Understanding Learners’ Experiences of Simulated Person Methodology in an Athletic Therapy Program
Bibliographic record
Abstract
Introduction Key skills required of today's students include critical thinking, problem-solving, creativity, innovation, collaboration, and communication. The acquisition of these skills is foundational to success in a variety of professions and contexts. This study complements a larger simulated person methodology (SPM) project that utilizes simulators (individuals who are trained to realistically reproduce scenarios by providing specific information, displaying signs and behaviours, and creating a realistic encounter in a consistent manner) to replicate real workplace issues, thus affording students an opportunity to apply knowledge and practice real-life skills necessary to the workplace. The primary objective of this study is to apply this innovative teaching approach in higher education as a means of developing proficient critical-thinking and interpersonal skills. Methods This pilot study uses an exploratory mixed-methods design to explore the experiences of 12 students enrolled in an athletic therapy (AT) certificate program that uses SPM. Our hypothesis is that SPM will have a positive impact on student learning and professional development. Results The students responded favourably to the use of SPM. Indeed, 80% "felt challenged and stimulated" and deemed SPM to be a "more effective method" of practicing communication skills than practicing with fellow students. These findings can inform future research and support work towards enhancing this methodology as a pedagogical approach. In tandem, this study and the larger SPM project are poised to provide an effective undergraduate education experience across various faculties at the pilot university. More work is required to align this teaching approach with the AT education program redesign.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".