人工智能赋能概率统计教学改革——基于AIGC的案例教学模式构建与实践成效分析

Reforming Probability and Statistics Teaching through Artificial Intelligence—Construction of an AIGC-Based Case Teaching Model and Analysis of Its Practical Effectiveness

摘要: 本文以《概率论与数理统计》课程为研究对象，对比分析常规教学班与人工智能辅助教学模式实验班的教学成效。通过构建基于人工智能生成内容(AIGC)的案例教学体系，研究发现实验班无论在期末成绩均值、总评成绩均值还是及格率等指标方面均显著优于常规班。教学改革与促进学生竞赛能力的提升存在显著正相关性，学生累计获得多项省级以上奖项。研究表明，AIGC支持的案例教学模式能够有效提升概率统计课程教学效果，为人工智能时代下的数学教学改革提供实践路径。

Abstract: This paper focuses on the course “Probability Theory and Mathematical Statistics” as the research subject, conducting a comparative analysis of the teaching effectiveness between regular classes and experimental classes employing an artificial intelligence teaching model. By developing a case-based teaching system supported by AI-Generated Content (AIGC), the study finds that the experimental class significantly outperforms the control class in terms of average final exam scores, overall average grades, and pass rates. The teaching reform also enhances students’ competition abilities, with students cumulatively winning multiple awards at the provincial level and above. The research demonstrates that the AIGC-supported case-based teaching model effectively improves the teaching outcomes of probability and statistics courses, offering a practical pathway for mathematics teaching reform in the era of artificial intelligence.