Data · dataset · 2025
DATA- Effectiveness of simulation and gamification as learning tools in medical education. A systematic review and meta- analysis
Listed in Teesside University Research Data Repository
A systematic review was conducted from October 2024 to January 2025.
Description
The final search was carried out on January 21st, 2025. Databases used for research were Pubmed, Scopus and Web of Science (WoS).
The research question was structured using the PICO framework to ensure a clear and focused approach. The population of interest comprises students and professionals in the field of medicine, as these groups are directly involved in the educational processes being studied. The intervention focuses on the use of simulation and gamification as learning tools, highlighting their potential to enhance educational experiences and outcomes in medical training.
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The comparison is established against traditional teaching methods commonly employed in medical education, such as lectures and standard clinical training, to evaluate the added value of simulation and gamification. The outcomes of interest are centered on measurable improvements in key areas, including the acquisition of clinical skills, enhanced decision-making abilities, and increased performance in both simulated and real-world settings.
This structure ensures that the research remains targeted and capable of addressing the effectiveness of these innovative educational strategies in medical education.
Links
Where it is published
- DOI doi.org/10.17632/zf3bgs5ztm.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Earth & Environmental Science · Medicine & Health · Social Science
- Inferred from text
- Simulation 75%
Provenance · 1 source records, 9 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/zf3bgs5ztm.1 | 19 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[method].local:method:simulation | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |