The effect of educational games on medical students’ learning outcomes: A systematic review: BEME Guide No 14
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
BACKGROUND: An educational game is 'an instructional method requiring the learner to participate in a competitive activity with preset rules.' A number of studies have suggested beneficial effects of educational games in medical education. AIM: The objective of this study was to systematically review the effect of educational games on medical students' satisfaction, knowledge, skills, attitude, and behavior. METHODS: We used the best evidence medical education (BEME) collaboration methods for conducting systematic reviews. We included randomized controlled trials (RCT), controlled clinical trials, and interrupted time series. Study participants were medical students. Interventions of interest were educational games. RESULTS: The title and abstract screening of the 1019 unique citations identified 26 as potentially eligible for this article. The full text screening identified five eligible papers, all reporting RCTs with low-to-moderate methodological quality. Findings in three of the five RCTs suggested but did not confirm a positive effect of the games on medical students' knowledge. CONCLUSION: The available evidence to date neither confirm nor refute the utility of educational games as an effective teaching strategy for medical students. There is a need for additional and better-designed studies to assess the effectiveness of these games and this article will inform this research.
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 | 0.012 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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