远程教育杂志2026，Vol.44Issue(5)：58-69,12.DOI:10.15881/j.cnki.cn33-1304/g4.2026.05.007
面向系统思维培养的智能化多主体建模学习工具设计与实证研究
Design and Empirical Study of an Intelligent Multi-agent-based Modeling Tool for the Cultivation of Systems Thinking
摘要
Abstract
Systems thinking requires students to recognize complex relationships among multiple variables in complex systems and to engage in nonlinear and cross-level reasoning to make sense of complex systemic phenomena.However,secondary school stu-dents often encounter cognitive difficulties in constructing causal reasoning chains and developing a systemic understanding when learning about complex systems.Although multi-agent-based modeling(MABM)offers advantages in representing dynamic interac-tions,students still struggle to develop systematic reasoning and mechanism-based scientific explanations within such environments.Guided by the principles of"structuring inquiry processes,dynamizing model representations,hierarchically organizing causal reason-ing,and intelligentizing feedback mechanisms",this study designed and developed an intelligent multi-agent-based modeling learning tool and empirically validated its effectiveness.A quasi-experimental design with three conditions was implemented among 104 eighth-grade students:an unsupported multi-agent modeling condition,a condition with hierarchical prompting scaffolds only,and a condition combining hierarchical prompting scaffolds with a chatbot.Group performance was compared in terms of content accuracy,reasoning complexity,and overall reasoning performance.The results showed that both conditions with hierarchical prompting scaffolds significantly outperformed the unsupported condition on all three indicators,whereas adding the chatbot on top of the scaffolds yielded slight but non-significant improvements.These findings suggest that embedding question-chain-based hierarchical prompting scaf-folds in a multi-agent-based modeling environment constitutes an important pathway for fostering middle school students' systems thinking,while the chatbot primarily plays a supplementary role in providing targeted knowledge support and conceptual clarification.The study offers empirical evidence and design implications for the further optimization and application of intelligent simulation-based learning environments.关键词
系统思维/复杂系统推理/多主体建模/智能聊天机器人/问题链Key words
Systems thinking/Complex system reasoning/Multi-agent-based modeling/Intelligent chatbots/Question chains分类
社会科学引用本文复制引用
陈凯亮,陈娟娟,沈晓臣..面向系统思维培养的智能化多主体建模学习工具设计与实证研究[J].远程教育杂志,2026,44(5):58-69,12.基金项目
2023年度国家自然科学基金面上项目"K12学生科学建模中多层次科学思维的智能评测及干预技术研究"(项目编号:62377042)、2025年度中国博士后科学基金第78批面上资助"仿真学习环境下中学生复杂系统推理过程智能监测与适应性反馈研究"(资助编号:2025M781599)、2026年度华中师范大学优秀种子培育项目"基于结构—行为—语言多模态数据的复杂系统推理过程自动化评价方法研究"(项目编号:CCNU26XJ005). （项目编号:62377042）
