I am a researcher focusing on machine learning application in educational domain within fields of Educational Data Mining and Learning Analytics. My research interests covers machine learning, explainable AI, signal processing, and R. My current position is with the “Didaktik der Informatik / Informatik und Gesellschaft” research group at Humbold-University of Berlin and Educational Technology Lab at German Research Center for Artificial Intelligence.

Research Interests

Selected Publications

Cavus, M., & Kuzilek, J. (2024) 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.

Ifenthaler, D., Schumacher, C., & Kuzilek, J. (2023) Investigating students’ use of self-assessments in higher education using learning analytics. Journal of Computer Assisted Learning, vol. 39, no. 1, pp. 255–68.

Kuzilek, J., Zdrahal, Z., Vaclavek, J., Fuglik, V., Skocilas, J., & Wolff, A. (2023) First-Year Engineering Students’ Strategies for Taking Exams. International Journal of Artificial Intelligence in Education, vol. 33, no. 3, pp. 583–608.

Marmolejo-Ramos, F. 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, J., Zdrahal, Z., & Fuglik, V. (2021). Student success prediction using student exam behaviour. Future Generation Computer Systems.

Schumacher, C., Reich-Stiebert, N., Kuzilek, J., Burchart, M., Raimann, J., Voltmer, J.-B., & Stürmer, S. (2021). Group perceptions vs. group reality: Exploring the fit of self-report and log file data in the process of collaboration. In Companion proceedings of Conference on Learning Analytics and Knowledge 2021, Virtual Conference, 15-04-2021.

Kuzilek, J., Hlosta, & Zdrahal, Z. (2017). Open University Learning Analytics dataset. Scientific Data, 4.

Kuzilek, J., Hlosta, M., Herrmannova, D., Zdrahal, Z., Vaclavek, J., & Wolff, A. (2015). OU Analyse: analysing at-risk students at The Open University. LACE: Learning Analytics Review, 1–16.

Kuzilek, J., Kremen, V., Soucek, & Lhotska, L. (2014). Independent Component Analysis and Decision Trees for ECG Holter Recording De-Noising. PLoS ONE, 9(6), 1–16.

Kuzilek, J., & Lhotska, L. (2013). Electrocardiogram Beat Detection Enhancement Using Independent Component Analysis. Medical Engineering & Physics, 35(6), 704–711.

Kuzilek, J., Lhotska, & Hanuliak, M. (2011). An Automatic Method for Holter ECG Denoising Using ICA. In In ACM Digital Library: Proceedings of 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies (pp. 1–5). Best paper award.

Chudacek, V., Zach, L., Kuzilek, J., Spilka, & Lhotska, L. (2011). Simple Scoring System for ECG Signal Quality Assessment on Android Platform. In Computing in Cardiology (pp. 449–451). Second place in CINC Challenge 2011.