现代教育技术2026，Vol.36Issue(9)：5-13,9.DOI:10.3969/j.issn.1009-8097.2026.09.001
生成式人工智能支持的跨学科主题学习设计模式研究
Research on the Design Model of Interdisciplinary Thematic Learning Supported by Generative Artificial Intelligence
摘要
Abstract
Interdisciplinary thematic learning has attracted considerable attention in educational reform.Although generative artificial intelligence(GenAI)has been preliminarily applied to automated instructional design,its response quality and professional appropriateness in supporting complex design tasks remain inadequate.To address this challenge,this paper constructs a design model of interdisciplinary thematic learning supported by GenAI,in which the"thinking model"is taken as the cognitive support framework of this design model.The proposed model constrains and optimizes the generation logic through four dimensions of domain knowledge,solution procedures,outcome examples,and task criteria.Based on backward design theory and design principles,this paper elaborates the key structure,implementation process,and practical logic of the design model of interdisciplinary thematic learning based on thinking model.On this basis,structured prompts corresponding to each sub-tasks are developed to support instructional design generation under predefined constraints.Empirical results show that GenAI adopting this model achieves outstanding performance in dimensions such as"learning objective design"and"learning assessment design",while room for improvement remains in"learning activity design"and other dimensions that highly rely on contextual judgment.This paper provides a transferable theoretical model and practical implications for human-AI collaborative design of interdisciplinary thematic learning.关键词
生成式人工智能/结构化提示语/跨学科主题学习/逆向设计/思考模型Key words
GenAI/structured prompts/interdisciplinary thematic learning/backward design/thinking model分类
社会科学引用本文复制引用
朱晓悦,杨淑婷,陈怡,闫寒冰..生成式人工智能支持的跨学科主题学习设计模式研究[J].现代教育技术,2026,36(9):5-13,9.基金项目
本文受2023年度国家社会科学基金教育学一般项目"面向教师数字能力发展的场景构建与应用研究"(项目编号:BCA230283)资助. （项目编号:BCA230283）
