eSTEeM

Centre for Scholarship and Innovation

Supporting students

An investigation into the use of Artificial Neural Networks to predict student failure, and the efficacy of sustainable additional support for those students

John Woodthorpe

The project analysed Virtual Learning Enviornment (VLE) data with Artificial Neural Networks (ANNs), in order to identify patterns of behaviour that correlate with the likelihood of a student failing the End of Module Assessment (EMA).

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SDK125 Student Intentions and Retention Study

Basiro Davey

SDK125 (Introducing health sciences) registrations have increased from <400 students in 2007 to a combined total of >2,000 in dual presentations in 2012/13, but in the last two years, retention has inexplicably fallen from previous sustained levels around the Science average rate.

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Developing practice in online synchronous tuition by peer observation, feedback and reflection

Mark Jones

An issue in adoption of online synchronous tutorials (such as OU Live) is that training and development tends to focus on technical usage rather than reflection on teaching practice.

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