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.

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Description/Abstract

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
Related URLs:
Organisations: Web & Internet Science
ePrint ID: 405268
Date :
Date Event
20 January 2017Accepted/In Press
March 2017e-pub ahead of print
Date Deposited: 02 Feb 2017 11:16
Last Modified: 10 Jun 2017 04:03
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/405268

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