Dr. Jakub Kuzilek

English

Dr. Jakub Kuzilek Foto: Privat

Dr. Jakub Kuzilek

Wissenschaftlicher Mitarbeiter in der Forschungsprofessur „Learning Sciences in Higher Education“

E-Mail: jakub.kuzilek

Universitätsstraße 27 – PRG / Gebäude 5
58097 Hagen


Was ist meine Rolle in CATALPA?

Ich bin Forscher mit Schwerpunkt auf Bildungsdaten und deren Nutzung zur Verbesserung von Lernprozessen und Lernerfahrungen. Damit tue ich das, was ich am besten kann – ich arbeite mit Daten, verbessere Datenflüsse und liefere KI-gestützte Lösungen, um die Lernfortschritte und den Lernerfolg zu verbessern und nützliche Erkenntnisse über die Lernprozesse zu gewinnen.

Warum CATALPA?

Meiner Meinung nach ist CATALPA in einer einzigartigen Position, um umfassende datengestützte Lösungen zur Verbesserung der Lehre und des Lernens an der FernUniversität in Hagen anzubieten. Ich glaube, dass die Daten die Art und Weise verändern können, wie wir Studierende unterrichten, insbesondere im Online- und Fernunterricht. Mit rund 80.000 Studierenden gibt es eine Fülle von Informationen und Möglichkeiten, nicht nur das Lernen an der FernUniversität, sondern auch im gesamten Hochschulbereich in Deutschland zu verändern. Und dabei möchte ich helfen.

    • Doktorand in KI und Biokybernetik (CTU in Prag; 2009–2013)

    • Wissenschaftlicher Mitarbeiter im Bereich Lernanalytik und Bildungsdatenauswertung (KMi, OU, Milton Keynes; 2013–2017)

    • Wissenschaftlicher Mitarbeiter und Forscher im Bereich KI in der Bildung (CTU in Prag, 2010–2020)

    • Forscher im Bereich Lernanalytik und Bildungsdatenauswertung (CSES, HU Berlin, 2020–2025)

    • Educational Data Mining

    • Explainable AI

    • Machine Learning & Signal Processing

    • Learning Analytics

    • Learning Analytics infrastructures

    • Educational Technology

  • Ich bin derzeit dem Projekt LEAD:FUH angeschlossen.

  • 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.

  • Ich bin Mitglied im Netzwerk SoLAR.

CATALPA | 23.10.2025