Student Evaluations of Teaching: A Six-Step Strategy Turns Flawed Feedback into Faculty Growth

Student evaluations of teaching, or SETs, have become an unavoidable fixture of academic careers, and a new commentary in BMC Proceedings argues that faculty can turn these often-criticized instruments into a structured engine for professional development rather than a source of anxiety. Written by a team of scientist educators drawing on both the scholarly literature and their own lived experience, the article lays out a six-step strategy for reading, analyzing, and acting on SET data while repeatedly warning that the evaluations reflect student perception, not a direct measure of teaching effectiveness or student learning.

The commentary arrives amid a long-running controversy. Formal SETs in the United States originated in the 1920s as confidential feedback tools meant to help instructors improve, with early instruments developed by educational researchers at Purdue University and the University of Washington. By the 1950s, however, university administrators were widely using them to assess faculty members, often at the behest of student groups. The real shift toward high-stakes use came later: widespread use of SETs in personnel decisions did not begin until the 1980s, and by the 1990s, 86 percent of U.S. colleges were using SET data to inform hiring, salaries, and promotions. By 2010, that figure had risen to 94 percent, driven by growing demands for accountability from accreditation agencies, boards of trustees, and employers.

Concerns about the validity, reliability, and fairness of SETs, especially when used for comparative purposes, were being voiced as early as the 1970s, and faculty support waned as their use in personnel decisions spread. Today, the authors note, SETs remain widespread largely because no other method of evaluating teaching has gained comparable acceptance, even as research documenting bias continues to accumulate and universities face pressure to reconsider how they use them.

That bias research is central to the commentary’s argument. Instructor identity, including gender, race, ethnicity, accent, sexual orientation, or disability status, can affect results through equity bias. Studies indicate that male instructors are more likely to be perceived as competent, brilliant, or organized, while non-white instructors tend to receive lower SET ratings than their white colleagues. Women and faculty members of color receive more negative comments related to personality, appearance, mannerisms, competence, and professionalism. Class size adds another layer, with instructors of larger classes often experiencing what researchers call a large class penalty, and course characteristics such as required versus elective status, difficulty, meeting time, and discipline further shape the numbers.

Discipline matters in ways instructors cannot control. The commentary cites a recent study finding that STEM students tend to have lower grades and grade point averages, primarily due to more stringent grading in STEM courses, a disparity that may partially explain why SET ratings in STEM courses are generally lower than in non-STEM courses. Generating student interest in statistics, the authors observe, is simply harder than in social psychology. Given these distortions, the authors argue that administrators should avoid relying on SETs as the sole measure of teaching effectiveness and should treat them as reflections of student perception and experience.

The heart of the article is the six-step analysis and reflection strategy the authors propose to fill what they identify as a gap: limited guidance on how faculty can systematically use SET data for professional development and career advancement. Step one is an initial SET review, ideally several fast readings for content and first impressions only, spaced days or weeks apart to help manage the discomfort that SETs can provoke. Step two is a close review with note-taking and reflection to identify trends in the data. Step three is data extraction and analysis, in which faculty transfer numerical scores and comments, often manually from a PDF report, into a spreadsheet that allows plotting, graphing, and longitudinal tracking against departmental or institutional benchmarks.

The authors emphasize that this extracted data can pay direct career dividends, particularly for pre-tenure faculty, whose analysis, graphs, and tables can be included in annual review documents and tenure and promotion dossiers. They even suggest, cautiously, that generative artificial intelligence could assist with SET analysis, while stressing that the technology is still developing and should be used with care. When interpreting comments, the commentary advises focusing on recurring themes across multiple evaluations and courses rather than isolated remarks, prioritizing feedback representative of the majority of students, and giving particular weight to actionable suggestions, such as a call to incorporate more real-world examples, over vague critiques of an instructor’s style.

Steps four through six turn analysis into change. Reflection, the fourth step, benefits from a longitudinal perspective: analyzing trends over time can reveal where prior adjustments succeeded and highlight persistent challenges, and maintaining a reflective teaching journal lets instructors compare their own observations against SET data trends. Step five is identifying changes to teaching practice that align with the data, leverage an instructor’s strengths, and are prioritized rather than attempted all at once, since implementing too many changes simultaneously is not recommended. Step six is determining an action strategy, taking stock of the labor each change requires, from simple syllabus modifications to revamping a lab component, and addressing only as many as is reasonable in one term so the impact of each change can actually be assessed.

Throughout, the authors insist SETs should never stand alone. They are not designed for direct comparison across faculty or disciplines but for observing an individual instructor’s trajectory over time, ideally within a single course, and administrators should examine the overall distribution or median response rather than a mean that a few low ratings can skew. The commentary advocates a holistic evaluation of teaching, often described as a three-voice framework incorporating students, peer reviewers, and the instructor’s own self-reflection. Peer evaluation, when structured and conducted over time, brings disciplinary expertise, assesses elements SETs overlook such as course rigor and workload expectations, and is less susceptible to the systemic biases tied to an instructor’s gender, race, or appearance. Notably, the authors report that student learning outcome measures, while valuable evidence of learning, often show little to no positive correlation with SETs.

For institutional leaders, the recommendations are concrete: contextualize numerical scores for class size, course complexity, and student demographics; analyze evaluations longitudinally rather than as single-year snapshots; incentivize student participation, for example through early grade release; and combine SETs with peer evaluations, self-reflection, and student learning outcome assessments. The authors close with a pointed reminder that SETs, as constructed by institutions, may not reveal whether a course’s learning objectives are actually being met, and that relying on them as the cornerstone of teaching assessment sacrifices the effective angles other methods provide. Used intentionally and reflectively, alongside peer evaluation, they argue, SETs can still become an invaluable tool for educators striving to teach and serve students effectively.

Subject of Research: A commentary proposing a six-step strategy for faculty to use student evaluations of teaching for professional development while acknowledging their biases.

Article Title: Faculty professional development and career advancement through Student Evaluations of Teaching (SETs)

Article References: Cabail, M. Z., Crowder, R. N., Das, M., & Segarra, V. A. (2026). Faculty professional development and career advancement through Student Evaluations of Teaching (SETs). BMC Proceedings, 18(S1), Article 34. https://doi.org/10.1186/s12919-026-00392-2

Image Credits: AI Generated

DOI: 10.1186/s12919-026-00392-2

Keywords: student evaluations of teaching, faculty development, higher education, teaching evaluation bias, academic promotion, peer evaluation, STEM education, holistic teaching evaluation, BMC Proceedings, commentary, Faculty, professional