Extended Abstract
Background
Simulation-based education (SBE) has emerged as one of the most innovative and effective approaches in medical and health professions education, enabling learners to practice complex clinical and decision-making skills in safe, controlled environments. Despite its proven educational impact, the rapid pace of technological innovation, the emergence of digital learning ecosystems, and the evolving expectations of new learner generations call for a framework-oriented approach to the development and governance of SBE. This study aimed to design a framework for simulation-based medical education by integrating global trend analysis with expert consensus obtained through the Delphi method.
Methods This mixed-methods study was conducted in two complementary phases. In Phase I, systematic searches of PubMed, Scopus, Web of Science, Embase, and Google Scholar identified articles published between 2015 and 2025 addressing global trends, emerging technologies, and future directions in simulation-based medical education. Eligible sources included original research, reviews, and policy reports addressing foresight, innovation, or technological evolution in SBE. Data were extracted and thematically analyzed to identify key global drivers and trends.
In Phase II, a three-round Delphi study was conducted to validate and prioritize the trends identified in Phase I and to develop a conceptual framework. A purposive sample of 25 national experts in medical education, health informatics, and educational technology participated. In each round, experts rated the importance, likelihood, and impact of the identified trends on a five-point Likert scale. Consensus was determined using the Content Validity Ratio (CVR) and mean ratings; items that did not meet the predefined thresholds (CVR > 0.37 and mean > 3.5) were excluded.
Results
The scoping review identified 81 relevant studies and policy documents, which were categorized into thematic clusters. Thematic synthesis revealed six major global drivers shaping the future of SBE:
1. Technological transformation (artificial intelligence, mixed reality, Metaverse)
2. Data-driven education and learning analytics
3. Changing roles of faculty and learners
4. Personalized and adaptive learning
5. Ethical and legal imperatives in simulation
6. Expansion of interprofessional and team-based education
7. Delphi consensus confirmed thirteen core components, organized into a three-layer future-oriented framework:
· Layer 1: Global Trends and Driving Forces: This layer encompasses (1) technological transformation, including artificial intelligence (AI), virtual reality (VR), augmented reality (AR), mixed reality (MR), and the metaverse; (2) data-driven education and assessment; (3) changing roles of faculty and learners; and (4) ethical and legal requirements. Evidence from the literature suggests that these driving forces are among the most likely to profoundly influence the structures and approaches of teaching and learning over the coming decade.
· Layer 2: Organizational Response and Adaptation Strategies: This layer comprises (1) development of technological infrastructure; (2) faculty reskilling, retraining, and capacity building; (3) curriculum revision and the design of personalized learning pathways; and (4) data-driven educational assessment. It defines the operational and managerial measures required to effectively respond to and capitalize on the driving forces identified in Layer 1.
· Layer 3: Future-Oriented Educational Outcomes: The anticipated outcomes include (1) increased educational effectiveness; (2) improved learners’ clinical readiness; (3) reduced clinical errors in practice; (4) promotion of lifelong learning; and (5) greater adaptability and resilience of the educational system to rapid technological change.
The Delphi process achieved strong expert agreement across all final dimensions (mean importance ≥ 3.7; CVR range: 0.64–0.84).
Conclusion
These findings suggest that the future of simulation-based medical education will be shaped by synergistic interactions among technology, data, and human capacity development. While technological innovation is a key driver, sustainable progress requires parallel investment in faculty development, curricular innovation, and ethical governance. The proposed framework aligns with global foresight studies, underscoring the need for strategic readiness and adaptability within educational systems. Ethical and legal considerations surrounding AI integration, data transparency, and learner privacy emerged as critical future challenges.
This study offers a validated, evidence-informed three-layer foresight framework for the future of simulation-based education in the medical sciences. By combining systematic trend analysis with Delphi-based expert consensus, it provides universities, simulation centers, and policymakers with a practical basis for anticipating emerging shifts, designing flexible strategies, and aligning educational infrastructure with technological and societal change. The model also lays groundwork for future foresight research, predictive modeling, and policy design in medical education.
Practical Implications of Research
This framework offers universities, simulation centers, and educational policymakers a structured basis for developing technological infrastructure, retraining faculty, revising curricula, and aligning educational systems with global developments. It may further inform national policy on simulation-based education and strengthen institutional preparedness for future technological transformation.