Students Are Willing to Evaluate — They Just Doubt Anyone Listens: The Spencer & Schmelkin Evidence

The short answer

When Spencer and Schmelkin (2002) asked students directly what they think about evaluating their teachers, the answer was not the cynicism administrators often assume. Students were generally willing to complete evaluations and took the task reasonably seriously. What they lacked was confidence that their evaluations were actually read, valued, or acted upon by instructors and administrators. Later work confirms the corollary: students are most motivated to give feedback when they believe it will improve teaching and the course — and least motivated when its only visible use is administrative (tenure, promotion files) that never loops back to them (Chen & Hoshower, 2003).

The practical implication is the opposite of the usual reflex. The biggest threat to your response rate and your data quality is not student apathy you must bribe away; it is a credibility gap — students who suspect the survey disappears into a void. Closing that gap, by showing feedback is used, is the single most evidence-based lever a quality-assurance office has for both participation and honesty.

What the research says

The Spencer and Schmelkin study

Spencer, K. J., and Schmelkin, L. P. (2002), Student Perspectives on Teaching and Its Evaluation, published in Assessment & Evaluation in Higher Education (27(5), 397–409), administered a survey to a random sample of undergraduates to capture how students themselves regard the evaluation process. Three themes recurred:

1. Willingness to participate. Contrary to the stereotype of the disengaged student, respondents were broadly willing to provide feedback and did not view the task as illegitimate or pointless in principle.
2. Comfort and candour conditions. Students were generally comfortable giving feedback — but their candour was tied to conditions, particularly anonymity and the absence of fear that honest criticism could rebound on them.
3. Doubt about impact. The weak point was efficacy belief: students had little confidence that their evaluations were genuinely taken into account by faculty or administration. They suspected the forms were collected and shelved.

In other words, the limiting reagent in a course-evaluation system is not students' goodwill; it is their belief that the exercise matters.

Corroboration: motivation is about perceived use

Chen and Hoshower (2003), Student Evaluation of Teaching Effectiveness: An Assessment of Student Perception and Motivation (Assessment & Evaluation in Higher Education, 28(1), 71–88), examined what actually motivates students to participate. The most attractive outcome to students was an improvement in teaching; the second was using feedback to improve course content and format. Using evaluations for personnel decisions (tenure, promotion, pay) or for publishing instructor league tables was markedly less motivating. The signal is unambiguous: students engage when feedback is formative and visibly returned to them, not when it is purely summative and invisible.

This connects to a wider expectancy logic — students complete a survey carefully when they expect it to lead to a valued outcome. Remove the expected outcome and you get the familiar failure modes: low response rates, straightlining, and thin open-text comments. The credibility gap and the data-quality problem are the same problem.

Why this matters more, not less, in the online era

Spencer & Schmelkin wrote when paper forms handed out in class were still common, and the in-room ritual itself created social pressure to participate. The sector-wide shift to online and mobile administration removed that ambient pressure and exposed the underlying efficacy belief: when nobody is watching you fill in the form, you only do it if you think it is worth doing. This is one reason online response rates fell when institutions dropped paper, and it explains why incentive gimmicks produce diminishing returns — they raise the cost of not responding without touching the reason students disengaged. For European quality-assurance frameworks (the ESG and ENQA standards) that expect student voice to feed a genuine improvement cycle, the lesson is structural: a high response rate is a downstream indicator of a credible feedback culture, not something to be manufactured in isolation. If students across a faculty quietly believe evaluation is theatre, no reminder schedule will fix the data; the institution has to make the loop visible first.

Why it matters for course evaluation in practice

If the binding constraint is students' belief that feedback is used, then the standard playbook — chase response rates with reminders and incentives — treats the symptom and ignores the cause. Four practical moves follow.

1. Close the loop visibly, and say so before you ask again. The most powerful response-rate intervention is the one most programmes skip: tell students what changed because of last cycle's feedback. A simple "you said / we did" summary, published before the next evaluation opens, converts the abstract promise that feedback matters into evidence. Spencer & Schmelkin and Chen & Hoshower together predict this lifts both participation and the quality of what students write.

2. Protect candour with credible anonymity. Students' comfort is conditional on not being identifiable and not fearing reprisal. Anonymity is not just an ethics checkbox; it is a precondition for the honest signal you are trying to collect. If students doubt anonymity, social-desirability pressure flattens the data.

