网络学生评价中性别偏见的多层面分析
A Multi-aspect Analysis of Gender Bias on Online Student Evaluations
摘要：
学校广泛使用学生评价来评估教师的教学表现，但潜在的趋势和偏见会影响他们的解释。使用从率我的教授的数据，我们进行了最大的和最新的定量数据分析，以研究有关的问题，学生的评价标准，当他们审查他们的男性和女性教授的表现。我们的分析涵盖了二十年（1999-2019）的数据，因此考虑到了网站和学生看法的最新变化，并展示了与学生如何看待他们的男性和女性教授的教学风格和个性特征有关的有趣见解。我们还提出了第一个分析，调查性别偏见如何随着时间的推移和空间的变化。我们相信，我们的研究结果是有趣的，从社会学的角度来看，因为他们调查性别在高等教育中的作用，揭示学生如何看待和评价不同性别的教授。此外，我们认为，我们的研究结果可以是有用的教育机构时，考虑可能存在的偏见，在其教师的评价。
英文摘要：
Institutions widely use student evaluations to assess the faculty's teaching performance, but underlying trends and biases can influence their interpretation. Using data from Rate My Professors, we conduct the largest and most recent quantitative data analysis to study questions related to the evaluation criteria that students have when they review the performance of their male and female professors. Our analysis spans data from two decades (1999-2019), thus taking into account recent changes on the website and in the perception of students, and demonstrates interesting insights related to how students perceive the teaching style and personality traits of their male and female professors. We also present the first analysis that investigates how gender bias evolves over time and changes over space. We believe that our results are interesting from a sociological viewpoint, as they investigate the role of gender in higher education by disclosing how students perceive and evaluate professors of different genders. In addition, we believe that our findings can be useful to educational institutions when considering possible biases that exist in the evaluations of their faculty.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
