Frederik Baucks

Publications

Welcome to my portfolio of publications, where advanced data analytics and machine learning intersect with educational strategies. Here, you'll find my research on using Item Response Theory to assess course difficulty variations, contributing to enhanced curriculum design. Among the featured works is the development of a dashboard tool for academic counseling, which serves as a bridge between theoretical research and practical application. Highlighted as well is my work mitigating biases for curriculum analytics measures with an additive grade point model.

Last updated on 11/30/23

Baucks, F., & Wiskott, L. (2024, July). Empowering Advisors: Designing a Dashboard for University Student Guidance. In P. Salden & Leschke, J. (Eds.), Learning Analytics und Künstliche Intelligenz in Studium und Lehre. Erfahrungen und Schlussfolgerungen aus einer hochschulweiten Erprobung, accepted. Wiesbaden, Germany: Springer VS Fachmedien.
Baucks*, F., Schmucker*, R., & Wiskott, L. (2024, March). Gaining Insights into Course Difficulty Variations Using Item Response Theory. LAK24: 14th International Learning Analytics and Knowledge Conference, accepted. New York, NY, USA: Association for Computing Machinery.
Baucks, F., & Wiskott, L. (2023). Von der Forschung in die Praxis: Entwicklung eines Dashboards für die Studienberatung.
Baucks, F., Leschke, J., Metzger, C., & Wiskott, L. (2023). Ein Dashboard für die Studienberatung: Technische Infrastruktur und Studienverlaufsplanung im Projekt KI:edu.nrw. Workshop Proceedings of the 21th Fachtagung Bildungstechnologien (DELFI), Accepted. Bonn: Gesellschaft für Informatik e.V.
Baucks, F., & Wiskott, L. (2023). *Best Paper Nominee* Mitigating Biases using an Additive Grade Point Model: Towards Trustworthy Curriculum Analytics Measures. 21. Fachtagung Bildungstechnologien (DELFI), 41–52. doi:10.18420/delfi2023-12
Baucks*, F., Schmucker*, R., & Wiskott, L. (2023). Tracing Changes in University Course Difficulty Using Item-Response Theory.
Baucks, F., & Wiskott, L. (2022). Simulating Policy Changes in Prerequisite-Free Curricula: A Supervised Data-Driven Approach. Proceedings of the 15th International Conference on Educational Data Mining, 470–476. doi:10.5281/zenodo.6853177