Abstract
This chapter explores cognitive load theory (CLT) in the context of networked learning (NL). CLT supports NL practitioners’ efforts to understand and eliminate barriers to learning in NL situations. The premise is that by recognising unnecessary cognitive load in NL, educators can improve learners’ abilities to acquire and develop schema and, in doing so, support learning in NL situations. The chapter is structured into three main sections. The first section provides the background to the exploration of CLT in the context of NL. It includes an overview of CLT and its development, an overview of NL and a definition of the problem. The second section explores common features of NL and identifies potential sources of cognitive load in NL situations. It is organised according to the key features of NL ‘architecture’: the learning environment, learning tasks and learner activity. The third section identifies a potential research agenda to guide further explorations of CLT in NL including: research into technical aspects of NL to improve the presentation of information and computer interfaces, research into the use of instructional design techniques sympathetic to CLT and specifically targeting NL and engagement tasks and research to understand learning to learn online in NL from a CLT perspective.
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Kehrwald, B.A., Bentley, B.P. (2020). Understanding and Identifying Cognitive Load in Networked Learning. In: Dohn, N., Jandrić, P., Ryberg, T., de Laat, M. (eds) Mobility, Data and Learner Agency in Networked Learning. Research in Networked Learning. Springer, Cham. https://doi.org/10.1007/978-3-030-36911-8_7
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