Frederik Baucks, M.Sc.
Theory of Neural Systems
Theory of Neural Systems
Ruhr-Universität Bochum
Institut für Neuroinformatik
Universitätsstraße 150
Building NB, Room NB 3/35
Universitätsstraße 150
Building NB, Room NB 3/35
D-44801 Bochum, Germany
Selected Publications
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*Best Paper Nominee* Gaining Insights into Course Difficulty Variations Using Item Response TheoryBaucks, F., Schmucker, R., & Wiskott, L.In LAK24: 14th International Learning Analytics and Knowledge Conference (pp. 450–461) New York, NY, USA: Association for Computing Machinery
@inproceedings{BaucksSchmuckerWiskott2024, author = {Baucks, Frederik and Schmucker, Robin and Wiskott, Laurenz}, title = {*Best Paper Nominee* Gaining Insights into Course Difficulty Variations Using Item Response Theory}, booktitle = {LAK24: 14th International Learning Analytics and Knowledge Conference}, pages = {450–461}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, month = {March}, year = {2024}, doi = {10.1145/3636555.3636902}, }Baucks, F., Schmucker, R., & Wiskott, L.. (2024). *Best Paper Nominee* Gaining Insights into Course Difficulty Variations Using Item Response Theory. In LAK24: 14th International Learning Analytics and Knowledge Conference (pp. 450–461). New York, NY, USA: Association for Computing Machinery. http://doi.org/10.1145/3636555.3636902Gaining Insights into Group-Level Course Difficulty via Differential Course FunctioningBaucks, F., Schmucker, R., Borchers, C., Pardos, Z. A., & Wiskott, L.In Proceedings of the Eleventh ACM Conference on Learning @ Scale (pp. 165–176) Atlanta, GA, USA: Association for Computing Machinery@inproceedings{BaucksSchmuckerBorchersEtAl2024, author = {Baucks, Frederik and Schmucker, Robin and Borchers, Conrad and Pardos, Zachary A. and Wiskott, Laurenz}, title = {Gaining Insights into Group-Level Course Difficulty via Differential Course Functioning}, booktitle = {Proceedings of the Eleventh ACM Conference on Learning @ Scale}, pages = {165–176}, publisher = {Association for Computing Machinery}, series = {L@S ′24}, address = {New York, NY, USA}, year = {2024}, doi = {10.1145/3657604.3662028}, }Baucks, F., Schmucker, R., Borchers, C., Pardos, Z. A., & Wiskott, L.. (2024). Gaining Insights into Group-Level Course Difficulty via Differential Course Functioning. In Proceedings of the Eleventh ACM Conference on Learning @ Scale (pp. 165–176). Atlanta, GA, USA: Association for Computing Machinery. http://doi.org/10.1145/3657604.3662028Empowering Advisors: Designing a Dashboard for University Student GuidanceBaucks, F., & Wiskott, L.In P. Salden & Leschke, J. (Eds.), Learning Analytics und Künstliche Intelligenz in Studium und Lehre: Erfahrungen und Schlussfolgerungen aus einer hochschulweiten Erprobung (pp. 27–44) Wiesbaden: Springer Fachmedien Wiesbaden@inbook{BaucksWiskott2024, author = {Baucks, Frederik and Wiskott, Laurenz}, title = {Empowering Advisors: Designing a Dashboard for University Student Guidance}, editor = {Salden, Peter and Leschke, Jonas}, pages = {27–44}, publisher = {Springer Fachmedien Wiesbaden}, address = {Wiesbaden}, year = {2024}, doi = {10.1007/978-3-658-42993-5_2}, }Baucks, F., & Wiskott, L.. (2024). 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 (pp. 27–44). Wiesbaden: Springer Fachmedien Wiesbaden. http://doi.org/10.1007/978-3-658-42993-5_22023
*Best Paper Nominee* Mitigating Biases using an Additive Grade Point Model: Towards Trustworthy Curriculum Analytics MeasuresBaucks, F., & Wiskott, L.In 21. Fachtagung Bildungstechnologien (DELFI) (pp. 41–52) Bonn: Gesellschaft für Informatik e.V.@inproceedings{BaucksWiskott2023, author = {Baucks, Frederik and Wiskott, Laurenz}, title = {*Best Paper Nominee* Mitigating Biases using an Additive Grade Point Model: Towards Trustworthy Curriculum Analytics Measures}, booktitle = {21. Fachtagung Bildungstechnologien (DELFI)}, pages = {41–52}, publisher = {Gesellschaft für Informatik e.V.}, address = {Bonn}, year = {2023}, doi = {10.18420/delfi2023-12}, }Baucks, F., & Wiskott, L.. (2023). *Best Paper Nominee* Mitigating Biases using an Additive Grade Point Model: Towards Trustworthy Curriculum Analytics Measures. In 21. Fachtagung Bildungstechnologien (DELFI) (pp. 41–52). Bonn: Gesellschaft für Informatik e.V. http://doi.org/10.18420/delfi2023-122022
