Predicting the Well-functioning of Learning Groups under Privacy Restrictions

Abstract

Establishing small learning groups in online courses is a possible way to foster collaborative knowledge building in an engaging and effective learning community. To enable group activities it is not enough to design collaborative tasks and to provide collaboration tools for online scenarios. Collaboration in such learning groups is prone to fail or even not to be initiated without explicit guidance. In the target situations, interventions and guiding mechanisms have to scale with a growing number of course participants. To achieve this under privacy constraints, we aim at identifying target indicators for well-functioning group work that do not rely on any kind of information about individual learners.