Game-based versus traditional case-based learning: comparing effectiveness in stroke continuing 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
OBJECTIVE: To evaluate family physicians' enjoyment of and knowledge gained from game-based learning, compared with traditional case-based learning, in a continuing medical education (CME) event on stroke prevention and management. DESIGN: An equivalence trial to determine if game-based learning was as effective as case-based learning in terms of attained knowledge levels. Game questions and small group cases were developed. Participants were randomized to either a game-based or a case-based group and took part in the event. SETTING: Ontario provincial family medicine conference. PARTICIPANTS: Thirty-two family physicians and 3 senior family medicine residents attending the conference. INTERVENTION: Participation in either a game-based or a case-based CME learning group. MAIN OUTCOME MEASURES: Scores on 40-item immediate and 3-month posttests of knowledge and a satisfaction survey. RESULTS: Results from knowledge testing immediately after the event and 3 months later showed no significant difference in scoring between groups. Participants in the game-based group reported higher levels of satisfaction with the learning experience. CONCLUSION: Games provide a novel way of organizing CME events. They might provide more group interaction and discussion, as well as improve recruitment to CME events. They might also provide a forum for interdisciplinary CME. Using games in future CME events appears to be a promising approach to facilitate participant learning.
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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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