Are science competitions meeting their intentions? a case study on affective and cognitive predictors of success in the Physics Olympiad. Wulff, P., Tschingale, P., Steegh, A., Petersen, S., Kubsch, M. & Neumann, K. (2024). Are science competitions meeting their intentions? a case study on affective and cognitive predictors of success in the Physics Olympiad. , Discip Interdscip Sci Educ Res 6, 10, 2024. | Artikel Details |
David vs. Goliath: comparing conventional machine learning and a large language model for assessing students' concept use in a physics problem. Kieser, F., Tschisgale, P., Bai, X., Maus, H., Petersen, S., Stede, M., Neumann, K. & Wulff, P. (2024). David vs. Goliath: comparing conventional machine learning and a large language model for assessing students' concept use in a physics problem. , Front. Artif. Intell. (Section Machine Learning and Artificial Intelligence), 2024(7). | Artikel Details |
Physics language and language use in physics—What do we know and how AI might enhance language-related research and instructionWulff, P. (2024). Physics language and language use in physics—What do we know and how AI might enhance language-related research and instruction, European Journal of Physics, 2024(45). | Artikel Details |
Using Large Language Models to Probe Cognitive Constructs, Augment Data, and Design Instructional MaterialsWulff, P. & Kieser, F. (2024). Using Large Language Models to Probe Cognitive Constructs, Augment Data, and Design Instructional Materials, Machine Learning in Educational Sciences (S.293-313). Singapore: Springer. | Sammelband Details |
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