Lost in translation: barriers to learning in health professional clinical education
Bibliographic record
Abstract
Abstract The perennial debate concerning the so‐called ‘theory‐practice gap’ pervades health professional education. It is uncertain whether this gap – the notion that knowledge gained in university does not translate well into the workplace – is unavoidable or if it is a manifestation of the learning approaches used and the cultures operative in the two locations. This paper examines how nursing students’ knowledge and skills gained within university clinical laboratories transfer into the reality of the clinical environment. A series of one‐on‐one interviews were conducted over a two year period with second and third year nursing students ( n = 28) participating in a preceptorship clinical placement model at one healthcare organisation. This paper focuses on data from the students' first interview. Data were transcribed and imported into NVivo 8 for thematic analysis. Four key themes emerged, including: ‘How I learn’ which focuses on students’ perceptions of their learning preferences; ‘Lack of engagement – it’s not real’ which concerns a perceived lack of authenticity of clinical laboratories; ‘Lack of affordances’ relating to the learning opportunities available in the clinical setting; and ‘Teacher Impact’ which focuses on the influence of individual teachers on student learning. The ‘parallel universes’ of academia and the workplace create dissonance for students as they juxtapose the authenticity of the clinical laboratories with the reality of professional healthcare practice. Transfer is inextricably linked with the individuals’ learning preferences, the affordances the workplace offers to students, and the willingness of staff to provide exciting, engaging learning opportunities. The challenge for health professional education is to provide a model of clinical education that meets not only the needs of university and clinical staff, but most importantly, the needs of students.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".