调查大模型对师生教学与学习方式的影响，为教育政策提供依据。
Measuring Changes in Instructor Class Design and Student Learning After the Release of Large Language Models (LLMs)
- 通过问卷与成绩数据结合，分析大模型使用前后的教学变化。
- 发现学生课业方式改变，教师课程设计也相应调整。
- 适合关注AI教育应用的教师与高校管理者参考。
生成式人工智能（GenAI）在学生完成作业中的广泛应用，已引发高等教育的重大变革。尽管其使用普遍，但对学生学习方法、教师课程设计、成绩评定及整体学习效果的影响尚不明确。本研究采用混合方法，在美国新英格兰地区一所大学开展多课程调研，结合回顾性定量分析、教师问卷和匿名学生问卷，旨在识别并记录师生对大模型作为学习工具的感知与体验。通过对教师与学生问卷的量化与主题分析，以及历史成绩数据（提交至大学注册办公室）的交叉验证，研究考察了大模型出现前后学习成效的变化。结果可为教授、高校及其他教育机构制定生成式人工智能相关政策提供参考，助力在人工智能时代优化学生学习效果。本研究可作为其他机构开展类似研究的初步范例。
原文摘要 · Abstract (English)
Student use of Generative AI (GenAI) products in completing their classwork, with or without their professors' knowledge and/or approval, has resulted in substantial shifts in higher education. While GenAI use is widespread, its impact on student study methods, faculty course development, grade reporting, and overall learning is not well documented. This is a mixed-methods, multi-course study using retrospective quantitative analysis, instructor surveys, and anonymous student surveys at a university in the New England region of the United States. This research seeks to identify and document patterns in student and faculty perceptions of, and experiences in, the use of LLMs as a learning tool inside and outside of the university classroom. Alongside quantitative and thematic analysis of both faculty and student survey responses, historical grade data as reported to the university registrar is used to triangulate the phenomenon of learning achievement in pre- and post-LLM eras. It is hoped that this research can serve as a pilot study for a broader set of institutions. Results from this study can inform GenAI policy for professors, universities, and other educational institutions that are trying to maximize student learning in the age of AI.
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