Becoming a Global Citizen through Nursing Education: Lessons Learned in Developing Evaluation Tools
Bibliographic record
Abstract
While global health practica are being increasingly described in nursing education literature, course evaluation of same receives comparatively less attention. In this article, authors report on an evaluation project, undertaken to rigorously examine the existing evaluation methods for an elective global health practicum with placements in India and northern Canada. Sixteen students were interviewed and course evaluation tools were reviewed. Resulting themes include students' sense of preparedness, the centrality of the student-preceptor relationship, the importance of supported self-reflection, and the usefulness of evaluation methods. Participants viewed existing course evaluation methods as generally useful, therefore requiring only minor adjustments. There were also structural revisions to the preparation, placement, and post-placement phases of the course and broader lessons learned. Lessons include the importance of critical social perspectives and the value of past students revisiting their experiences in such a way as make conscious connections between placement experiences and their current professional practice.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 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".