人工智能在研究生《回归分析》课程中的实践探索

Practical Exploration of Artificial Intelligence for the Postgraduate-Level Regression Analysis Course

摘要: 回归分析是应用统计专业研究生的核心专业课程，课程兼具数学理论推导与数据分析实践的双重特性，存在概念抽象难懂、知识点碎片化、理论与实践脱节、个性化教学难以实现等现实教学痛点。人工智能技术为课程教学改革提供新的技术路径。本文以研究生《回归分析》课程为研究对象，将大语言模型、知识图谱、智能任务引擎、数据仿真、学情分析等AI工具融入备课、课堂教学、课后探究、作业评价全教学流程。从教学定位、应用场景、实施方案等方面开展实践研究，探索AI赋能回归分析课程的实施策略。

Abstract: Regression Analysis is a core professional course for postgraduate students majoring in Applied Statistics. Featuring both mathematical theoretical derivation and data-analysis practice, the course faces practical teaching challenges including abstract and hard-to-grasp concepts, fragmented knowledge points, disconnection between theory and practice, and difficulties in realizing personalized teaching. Artificial intelligence technology offers new technical approaches for curriculum teaching reform. Taking the postgraduate course Regression Analysis as the research subject, this paper integrates AI tools such as large language models, knowledge graphs, intelligent task engines, data simulation and learning-situation analysis into the full teaching workflow covering lesson preparation, in-class teaching, after-class inquiry and assignment evaluation. Practical research is carried out from the perspectives of teaching orientation, application scenarios and implementation schemes to explore implementation strategies for empowering the Regression Analysis course with AI.