Comparison of Knowledge Retention after the Use of a Virtual Patient versus a High-Fidelity Physical Simulator and Traditional Training
Why this work is in the frame
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Bibliographic record
Abstract
Aim: This research assesses the effect of a virtual patient simulation platform CyberPatient (CP) compared to a high-fidelity physical simulator SimJunior (SJ) and traditional bedside training (TBT) on knowledge retention and competencies in a health education environment. Material: A total of 143 fifth-year medical students were randomly assigned to three groups: TBT-Group (n = 55) received traditional education; CP-Group (n = 44) was trained with a virtual patient platform CyberPatient; and SJ-Group (n = 44) was trained using a high-fidelity simulator SimJunior. Educational content for all groups included competencies on pediatric asthma. Methods: Students’ level of knowledge acquisition was measured with a multiple-choice question test (MCQ) administered before the application of educational methods (Assessment I), immediately after completion of pediatric asthma training (Assessment II), and knowledge retention was measured two months later the completion of training (Assessment III). At the end of the study, student satisfaction was also measured by a survey questionnaire containing 5 questions rated on a Likert scale. Results: Assessment of acquired knowledge immediately after completion of pediatric asthma training revealed a significant difference between TBT-Group and SJ-Group (p p Conclusions: Virtual training with CyberPatient and high-fidelity physical simulation had a significant (p
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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