What’s going on in the clinical examination room?-An exploratory and comparative study of two types of clinical exams and their meaning for nursing students in the final year of the nursing education
Bibliographic record
Abstract
This study is an education experiment based on a comparative approach, where two clinical exams – a bedside exam and a written case study exam – are investigated simultaneously. The article explores what’s going on in the two exams and how nursing students assess and experience them. Based on these findings, we discuss the types of logics, knowledge, and competencies the two exams enhance and limit, respectively. Data consists of a questionnaire survey with 104 students (56/48), observations of twelve exams (6/6), followed by two focus group interviews with nurse students. The analysis shows that the bedside exam enhances ‘knowing-in-action’, ‘reflection-in-action’, ‘shows how’ and ‘does’ by its focus on nursing actions. It is unpredictable and promotes ‘logics of relational care, care production and care education'. The written case study exam enhances ‘reflection-on-action’, ‘knows’ and ‘knows-how’ by its focus on theoretically based reflections on nursing practice. It is predictable and enhances ‘logic of care education’.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 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".