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Simulation, artificial intelligence, and competency-based frameworks in veterinary medical education: a narrative
Hui Zhang1,2, Aoyun Li3, Ying Li4
1Department of Clinical Veterinary Medicine, College of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, China.
Journal of Veterinary Science
|June 1, 2026
Summary
Veterinary education is advancing with simulation, virtual reality (VR), and artificial intelligence (AI) to improve skills and address patient access challenges. These technologies enhance training, standardize development, and increase access, especially in resource-limited settings.
Area of Science:
- Veterinary Medical Education
- Educational Technology
- Clinical Skills Training
Background:
- Veterinary medical education faces challenges with patient availability and inconsistent assessments.
- Innovations like simulation, virtual reality (VR), and artificial intelligence (AI) are transforming training.
- Competency-based frameworks aim to enhance workplace readiness.
Purpose of the Study:
- To review current evidence on technology integration in veterinary education.
- To highlight practical implications for curriculum design and clinical preparedness.
- To identify essential factors for sustainable, technology-enhanced veterinary training.
Main Methods:
- Literature review of existing studies on simulation, VR, AI, and competency-based education.
- Analysis of reported benefits, challenges, and practical implications.
- Synthesis of evidence for curriculum enhancement and clinical preparedness.
Main Results:
- High-fidelity simulators and VR improve procedural confidence, skills, and satisfaction.
- AI tools aid decision-making but raise concerns about accuracy and bias.
- Competency-based frameworks improve readiness but have varied implementation.
- Barriers include unequal digital access, costs, and faculty training.
Conclusions:
- Simulation, digital environments, and AI enhance veterinary training when integrated appropriately.
- These technologies support safer practice, standardize skills, and broaden access.
- Continued investment in faculty, ethical AI use, and infrastructure is crucial.