数字化背景下《概率论与数理统计》课程教学改革研究

Research on Teaching Reform of “Probability Theory and Mathematical Statistics” Course under Digitalization Background

摘要: 随着人工智能、大数据云计算这类新技术不断更新，我国高等教育的数字化教学转型节奏正在加快。理工科和经济管理类专业都开设有《概率论与数理统计》这门核心基础课，传统的教学模式已经难以适应当前社会对创新型、应用型人才的培养需求。本文的研究工作主要包含有：梳理《概率论与数理统计》课程教学中的现存问题，搭建的整体框架，在智能教学资源建设、个性化学习路径设计、数据驱动评价体系构建、智慧教学平台应用这些方面开展实践探索和研究。通过为期两学年的准实验研究(采用“前测–后测”非等组设计，并辅以协方差分析)，结果表明，实验组课程平均成绩显著高于对照组，及格率上升12个百分点，学生整体满意度达88.3%，学生的学习积极性和自主学习能力有了明显的提升。相关研究成果可以作为同类核心数学基础课程数字化教学改革的理论参考和借鉴。

Abstract: With the continuous advancement of technologies such as artificial intelligence, big data, and cloud computing, China’s higher education sector is accelerating its digital transformation in teaching methodologies. Core foundational courses like “Probability Theory and Mathematical Statistics” are offered across STEM disciplines and economics management programs, yet traditional teaching approaches struggle to meet contemporary demands for cultivating innovative and application-oriented professionals. This study focuses on: identifying existing challenges in teaching “Probability Theory and Mathematical Statistics”, establishing an integrated framework, and conducting practical explorations in intelligent teaching resource development, personalized learning pathway design, data-driven evaluation systems, and smart teaching platform implementation. Through a two-year quasi-experimental study employing a “pre-test-post-test” non-randomized design supplemented by covariance analysis, results demonstrated that the experimental group achieved significantly higher average course grades than the control group, with a 12-percentage-point increase in pass rates and overall student satisfaction reaching 88.3%. Students also showed marked improvements in learning motivation and self-directed learning capabilities. These findings provide valuable theoretical references for digital teaching reforms in similar core mathematics foundational courses.