Abstract
Massive open online courses (MOOCs) offer unprecedented opportunities to learn at scale. For those engaged in learning analytics and educational data mining, MOOCs have provided an exciting opportunity to develop innovative methodologies that harness big data in education. This chapter argues that in order to capture learning in mass-scale crowd-based environments, a mixed method approach is required, which combines data mining with a wide set of social science techniques that are primarily qualitative in nature. These include observation, interviews, and surveys, more traditionally used in education research. The chapter discusses a constructive way of addressing the issue of mixed method research by adopting a pragmatic paradigm, where the primary attention is given to the research question asked, as opposed to holding a particular allegiance to a philosophy or methodology when carrying out the research. As the hype around MOOCs begins to fall away, research opportunities remain very rich both for online education and beyond.
Original language | English |
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Title of host publication | Data Mining And Learning Analytics |
Subtitle of host publication | Applications in Educational Research |
Publisher | Wiley-Blackwell |
Pages | 207-221 |
Number of pages | 15 |
ISBN (Electronic) | 9781118998205 |
ISBN (Print) | 9781118998236 |
DOIs | |
Publication status | Published - 14 Oct 2016 |
Keywords
- Communication patterns
- Data mining
- Massive open online courses
- Mixed method approach
- Pragmatic paradigm
- Qualitative methods
- Social science techniques