Continuity from adult-nursing practice to clinical training: Reviewing students’ clinical training experience
Bibliographic record
Abstract
Objective: In this study, we analyzed a sample of nursing students, focusing on their self-directed learning experiences as they completed a program comprising specialized exercises and examinations and clinical training. Through this, we aimed to identify means of improving nurses’ self-directed learning skills during nursing education.Methods: Sixty-six third-year university students underwent a six-week adult-nursing training involving participatory-type simulated-patient (SP) exercises and objective structured clinical examinations (OSCEs), during which they maintained portfolios in which they noted their experiences and thoughts as they engaged in this education. We analyzed, through qualitative induction, the written data in these portfolios. We followed this by cross-sectionally integrating, using a chronological perspective, experiences reported by the same sample in previous research, consequently clarifying the structure of the students’ self-directed learning.Results: The students’ self-directed learning experiences during the adult-nursing training were divided into six classifications. Comparison of self-directed learning in participatory-type SP exercises, OSCE, and training, respectively, showed that few students applied their experience of the SP and OCSE exercises in training. However, during training they showed a strong ability to independently perform reviews of challenges that arose in actual practice and to engage in collaboration. They also showed increased desire to perform nursing.Conclusions: As the exercises and practice were not conducted consecutively, external experiences may have affected the continuity of the education, and hindered the students’ ability to maintain a sense of continuous development. Thus, encouraging students to regularly review their education may enhance their self-directed learning skills.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".