Impact and Attitudes about Peer Review of Teaching in a Canadian Pharmacy School
Bibliographic record
Abstract
Objective. To evaluate attitudes toward peer review of teaching and its impact on teaching practices and perceptions. Methods. The University of Waterloo School of Pharmacy implemented a peer-review process for its teaching program in 2015. Those reviewed were invited to complete an electronic survey that captured their attitudes toward teaching, attitudes toward peer review, and changes in teaching practices, and to participate in semi-structured follow-up interviews for more in-depth discussion of these issues. Results. Twenty-six (76%) instructors completed the survey. Instructors agreed that peer reviews of teaching are a development opportunity (96%), and 73% were comfortable with the idea of peer review. Over half (58%) indicated that the review made them feel more confident that their teaching strategies were effective, and the same percentage indicated that they planned to make changes to their teaching as a result of the feedback received from the peer review. Only a few instructors indicated that peer review changed their attitudes toward teaching (12%) or increased the value they placed on teaching (34%). Eight instructors (23.5%) participated in the semi-structured interviews. Themes that emerged included: attempts to make the reviewee comfortable during the peer review were successful; the feedback provided to instructors regarding their teaching was positive but not critical enough; there was lack of clarity as to the purpose of the feedback; and instructors planned to make only minor changes to their teaching as a result of the review. Conclusion. Peer review of teaching was well received and feedback was confirmatory in nature but had minimal impact on teaching practices as it was not deemed to be critical enough. Changes to the peer review program are needed to increase its impact on teaching practices.
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.
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 | 0.011 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".