Simulating Policy Changes in Prerequisite-Free Curricula: A Supervised Data-Driven ApproachBaucks, F., & Wiskott, L.In Proceedings of the 15th International Conference on Educational Data Mining (pp. 470–476) International Educational Data Mining Society@inproceedings{BaucksWiskott2022, author = {Baucks, Frederik and Wiskott, Laurenz}, title = {Simulating Policy Changes in Prerequisite-Free Curricula: A Supervised Data-Driven Approach}, booktitle = {Proceedings of the 15th International Conference on Educational Data Mining}, pages = {470–476}, publisher = {International Educational Data Mining Society}, month = {July }, year = {2022}, doi = {10.5281/zenodo.6853177}, }Baucks, F., & Wiskott, L.. (2022). Simulating Policy Changes in Prerequisite-Free Curricula: A Supervised Data-Driven Approach. In Proceedings of the 15th International Conference on Educational Data Mining (pp. 470–476). International Educational Data Mining Society. http://doi.org/10.5281/zenodo.6853177-
*Best Paper Nominee* Gaining Insights into Course Difficulty Variations Using Item Response TheoryBaucks, F., Schmucker, R., & Wiskott, L.In LAK24: 14th International Learning Analytics and Knowledge Conference (pp. 450–461) New York, NY, USA: Association for Computing Machinery
@inproceedings{BaucksSchmuckerWiskott2024, author = {Baucks, Frederik and Schmucker, Robin and Wiskott, Laurenz}, title = {*Best Paper Nominee* Gaining Insights into Course Difficulty Variations Using Item Response Theory}, booktitle = {LAK24: 14th International Learning Analytics and Knowledge Conference}, pages = {450–461}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, month = {March}, year = {2024}, doi = {10.1145/3636555.3636902}, }Baucks, F., Schmucker, R., & Wiskott, L.. (2024). *Best Paper Nominee* Gaining Insights into Course Difficulty Variations Using Item Response Theory. In LAK24: 14th International Learning Analytics and Knowledge Conference (pp. 450–461). New York, NY, USA: Association for Computing Machinery. http://doi.org/10.1145/3636555.3636902Gaining Insights into Group-Level Course Difficulty via Differential Course FunctioningBaucks, F., Schmucker, R., Borchers, C., Pardos, Z. A., & Wiskott, L.In Proceedings of the Eleventh ACM Conference on Learning @ Scale (pp. 165–176) Atlanta, GA, USA: Association for Computing Machinery@inproceedings{BaucksSchmuckerBorchersEtAl2024, author = {Baucks, Frederik and Schmucker, Robin and Borchers, Conrad and Pardos, Zachary A. and Wiskott, Laurenz}, title = {Gaining Insights into Group-Level Course Difficulty via Differential Course Functioning}, booktitle = {Proceedings of the Eleventh ACM Conference on Learning @ Scale}, pages = {165–176}, publisher = {Association for Computing Machinery}, series = {L@S ′24}, address = {New York, NY, USA}, year = {2024}, doi = {10.1145/3657604.3662028}, }Baucks, F., Schmucker, R., Borchers, C., Pardos, Z. A., & Wiskott, L.. (2024). Gaining Insights into Group-Level Course Difficulty via Differential Course Functioning. In Proceedings of the Eleventh ACM Conference on Learning @ Scale (pp. 165–176). Atlanta, GA, USA: Association for Computing Machinery. http://doi.org/10.1145/3657604.3662028Empowering Advisors: Designing a Dashboard for University Student GuidanceBaucks, F., & Wiskott, L.In P. Salden & Leschke, J. (Eds.), Learning Analytics und Künstliche Intelligenz in Studium und Lehre: Erfahrungen und Schlussfolgerungen aus einer hochschulweiten Erprobung (pp. 27–44) Wiesbaden: Springer Fachmedien Wiesbaden@inbook{BaucksWiskott2024, author = {Baucks, Frederik and Wiskott, Laurenz}, title = {Empowering Advisors: Designing a Dashboard for University Student Guidance}, editor = {Salden, Peter and Leschke, Jonas}, pages = {27–44}, publisher = {Springer Fachmedien Wiesbaden}, address = {Wiesbaden}, year = {2024}, doi = {10.1007/978-3-658-42993-5_2}, }Baucks, F., & Wiskott, L.. (2024). 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 (pp. 27–44). Wiesbaden: Springer Fachmedien Wiesbaden. http://doi.org/10.1007/978-3-658-42993-5_22023
