Date: 18 March 2015
Authors: Jakub Kuzilek, Martin Hlosta, Drahomira Herrmannova, Zdenek Zdrahal, Jonas Vaclavek and Annika Wolff
Citation: Kuzilek, J., Hlosta, M., Herrmannova, D., Zdrahal, Z. and Wolff, A., LAK15 Case Study 1: OU Analyse: Analysing At-Risk Students at The Open University, Learning Analytics Review, no. LAK15-1, March 2015, ISSN: 2057-7494. http://www.laceproject.eu/learning-analytics-review/analysing-at-risk-students-at-open-university/
Short link (for use in Twitter): http://bit.ly/lace-review-lak15-1
The OU Analyse project aims at providing early prediction of ‘at-risk’ students based on their demographic data and their interaction with Virtual Learning Environment. Four predictive models have been constructed from legacy data using machine learning methods. In Spring 2014 the approach was piloted and evaluated on two introductory university courses with about 1,500 and 3,000 students, respectively. Since October 2014 the predictions have been extended to include 10+ courses of different level. The OU Analyse dashboard has been implemented, for presenting predictions and providing a course overview and a view of individual students.
This case study has been published as part of the practitioner track of the Learning Analytics and Knowledge conference LAK15, Scaling Up: Big Data to Big Impact held in Marist College, New York on 16-20 March 2015.
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