基于知识图谱的《应用回归分析》课程教学设计研究——以长沙理工大学应用统计学专业为例

Research on Teaching Design of the Course “Applied Regression Analysis” Based on Knowledge Graphs—A Case Study of Applied Statistics Major at Changsha University of Science and Technology

摘要: 将知识图谱技术应用于《应用回归分析》课程教学，有利于梳理课程复杂的知识点逻辑关联，重构碎片化知识体系，推进统计类课程数字化教学改革，创新数据分析类课程教学模式。本文以长沙理工大学应用统计学专业的教学实践为基础，将知识图谱技术融入《应用回归分析》的课程教学设计中，构建“知识–能力–思政–评价”四位一体的教学体系。通过搭建课程层级化知识图谱，梳理知识点关联逻辑、整合立体化教学资源、重构教学流程、优化评价体系，实现碎片化知识系统化、抽象理论可视化、分层教学精准化。实践表明，基于知识图谱的教学设计能够有效提升学生统计建模思维与实操能力，落实课程思政育人目标，为统计学类专业课程信息化教学改革提供参考。

Abstract: Applying knowledge graph technology to the teaching of “Applied Regression Analysis” helps clarify the logical connections among complex course concepts, reconstruct fragmented knowledge systems, advance digital teaching reform in statistics courses, and innovate teaching models for data analysis courses. Based on teaching practices in the Applied Statistics program at Changsha University of Science and Technology, this study integrates knowledge graph technology into the instructional design of “Applied Regression Analysis”, establishing an integrated teaching system encompassing “knowledge, competence, ideological and political education, and assessment”. By constructing a hierarchical knowledge graph for the course, organizing the logical relationships among concepts, integrating multidimensional teaching resources, restructuring teaching processes, and optimizing evaluation systems, the approach achieves systematic organization of fragmented knowledge, visualization of abstract theories, and precise tiered instruction. Practice shows that knowledge graph-based teaching design effectively enhances students’ statistical modeling thinking and practical skills, fulfills the educational goals of ideological and political integration in courses, and provides valuable references for informatization reform in statistics-related curricula.