Von der Forschung in die Praxis: Entwicklung eines Dashboards für die StudienberatungBaucks, F., & Wiskott, L.Abstract presented at 2nd Learning AID@unpublished{BaucksWiskott2023b, author = {Baucks, Frederik and Wiskott, Laurenz}, title = {Von der Forschung in die Praxis: Entwicklung eines Dashboards für die Studienberatung}, month = {August}, year = {2023}, }Baucks, F., & Wiskott, L.. (2023, August). Von der Forschung in die Praxis: Entwicklung eines Dashboards für die Studienberatung. Abstract presented at 2nd Learning AID.Ein Dashboard für die Studienberatung: Technische Infrastruktur und Studienverlaufsplanung im Projekt KI:edu.nrwBaucks, F., Leschke, J., Metzger, C., & Wiskott, L.In Workshop Proceedings of the 21th Fachtagung Bildungstechnologien (DELFI) (pp. 185–188) Bonn: Gesellschaft für Informatik e.V.@inproceedings{BaucksLeschkeMetzgerEtAl2023, author = {Baucks, Frederik and Leschke, Jonas and Metzger, Christian and Wiskott, Laurenz}, title = {Ein Dashboard für die Studienberatung: Technische Infrastruktur und Studienverlaufsplanung im Projekt KI:edu.nrw}, booktitle = {Workshop Proceedings of the 21th Fachtagung Bildungstechnologien (DELFI)}, pages = {185–188}, publisher = {Gesellschaft für Informatik e.V.}, address = {Bonn}, year = {2023}, }Baucks, F., Leschke, J., Metzger, C., & Wiskott, L.. (2023). Ein Dashboard für die Studienberatung: Technische Infrastruktur und Studienverlaufsplanung im Projekt KI:edu.nrw. In Workshop Proceedings of the 21th Fachtagung Bildungstechnologien (DELFI) (pp. 185–188). Bonn: Gesellschaft für Informatik e.V.*Best Paper Nominee* Mitigating Biases using an Additive Grade Point Model: Towards Trustworthy Curriculum Analytics MeasuresBaucks, F., & Wiskott, L.In 21. Fachtagung Bildungstechnologien (DELFI) (pp. 41–52) Bonn: Gesellschaft für Informatik e.V.@inproceedings{BaucksWiskott2023, author = {Baucks, Frederik and Wiskott, Laurenz}, title = {*Best Paper Nominee* Mitigating Biases using an Additive Grade Point Model: Towards Trustworthy Curriculum Analytics Measures}, booktitle = {21. Fachtagung Bildungstechnologien (DELFI)}, pages = {41–52}, publisher = {Gesellschaft für Informatik e.V.}, address = {Bonn}, year = {2023}, doi = {10.18420/delfi2023-12}, }Baucks, F., & Wiskott, L.. (2023). *Best Paper Nominee* Mitigating Biases using an Additive Grade Point Model: Towards Trustworthy Curriculum Analytics Measures. In 21. Fachtagung Bildungstechnologien (DELFI) (pp. 41–52). Bonn: Gesellschaft für Informatik e.V. http://doi.org/10.18420/delfi2023-12Tracing Changes in University Course Difficulty Using Item-Response TheoryBaucks*, F., Schmucker*, R., & Wiskott, L.AAAI Workshop on AI for Education: https://ai4ed.cc/workshops/aaai2023@misc{Baucks*Schmucker*Wiskott2023, author = {Baucks*, Frederik and Schmucker*, Robin and Wiskott, Laurenz}, title = {Tracing Changes in University Course Difficulty Using Item-Response Theory}, howpublished = {AAAI Workshop on AI for Education: https://ai4ed.cc/workshops/aaai2023}, year = {2023}, }Baucks*, F., Schmucker*, R., & Wiskott, L.. (2023). Tracing Changes in University Course Difficulty Using Item-Response Theory. AAAI Workshop on AI for Education: https://ai4ed.cc/workshops/aaai2023.2022
Simulating Policy Changes in Prerequisite-Free Curricula: A Supervised Data-Driven ApproachBaucks, F., & Wiskott, L.In Proceedings of the 15th International Conference on Educational Data Mining (pp. 470–476) International Educational Data Mining Society@inproceedings{BaucksWiskott2022, author = {Baucks, Frederik and Wiskott, Laurenz}, title = {Simulating Policy Changes in Prerequisite-Free Curricula: A Supervised Data-Driven Approach}, booktitle = {Proceedings of the 15th International Conference on Educational Data Mining}, pages = {470–476}, publisher = {International Educational Data Mining Society}, month = {July }, year = {2022}, doi = {10.5281/zenodo.6853177}, }Baucks, F., & Wiskott, L.. (2022). Simulating Policy Changes in Prerequisite-Free Curricula: A Supervised Data-Driven Approach. In Proceedings of the 15th International Conference on Educational Data Mining (pp. 470–476). International Educational Data Mining Society. http://doi.org/10.5281/zenodo.6853177Summer Term 2024
Lab courses An Introduction to Python for Data Analysis Summer Term 2023
Lab courses Introduction to Python The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.
Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, GermanyTel: (+49) 234 32-28967
Fax: (+49) 234 32-14210
2024