A Comparative Analysis of Teaching and Evaluation Methods in Nurse Practitioner Education Programs in Australia, Canada, Finland, Norway, the Netherlands and USA
Bibliographic record
Abstract
A scoping review of published literature and dialogue with international nurse practitioner educators and researchers revealed the education of nurse practitioner students varied within and between countries. This lack of cohesiveness hinders nurse practitioner role development and practice nationally and internationally. A rapid review of grey literature was conducted on nurse practitioner education standards in six countries (Australia, Canada, Finland, Norway, the Netherlands, and USA). Data were extracted from graduate level nurse practitioner education programs' websites from each country (n = 24). Extracted data were verified for accuracy and completeness with a nurse practitioner educator from each program. Data were analyzed using content analysis. Variations in nurse practitioner education within and between countries were explored by comparing admission criteria, curricular content, clinical requirements, teaching methods, and assignment and evaluative methods. The findings will help inform education programs and further research about nurse practitioner education internationally.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".