Brooks, Christopher

Dawson, Shane

Dowell, Nia

Gasevic, Dragan

Graesser, Arthur

Joksimovic, Srecko

Kovanovic, Vitomir

Mills, Caitlin

Poquet, Oleksandra

English

Despite a surge of empirical work on student participation in online learning environments, the causal links between the learning-related factors and processes with the desired learning outcomes remain unexplored. This study presents a systematic literature review of approaches to model learning in Massive Open Online Courses offering an analysis of learning related constructs used in the prediction and measurement of student engagement and learning outcome.Based on our literature review, we identify current gaps in the research, including a lack of solid frameworks to explain learning in open online setting. Finally, we put forward a novel framework suitable for open online contexts based on a well-established model of student engagement. Our model is intended to guide future work studying the association between contextual factors (i.e., demographic, classroom, and individual needs), student engagement (i.e.,academic, behavioral, cognitive, and affective engagement metrics) and learning outcomes (i.e.,academic, social, and affective). The proposed model affords further inter-study comparisons as well as comparative studies with more traditional education models

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How do we model learning at scale?:A systematic review of research on MOOCs

https://www.research.ed.ac.uk/files/45220544/JoksimovicEtalRER2017HowDoWeModelLearningAtScale.pdf

How do we model learning at scale?:A systematic review of research on MOOCs

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