生成式人工智慧應用於醫學教育的可行方式

Feasible Applications of Generative AI in Medical Education

隨著醫學知識的快速累積與臨床決策的日益複雜，傳統教學模式面臨挑戰，醫學教育需透過新興科技來提升學習效率與決策能力。生成式人工智慧（Generative AI），特別是大型語言模型（Large Language Models, LLMs）如ChatGPT，具備即時數據處理、個人化學習與臨床決策支持的優勢，為醫學教育提供新的發展契機。本文探討ChatGPT在醫學教育中的潛在價值，分析其在學習理論架構下的影響，並探討其在學術寫作、考試準備、臨床推理與決策輔助等方面的應用成效。ChatGPT能降低學習認知負荷、促進自主學習並強化批判性思考。然而，仍須考量AI在學術誠信、倫理規範與教育策略上的適切性，以確保其合理應用。並進一步提出學習成效評估指標，作為未來醫學教育與研究提供參考。

With the rapid expansion of medical knowledge and increasing complexity in clinical decision-making, traditional teaching methods face significant challenges. Integrating emerging technologies into medical education is essential to enhance learning efficiency and decision-making capabilities. Generative AI, particularly Large Language Models (LLMs) like ChatGPT, offers real-time data processing, personalized learning, and clinical decision support, presenting new opportunities for medical training. This study explores the potential value of ChatGPT in medical education, analyzing its impact through learning theories and its applications in academic writing, exam preparation, clinical reasoning, and decision support. ChatGPT reduces cognitive load, fosters self-directed learning, and enhances critical thinking. However, ethical considerations, academic integrity, and pedagogical strategies must be ad-dressed to ensure its proper implementation. This paper proposes evaluation criteria for assessing AI-driven learning outcomes, offering insights for future educational applications and research.