A framework for using SET when evaluating faculty
本文提出一个框架，通过结合OLS模型残差与平均SET分数，更细致地解读学生教学评价数据，帮助高校在教师人事决策中更公平地使用SET。
This paper presents a framework for utilizing Student Evaluations of Teaching (SET) in faculty evaluations. Recognizing the ongoing debate about the validity of SET as a measure of teaching effectiveness, the authors agree with scholars who propose viewing SET as a tool for gauging ‘student perceptions of learning’. They present a method that combines post-estimation residuals from an Ordinary Least Squares (OLS) model, which accounts for key confounding factors, with simple mean SET scores. This approach provides a more nuanced perspective on each faculty member's individual ratings. The authors draw on SET data from courses taught by tenured faculty in the Faculty of Arts and Sciences at a large, private university in the Northeastern United States. Their findings suggest that the proposed residual framework can help address some of the concerns associated with the use of SET in personnel decision-making. However, they caution that this approach requires careful explanation and should be used in conjunction with a comprehensive review of a professor's full teaching portfolio. The study contributes to the ongoing discourse on the use of SET in faculty evaluations, offering a more equitable and nuanced approach to interpreting SET data.