Web‐based student feedback: comparing teaching‐award and research‐award recipients
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We examined web‐based ratings and open‐ended comments of teaching‐award winners (n = 120) and research‐award winners (n = 119) to determine if teaching‐award winners received more favourable ratings and comments on RateMyProfessors.com. As predicted, students rated teaching‐award winners higher than research‐award winners on measures of teaching quality (i.e. helpfulness and clarity). A higher percentage of teaching‐award recipients relative to research‐award recipients received positive open‐ended comments about competence, use of humour, clarity, appearance and personality as well as both positive and negative open‐ended comments about level of course difficulty. We discuss implications of these findings for lending credibility to the RateMyProfessors.com indices and for promoting published faculty evaluations at post‐secondary institutions more generally.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.031 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it