《数学分析》全过程人机混合教学模式的探索

The Exploration of the Whole Process of “Mathematical Analysis” Man-Machine Mixed Teaching Mode

摘要: 针对《数学分析》课程抽象概念与直观感知断裂、学情反馈滞后、学生参与度低以及个性化辅导缺失等教学困境，文章提出一种以学习通和GeoGebra为技术支撑的人机混合教学模式。该模式构建了“课前循证靶向定教–课中协同精准施教–课后智能适配促学”的三维联动闭环：课前借助AI学情诊断实现数据驱动的精准备课；课中依托GeoGebra动态可视化、学习通平台互动机制和AI助教实现精准施教；课后通过AI隐形分层作业推送与AI陪练助手实现个性化延展。这三个环节将学情数据贯通衔接，使技术聚焦于数据统计与及时反馈等重复性劳动，让教师回归深度思维引导与价值判断，为数学类专业基础课程教学的数智化转型提供了可推广的实践方案。

Abstract: In view of the teaching difficulties such as the fracture of abstract concept and intuitive perception, the lag of learning feedback, the low participation of students and the lack of personalized guidance in the course of “Mathematical Analysis”, this paper proposes a man-machine mixed teaching mode supported by Chaoxing Learning Platform and GeoGebra. This model constructs a three-dimensional linkage closed-loop of “pre-class evidence-based targeted teaching-in-class collaborative precise teaching-after-class intelligent adaptation to promote learning”: before class, AI learning diagnosis is used to achieve data-driven precise lesson preparation; relying on GeoGebra dynamic visualization, Chaoxing Learning Platform interaction mechanism and AI teaching assistant, precise teaching is realized in the course. After class, personalized extension is realized through AI invisible layered homework push and AI accompanying assistant. These three links connect the learning situation data, make the technology focus on repetitive work such as data statistics and timely feedback, let teachers return to deep thinking guidance and value judgment, and provide a practical scheme that can be popularized for the mathematical intelligence transformation of the basic course teaching of mathematics majors.