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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).

    December 2013 to March 2016

    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.

    July 2013 to July 2014

    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.

    August 2011 to February 2016

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