The Experience of Nursing Instructors and Students on Professional Competency of Nursing Academic Staff: A Qualitative Study
Bibliographic record
Abstract
BACKGROUND: One of the most important purposes of health-oriented educational centers is to train competent nurses. This study was intended to discover the meaning of "competency of nursing academic staff" among nursing students and instructors. METHODOLOGY & METHODS: A qualitative study using the content analysis approach was conducted. The data was collected through in-depth interviews consisting of 30 individuals and a focus group. RESULTS: Data analysis resulted in the extraction of 15 categories and 6 themes. The themes included 'providing effective education', 'increasing research capability of oneself and that of the students', 'promoting managerial competency', 'being a cultural and behavioral role model', 'motivating and nurturing the students', and 'boosting teaching values and disposition'. CONCLUSION: This study resulted in discovering the real meaning of professional competency among the nursing faculty staff. The findings could be utilized in designing assessment tools for professional competency of nursing academic staff in nursing schools and other medical fields.
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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 | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".