Improvisation Games in a Pharmacy Communications Course: “It was kind of interesting to get to step out of my science-orientated mind and get to be creative!”
Bibliographic record
Abstract
Introduction: Improvisational exercises were integrated into the first year Pharmacy Communication courses to enhance students’ ability to listen and develop a conversation without anticipating its progression. Specific objectives were to describe pharmacy students’ experiences with improvisation and determine if improvisation influences how students learn communication skills. Description of Improvisation: In 2009-10, pharmacy students were introduced to improvisation games with a communication focus. After an initial training, half of the class used improvisation to prepare for two standardized patient-interactions. Evaluation: Three sources of data were collected over the course of the study: reflection assignments, a focus group, and course evaluation surveys. Four main themes arose: difficulties, pharmacy practice relevance, negative outcomes, and positive outcomes. Discussion and Future Plans: Pharmacy students were ambivalent towards improvisation; identifying both challenges and benefits. In future communication courses, improvisation games will be integrated into relevant lecture time.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".