Nurse Educator Certification: Overview and Evaluation of the Canadian Association of Schools of Nursing Program
Bibliographic record
Abstract
The Canadian Association of Schools of Nursing (CASN) has spearheaded an education institute and fostered the growth of an accessible cadre of innovative educational programming that were built on identified national nursing educator competencies. The purpose of this article is to outline the development and structure of the CASN Canadian Nurse Educator Certification Program, share an analysis of one aspect of program evaluation data and summarize the program’s current value to nurse educators. The program offers flexible professional development for Canadian nurse educators through three online modules that prepare participants to sit the national certification exam and attain the designation of Canadian Certified Nurse Educator (CCNE). Part of an ongoing program evaluation conducted by CASN in 2021 sought to provide information on the perception of certification of nurse educators in Canada. A review of the process of module delivery that prepares educators to sit the certification exam and how certification is perceived as valuable or not by nurse educators was the focus. The CCNE program participants’ perspectives on the value of module learnings in terms of academic practice were evaluated using the Perceived Value of Certification Tool for the Nurse Educator. Of the 108 respondents to the survey questions, the findings indicate that most CCNE nurse educators perceived that there is value in nurse educator certification. A key survey finding was that educators perceived intrinsic value more so than extrinsic value in obtaining certification. Overall, the respondents believed that certification was not fully recognized by employers, colleagues, or students and that enhancing others’ perceptions of certification was needed. Despite consistent enrolments in the CASN program modules, the program and CCNE designation appear to require further formal recognition from teaching and academic institutions across the country. With the shortage of qualified nursing faculty, the need to strengthen current academic faculty members’ competencies is imperative. The certification and credentialing of academic nurse educators needs to be recognized. Educators should be provided merit for the acquisition of the specialized knowledge, expertise, and competencies required for the role. Résumé L’Association canadienne des écoles de sciences infirmières (ACESI) a dirigé un institut de formation et favorisé la croissance d’un cadre accessible de programmes éducatifs novateurs fondés sur les compétences nationales identifiées des enseignant(e)s en sciences infirmières. Le but de cet article est de décrire le développement et la structure du Programme canadien de certification pour infirmières et infirmiers enseignant(e)s de l’ACESI, de partager une analyse
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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 | 0.034 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".