Design of a conceptual knowledge extraction framework for a social learning environment based on Social Network Analysis methods

The advent of social media in education has the potential to foster collaborative learning. Exploring students' interactions on the social media tools is an important research direction, which could bring an insight into the collaborative learning process. Therefore, our aim is to propose a conceptual framework for knowledge extraction and visualization from a social media-based learning environment. In particular, we focus on our in-house platform, called eMUSE, which has been successfully used in a project-based learning scenario. The paper addresses the construction of a social graph starting from students' interactions on the social media tools; the objective is to identify appropriate social network analysis techniques that can answer specific educational needs and integrate them in a conceptual knowledge extraction framework. The basis, rationale and analysis levels of the framework are discussed in the paper.