本文利用开源生成式 AI 汇总 75 门计算机科学课程的 742 份学生评价，为教师生成真实、可执行的课程反馈摘要，验证了该方法支持教学改进的可行性与成本效益。
摘要：
学期末的学生教学评价是向高校教师反馈其教学实践的主要机制。然而，对于大班课程而言，反馈数量庞大，使得这些工具难以实际用于该目的。本文探索使用开源生成式 AI，从这些问卷回复中综合出真实、可执行且恰当的学生反馈摘要。在我们的设置中，拥有来自计算机科学系 75 门课程的 742 份学生回复。对于每门课程，我们综合生成课程评价摘要以及面向授课教师的可执行事项。研究结果揭示了一条在课堂环境中改进教学实践的有前景途径。我们的贡献在于证明了使用生成式 AI 为教师生成富有洞见的反馈的可行性，从而提供一种具有成本效益的方式来支持教育工作者的发展。总体而言，我们的工作强调了在课堂环境中使用生成式 AI 为教师生成真实、可执行且恰当反馈的可能性。
英文摘要：
End of semester student evaluations of teaching are the dominant mechanism for providing feedback to academics on their teaching practice. For large classes, however, the volume of feedback makes these tools impractical for this purpose. This paper explores the use of open-source generative AI to synthesise factual, actionable and appropriate summaries of student feedback from these survey responses. In our setup, we have 742 student responses ranging over 75 courses in a Computer Science department. For each course, we synthesise a summary of the course evaluations and actionable items for the instructor. Our results reveal a promising avenue for enhancing teaching practices in the classroom setting. Our contribution lies in demonstrating the feasibility of using generative AI to produce insightful feedback for teachers, thus providing a cost-effective means to support educators' development. Overall, our work highlights the possibility of using generative AI to produce factual, actionable, and appropriate feedback for teachers in the classroom setting.
What Don't You Understand? Using Large Language Models to Identify and Characterize Student Misconceptions About Challenging Topics
Harvard Medical School and Division of Pulmonary, Critical Care and Sleep Medicine, Beth Israel Deaconess Medical Center（哈佛医学院和肺科、重症医学及睡眠医学部门，贝斯以色列德aconess医疗中心）
A literature survey on student feedback assessment tools and their usage in sentiment analysis
Norwegian University of Science and Technology（挪威科技大学）；Department of Information Technology and Electrical Engineering（信息技术与电气工程系）；Gjøvik, Norway（挪威吉维克（此处按要求不提取地址，实际应为机构外信息，正确处理应为仅保留大学名称，即原回答中“挪威科技大学”））
ChatGPT and Gemini participated in the Korean College Scholastic Ability Test -- Earth Science I
Institute for Research Excellence in Learning Sciences（学习科学卓越研究所）；Seoul National University（首尔大学）；National Taiwan Normal University（台湾师范大学）；Universitas Negeri Malang（玛琅国立大学）
The Missing Evaluation Axis: What 10,000 Student Submissions Reveal About AI Tutor Effectiveness
University of California, Berkeley, USA（加州大学伯克利分校）；North Carolina State University, USA（北卡罗来纳州立大学）；University of Pittsburgh, USA（匹兹堡大学）；Aalto University, Finland（阿尔托大学）
