Nursing Students' Learning in High Fidelity Simulation: An Ethnographic Study
Bibliographic record
Abstract
Understanding what happens to students’ learning in high-fidelity simulation (HFS) is important as we build our knowledge around the use of HFS in nursing education. Research in the area of high-fidelity is emerging at a rapid pace, however much of the literature surrounds the area of self-efficacy and or that of outcomes related to the clinical skill performance in HFS. To date there has been little research that examines what happens in HFS that affects nursing students’ learning. The purpose of this thesis was to look at the culture of learning in HFS in undergraduate nursing education. Specific areas that were explored were students’ and instructors’ views about: the use of HFS on student learning, what it is like to participate in HFS, and factors that either enhance or impair the simulated clinical experience. Using the ethnographic method, participant observations were conducted over a period of two academic terms. A convenience sample of 12 students and two clinical instructors were interviewed regarding their perspectives, and 20 instructors participated in one of two focus groups. The interviews and observations yielded rich data that was initially coded and then segmented to form themes. Member checks were conducted to ensure rigor. To triangulate data, four reflective journals were also used in this focused ethnographic study. The key findings were that students believed that the level of instructor involvement at critical points during HFS was important and instructors believed that their comfort level in teaching with HFS had an important influence on teaching and subsequently learning in HFS. Other factors that enhanced or impaired the simulated clinical experience included realism, the ability to make mistakes in HFS and the specific roles assigned to students during HFS. An important limitation of the study was the possible bias that might have resulted from the researcher’s extensive experience with HFS. A major implication for practice pertains to the preparation of faculty and students for HFS. How students’ mistakes during HFS inform their clinical practicum is an important question to address in future research.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 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".