Relational event models for social learning in MOOCs

The empirical value of new extensions is demonstrated through an analysis of social learning in Massive Open Online Courses (MOOCs). In particular, three modeling problems are considered from the network perspective: (1) the utility of social factors, performance indicators, and clickstream behaviors in the prediction of course dropout, (2) the social and temporal structure of learner interactions across discussion threads, and (3) the forms of mutual dependence of social learning interactions on prior learning success, and future learning success on forms of prior social learning interaction.