人机协同视域下医学免疫学思辨性教学的探索与实践——以“补体系统”章节为例

Exploration and Practice of Critical Thinking Teaching in Medical Immunology from the Perspective of Human-Machine Collaboration—Taking the “Complement System” Chapter as an Example

摘要: 生成式人工智能在提升医学教育效率的同时，易导致医学生思维惰性增强、批判性思维弱化。医学免疫学概念抽象、机制复杂，对思辨能力要求较高。为平衡技术赋能与思维训练，本文以人机协同教育理念为指导，构建“三阶六步”思辨性教学闭环模式，将AI定位为一种用于暴露认知偏差、促进反思的思维对照工具，并以“补体系统”为载体开展教学实践。该模式通过课前认知裸构、课堂人机对比批判、课后知识重构与临床迁移，引导学生在认知挣扎中深化理解，提升批判性思维与临床应用能力。实践表明，新模式可显著提高学生知识掌握深度与临床迁移能力，缓解AI依赖带来的思维弱化问题，为AI时代医学免疫学教学改革提供可推广范式。

Abstract: While generative artificial intelligence (AI) boosts the efficiency of modern medical education, it may inadvertently exacerbate intellectual inertia and impair critical thinking abilities among medical students. Medical Immunology is characterized by abstract concepts and sophisticated immune mechanisms, which place high demands on students’ critical thinking and reasoning capacity. To balance technological empowerment and cognitive thinking training in medical teaching, this study constructs a closed-loop critical thinking teaching model termed the “Three-Stage and Six-Step” framework under the guidance of the human-machine collaborative education philosophy. In this model, generative AI is adopted as a cognitive reference tool to expose learners’ cognitive biases and promote reflective thinking, and teaching practice is carried out with the complement system as the core teaching carrier. The proposed model covers three core teaching procedures: pre-class independent cognitive construction, in-class human-machine comparative critical analysis, and post-class knowledge reconstruction and clinical knowledge transfer. It drives students to actively engage in cognitive dilemma and in-depth thinking, thereby consolidating disciplinary understanding and improving their critical thinking competency and clinical application capacity. Practical teaching results indicate that this innovative teaching model can effectively enhance students’ in-depth knowledge mastery and clinical transfer ability, and alleviate the deterioration of critical thinking caused by excessive reliance on generative AI. This study provides a feasible and promotable paradigm for the teaching reform of Medical Immunology in the generative AI era.