Affiliation:
1. The University of Auckland, New Zealand
2. The Open University, UK
Abstract
Massive open online courses (MOOCs) are described as disruptive and democratising. It is claimed MOOCs have characteristics that challenge traditional forms of education. This chapter critiques these claims, arguing that MOOCs do not always allow for the diverse motivations of masses of learners. This brings into question forms of data-based support based on and in response to learner behaviours. The chapter interrogates narrative accounts of MOOC learner experiences to pinpoint four distinct ways people learn in MOOCs. Factors critical to learning are motivation, self-regulation, environment and socialisation. Developing analytic tools that address these are important. However, analytics systems tend to personalise learner support in relation to pre-defined course goals, rather than focusing on the goals of the learner. Next generation systems are already focusing on empowering learners to follow their own goals and flexing course designs to fit the goals of each learner. These are more powerful than systems where the students have to adapt to a course designed for the masses.
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