Institutional accreditation by nursing education and training quality assurance: Perspectives of heads of private nursing institutions in South Africa
Bibliographic record
Abstract
Background and objective: Nursing education throughout the world is striving for international competitiveness and accountability for effectiveness, quality, and trust to the students, patients, and the community, thus making the issue of institutional accreditation increasingly important. The aim of this paper was to explore the perceptions of heads of private nursing institutions on the benefits of school accreditation by nursing education and training quality assurance (ETQA) in KwaZulu-Natal region, South Africa.Methods: The study adopted a qualitative approach. Data were collected from seven heads of private nursing institutions. In-depth interviews were used to explore the perceived benefits of the accreditation of nursing institutions by Nursing ETQA. Thematic content analysis was used in this study to analyse the collected data. The study adhered to all ethical principles.Results: The findings from this study revealed that heads of private nursing institutions perceived the accreditation by nursing ETQA as a tool used to promote quality outcomes in nursing education. Results from this study further revealed that accreditation is a mechanism of ensuring high standards of performance, and it increases trust, confidence, and reinforcement of uniformity across the nursing education sector. In this study, several challenges were reported to hinder the accreditation process including as a disjoint and an inconsistent process of accreditation, unclear criteria for accreditation, the high cost of accreditation, accreditation being detrimental to teaching the outcome, lack of uniformity in the recommendations; and a lengthy process of accreditation.Conclusions: Accreditation is an important tool to ensure that programs and degrees meet the highest standards of education. In nursing education, the accreditation process is associated with several challenges, and there is a need for collaborative and well-coordinated accreditation of nursing schools nationally and globally.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".