Collaborative online international learning in pre-licensure nursing: A case study
Bibliographic record
Abstract
Background: Despite the many noted benefits of collaborative online international learning (COlL) projects, it has rarely been used in nursing education. Nursing curricula must employ multiple strategies to prepare graduates for professional practice. With COIL’s benefits, its application to nursing education should be explored.Methods: A qualitative case study approach guided by social constructivist theory was used to assess the impact of COIL on pre-licensure students' understanding of community/public health nursing, and the impact on preparedness for practice. 10 participants completed COIL projects and two surveys.Results: Three themes were identified: enhanced perspectives of public health issues/practices/interventions; enhanced knowledge; and broadened understanding of role and scope of practice. 10 participants noted an impact on preparation for professional practice. 7/10 demonstrated a difference in definitions of community/public health nursing.Conclusions: Further inclusion in pre-licensure curricula should be explored, particularly for its potential impact on preparation for professional practice.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".