ArticleBMC medical education2026
Exploration of an artificial intelligence-supported training mechanism for teaching competence development in graduate students of prosthodontics.
Article in BMC medical education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThis study aimed to evaluate the effectiveness of an artificial intelligence-supported training framework in enhancing the teaching competence of prosthodontics graduate students.
methodsTwenty-one first-year prosthodontics graduate students at Fujian Medical University participated in a structured, four-stage intervention over two semesters: baseline assessment, AI platform training, AI-assisted iterative teaching practice, and final evaluation. DeepSeek served as the core AI tool for lesson preparation, lecture script drafting, concept map generation, and interactive teaching design. Teaching competence was assessed at seven time points across five dimensions: teaching attitude and language, teaching content, logical structure, professional accuracy, and interactivity. Longitudinal changes were evaluated using repeated measures analysis, and students also rated the usefulness of the AI tool on a 5-point Likert scale.
resultsOverall teaching competence improved significantly from baseline (56.52 ± 4.83) to the final evaluation (77.24 ± 4.11; F = 45.32, p < 0.001, η
conclusionThe AI-assisted training framework was associated with improvements in prosthodontics graduate students' teaching competence, particularly in content completeness and structural coherence. The introduction of DeepSeek, with strengths in Chinese semantic processing and professional reasoning, offers a potentially useful and localized tool for dental education. This framework may provide a strategy to help cultivate graduate students with skills in research, clinical practice, and teaching, potentially supporting the development of future high-quality faculty.
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