Promoting empathy through immersive learning
Bibliographic record
Abstract
Objectives: This paper reports on a mixed methods study to explore the use of immersive learning with a convenience sample of healthcare students (seven of Mental Health Nursing and twelve of Occupational therapy) in promoting empathy. Two immersive learning scenarios were created using real life stories of the symptoms experienced by people with psychosis and sufferers of Post Traumatic Stress Disorder (PTSD). Methods: Data were collected using a mixed methods approach: quantatively, using a pre and post test measure using two previously validated tools together with qualitative reflections related to the immersive learning experience. Results: The quantitative aspect of the study demonstrated that the immersive experience solidified the already positive attitude that the participants had towards mental health and to empathy. The qualitative findings demonstrate that immersive learning brought an awareness of being empathic to the fore. Conclusions: The findings provide evidence regarding the impact of immersive learning as a pedagogical approach. The experience provided students with an opportunity to embody people with mental illness, and students were able to consider their own future practice in relation to people experiencing auditory and visual hallucinations and flashbacks associated with PTSD.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".