Alumni Member
Martin Hlosta (Alumni) 
Visiting Fellow
I am a Visiting Research Fellow. Currenlty at Swiss Distance University of Applied Sciences
(Fernfachhochschule Schweiz – FFHS) - The Institute for
Research in Open, Distance and eLearning (IFeL) I spent 7 years in KMi, most recently as 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 was responsible for 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
Publications
Bayer, V., Mulholland, P., Hlosta, M., Farrell, T., Herodotou, C. and Fernandez, M. (2024). Co‐creating an equality diversity and inclusion learning analytics dashboard for addressing awarding gaps in higher education. British Journal of Educational Technology, 55(5), pp. 2058–2074. https://oro.open.ac.uk/98718/.
Bonnin, G., Bayer, V., Fernandez, M., Herodotou, C., Hlosta, M. and Mulholland, P. (2023). CERSEI: Cognitive Effort Based Recommender System for Enhancing Inclusiveness. In: 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, 4-8 Sep 2023, Aveiro, Portugal. https://oro.open.ac.uk/92414/.
Herodotou, C., Maguire, C., Hlosta, M. and Mulholland, P. (2023). Predictive Learning Analytics and University Teachers: Usage and perceptions three years post implementation. In: 13th International Learning Analytics and Knowledge Conference (LAK 2023), 13-17 Mar 2023, Arlington, Texas. https://oro.open.ac.uk/86454/.
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. International Journal of Educational Technology in Higher Education, 18(1), https://oro.open.ac.uk/77291/.
Hlosta, M., Herodotou, C., Fernandez, M. and Bayer, V. (2021). Impact of Predictive Learning Analytics on Course Awarding Gap of Disadvantaged students in STEM. In: Artificial Intelligence in Education, AIED 2021, 14-18 Jun 2021, Online / Utrecht, NL. https://oro.open.ac.uk/76042/.
Bayer, V., Hlosta, M. and Fernandez, M. (2021). Learning Analytics and Fairness: Do Existing Algorithms Serve Everyone Equally? In: AIED 2021; 22nd International Conference on Artificial Intelligence in Education, 14-18 Jun 2021, ONLINE from Utrecht. https://oro.open.ac.uk/76185/.
Hlosta, M., Bayer, V. and Zdrahal, Z. (2020). Mini Survival Kit: Prediction based recommender to help students escape their critical situation in online courses. In: Proceedings of the 10th International Conference on Learning Analytics and Knowledge (LAK20), 23-27 Mar 2020, Frankfurt am Main, Germany. https://oro.open.ac.uk/69302/.
Hlosta, M., Zdrahal, Z., Bayer, V. and Herodotou, C. (2020). Why Predictions of At-Risk Students Are Not 100% Accurate? Showing Patterns in False Positive and False Negative Predictions. In: Proceedings of the 10th International Conference on Learning Analytics and Knowledge (LAK20), 23-27 Mar 2020, Frankfurt am Main, Germany. https://oro.open.ac.uk/69150/.
Herodotou, C., Rienties, B., Hlosta, M., Boroowa, A., Mangafa, C. and Zdrahal, Z. (2020). The scalable implementation of predictive learning analytics at a distance learning university: Insights from a longitudinal case study. Internet and Higher Education, 45 https://oro.open.ac.uk/68953/.
Celik, D., Mikroyannidis, A., Hlosta, M., Third, A. and Domingue, J. (2019). ADA: A System for Automating the Learning Data Analytics Processing Life Cycle. In: EC-TEL 2019 14th European Conference on Technology Enhanced Learning, 16-19 Sep 2019, Delft, Netherlands. https://oro.open.ac.uk/62422/.
Herodotou, C., Hlosta, M., Boroowa, A., Rienties, B., Zdrahal, Z. and Mangafa, C. (2019). Empowering online teachers through predictive learning analytics. British Journal of Educational Technology, 50(6), pp. 3064–3079. https://oro.open.ac.uk/62192/.
Herodotou, C., Rienties, B., Boroowa, A., Zdrahal, Z. and Hlosta, M. (2019). A large-scale implementation of Predictive Learning Analytics in Higher Education: the teachers' role and perspective. Educational Technology Research and Development, 67(5), pp. 1273–1306. https://oro.open.ac.uk/62191/.
Hlosta, M., Kocvara, J., Beran, D. and Zdrahal, Z. (2019). Visualisation of key splitting milestones to support interventions. In: VISLA 2019: Workshop on Visual Approaches to Learning Analytics, 05 Mar 2019, Tempe, AZ, USA. https://oro.open.ac.uk/59341/.
Zdrahal, Z., Hlosta, M. and Kuzilek, J. (2016). Analysing performance of first year engineering students. In: Learning Analytics and Knowledge: Data literacy for Learning Analytics Workshop, 26 Apr 2016, Edinburgh. https://oro.open.ac.uk/58597/.
Huptych, M., Hlosta, M., Zdrahal, Z. and Kocvara, J. (2018). Investigating Influence of Demographic Factors on Study Recommenders. In: 19th International Conference on Artificial Intelligence in Education (AIED 2018) Artificial Intelligence in Education, 27-30 Jun 2018, London. https://oro.open.ac.uk/56293/.
Hlosta, M., Zdrahal, Z. and Zendulka, J. (2018). Are we meeting a deadline? classification goal achievement in time in the presence of imbalanced data. Knowledge-Based Systems, 160 pp. 278–295. https://oro.open.ac.uk/56292/.
Kuzilek, J., Hlosta, M. and Zdrahal, Z. (2017). Open University Learning Analytics dataset. Scientific Data, 4 https://oro.open.ac.uk/53873/.
Hlosta, M., Zdrahal, Z. and Zendulka, J. (2017). Ouroboros: early identification of at-risk students without models based on legacy data. In: LAK17 - Seventh International Learning Analytics & Knowledge Conference, 13-17 Mar 2017, Vancouver, BC, Canada. https://oro.open.ac.uk/49731/.
Huptych, M., Bohuslavek, M., Hlosta, M. and Zdrahal, Z. (2017). Measures for recommendations based on past students' activity. In: LAK17 Learning Analytics & Knowledge Conference, 13-17 Mar 2017, Vancouver, BC, Canada. https://oro.open.ac.uk/49661/.
Herodotou, C., Gilmour, A., Boroowa, A., Rienties, B., Zdrahal, Z. and Hlosta, M. (2017). Predictive modelling for addressing students’ attrition in Higher Education: The case of OU Analyse. In: CALRG Annual Conference 2017, 14-16 Jun 2017, The Open University, Milton Keynes, UK. https://oro.open.ac.uk/49470/.
