Prompting Paramedics: The Effect of Simulation on Paramedics’ Identification of Learning Objectives
Bibliographic record
Abstract
INTRODUCTION: Simulation has emerged as a useful educational tool for the continued training of paramedics. Practicing paramedics are thought to learn through reflecting on their own actions in practice, and it is hoped that simulation could spur similar reflection, which could then lead to practice change. Despite this, there is limited data on how these practitioners use simulated experiences to set learning objectives. This study aimed to explore how simulation training affects self-identification of learning objectives in emergency medical services (EMS) providers (a.k.a. paramedics). METHODS: Paramedics (primary care and advanced care) participated in a 30-minute simulated learning session. All participants filled out pre-post surveys identifying their own learning objectives immediately before and after the simulation. An inductive qualitative analysis of these responses were conducted by two authors (EJ, TC) using an interpretive description approach, yielding a list of key themes commonly found in the learning objectives. Pre-post learning objectives were individually compared by the level of specificity as determined by the authorship team. Simple descriptive statistics were generated to describe the number of times that the paramedics' learning objectives became more or less specific, different, or same. RESULTS: Thirty-five paramedics who completed the simulation and survey were included. Four major themes emerged in the learning objectives: 1) assessment and diagnostic; 2) communication and collaboration; 3) integration of knowledge; and 4) treatment and management. After simulation, the learning objectives became more specific in 6 (17.1%), less specific in 3 (8.6%), different in 22 (62.9%), and remained same in 4 (11.4%). CONCLUSION: Simulation training shows promise in refining perceived learning needs. The results from this study offer insight into paramedics' self-identification of learning objectives and gaps pre-post simulation experiences. Understanding the underlying psychology of paramedics participating in simulation may help educators better understand how to guide reflection and continuous improvement.
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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 | 0.011 | 0.102 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.005 | 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".