University Competency-Based Courses for Internationally Educated Nurses (IENs) in Ontario: A Pilot Education Pathway to Registered Nurse (RN) Licensure
Bibliographic record
Abstract
In 2014, a team of nurse educators and champions of internationally educated nurses (IENs) in Ontario came together to address the issue of supporting IEN transition to practice as one route to help address nursing shortages. Courses were developed with funding from the Government of Ontario, and policy and coordination support from the Council of Ontario Universities, to pilot an educational bridging pathway for IENs. The faculty team across four Ontario universities used a consortium approach to coalesce province-wide expertise in IEN education. What began as a selection of targeted, competency-based courses has since evolved into a full Competency-Bridging Program of Study for Internationally Educated Nurses in Ontario, aligned with other IEN bridging program offerings across the province. This paper describes the initial process of the group, from 2015 to 2018, to create foundational learning and competency-based courses to meet targeted entry-to-practice (ETP) competencies for registered nurse (RN) registration with the College of Nurses of Ontario (CNO). The barriers to IENs in meeting ETP requirements and how the gap in the existing Ontario IEN bridging to a Bachelor of Science in Nursing (BScN) education to meet regulatory requirements are also addressed. This article explores how Ontario may respond to the increasing nursing shortages and the need to engage ethically and retain IENs in practice. Lessons learned from competency-course development add to the growing body of knowledge about IEN program experiences in Canada to enable more IENs to enter the Ontario nursing workforce.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".