Validating the effectiveness of the Moodle Engagement Analytics Plugin to predict student academic performance

Liu, Danny and Froissard, Chris and Richards, Deborah and Atif, Amara (2015) Validating the effectiveness of the Moodle Engagement Analytics Plugin to predict student academic performance. In: Twenty-first Americas Conference on Information Systems, August 13-15, 2015, Puerto Rico.

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Abstract

Given the focus on boosting retention rates and the potential benefits of pro-active and early identification of students who may require support, higher education institutions are looking at the data already captured in university systems to determine if they can be used to identify such students. This paper uses historical student data to validate an existing learning analytics tool, the Moodle Engagement Analytics Plugin (MEAP). We present data on the utility of the MEAP to identify students ‘at risk’ based on proxy measurements of online activity for three courses/units in three different disciplines. Our results suggest that there are real differences in the predictive power of the MEAP between different courses due to differences in the extent and structure of the learning activities captured in the learning management system.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Learning Analytics, Moodle Engagement Analytics Plugin, Academic Performance, Data Mining
Subjects:	Educational technology > Learning analytics Educational technology > Plugins
Divisions:	Higher education, Universities, Vocational training, Colleges
Depositing User:	Elizabeth Dalton
Date Deposited:	15 Dec 2016 05:01
Last Modified:	16 Dec 2016 01:52
URI:	http://research.moodle.org/id/eprint/148

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