A MOOC Taxonomy Based on Classification Schemes of MOOCs

Tharindu R. Liyanagunawardena 1 , Karsten Lundqvist 2 , Richard Mitchell 3 , Steven Warburton 4  and Shirley A. Williams 5
  • 1 University College of Estate Management, , RG1 4BS, Reading
  • 2 Victoria University of Wellington, , 6140, Wellington, New Zealand
  • 3 University of Reading, Department of Computer Science, RG6 6AY, Reading
  • 4 Victoria University of Wellington, , 6140, Wellington, New Zealand
  • 5 Department of Computer Science, University of Reading, RG6 6AY, Reading


In recent years there has been a significant growth in the number of online courses known as MOOCs available via online providers such as edX and Coursera. The result has been a marked reduction in the clarity around the different course offerings and this has created a need to reconsider the classification schemes for MOOCs to help inform potential participants. Many classifications have been proposed which cover the needs of academics and providers but may not be suitable for learners choosing a course. In this paper, the various classifications used by MOOC providers and aggregator services to categorise MOOCs in presenting information to prospective learners are gathered and analysed. As a result, 13 different categories are identified, which cover information provided to learners before entering a course. These categories are then compared and combined with classifications from the literature to create a taxonomy centred round eight terms: Massive (e.g. enrolments), Open (e.g. pre-requisites), Online (e.g. Timings), Assessment, Pedagogy (e.g. instructor-led), Quality (e.g. reviews), Delivery (e.g. educators), Subject (e.g. Syllabus). Thus, producing a taxonomy capable of categorising MOOCs from a wider perspective.

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