Temporally-focused analytics of self-regulated learning: A systematic review of literature

We present a systematic literature review of data-driven self-regulated learning (SRL) that emphasises the methodological importance temporality and sequence, as opposed to conventional statistical analysis. Researchers seem unanimous in their view SRL modern online blended educational settings; this is borne out by number reviews on subject. There has, yet, been no treatment context its conceptualisation phenomenon unfolds sequences over time. To address limitation, explores corpus work (n = 53) which related dimensions are analysed through lenses temporality, sequence order. The results show that, pursuit validity impact, key decisions need be addressed regard theoretical grounding, data collection, analytic methods. Based these outcomes, we propose framework directives questions aid researchers who want push forward field. This comprises four sub-areas: i) considerations, relating capture processes; ii) usage models dimensions; iii) robustness chosen outcomes studied; iv) temporal articulation sequence.