面向交通领域的统计学专业课程体系与教材知识图谱的构建与应用研究

Research on the Construction and Application of Statistical Professional Curriculum Systems and Textbook Knowledge Graphs in the Transportation Field

摘要: 本研究针对AI时代背景下统计学专业人才培养与交通行业需求脱节、课程知识碎片化等问题，提出了一个面向交通领域的统计学专业课程体系与教材知识图谱的构建与应用框架。首先，文章在分析交通行业能力需求的基础上，设计了一个包含“通识基础 + 专业核心 + 工科交叉 + AI赋能 + 实践项目”的五模块课程体系。其次，文章提出以课程教材为核心语料，采用知识蒸馏与多模型协作技术，构建一个包含“概念层–方法层–场景层”的知识图谱。最后，文章从“教–学–评–管”四个维度探讨了该课程体系与知识图谱整合框架的应用路径，旨在促进“统计 + 交通”复合型人才的培养，为统计学专业的特色化转型提供方案。

Abstract: In response to the disconnection between talent cultivation and industry demands, as well as the fragmentation of course knowledge in statistics programs under the background of Emerging Engineering Education, this paper proposes a framework for constructing a curriculum system and textbook knowledge graph for statistics oriented to the transportation field. Based on an analysis of the competency requirements for statistical talents in the transportation industry, a modular curriculum system comprising “general education foundation + professional core + engineering intersection + AI empowerment + practical projects” is designed. Furthermore, using textbooks as the core corpus, a multi-level knowledge graph is constructed through knowledge distillation and multi-model collaboration techniques. Its application pathways are explored from the four dimensions of “teaching, learning, assessment, and management”. The research indicates that the deep integration of domain-oriented curriculum system reconstruction and knowledge graphs can effectively promote the cultivation of “statistics + transportation” interdisciplinary talents, providing a reference for the characteristic transformation of statistics programs in the current era.