Measuring Student Responses in and Instructors’ Perceptions of Student Evaluation Teaching (SETs), Pre and Post Intervention
Bibliographic record
Abstract
At most colleges and universities, students are invited to complete Student Evaluation of Teaching (SETs), which have both formative and summative purposes. In this convergent mixed methods study we evaluated if we could influence (a) students’ numerical responses and nature of their comments and (b) instructors’ physical and emotional responses to SET results, their perceptions of their results, and perceptions of SETs overall. Students who received an in-class intervention submitted more qualified comments, addressed specific issues, and made more recommendations for improvements compared to students who did not receive the intervention. Instructors reported reduced physical symptoms related to SETs after they received the intervention. Instructors reported that the intervention helped them let go of feelings of frustration and isolation and that they had acquired new strategies for opening, reading, and interpreting SET results. They continued, however, to report feeling apprehensive, uneasy, and uncertain about impending SET results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".