Humboldt-Universität zu Berlin - Faculty of Mathematics and Natural Sciences - Computer Science Education | Computer Science and Society

Nathalie Rzepka, M.Sc.

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Email: nathalie.rzepka@hu-berlin.de 

Nathalie joined the research group of Prof. Dr. Pinkwart in January 2021 as an external PhD student. She works at the University of Applied Sciences (HTW) Berlin and is doing a collaborative PhD on the effectiveness of AI-based learning environments for the acquisition of spelling and grammar skills.


Nathalie obtained her master's degree at the University of Applied Sciences in September 2020. In her master's thesis, she developed a microservice architecture for pseudonymization of vehicle data in collaboration with Mercedes-Benz GmbH.

Research Interest

  • Adaptive online learning
  • Language learning
  • Learning Analytivs and Discrimination

Publications

N. Rzepka, K. Simbeck, and N. Pinkwart. Learning Analytics und Diskriminierung. Datafizierung (in) der Bildung. Kritische Perspektiven auf digitale Vermessung in pädagogischen Kontexten, transcript, pages 211-228, 2023. N. Rzepka, K. Simbeck, H. Müller, M. Bültemann, and N. Pinkwart. Show me the numbers! - Student-facing Interventions in Adaptive Learning Environments for German Spelling. 21. Fachtagung Bildungstechnologien (DELFI), Gesellschaft für Informatik e.V., pages 289-290, 2023. N. Rzepka, K. Simbeck, H.-G. Müller, and N. Pinkwart. Go with the Flow: Personalized Task Sequencing Improves Online Language Learning. International Conference on Artificial Intelligence in Education, pages 90-101, July 2023. N. Rzepka, L. Fernsel, H.-G. Müller, K. Simbeck, and N. Pinkwart. Unbias me! Mitigating Algorithmic Bias for Less-studied Demographic Groups in the Context of Language Learning Technology. Computer-Based Learning in Context, volume 6, issue 1, pages 1-23, May 2023. N. Rzepka, K. Simbeck, and H.-G. Müller. Impact of the Covid-19 pandemic on students’ spelling ability. Research on Education and Media, volume 14, issue 2, pages 57-63, 2022. N. Rzepka, K. Simbeck, H.-G. Müller, and N. Pinkwart. Adaptive Learning as a Service--A concept to extend digital learning platforms? 20. Fachtagung Bildungstechnologien (DELFI), Gesellschaft für Informatik eV, 2022. N. Rzepka, K. Simbeck, H.-G. Müller, and N. Pinkwart. An Online Controlled Experiment Design to Support the Transformation of Digital Learning towards Adaptive Learning Platforms. Proceedings of the 14th International Conference on Computer Supported Education - Volume 2: CSEDU,, SciTePress, pages 139-146, 2022. N. Rzepka, K. Simbeck, H.-G. Müller, and N. Pinkwart. Fairness of In-session Dropout Prediction. Proceedings of the 14th International Conference on Computer Supported Education - Volume 2: CSEDU,, SciTePress, pages 316-326, 2022. N. Rzepka, K. Simbeck, H.-G. Müller, and N. Pinkwart. Keep It Up: In-session Dropout Prediction to Support Blended Classroom Scenarios. Proceedings of the 14th International Conference on Computer Supported Education - Volume 2: CSEDU,, SciTePress, pages 131-138, 2022. N. Rzepka, H.-G. Mueller, and K. Simbeck. What you apply is not what you learn! Examining students' strategies in German capitalization tasks. International Conference on Educational Data Mining, 2021.