Qualitative and Quantitative Outcomes of Audience Response Systems as an Educational Tool in a Plastic Surgery Residency Program
Bibliographic record
Abstract
BACKGROUND: In-training evaluations in graduate medical education have typically been challenging. Although the majority of standardized examination delivery methods have become computer-based, in-training examinations generally remain pencil-paper-based, if they are performed at all. Audience response systems present a novel way to stimulate and evaluate the resident-learner. The purpose of this study was to assess the outcomes of audience response systems testing as compared with traditional testing in a plastic surgery residency program. METHODS: A prospective 1-year pilot study of 10 plastic surgery residents was performed using audience response systems-delivered testing for the first half of the academic year and traditional pencil-paper testing for the second half. Examination content was based on monthly "Core Quest" curriculum conferences. Quantitative outcome measures included comparison of pretest and posttest and cumulative test scores of both formats. Qualitative outcomes from the individual participants were obtained by questionnaire. RESULTS: When using the audience response systems format, pretest and posttest mean scores were 67.5 and 82.5 percent, respectively; using traditional pencil-paper format, scores were 56.5 percent and 79.5 percent. A comparison of the cumulative mean audience response systems score (85.0 percent) and traditional pencil-paper score (75.0 percent) revealed statistically significantly higher scores with audience response systems (p = 0.01). Qualitative outcomes revealed increased conference enthusiasm, greater enjoyment of testing, and no user difficulties with the audience response systems technology. CONCLUSIONS: The audience response systems modality of in-training evaluation captures participant interest and reinforces material more effectively than traditional pencil-paper testing does. The advantages include a more interactive learning environment, stimulation of class participation, immediate feedback to residents, and immediate tabulation of results for the educator. Disadvantages include start-up costs and lead-time preparation.
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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 | 0.021 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".