Personal learning networks with open learning groups - A formal approach

A continuous trend of the past decade has shifted educational responsibility to individuals, while elaborate Internet technologies have fostered easy and open ways to content and communication in a location- and time-independent manner. Personal Learning Networks (PLNs) have emerged as a new paradigm within the context of network-centric learning. While interacting with others interested in the same topic, learners create networks that interrelate elements of information and communication. These networks form a space for exchanging learning content and for collaboration. Our work is centered on learning in Online Social Networks (OSNs), focussing on the core mechanisms to establish group formation and content recommendation. In this paper, we characterize this specific approach to PLNs from a formal perspective and transfer these findings to our eLearning-enabled Online Social Network. The network consists of a multi-entity graph that represents users as well as all relevant eLearning and communication objects. Based on this context-rich graph, we derive a content recommendation algorithm to aid learning groups with relevant content elements.