Factors Influencing Nursing Education and Teaching Methods in Nursing Institutions: A Case Study of South West Nigeria
Bibliographic record
Abstract
BACKGROUND: Teaching and learning are like two composites sides of a coin. While the indispensability of teaching to knowledge and skill acquisition among professionals including nurses is never in doubt, certain teaching methods have been proven to yield more fruitful results than others. This study therefore explored the lived experience of nurse educators regarding teaching methods and the challenges encountered in nursing education institutions in South West Nigeria. METHODOLOGY: A qualitative inquiry research approach was used. Fifteen nursing educators were purposively selected from three nursing institutions in South West Nigeria with at least one year of teaching experience. Data was collected through semi-structured, in-depth individual interviews with the selected participants. All interview sessions were audio recorded with participants' permission and later transcribed verbatim. Thereafter, the collected data was analyzed using thematic content analysis. RESULTS: The study identified a number of factors that hindering teaching methods that support students learning by nurse educators. Results showed six themes viz: Inadequate preparedness of the students for higher education; Insufficient facilitation skills of the teachers; Misconceptions about teaching practices; Resource constraints; Resistance to change; and Lack of incentives. Further analysis revealed that the dynamic changes occurring in the health care professions, require a radical shift in the way nursing students are taught, to develop them into competent nurses of the future, who are capable of using their skills to solve the health care needs of the populace. CONCLUSIONS: The effective use of teaching methods is the cornerstone of the future of general nursing and nursing practice. Nurses need to be trained with an objective to become skilled and competent through effective teaching and learning by taking into account the diversity of higher education institutions and responding effectively to the needs of nursing educators and nursing students, as well as institutional demands.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".