Student Evaluations of Teaching (SETs) are widely used in colleges and universities. Typically SET results are summarized for instructors in a static PDF report. The report often includes summary statistics for quantitative ratings and an unsorted list of open-ended student comments. The lack of organization and summarization of the raw comments hinders those interpreting the reports from fully utilizing informative feedback, making accurate inferences, and designing appropriate instructional improvements. In this work, we introduce a novel system, SETSum, that leverages sentiment analysis, aspect extraction, summarization, and visualization techniques to provide organized illustrations of SET findings to instructors and other reviewers. Ten university professors from diverse departments serve as evaluators of the system and all agree that SETSum helps them interpret SET results more efficiently; and 6 out of 10 instructors prefer our system over the standard static PDF report (while the remaining 4 would like to have both). This demonstrates that our work holds the potential to reform the SET reporting conventions in the future. Our code is available at https://github.com/evahuyn/SETSum

翻译：教学学生评价(SETs)在大专院校广泛使用,一般在静态的PDF报告中为教员总结SET结果,报告经常包括数量评分的简要统计和未分类的不限名额学生评论清单;原始评论缺乏组织和汇总,妨碍解释报告的人充分利用信息反馈,作出准确的推论,并设计适当的教学改进;在这项工作中,我们引进了新颖的SETSum系统,利用情绪分析、方位提取、汇总和直观化技术,向教员和其他审查者提供有组织地展示SET调查结果的图解;来自不同部门的10名大学教授担任系统的评价员,一致认为SETSUm帮助他们更有效地解释SET结果;10名教员中有6名倾向于我们系统,而不是标准的静态PDF报告(其余4名教师希望同时同时),这表明我们的工作有可能在今后改革SET报告公约。我们的代码可在https://github.com/evahuyn/SETSTSTUR姆查阅。