning (SRL) as processes of learning
events derived from trace data has attracted increasing interest over the past decade …

Abstract MOOCs (Massive Open Online Courses) have usually high dropout rates. Many
articles have proposed predictive models in order to early detect learners at risk to alleviate …

The importance of learning design in education is widely acknowledged in the literature.
Should learners make effective use of opportunities provided in a learning design …

Background Select and enact appropriate learning tactics that advance learning has been
considered a critical set of skills to successfully complete highly flexible online courses, such …

The advancement of learning analytics has enabled the development of predictive models to
forecast learners' behaviors and outcomes (eg, performance). However, many of these …

The recent focus on learning analytics (LA) to analyze temporal dimensions of learning
holds the promise of providing insights into latent constructs, such as learning strategy, self …

Compared to traditional classroom learning, success in online learning tends to depend
more on the learner's skill to self-regulate. Self-regulation is a complex meta-cognitive skill …