Prediction of Learning Success Via Rate of Events in Social Networks for Education


The widespread use of computing and communications technologies has enabled the popularity of social networks oriented to learn. Earlier studies have shown the power of online learning systems data to develop prediction methods that try to identify successful students patterns of accomplishment and engagement to allow timely pedagogical interventions. Our learning platform, SocialWire, collects a detailed record of the students’ activity so, in this paper, we compare and combine the power of different statistical learning techniques , using some of the features recorded as predictors of learning success or failure.

Proceedings of the 10th International Conference on Computer Supported Education, Funchal, Portugal