Student evaluations of teaching (SETs) are a staple in higher education, but what do they really tell us? Research shows that evaluations can be biased, unreliable, and more reflective of student satisfaction than actual teaching effectiveness. If SETs are going to play a role in assessing teaching, we should rethink what they measure, how they’re used, and how we address their limitations.

Issues with Traditional Student Evaluations

One of the biggest issues with SETs is their susceptibility to bias. Studies have consistently shown that women and faculty of color receive lower ratings than their white male counterparts, regardless of teaching quality (Aragón et al., 2023; Kreitzer & Sweet-Cushman, 2022). Department gender composition can further amplify this bias, with women in male-dominated fields facing harsh evaluations, for example.

Another major issue is the connection between grades and evaluations. Research from Kogan et al. (2022) confirms that students who are dissatisfied with their grades tend to give lower ratings, making evaluations more about personal frustration as opposed to teaching effectiveness. Even when evaluations are statistically valid, they can still be unfair due to systemic biases and structural issues in how they’re used (Esarey & Valdes, 2020).

If SETs don’t reliably measure teaching quality, how can we make them more meaningful?

What Should Evaluations Measure?

Instead of asking students how much they “liked” a course or instructor, evaluations should focus on aspects of teaching that directly impact learning. University of Michigan CRLT’s Course Evaluation Guidance (2015) recommends prioritizing:

• Clarity and organization – Were expectations and learning objectives clearly communicated?
• Engagement – Did the instructor create opportunities for meaningful participation?
• Support for learning – Did the course provide the resources and feedback students needed to succeed?
• Skill development – Did students leave the course with improved critical thinking, problem-solving, or subject-specific knowledge?

Reframing SETs around these elements could make them more useful for both faculty and institutions.

How Can We Improve Student Evaluations?

Even with their flaws, student evaluations aren’t going away anytime soon. So, we need to try to make them better. Research points to several strategies for improving how evaluations are designed, interpreted, and used:

• Use multiple methods to assess teaching – Peer observations, self-reflection, and student learning outcomes should be considered alongside evaluations (Kreitzer & Sweet-Cushman, 2022).
• Revise evaluation questions – Broad, vague questions about “teaching effectiveness” should be replaced with specific, learning-focused questions (ACUE, 2022).
• Tackle bias directly – Explicit bias intervention messaging can reduce gendered perceptions in evaluations, making feedback fairer (Kim et al., 2024).
• Discuss bias with students – Educating students about bias in SETs can lead to more thoughtful and accurate feedback (DeWall, 2023).
• Support faculty in processing evaluations – Negative feedback can be difficult to navigate, but strategies like focusing on constructive comments and looking for patterns over time can make evaluations more useful (Rubino, n.d.; Bartholomae, 2024).

Explicit Bias Intervention Messaging

According to Kim et al. (2024), explicit bias intervention messaging can help mitigate gender bias in student evaluations by making students aware of their potential biases before they complete evaluations. Bias intervention messages work by prompting students to reflect on fairness, implicit biases, and what constitutes effective teaching.

Idea into Action:

• Include a Bias Awareness Statement – Before students complete evaluations, institutions can include a statement reminding them to focus on teaching effectiveness rather than personal characteristics. For example, messages could highlight research showing that gender and racial biases can impact evaluations and encourage students to evaluate all instructors fairly.
• Reframe Student Focus – Bias intervention messages can emphasize the importance of evaluating course structure, instructor preparation, and clarity of instruction rather than subjective traits like likability or personality.
• Tailor Messaging for Maximum Effect – Kim et al. (2024) found that students’ perceptions of bias messaging vary depending on their own gender and experiences. Therefore, institutions should consider testing different wording to determine what is most effective for their student population.

Educating Students about Bias in SETs

Discussing bias with students could also lead to more thoughtful and accurate feedback because it increases their awareness of the ways unconscious biases can shape their evaluations. DeWall (2023) argues that most students are unaware of the biases that influence SETs, but when they are explicitly taught about them, they are more likely to engage in fair and reflective evaluation practices.

