A redesign of the introductory nuclear and particle physics course at Ruhr University Bochum is reported, in which AI was permitted and encouraged alongside traditional tools on unusually difficult, research-shaped assignments, found that most students remained engaged with the assignments throughout the course and produced ambitious work, while the course did not reliably secure its foundational objective.
Abstract
Generative AI can produce perfect solutions to standard physics homework, weakening the connection between submitted work and knowledge a student can use independently. We report a redesign of the introductory nuclear and particle physics course at Ruhr University Bochum, in which AI was permitted and encouraged alongside traditional tools on unusually difficult, research-shaped assignments. We found that most students remained engaged with the assignments throughout the course and produced ambitious work, while the course did not reliably secure its foundational objective. We offer this mixed experience as a reference point for discussion.
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