3. Lead with formative, not summative, framing. Because improvement is the outcome students care about most, frame evaluations as a route to better teaching and a better course — not as a managerial audit. Where evaluations do feed personnel decisions, be transparent about it, but do not let that be the only visible purpose, or you depress the very motivation that produces good data.

4. Treat low engagement as a diagnosis, not a defect. A sagging response rate is information: it often means students have learned, correctly, that feedback goes nowhere. The fix is upstream — demonstrate use — not downstream coercion.

Limitations and honest caveats

• Self-report about attitudes is not behaviour. Students saying they are willing to participate is not the same as participating, and stated motivations can diverge from what actually drives response under real conditions.
• The study is two decades old and U.S.-based. Student expectations, the shift from paper to online and mobile administration, and survey-fatigue dynamics have all changed since 2002. The core mechanism — efficacy belief drives engagement — appears robust, but specific magnitudes may not transfer to a 2026 European cohort.
• Single-institution sampling. Generalizing one campus's student attitudes to all disciplines, cultures and degree levels requires caution; response cultures differ markedly across national higher-education systems.
• Closing the loop is necessary, not sufficient. Demonstrating use will not rescue a badly designed instrument, an over-surveyed cohort, or a survey fielded at the wrong time. It is one powerful lever among several, not a universal cure for low response.

How Koji incorporates this

Koji is an AI-native course-evaluation platform, and the Spencer & Schmelkin finding — that perceived use, not apathy, governs engagement — is central to how it is designed.

• Conversational engagement that signals the feedback is heard. A static Likert form silently communicates "tick the box and move on." Koji's AI-moderated conversational interviews respond to what a student says, ask a relevant follow-up, and acknowledge the point — an interaction that feels listened-to in the moment, which is exactly the efficacy signal students report missing. This is designed to lift both completion and the richness of open-text responses.
• Closing-the-loop and action tracking by design. Because the strongest lever is visibly using feedback, Koji supports automatic thematic analysis that turns hundreds of comments into a small set of actionable themes a programme can respond to, plus action tracking to record and report what changed — the raw material for a credible "you said / we did" message back to students.
• Credible anonymity to protect candour. Consistent with students' conditional comfort, Koji is built to collect feedback under clear anonymity and to report at aggregate, theme level rather than exposing individuals — reducing the social-desirability pressure that distorts non-anonymous feedback.
• Formative, mid-cycle collection. Since students value feedback that improves their course, Koji supports mid-cycle/formative collection so a cohort can see changes within their own term — the most direct possible demonstration that evaluation is not a void.

As always, these are framed as mitigations rather than guarantees: a platform can make feedback feel heard and make closing the loop easy, but the institution still has to actually act. For teams whose research extends beyond teaching into product and customer insight, Koji's core research platform at koji.so applies the same AI-moderated interview engine, where the same "respondents engage when they believe they are heard" principle holds.

Related Resources

• Does Anonymity Make Students More Honest? Social Desirability and Course Feedback
• What Actually Raises Course-Evaluation Response Rates? The Experimental Evidence
• Does Closing the Feedback Loop Actually Matter? The Evidence on Acting on Student Evaluations
• Survey Fatigue: Why Over-Surveying Students Quietly Wrecks Your Response Rates
• Do Student Evaluations Actually Improve Teaching? The Feedback-Intervention Evidence
• Should Student Evaluations Decide Tenure? The Ryerson Arbitration and the Limits of High-Stakes SET

References

• Spencer, K. J., & Schmelkin, L. P. (2002). Student perspectives on teaching and its evaluation. Assessment & Evaluation in Higher Education, 27(5), 397–409. https://doi.org/10.1080/0260293022000009285
• Chen, Y., & Hoshower, L. B. (2003). Student evaluation of teaching effectiveness: An assessment of student perception and motivation. Assessment & Evaluation in Higher Education, 28(1), 71–88. https://doi.org/10.1080/02602930301683
• Benton, S. L., & Cashin, W. E. (2012). Student ratings of teaching: A summary of research and literature (IDEA Paper No. 50). The IDEA Center. https://www.ideaedu.org/idea_papers/student-ratings-of-teaching-a-summary-of-research-and-literature/
• Spooren, P., Brockx, B., & Mortelmans, D. (2013). On the validity of student evaluation of teaching: The state of the art. Review of Educational Research, 83(4), 598–642. https://doi.org/10.3102/0034654313496870