Dr. Jakub Kuzilek

Deutsch

Dr. Jakub Kuzilek Photo: Private

Dr. Jakub Kuzilek

Researcher at research professorship "Learning Science in Higher Education"

Email: jakub.kuzilek

Universitätsstraße 27 – PRG / Building 5
58097 Hagen

What is my role within CATALPA?

I am researcher focused on the educational data and their use for improving the learning processes and study experience. Thus, I am doing what I am best at – working with data, improving data flows and delivering AI driven solutions to improve retention, learning gain and to provide the useful insights on the learning processes.

Why CATALPA?

By my opinion, CATALPA is in unique position to deliver full-scale data-driven solutions to improve the education and learning at FernUniversität in Hagen. I believe that the data can change the way how we are teaching student, especially in online and distance learning settings. With 80.000-ish students there will be lot of information and space for the changing not just the learning at FernUniversität but also in the higher education sector in Germany. And I want to help with that.

    • PhD student in AI & Biocybernetics (CTU in Prague; 2009 – 2013)
    • Research associate in Learning Analytics & Educational Data Mining (KMi, OU, Milton Keynes; 2013 – 2017)
    • Research assistant & Researcher in AI in Education (CTU in Prague, 2010 – 2020)
    • Researcher in Learning Analytics & Educational Data Mining (CSES, HU Berlin, 2020 – 2025)

    • Educational Data Mining

    • Explainable AI

    • Machine Learning & Signal Processing

    • Learning Analytics

    • Learning Analytics infrastructures

    • Educational Technology

  • My current affiliation is with the project LEAD:FUH.

  • Zeitschriften

    • Çavuş, Mustafa, and Jakub Kuzilek. 2024. “An Effect Analysis of the Balancing Techniques on the Counterfactual Explanations of Student Success Prediction Models.” Journal of Measurement and Evaluation in Education and Psychology 15 (Special Issue): 302–17. https://doi.org/10.21031/epod.1526704.
    • Ifenthaler, Dirk, Clara Schumacher, and Jakub Kuzilek. 2023. “Investigating Students’ Use of Self-Assessments in Higher Education Using Learning Analytics.” Journal of Computer Assisted Learning 39 (1): 255–68.
    • Kuzilek, Jakub, Zdenek Zdrahal, Jonas Vaclavek, Viktor Fuglik, Jan Skocilas, and Annika Wolff. 2023. “First-Year Engineering Students’ Strategies for Taking Exams.” International Journal of Artificial Intelligence in Education 33 (3): 583–608. https://doi.org/10.1007/s40593-022-00303-4.
    • Marmolejo-Ramos, Fernando, Mauricio Tejo, Marek Brabec, et al. 2022. “Distributional Regression Modeling via Generalized Additive Models for Location, Scale, and Shape: An Overview Through a Data Set from Learning Analytics.” Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, e1479.
    • Kuzilek, Jakub, Zdenek Zdrahal, and Viktor Fuglik. 2021. “Student Success Prediction Using Student Exam Behaviour.” Future Generation Computer Systems 125: 661–71. https://doi.org/https://doi.org/10.1016/j.future.2021.07.009.
    • Kuzilek, J. and Hlosta, M., and Zdrahal, Z. 2017. “Open University Learning Analytics Dataset.” Scientific Data 4. https://doi.org/10.1038/sdata.2017.171.
    • Kuzilek, J. and Hlosta, M. and Herrmannova, D. and Zdrahal, Z. and Wolff, A. 2015. “OU Analyse: Analysing at-Risk Students at the Open University.” LACE: Learning Analytics Review, 1–16. https://oro.open.ac.uk/42529/1/__userdata_documents4_ctb44_Desktop_analysing-at-risk-students-at-open-university.pdf.

