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arXiv 2603.06342physics.ed-ph
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大学物理学生如何利用生成式人工智能进行计算建模

How undergraduate physics students use generative AI for computational modeling

University of Oslo（奥斯陆大学）；Rochester Institute of Technology（罗切斯特理工学院）

Karl Henrik Fredly, Tor Ole B. Odden, Benjamin M. Zwickl

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AI总结：

研究探讨了大学物理学生使用生成式AI进行计算建模的方式，发现其影响包括建模规划、实现和调试，同时指出过度依赖AI带来的挑战及教学改进的必要性。

摘要：

生成式人工智能（genAI）在物理学中正变得越来越普遍和强大，特别是在编程相关任务中。那么，genAI是如何影响学生计算建模的呢？我们采访了19名刚刚完成了一个鼓励使用genAI的开放性计算作业的本科生，询问他们是如何使用genAI的。然后，我们使用一个物理计算建模的框架对这些访谈进行了主题分析。我们发现，genAI显著影响学生计算建模的多个方面，例如计算模型的规划、实现和调试。genAI还可以帮助学生查找资源，并介绍他们新的计算工具。genAI的有益使用与学生将其使用限制在建模过程中的小步骤，并且始终双检查其提供的公式、解释和代码有关。我们还识别了学生由于过度依赖genAI而面临的问题，例如基于错误的模型假设工作，以及不花时间学习计算建模的基础，特别是调试。最后，我们讨论了教学的含义，如需要教授学生如何有效地使用genAI，并敦促他们在编写代码前进行计划。我们还强调了低风险评估和教学助教在教学计算建模中的持续价值，因为即使引入了genAI，这项任务仍然具有挑战性。

英文摘要：

Generative artificial intelligence (genAI) is becoming increasingly prevalent and capable in physics, particularly for programming-related tasks. How, then, does genAI affect students' computational modeling? We interviewed 19 undergraduate students who had recently completed an open-ended computational assignment that encouraged the use of genAI, asking them how they used it. We then conducted a thematic analysis of these interviews using a framework for computational modeling in physics. We found that genAI significantly impacts several aspects of students' computational modeling, such as the planning, implementing, and debugging of computational models. GenAI can also help students find resources and introduce them to new computational tools. Productive use of genAI was associated with students limiting its use to small steps in the modeling process and consistently double-checking the formulas, explanations, and code it provided. We also identified challenges students faced due to an over-reliance on genAI, such as working from false model assumptions and not spending time learning the fundamentals of computational modeling, especially debugging. Finally, we discuss implications for teaching, such as the need to teach students how to use genAI productively and to urge them to plan before they code. We also highlight the continued value of low-stakes assessment and teaching assistants for teaching computational modeling, as the task remains difficult even with the introduction of genAI.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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