Member
Vaclav Bayer
Technical Programme Manager
+44 (0)1908 858666
I am a Data Engineer at the OUAnalyse team and currently also a technical lead of the project. As a part-time PhD student, I am investigating how Learning Analytics can be used to target awarding gaps, which is a severe problem occurring in Higher Education institutions across the whole UK. My main focus is currently the development of an Equity, Diversity and Inclusion dashboard to spotlight awarding gaps across diverse groups of students within their modules and help understand the driving factors of awarding gaps.
Keys: Learning Analytics; Predictive Learning Analytics; Recommender Systems; Equity, Diversity and Inclusion; Research software development
Team: Miriam Fernandez, Martin Hlosta, Alba Morales Tirado, Paul Mulholland, Zdenek Zdrahal
News
10 Oct 2024
17 Sep 2024
16 Jul 2024
25 Jun 2024
08 Feb 2024
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, pp. (Early access)
Herodotou, C., Shrestha, S., Comfort, C., Fernandez, M., Andrews, H., Mulholland, P., Bayer, V., Maguire, C. and Lee, J. (2023) PVC-Challenges Response: A student facing dashboard for online undergraduate students
Bonnin, G., Bayer, V., Fernandez, M., Herodotou, C., Hlosta, M. and Mulholland, P. (2023) CERSEI: Cognitive Effort Based Recommender System for Enhancing Inclusiveness, 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, Aveiro, Portugal
Reyero Lobo, P., Mensio, M., Pavon Perez, A., Bayer, V., Kwarteng, J., Fernandez, M., Daga, E. and Alani, H. (2022) Estimating Ground Truth in a Low-labelled Data Regime: A Study of Racism Detection in Spanish, Workshop on Novel Evaluation Approaches for Text Classification Systems on Social Media (NEATCLasS), Atlanta, Georgia
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
