Traditional veterinary infectious disease education faces inherent limitations, particularly in presenting abstract mechanisms, complex epidemiology, and high-risk scenarios. To address these challenges and meet the World Organisation for Animal Health (OIE)’s capacity building requirements, digital-intelligent teaching is driving a paradigm shift from “knowledge transmission” to “competency development.” This study systematically constructs a clearly layered (macro-meso-micro) conceptual model for digital-intelligent teaching, hierarchically integrating pedagogical philosophy (macro), technological architecture (meso), and instructional implementation (micro). Specifically, at the macro level, it establishes the “AI-Enhanced Student-Led Tutorial Education” Teaching Model as a philosophical foundation to reshape the triadic interaction between teachers, students, and machines. The meso level centers on three technological cores—Knowledge Graph, AI, and Task Engines—which integrate to create personalized, immersive learning environments. Finally, at the micro level, the model implements a human-computer collaborative approach designed specifically to train clinical thinking skills. Furthermore, targeting the critical shortage of digitally-proficient faculty in Southwest China’s border regions, the study proposes a “Cloud-Empowered Lightweight Adoption” model designed to lower technical thresholds. The feasibility of this approach in bridging infrastructural gaps and empowering regional talent cultivation was validated through a practical case study at Kunming University. This research establishes a novel pedagogical paradigm that not only guides the reform of veterinary infectious disease education in Western China but also offers a scalable model for institutions worldwide facing similar resource constraints, thereby contributing to the global advancement of veterinary capacity building.
Wang et al. (Thu,) studied this question.