From practical nurse to bachelor of nursing student: bridging the transition
Bibliographic record
Abstract
Abstract Background A streamlined academic approach for career advancement is needed that allows practical or enrolled nurses to obtain a Bachelor of Nursing (BN) degree. One strategy in this approach is offering college-prepared Practical Nurses (PNs) the opportunity to transition into a baccalaureate program through a bridging course. Bridging initiatives serve as professional development opportunities for learners with personal growth and financial advantages on degree completion and enhance health and human resources for health care systems within national and international landscapes. Objective and methods A curricular model and strategies on how such a bridging course can be constructed are discussed in this article. The model integrates teaching and learning strategies as well as course sequencing, structure, and assessment strategies. Results and conclusion This innovative bridging curriculum offers Canadian and international nurse educators a programmatic guideline to create educational pathways for practical or enrolled nurses to obtain a baccalaureate degree. Completion of the bridging curriculum and BN program allow graduates to assume the RN role following a successful pass on the National Council Licensure Examination (NCLEX).
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".