基于ADDIE模型的生成式人工智能辅助遗传病标准化病人案例构建方法

A Generative AI-Assisted Method for Standardized Patient Case Construction in Genetic Diseases Based on the ADDIE Model

摘要: 针对遗传病标准化病人(Standardized Patients, SP)案例开发中存在生命全周期覆盖不足、家系逻辑校验缺位及变异解读滞后等问题，本研究基于ADDIE模型提出生成式AI辅助的SP案例标准化生成方法。该方法以结构化参数驱动为核心，将遗传病演化逻辑转化为“实体–属性–规则”参数集，经ADDIE五环节实现学科知识向可演绎案例的系统转化；同时构建嵌入伦理护栏与三重防幻觉机制的生成流程，并建立五维质量标尺保障案例医学有效性与教学适用性。该框架可将专家经验沉淀为可复用规则资产，提升案例开发效率与逻辑一致性，为遗传咨询SP教学资源规模化建设提供方法论支撑，但教学实效与量表信效度仍需实证验证。

Abstract: In the development of Standardized Patient (SP) cases for genetic diseases, three practical issues remain to be addressed: insufficient full-lifecycle coverage, lack of pedigree logic validation, and delayed variant interpretation. This study proposed a standardized generation method for SP cases using generative AI, grounded in the ADDIE model. The method was driven by structured parameterization, translating the evolutionary logic of genetic diseases into a parameter set comprising “entity - attribute - rule.” Through the five phases of ADDIE, disciplinary knowledge was systematically converted into demonstrable cases. Concurrently, a generation workflow was constructed with ethical safeguards and a triple anti-hallucination mechanism, alongside a five-dimensional quality scale to ensure both medical validity and pedagogical applicability. This framework could transform expert experience into reusable rule assets, improving case development efficiency and logical consistency. It offered methodological support for scalable SP resource construction in genetic counseling education; however, the teaching effectiveness and the reliability and validity of the scale still required empirical validation.