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- Title
Digital Games-Based Learning Pedagogy Enhances the Quality of Medical Education: A Systematic Review and Meta-Analysis.
- Authors
Zhao, Jingjie; Zhou, Kaiyuan; Ding, Yi
- Abstract
Applying digital games (DG) in medical education and learning is increasing. The purpose of this meta-analysis was to determine the effectiveness of DG compared with other methods in terms of improving knowledge or satisfaction of learners in the medical field. An extensive search of publications dated between 2010 and 2020 was carried out through five databases. The citations as well as extracted data from articles were independently assessed, and randomized controlled trials (RCTs) were eligible acceding to inclusion. The methodological quality was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluations assessment (GRADE). To screen the systematic results, standardized mean difference (SMD) was used, and the pooled effect sizes were calculated by random effects model. I2 statistics, meta-regression and subgroup analyses were applied to evaluate the heterogeneity. In total 13 RCTs with 1236 subjects were included in research. The systemic analysis indicated a significantly improved effectiveness in support of DG compared to controls in medical education (SMD = 0.58, 95% confidence interval (CI) [0.46–0.69], p < 0.001), without significant publication bias. Additionally, significantly better outcomes were found in the long-retention of knowledge score (SMD = 0.37, 95% CI [0.19–0.55], p < 0.001). However, in the subgroup analysis no significance was indicated in the outcome of overall knowledge after using DG compared with other digital methods (SMD = 0.58, 95% CI [0.46–0.69], p < 0.001). Additionally, six studies assessed the attitude of learners, all of which reported a preference for DG. These results suggest that a DG-based medical curriculum could generate a significant improvement in learning compared to traditional methods.
- Subjects
DIGITAL learning; MEDICAL education; EDUCATIONAL quality; RANDOM effects model; META-analysis; PUBLICATION bias
- Publication
Asia-Pacific Education Researcher (Springer Science & Business Media B.V.), 2022, Vol 31, Issue 4, p451
- ISSN
0119-5646
- Publication type
Article
- DOI
10.1007/s40299-021-00587-5