The PEGASUS Games: Physical Exam, Gross Anatomy, phySiology and UltraSound Games for Preclinical Medical Education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: Gamification engages learners and has successfully taught point-of-care ultrasound (POCUS) to residents and fellows. Yet ultrasound (US) curricula in undergraduate medical education remains limited. This study assessed a gamification model integrating US, anatomy, physiology, physical examination, and radiology created for preclinical medical students as compared with traditional didactic education. Methods: Twenty first-year medical students participated in a session on neck and thyroid material. Students were randomly assigned to a game or non-game group. Game students participated in games incorporating thyroid US with exam maneuvers, other imaging modalities, physiology, and pathology. Non-game students were taught the same material with an instructor. Students were assessed with a pretest and immediate and delayed post-tests. Group differences and scores were assessed using t-tests. A Likert scale evaluated learners’ opinions of the educational experience. Results: The game group performed better than the non-game group on the immediate post-test (p = 0.007, CI = [0.0305, ∞]). There was no significant difference between the groups on the delayed post-test (p = 0.726, CI = [-0.120, ∞]). Students in both groups felt more confident in their knowledge of the material, and all students in the game group agreed that the games encouraged teamwork. Most (9/10) stated the games allowed them to learn the material more effectively and would like to see more gamification (8/10). Conclusion: This US education model incorporating gamification for preclinical medical students promotes teamwork and is as effective for learning material than a traditional learning model. Students additionally convey a positive attitude towards gamification.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it