Experiences of Student Nurses on the Use of the Two-Week Block System at the Satellite Campus of a Higher Education Institution in Namibia
Bibliographic record
Abstract
Clinical Training is intended to prepare nursing students for future nursing practice in both private and public facilities. As do many nursing training institutions globally, this Higher Education Institution (HEI) uses the two-week block system as a teaching system. However, despite the two-week block system, it would appear that, due to the increased number of nursing students, the aligning of practical exposure with theoretical instruction is becoming difficult in balancing theory and practice for both student and academics. Such alignment requires institutions of higher learning to establish which teaching systems are likely to promote the correlation between theory and practice. The experiences of students may be used to identify positive learning environment for students. This study aimed to explore and understand the personal experiences of student nurses studying at Higher Education Institution HEI in Namibia in relation to the use of the two-week block system. The objectives of the study included exploring and describing the experiences of student nurses regarding the two-week block system at the HEI with a view to ascertaining the negative impact, if any, of such a teaching system on their studies. A study employed a qualitative approach which comprised an explorative and descriptive research design, using purposive sampling. The research population in the study consisted of first to fourth year, undergraduate nursing students who were studying at a satellite campus of a HEI in Namibia. The requisite data was collected from four focus group discussions which were each conducted with six to seven participants. The transcribed interviews and narratives from the research notes were then organised into main themes and sub-themes. Three main themes and nine sub-themes were identified. The findings of the study indicated that two-week block system was associated with challenges as was evidenced by the following themes that had emerged from the study, namely, different experiences of the two-week block system, various effects of the two-week block system and recommendations to School of Nursing (SoN).The study recommended that the HEI extend the two-week block system to a one-month block system in order to give the students sufficient time in which to put the theory they have learnt into practice.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 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".