Idea into Action:

• Integrate Bias Discussions into the Course – Faculty can include discussions about evaluation bias in class, perhaps when explaining how SETs work and why student feedback matters. This can be a short, structured conversation or a quick mention before students complete evaluations.
• Use Pre-Evaluation Reflection Activities – Before filling out evaluations, we can ask students to reflect on what effective teaching looks like and to consider how their own expectations might be influenced by factors unrelated to teaching quality.
• Provide Research-Based Examples – DeWall (2023) suggests sharing examples from studies showing how factors like gender, race, and grade expectations impact evaluations. Seeing concrete evidence could help students recognize the importance of fair SETs.
• Frame Evaluations as a Professional Task – Encouraging students to approach SETs with the same level of professionalism as a workplace evaluation can shift their focus from personal preferences to meaningful feedback about teaching effectiveness.

Final Thoughts

If student evaluations are meant to improve teaching and student learning, they should ideally be designed with that goal in mind. By focusing on meaningful aspects of instruction, addressing bias, and using multiple forms of assessment, we can move toward a system that supports both faculty and student learning. If we’re going to keep using SETs, it’s time to make them work for everyone.

Resources:

• Aragón, O.R., Pietri, E.S., and Powell, B.A. (2023). Gender bias in teaching evaluations: the causal role of department gender composition. Proceedings of the National Academy of Sciences of the United States of America, 120(4), e2118466120. https://doi.org/10.1073/pnas.2118466120
• Bartholomae, C. (2024). Put your teaching evaluations in a jar. Inside Higher Ed. https://www.insidehighered.com/opinion/career-advice/teaching/2024/01/04/making-most-critical-student-evaluations-opinion
• Center for Research and Learning and Teaching. (2015). Course evaluation guidance one-pager. University of Michigan. https://crlt.umich.edu/sites/default/files/resource_files/Course%20Evaluation%20Guidance%20One-Pager.pdf
• DeWall, N. (2023). It’s time to discuss student evaluations bias with our students (seriously). The Teaching Professor. https://www.teachingprofessor.com/free-article/its-time-to-discuss-student-evaluations-bias-with-our-students-seriously/
• Esarey, J., & Valdes, N. (2020). Unbiased, reliable, and valid student evaluations can still be unfair. Assessment & Evaluation in Higher Education, 45(8), 1106–1120. https://doi.org/10.1080/02602938.2020.1724875
• Kim, F., Williams, L.A., Johnston, E.L., and Fan, Y. (2024). Bias intervention messaging in student evaluations of teaching: The role of gendered perceptions of bias. Heliyon,10(17), e37140. https://doi.org/10.1016/j.heliyon.2024.e37140
• Kogan, V., Genetin, B., Chen, J., and Kalish, A. (2022). Students’ grade satisfaction influences evaluations of teaching: Evidence from individual-level data and an experimental intervention (EdWorkingPaper: 22-513). Retrieved from Annenberg Institute at Brown University: https://doi.org/10.26300/spsf-tc23
• Kreitzer, R.J., and Sweet-Cushman, J. (2022) Evaluating student evaluations of teaching: A review of measurement and equity bias in SETs and recommendations for ethical reform. Journal of Academic Ethics, 20, 73–84. https://doi.org/10.1007/s10805-021-09400-w
• Rubino, D. (n.d.). 5 strategies to manage the hurt of student evaluations. Wiley. https://www.wiley.com/network/instructors-students/education-trends/5-strategies-to-manage-the-hurt-of-student-evaluations
• Snow, M., Lawner, E.K., Gyurko, J., and Pippins, T. (2022). Student evaluations of teaching: Best practices. ACUE. https://acue.org/wp-content/uploads/2023/06/ACUE-Student-Evaluations-of-Teaching-Best-Practices.pdf