The topics associated to the KMi publications listed in this page were automatically generated using the CSO Classifier, a solution developed by the SKM3 team in KMi. This technology has also been adopted by Springer Nature and is used routinely by them to generate automatically the metadata for all Computer Science conference proceedings they publish.
Kuzilek, J., Hlosta, M. and Zdrahal, Z. (2017). Open University Learning Analytics dataset. Scientific Data, 4 https://oro.open.ac.uk/53873/.
Herrmannova, D., Hlosta, M., Kuzilek, J. and Zdrahal, Z. (2015). Evaluating Weekly Predictions of At-Risk Students at The Open University: Results and Issues. In: EDEN 2015 Annual Conference Expanding Learning Scenarios: Opening Out the Educational Landscape, 9-12 Jun 2015, Barcelona, Spain. https://oro.open.ac.uk/44019/.
Kuzilek, J., Hlosta, M., Herrmannova, D., Zdrahal, Z., Vaclavek, J. and Wolff, A. (2015). OU Analyse: analysing at-risk students at The Open University. Learning Analytics Review, LAK15-1 pp. 1–16. https://oro.open.ac.uk/42529/.
Hlosta, M., Herrmannova, D., Vachova, L., Kuzilek, J., Zdrahal, Z. and Wolff, A. (2014). Modelling student online behaviour in a virtual learning environment. In: Machine Learning and Learning Analytics workshop at The 4th International Conference on Learning Analytics and Knowledge (LAK14), 24-28 March 2014, Indianapolis, Indiana, USA, 24-28 Mar 2014, Indianapolis, Indiana, USA. https://oro.open.ac.uk/40670/.
Wolff, A., Zdrahal, Z., Herrmannova, D., Kuzilek, J. and Hlosta, M. (2014). Developing predictive models for early detection of at-risk students on distance learning modules. In: Machine Learning and Learning Analytics Workshop at The 4th International Conference on Learning Analytics and Knowledge (LAK14), 24-28 Mar 2014, Indianapolis, Indiana, USA. https://oro.open.ac.uk/40669/.
