RETAIN

Retaining Students through Intelligent Interventions

The RETAIN project aims to extend the Open University’s existing Business Intelligence systems, with a particular focus on improving student retention. RETAIN will make it possible to integrate additional data sources, such as data from VLE’s, with existing statistical methods and to further extend the functionality by using predictive modelling to identify students who are at risk of non-completion of their courses. This will allow for better targeted interventions towards these students. A demonstrator will be developed, for visualising retention data that allows viewing of both aggregated and individual student data on selected dimensions. This will be usable by tutors and programme managers for determining strategy in both the short-term and long-term, on individual, course and faculty levels. The developed tools and methods will be trialled with a view to longer term uptake and further extensions to Business Intelligence functionality. The predicted benefits are improved retention and progression, leading to a financial cost savings for the OU and a better student experience.

Chris Valentine

Wolff, A., Zdrahal, Z., Nikolov, A. and Pantucek, M. (2013) Improving retention: predicting at-risk students by analysing clicking behaviour in a virtual learning environment, Learning Analytics and Knowledge

Wolff, A., Zdrahal, Z., Herrmannova, D. and Knoth, P. (2013) Predicting Student Performance from Combined Data Sources, in eds. Alejandro Peña-Ayala, Educational Data Mining: Applications and Trends, 524, Springer

Wolff, A. and Zdrahal, Z. (2012) Improving retention by identifying and Supporting 'at-risk' students Case study for EDUCAUSE review online