Nursing students’ experience of a transformative approach to teaching cross cultural clinical decision making
Bibliographic record
Abstract
OBJECTIVES: This study reveals the learning gained by Canadian and Rwandan nursing students from a course to enhance cross cultural clinical decision-making skills using a collaborative approach across two countries. METHODS: A qualitative descriptive study was conducted using thematic analysis. The study included analysis of end of course reflections of 94 students. RESULTS: Students became more open-minded, curious, strengthening teamwork, increasing their critical thinking, and identifying cross-cultural similarities in practice. They challenged their previous beliefs about others. CONCLUSIONS: Students achieved a transformation of previous knowledge and decision-making skills. Results indicate the value of underpinning courses with theories and being open in allowing students to develop their own means to achieve expected learning outcomes. IMPLICATIONS FOR AN INTERNATIONAL AUDIENCE: Creating learning environments designed to stimulate open mindedness and exploration of cultures among students can be achieved through online learning. Providing opportunities for students to learn across other countries about their nursing practices and health systems are critical to understanding how future patients who are immigrants and refugees from other countries differing perspectives to their health care needs.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| 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".