基于建构主义理论的AI-医学PBL教学模式构建与实施

Construction and Implementation of AI-Medical PBL Teaching Model Based on Constructivism Theory

摘要: 当前，AI与医学PBL教学的融合仍面临“案例更新滞后、师资匹配不足、技术脱离教学实际、评价方式单一”等现实问题，制约了智能化教学模式的推广应用。针对“技术落地”难题，本研究创新构建了动态迭代型案例库，搭建涵盖教学全流程的AI工具矩阵并提出“软能力 + 硬指标”双维度AI评价模型。同时，创新性地建立“师资–技术–教学”三位一体协同机制，形成涵盖内容、工具、评价和保障为一体的AI-PBL教学模式。该模式已在临床医学专业的基础与临床课程中展开实践。结果显示，实验组学生在临床技能考核中的通过率较对照组显著提升了20.5%，教学满意度达到92.3%，教师案例准备时间缩短了40%。该模式有效实现了技术服务于教学目标的根本宗旨，避免了技术应用流于形式，为AI赋能医学教育改革提供了可复制、可推广的实施路径。

Abstract: At present, the integration of AI and medical PBL teaching still faces practical problems such as “lagging case updates, insufficient teacher matching, technology decoupling from teaching practice, and single evaluation methods”, which restrict the promotion and application of intelligent teaching models. To address the challenge of “technology landing”, this study innovatively constructs a dynamically iterative case library, builds an AI tool matrix covering the entire teaching process, and proposes a dual-dimensional AI evaluation model of “soft capabilities + hard indicators”. Meanwhile, it innovatively establishes a “teacher-technology-teaching” trinity coordination mechanism, forming an AI-PBL teaching model integrating content, tools, evaluation and guarantee. This model has been put into practice in basic and clinical courses for clinical medicine majors. Results show that the pass rate of experimental group students in clinical skill assessments increased by 20.5% compared with the control group, teaching satisfaction reached 92.3%, and teachers’ case preparation time was shortened by 40%. This model effectively achieves the fundamental purpose of technology serving teaching goals, avoids the formalization of technology application, and provides a replicable and promotable implementation path for AI-empowered medical education reform.