Exploring students' willingness to provide feedback: A mixed methods research on end-of-term student evaluations of teaching
Bibliographic record
Abstract
Student Evaluations of Teaching (SET) are one of the most consistently administered tools to assess teaching performance in higher education institutions. SET affect the careers of individuals (summative evaluation), and have potential to shape the quality of instruction (formative evaluation). Past studies have addressed several issues with SET, but few have focused on surveying and interviewing students to better understand how they navigate and complete these evaluations. Therefore, a mixed methods design was used to explore university students' willingness to provide feedback through SET as part of the teaching evaluation process. Results indicate students’ positive views about the evaluation process and their perception of usefulness of evaluations increased their willingness to provide feedback, whereas potential student biases decreased their willingness to provide feedback. More importantly, results also highlight students are still not aware of, and do not really understand, the implications of their SET responses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.084 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".