标题： 通过意义构建和机制推理的视角审视学生和人工智能对物理问题的回答 显示英文标题

标题： Student and AI responses to physics problems examined through the lenses of sensemaking and mechanistic reasoning

摘要： 多项教育报告呼吁通过促进基于课程理念的现实情景的合理性建构，来改造物理学习环境。最近，生成式人工智能在教育工作者群体中引起了越来越多的关注，因其在改造STEM学习方面的潜力备受瞩目。在这项探索性研究中，我们采用混合方法，通过合理性建构和机制推理的认知视角，比较分析了学生与AI针对一个物理问题两种不同形式的答案。学生数据来源于基础课程学生的有声思维访谈，而AI数据则来自使用零样本方法收集到的ChatGPT解决方案。结果显示，AI答案通过结构良好的解答反映了两种过程的大部分特征，而学生答案则通过反复改进论点有效利用了解答中的表征。换句话说，AI的回答反映了物理学是如何被讨论的，而学生则展示了物理学是如何被实践的。本文还讨论了这些结果在物理学教学中开发和部署AI系统方面的意义。 显示英文摘要

摘要： Several reports in education have called for transforming physics learning environments by promoting sensemaking of real-world scenarios in light of curricular ideas. Recent advancements in Generative-Artificial Intelligence has garnered increasing traction in educators' community by virtue of its potential in transforming STEM learning. In this exploratory study, we adopt a mixed-methods approach in comparatively examining student- and AI-generated responses to two different formats of a physics problem through the cognitive lenses of sensemaking and mechanistic reasoning. The student data is derived from think-aloud interviews of introductory students and the AI data comes from ChatGPT's solutions collected using Zero shot approach. The results highlight AI responses to evidence most features of the two processes through well-structured solutions and student responses to effectively leverage representations in their solutions through iterative refinement of arguments. In other words, while AI responses reflect how physics is talked about, the student responses reflect how physics is practiced. Implications of these results in light of development and deployment of AI systems in physics pedagogy are discussed.