Connectivism: Its place in theory-informed research and innovation in technology-enabled learning


  • Frances Bell University of Salford



theory, learning, implementation, research, evaluation, connectivism, actor network theory, social shaping of technology, activity theory, zone of proximal development, change management


The sociotechnical context for learning and education is dynamic and makes great demands on those trying to seize the opportunities presented by emerging technologies. The goal of this paper is to explore certain theories for our plans and actions in technology-enabled learning. Although presented as a successor to previous learning theories, connectivism alone is insufficient to inform learning and its support by technology in an internetworked world. However, because of its presence in massive open online courses (MOOCs), connectivism is influential in the practice of those who take these courses and who wish to apply it in teaching and learning. Thus connectivism is perceived as relevant by its practitioners but as lacking in rigour by its critics. Five scenarios of change are presented with frameworks of different theories to explore the variety of approaches educators can take in the contexts for change and their associated research/evaluation. I argue that the choice of which theories to use depends on the scope and purposes of the intervention, the funding available to resource the research/evaluation, and the experience and philosophical stances of the researchers/practitioners.

Author Biography

Frances Bell, University of Salford

Frances is a Senior Lecturer in Salford Business School whose teaching and research interest lie in information systems and emerging technologies. She has published extensively in journals and conferences and is currently co-editor of Research in Learning Technology (formerly ALT-J).



How to Cite

Bell, F. (2011). Connectivism: Its place in theory-informed research and innovation in technology-enabled learning. The International Review of Research in Open and Distributed Learning, 12(3), 98–118.