智慧醫療課程之設計與 AI 輔助教學及學習策略

Abstract

隨著人工智慧技術在醫療領域快速發展，欠缺架構完整的智慧醫療教育課程已成為一大問題，同時教育界對於如何有效整合 AI 輔助教學工具（如 ChatGPT）仍缺乏明確策略。本研究設計一套涵蓋醫學影像與人工智慧核心概念的智慧醫療課程，採用螺旋式架構並提供多種彈性學習路徑，以適應不同學習者需求。課程開發與教學過程廣泛應用生成式 AI 工具協助教材製作與教學策略規劃。本研究以混合研究方法，在為期六週的課程中進行驗證，並以課前課後問卷評估學習成效。結果顯示，學員自認在課程結束後於人工智慧、Python 程式設計與醫學知識方面皆有明顯進步；同時，AI 工具的應用有效提升教材開發效率並驗證了 AI 輔助教學策略的可行性。本研究亦提出 AI 輔助學習策略，以促進學習者更高效且深入地參與智慧醫療課程，研究成果可作為未來智慧醫療教育課程設計與 AI 工具整合的參考。

As artificial intelligence (AI) rapidly advances in healthcare, the lack of a comprehensive and structured medical AI educational curriculum has become a significant concern. Additionally, clear strategies for effectively integrating AI tools, such as ChatGPT, into educational practices remain scarce. To address these challenges, this study proposes a structured medical AI curriculum that encompasses core concepts in medical imaging and artificial intelligence. Utilizing a spiral curriculum framework, the design provides multiple flexible learning pathways to accommodate diverse learner needs. Throughout the course development and teaching process, generative AI tools were extensively employed to support the creation of instructional materials and the formulation of teaching strategies. A mixed methods approach was adopted, implementing a six-week pilot course, with pre-course and post-course questionnaires administered to evaluate learning effectiveness. The results indicated that learners perceived significant improvements in their knowledge of AI, Python programming, and medical concepts after completing the course. Furthermore, the use of AI tools significantly improved the efficiency of curriculum development, validating the feasibility of AI-assisted teaching strategies. This study also proposes specific AI-assisted learning strategies to facilitate deeper and more efficient engagement among learners in medical AI courses. The findings provide valuable insights and practical guidance for future medical AI curriculum design and the integration of AI tools in educational contexts.