Comparing attrition prediction in FutureLearn and edX MOOCs
Cobos, Ruth, Wilde, Adriana and Zaluska, Ed (2017) Comparing attrition prediction in FutureLearn and edX MOOCs At FutureLearn Workshop in Learning Analytics and Knowledge 2017 (LAK17), Canada. 13 - 17 Mar 2017. 20 pp.
- Accepted Manuscript
Restricted to Repository staff only until 11 March 2017.
Available under License University of Southampton Accepted Manuscript Licence.
There are a number of similarities and differences between FutureLearn MOOCs and those offered by other platforms, such as edX. In this research we compare the results of applying machine learning algorithms to predict course attrition for two case studies using datasets from a selected FutureLearn MOOC and an edX MOOC of comparable structure and themes. For each we have computed a number of attributes in a pre-processing stage from the raw data available in each course. Following this, we applied several machine learning algorithms on the pre-processed data to predict attrition levels for each course. The analysis suggests that the attribute selection varies in each scenario, which also impacts on the behaviour of the predicting algorithms.
|Item Type:||Conference or Workshop Item (Paper)|
|Venue - Dates:||FutureLearn Workshop in Learning Analytics and Knowledge 2017 (LAK17), Canada, 2017-03-13 - 2017-03-17
|Organisations:||Web & Internet Science|
|Date Deposited:||02 Feb 2017 11:16|
|Last Modified:||28 Apr 2017 02:53|
|Further Information:||Google Scholar|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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