    Konferenzbeiträge und Workshops

    • Swamy, Vinitra, Jakub Kuzilek, Juan Pinto, et al. 2025. “The 2nd Human-Centric eXplainable AI in Education (HEXED) Workshop.” In Proceedings of the 18th International Conference on Educational Data Mining, edited by Caitlin Mills, Giora Alexandron, Davide Taibi, Giosuè Lo Bosco, and Luc Paquette. International Educational Data Mining Society. https://doi.org/10.5281/zenodo.15870312.
    • Rüdian, Sylvio, Julia Podelo, Jakub Kužı́lek, and Niels Pinkwart. 2025. “Feedback on Feedback: Student’s Perceptions for Feedback from Teachers and Few-Shot LLMs.” Proceedings of the 15th International Learning Analytics and Knowledge Conference (New York, NY, USA), LAK ’25, 82–92. https://doi.org/10.1145/3706468.3706479.
    • Cavus, Mustafa, and Jakub Kuzilek. 2024b. “The Actionable Explanations for Student Success Prediction Models: A Benchmark Study on the Quality of Counterfactual Methods.” Human-Centric eXplainable AI in Education Workshop at 17th Educational Data Mining Conference 2024.
    • Palomino, Alonso, Andreas Fischer, Jakub Kuzilek, Jarek Nitsch, Niels Pinkwart, and Benjamin Paaßen. 2024. “EdTec-QBuilder: A Semantic Retrieval Tool for Assembling Vocational Training Exams in German Language.” Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 3: System Demonstrations), 26–35.
    • Schumacher, Clara, Dirk Ifenthaler, and Jakub Kuzilek. 2023. “Using Students’ Interaction with Self-Assessments During the Semester for Predicting Course Success.” EARLI 2023, 20th Biennial EARLI Conference.
    • Schumacher, C., N. Reich-Stiebert, J. Kuzilek, et al. 2021. “Group Perceptions Vs. Group Reality: Exploring the Fit of Self-Report and Log File Data in the Process of Collaboration.” Companion Proceedings of Conference on Learning Analytics and Knowledge 2021, Virtual Conference, 15-04-2021.
    • Paaßen, Benjamin, Andreas Bertsch, Katharina Langer-Fischer, et al. 2021. “Analyzing Student Success and Mistakes in Virtual Microscope Structure Search Tasks.” In Proceedings of the 15th International Conference on Educational Data Mining (EDM 2021), edited by François Bouchet, Jill-Jênn Vie, Sharon Hsiao, and Sherry Sahebi. International Educational Datamining Society. https://educationaldatamining.org/EDM2021/virtual/static/pdf/EDM21_paper_67.pdf.
    • Kuzilek, Jakub, Zdenek Zdrahal, Jonas Vaclavek, Viktor Fuglik, and Jan Skocilas. 2020. “Exploring Exam Strategies of Successful First Year Engineering Students.” Proceedings of the Tenth International Conference on Learning Analytics & Knowledge (New York, NY, USA), LAK ’20, 124–28. https://doi.org/10.1145/3375462.3375469.
    • Wolff, A. and Moore, J. and Zdrahal, Zdenek and Hlosta, M., and Kuzilek, Jakub. 2016. “Data Literacy for Learning Analytics.” Proceedings of the Sixth International Conference on Learning Analytics & Knowledge (New York, US), 500–501. https://doi.org/10.1145/2883851.2883864.
    • Zdrahal, Zdenek, Martin Hlosta, and Jakub Kuzilek. 2016. “Analysing Performance of First Year Engineering Students.” Learning Analytics and Knowledge: Data Literacy for Learning Analytics Workshop. https://oro.open.ac.uk/58597/.
    • Hlosta, M. and Herrmannova, D. and Vachova, L. and Kuzilek, J. and Zdrahal, Z., and Wolff, A. 2014. “Modelling Student Online Behaviour in a Virtual Learning Environment.” Proceedings of the 4th International Conference on Learning Analytics and Knowledge (New York, US), 1–4.

  • I am a SoLAR member.

CATALPA | 23.10.2025