计算思维目标导向下融合生成式AI的大学数学课程教学模式创新研究与实践

Research and Practice on Innovative Teaching Mode of College Mathematics Courses Integrated with Generative AI: A Computational Thinking Goal-Oriented Approach

摘要: 针对传统大学数学教学重计算技巧轻思维培养、重理论推导轻工程应用、学用脱节的核心痛点，以计算思维培养为核心目标，数值分析课程为实践载体，构建了生成式AI全流程融入的创新教学模式。研究重构了“理论–实践–思维”三位一体的教学内容体系，设计了“课前–课中–课后–实践”四环节联动的闭环教学流程与多元评价体系，并通过对照教学实验验证了模式的有效性。结果表明，该教学模式并未弱化学生对核心理论的掌握，能极显著提升学生在算法设计、工程建模、误差分析等维度的能力，对学生计算思维核心素养的培养效果突出。本研究形成的教学模式具备可复制推广性，可为大学数学课程的智能化教学改革提供实践参考。

Abstract: Aiming at the core pain points of traditional college mathematics teaching, including overemphasis on calculation skills while neglecting thinking cultivation, preference for theoretical derivation over engineering application, and disconnection between learning and application, this study takes the cultivation of computational thinking as the core goal, takes the Numerical Analysis course as the practical carrier, and constructs an innovative teaching mode with full-process integration of generative AI. This research reconstructs the three-in-one teaching content system of “theory-practice-thinking”, designs a closed-loop teaching process with four interlinked links of “pre-class, in-class, after-class, and practice” as well as a multi-dimensional evaluation system, and verifies the effectiveness of the mode through controlled teaching experiments. The results show that the teaching mode does not weaken students’ mastery of core theories, and can extremely significantly improve students’ performance in modules corresponding to the core competencies of computational thinking, such as algorithm design, engineering modeling and error analysis, which verifies the improvement effect of the teaching mode on students’ higher-order thinking ability. The teaching model developed in this study is replicable and scalable, and can provide practical reference for the intelligent teaching reform of college mathematics courses.