Identifying the potential organizational impact of an educational peer review program
Bibliographic record
Abstract
The literature on educational peer review (EPR) has focused on evaluating EPR's impact on faculty and/or student learning outcomes; no literature exists on the potential organizational impact. A qualitative (case study) research design explored perceptions of 17 faculty and 10 administrators within a school of nursing in an Ontario university regarding the potential impact of an EPR program on organizational goals. Findings suggested that the implementation of an EPR program may increase consistency in the delivery of the curriculum, provide opportunities for faculty development, act as a method of teaching evaluation, and enhance faculty retention. Higher education institutions may be more likely to provide the resources required for EPR if the organizational benefits can be demonstrated. La documentation au sujet de “l'évaluation éducative par les pairs” (educational peer review) (EPR) est centrée sur l'étude d'impact de l'EPR sur les objectifs d'apprentissage (learning outcomes) des enseignants et/ou des étudiants; il n'existe aucune documentation portant sur l'impact organisationnel potentiel. Cette recherche qualitative (études de cas) a permis d'explorer les perceptions à l'égard de l'impact potentiel d'un programme d'EPR sur les objectifs organisationnels de 17 enseignants et 10 administrateurs provenant d'une école de sciences infirmières rattachée à une université de l'Ontario (Canada). Les résultats suggèrent que l'implantation d'un programme d'EPR peut accroître la constance de mise en œuvre du cursus, fournir des occasions de développement pédagogique, servir de méthode d'évaluation de l'enseignement, et améliorer la rétention du corps enseignant. Les institutions d'enseignement supérieur seront peut‐être davantage susceptibles de fournir les ressources nécessaires à l'EPR si l'on peut faire la preuve de ses bénéfices organisationnels.
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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 | 0.072 | 0.245 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.005 |
| 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".