A Canadian Perspective on the ‘NCLEX-RN World’: Pragmatism When the Stakes are High
Bibliographic record
Abstract
According to the Ontario nursing regulatory body, the American-designed high stakes nursing licensure examination, the NCLEX-RN, is a valid measure to assess the Canadian entry-to-practice competencies requisite of each new graduate registered nurse. This examination is used to “…ensure that it grants registration only to those who demonstrate the nursing knowledge to provide safe care” (para. 1). However, limited research exists that explores, examines and evaluates the impact of the NCLEX-RN in Canada since adoption from the United States of America in January 2015. Particularly, no studies existed that explored the experiences and perceptions of practicing Registered Nurses (RNs) who have written the NCLEX-RN, outside of the first-year test-takers. This thesis document describes the findings of a collective case study to better understand the NCLEX-RN, as experienced by six Canadian RNs from both acute and non-acute healthcare environments in Ontario, Canada. A within-case, document, and cross-case thematic analysis was used. The participants described their experiences with, and perceptions about, the NCLEX-RN within four main themes – influencing preparedness; examining the Canadian RN; becoming ready for safe practice; and reflecting as a practicing RN. The findings of this study support existing literature that a lack of content reflective of Canadian healthcare values exists in the NCLEX-RN. The educational impact and consequences of high stakes testing such as, curricular molding to external evaluation and concerns related to exam validity, are also highlighted. Presently, Canadian nurse educators and future test-takers must approach the NCLEX-RN pragmatically to ensure licensure of graduates with minimal disruption to the Canadian baccalaureate nursing education.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.055 | 0.039 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 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".