Experiential learning has become central to undergraduate medical education (UGME) as institutions move beyond traditional didactic models. This systematic review aimed to assess the effectiveness of experiential learning models in UGME using the PICOS framework: Undergraduate medical students (Population); simulation, virtual reality (VR), problem-based learning (PBL), and service-learning (Intervention); compared to traditional or no instruction (Comparison); with outcomes related to knowledge, skills, empathy, and professionalism (Outcomes); across empirical study designs (Study design). Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines, we searched PubMed, Scopus, Web of Science, and ERIC (January 2020–August 2025). A total of 1236 records were screened, and 39 studies met the inclusion criteria. Risk of bias was assessed using Cochrane Risk of Bias 2.0, ROBINS-I, and Mixed Methods Appraisal Tool tools. Interventions clustered into six domains: Simulation, VR, PBL, service-learning/student-run clinics, blended/digital innovations, and professionalism outcomes. Simulation and VR consistently enhanced clinical reasoning, skills, and communication. PBL and artificial intelligence-guided models supported problem-solving and engagement. Service-learning fostered empathy and identity. Digital and blended formats offered flexibility during the coronavirus disease 2019 pandemic. Key limitations included study heterogeneity, short follow-ups, limited cost/equity reporting, and uneven technology access. Most advanced technologies were used in high-resource contexts. Experiential learning is affirmed as a core pedagogical approach in UGME. Future studies should emphasize longitudinal outcomes, economic analyses, and equitable implementation strategies.
Building similarity graph...
Analyzing shared references across papers
Loading...
Dharmendra K. Gupta
Rakesh Kumar
Current Medical Issues
National Institute of Technology Durgapur
Burdwan Medical College & Hospital
Building similarity graph...
Analyzing shared references across papers
Loading...
Gupta et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69d896166c1944d70ce0756b — DOI: https://doi.org/10.4103/cmi.cmi_164_25