Authors:
Shereif Eid
and
Gábor Kismihók
Affiliation:
Learning and Skills Analytic Group, Leibniz Center for Technology and Natural Sciences, Hannover, Germany
Keyword(s):
Socio-technical, e-Learning, Social Learning, Social Media Networks, Recommendation Systems.
Abstract:
We describe XEL-Group Learning, a socio-technical framework for socially oriented e-learning. The aim of the presented framework is to address the lack of holistic pedagogical solutions that take into account motivational theories, socio–technical factors, and cultural elements in social learning networks. The presented framework provides initiatives for collaboration by providing a dynamic psycho-pedagogical recommendation mechanism with validation properties. In this paper, we begin by highlighting the socio-technical concept associated with socially-oriented e-learning. Next, we describe XEL-GL’s main mechanisms such as group formation and the semantic matching framework. Moreover, through semantic similarity measurements, we show how cultural elements, such as the learning subject, can enhance the quality of recommendations by allowing for more accurate predictions of friends networks.