生成式AI赋能《机器学习与数据挖掘》课程“教–学–评”重构与实践研究

Research on the Restructuring and Practice of “Teaching-Learning-Assessment” in the Course of Machine Learning and Data Mining Empowered by Generative AI

摘要: 在生成式AI推动高等教育数字化转型的浪潮下，传统的《机器学习与数据挖掘》教学模式已难以适配智能时代对人才培养的新要求。文章以生成式AI为技术支撑，对课程“教–学–评”全过程进行系统性重构，打造人机协同的双师教学模式，构建“掌握–重构–创造”三级专创项目链的学习路径，建立以学生数字画像为核心的发展性评价体系。在此基础上，搭建“个性学习精准化、专创融合深度化、思政育人内驱化”三化融合的协同育人体系。基于三个学期的纵向对比数据分析，该路径有效提升了学生的个性化学习效率、专创融合实践能力与思政素养内化水平，实现了技术培养与价值塑造的同步深化。研究成果为高校工程类课程借助生成式AI实现育人模式创新，落实三全育人理念提供了实践样本与理论参考。

Abstract: In the wave of higher education digital transformation driven by generative AI, the traditional teaching model of the Machine Learning and Data Mining course can no longer meet the new requirements for talent cultivation in the intelligent era. Supported by generative AI technology, this paper systematically restructures the entire process of “teaching-learning-assessment” in the course. It creates a human-machine collaborative dual-teacher model, constructs a “Mastery-Reconstruction-Creation” three-level project-based learning path for specialized innovation, and establishes a developmental evaluation system centered on students’ digital portraits. Based on this, a collaborative education system integrating “precision in personalized learning, depth in the integration of specialized courses and innovation, and internal drive in ideological and political education” is developed. Through a longitudinal comparative analysis of data from three semesters, this approach has effectively enhanced students’ personalized learning efficiency, their practical ability in integrating specialized courses and innovation, and the internalization level of their ideological and political literacy, achieving a simultaneous deepening of technical training and value shaping. The research findings provide practical examples and theoretical references for engineering courses in higher education institutions to innovate education models and implement the “Three Comprehensive Education” with the aid of generative AI.