AI 中文总结
本研究针对生成式AI在物理教育中的广泛应用，开发并实施了一个教师学习共同体，通过六次双周会议共同应对课程政策、课堂对话、课程任务和评估等挑战，强调持久教学方法，并建立了共享资源库，为各系提供了可适应的理论模型。
AI 中文摘要
生成式人工智能工具正被学生在物理课程及课外广泛使用，这往往发生在教师和机构能够制定使用这些工具的政策和有效方法之前。基于人工智能时代变革框架，我们开发并实施了一个教师学习共同体，以帮助大学物理系共同应对这些挑战。在六次双周会议中，教师共同探讨了课程政策、关于AI的课堂对话、AI整合的课程任务以及评估。每次会议都遵循共同的结构：我们展示本地数据和系内来源的材料，在小组中测试它们，并共同讨论，强调持久的教学方法而非特定工具和平台，并以学生自身使用AI的证据为先导。该系列研讨会产生了一个共享的、不断发展的资源库供教师使用。这个研讨会为教师学习共同体提供了一个可适应、有理论依据的模型，各系可以在此基础上发展。
英文摘要
Generative AI tools are being widely taken up by students in their physics courses and beyond, often before instructors and institutions can develop policies and effective approaches for the use of these tools. Building on a framework for change in the era of AI, we developed and implemented a faculty learning community to help a university physics department address these challenges collectively. Over six biweekly sessions, faculty worked through course policies, classroom conversations about AI, AI-integrated coursework tasks, and assessment. Each session shared a common structure: we presented local data and department-sourced materials, tested them in small groups, and discussed them together, emphasizing durable pedagogical approaches over specific tools and platforms, and leading with evidence of students' own AI use. The series produced a shared, evolving repository of resources for faculty to draw on. This workshop provides an adaptable, theoretically informed model for a faculty learning community that departments can build on.
