Purpose: Within higher education, there was an abrupt shift from face-to-face to online lecturing with the introduction of social distancing measures in light of a global pandemic. The purpose of this study is to enrich the connection between students and instructors, the authors integrated elaborated interactive activities into large online…

The large-scale and granular interaction data collected in online learning platforms such as massive open online courses (MOOCs) provide unique opportunities to better understand individuals' learning processes and could facilitate the design of personalized and more effective support mechanisms for learners. In this paper, we present two…

The big data imposes the key problem of generalizability of the results. In the present contribution, we discuss statistical tools which can help to select variables adequate for target level of abstraction. We show that a model considered as over-fitted in one context can be accurate in another. We illustrate this notion with an example analysis…

Current schemes to categorise MOOC students result from a single view on the population which either contains the engagement of the students or demographics or self reported motivation. We propose a new hierarchical student categorisation, which uses common online activities capturing both engagement and achievement of MOOC students. A first level…

Research suggests that massive open online course (MOOC) students prefer to study in groups, and that social facilitation within the study groups may render the learning of difficult concepts a pleasing experience. We report on a longitudinal study that investigates how co-located study groups watch and study MOOC videos together. The study was…