AI 中文总结
本文报告了在粒子物理入门课程中允许并鼓励使用生成式AI完成研究型作业的重新设计，发现学生保持投入但基础目标未可靠实现，为AI教育应用提供参考。
AI 中文摘要
生成式人工智能能够为标准物理作业提供完美解答，从而削弱了提交作业与学生可独立运用知识之间的联系。我们报告了鲁尔大学波鸿分校核物理与粒子物理入门课程的一次重新设计，在该课程中，人工智能与传统工具一同被允许并鼓励用于异常困难、具有研究形态的作业。我们发现，大多数学生在整个课程期间保持了对作业的投入，并产出了有雄心的作品，而该课程并未可靠地实现其基础性目标。我们将这一喜忧参半的经验作为讨论的参考点。
英文摘要
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.
Comments5 pages, 2 figures
