Objective: This study aimed to evaluate the efficacy of an innovative triadic instructional model—integrating Outcome-Based Education (OBE) with a “Clinical Problem-AI Validation-Research Innovation” framework—in graduate-level Pathology Technology education. Methods: A cohort of 72 academic postgraduate students in clinical medicine (enrolled in 2024 and 2025) was instructed using this model. Guided by OBE principles, the curriculum was restructured around a progressive learning pathway: “from specimen to data, from protein to nucleic acid, from two-dimensional to three-dimensional, and from single-omics to multi-omics”. Key strategies included defining clear learning outcomes, backward course design, deep integration of AI tools, problem-based learning (PBL) case drivers, and a multidimensional assessment system. Results: The intervention yielded high student satisfaction, with 96% reporting enhanced learning motivation and 92% affirming that AI tools improved their experimental design efficiency. The rate of “excellent” performance on final examinations increased from 68% to 82% (a 14-percentage-point gain). Furthermore, the success rate for university-level research project grants rose from 28% to 43% (a 15-percentage-point increase), and the proportion of high-quality research proposals climbed from 35% to 46% (an 11-percentage-point improvement). Conclusion: The “OBE + Triadic Model” effectively enhances graduate students’ clinical reasoning, research innovation capabilities, and technical proficiency by leveraging authentic clinical problems as drivers, AI as an enabler, and research innovation as an extension.
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Li et al. (2026) studied this question.
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