Member
Martin Hlosta
Research Fellow
+44 (0)1908 332292
In KMi, I work as a Research Fellow acting as a technical lead and a data scientist of OU Analyse Project (https://analyse.kmi.open.ac.uk). The project is focused on improving student retention at Open University using machine learning techniques. I am exploring how to best use OUAnalyse to teachers (Associate Lecturers) in order to better use data and analytics for improving student outcomes. Moreover, I am responsible fore design and the development of the Curriculum Analytics Tool (CAT) - the tool has been deployed in 2017 to help in the curriculum review. It is expected to facilitate data-informed decisions on the curriculum and finance planning in the future.
Keys: OU Analyse Project, Machine Learning, CAT (Curriculum Analytics Tool)
Team: Vaclav Bayer, Stephane Carpenter, Miriam Fernandez, Zdenek Zdrahal
News
05 Jul 2021
29 Jun 2021
30 Sep 2020
01 May 2020
30 Apr 2020
Publications
Bayer, V., Hlosta, M. and Fernandez, M. (2021) Learning Analytics and Fairness: Do Existing Algorithms Serve Everyone Equally?, AIED 2021; 22nd International Conference on Artificial Intelligence in Education, ONLINE from Utrecht
Hlosta, M., Herodotou, C., Fernandez, M. and Bayer, V. (2021) Impact of Predictive Learning Analytics on Course Awarding Gap of Disadvantaged students in STEM, Artificial Intelligence in Education, AIED 2021, Online / Utrecht, NL
Rets, I., Herodotou, C., Bayer, V., Hlosta, M. and Rienties, B. (2021) Exploring critical factors of the perceived usefulness of a learning analytics dashboard for distance university students, pp. (In Press)
Herodotou, C., Maguire, C., McDowell, N., Hlosta, M. and Boroowa, A. (2021) The engagement of university teachers with predictive learning analytics
Hlosta, M., Papathoma, T. and Herodotou, C. (2020) Explaining Errors in Predictions of At-Risk Students in Distance Learning Education, International Conference on Artificial Intelligence in Education, online
