人工智能驱动的概率统计课程改革

AI-Driven Reform of the Probability and Statistics Curriculum

摘要: 概率论与数理统计是高校理工类及经管类专业的重要基础课程。随着新工科建设与人工智能技术的发展，传统教学模式在应用型高校中面临内容脱离实践、学生基础薄弱、教学方式滞后等问题。本文以“AI语音助手情绪识别”为教学范例，将统计建模、数据分析与概率估计融入真实工程任务，探索项目驱动下的教学改革路径。通过案例教学与实践导向的教学设计，增强学生的知识迁移与应用能力，为应用型高校概率统计课程的改革提供了可借鉴的实践范式。

Abstract: Probability and statistics are essential foundational courses for students in engineering and economics majors. With the advancement of new engineering disciplines and the rapid development of artificial intelligence, traditional teaching approaches face challenges in applied universities—such as disconnection from practical application, weak student foundations and outdated instructional methods. This paper takes “AI voice assistant emotion recognition” as a case-driven teaching example, integrating statistical modeling, data analysis, and probability estimation into a real-world engineering context. By adopting project-based teaching strategies, the reform aims to enhance students’ ability to transfer knowledge and apply it in practice. The proposed approach provides a replicable model for reforming probability and statistics education in applied undergraduate institutions.