L’évaluation de l’enseignement des sciences infirmières en milieu clinique : des compétences à développer, plutôt que des comportements à prioriser
Bibliographic record
Abstract
Le but premier de cet article est de préciser l’intention du processus d’évaluation de l’enseignement clinique, c’est-à-dire les éléments pouvant constituer l’objet de l’évaluation et ce, à partir des perceptions des professeures et des étudiantes en soins infirmiers. Une approche qualitative a été retenue pour analyser les données recueillies auprès des participantes. Les résultats indiquent que l’évaluation de l’enseignement clinique en sciences infirmières devrait être basée sur cinq compétences principales : (a) humaine, (b) pédagogique, (c) technique, (d) professionnelle infirmière et (e) organisationnelle. Ces compétences principales sont concrétisées par des compétences satellites, à leur tour explicitées par des indicateurs.
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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 | 0.026 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".