Artificial intelligence, extended reality, and emerging AI–XR integrations in medical education
Current evidence on AI, XR, and emerging AI-XR integrations suggests promising but preliminary benefits for learning and performance. The small number of fully integrated AI-XR interventions and the methodological limitations of many primary studies substantially limit the certainty and generalizability of these findings. Future research should use more rigorous and standardized designs, explicitly compare AI-only, XR-only, and AI-XR hybrid approaches, and be coupled with faculty development, robust technical support, and alignment with competency-based assessment.
Authors
- Richard Tene-Fernandez
- DIEGO FABIÁN VIQUE LOPEZ
- Talía Tene (ORCID: https://orcid.org/0000-0002-8588-6490)
- Marlene Jacqueline García Veloz
- Byron Stalin Rojas Oviedo
Institutions
- Universidad Técnica Particular de Loja (EC)
- Escuela Superior Politécnica del Chimborazo (EC)
- Hospital Metropolitano (EC)
Publication Details
- Journal
- Frontiers in Digital Health
- Published
- 2026-01-09
- DOI
- https://doi.org/10.3389/fdgth.2025.1740557
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 17.70
Funders
- Corporación Ecuatoriana para el Desarrollo de la Investigación y la Academia
- Universidad Técnica Particular de Loja