生成式人工智能赋能高中生数学自主学习能力提升的策略研究——基于人机协同的理论建构与实践路径

Strategies for Enhancing High School Students’ Self-Regulated Mathematics Learning through Generative AI—Theoretical Construction and Practical Pathways Based on Human-AI Collaboration

摘要: 生成式人工智能技术的突破性发展为高中数学教育变革提供了新范式。本研究针对传统数学自主学习中存在的个性化不足、反馈滞后、资源匮乏等现实困境，构建“认知脚手架–情感支持体–元认知发展”三维理论框架，提出生成式人工智能赋能高中生数学自主学习的“四阶螺旋”策略模型：智能诊断与路径规划、动态交互与深度探究、反思建构与迁移创新、社群协作与共生发展。通过准实验研究设计，在某重点高中开展为期一学期的教学实践，结果表明：实验组学生在自主学习效能感、高阶思维能力和数学成绩上显著优于对照组(p < 0.01)。研究进一步揭示了“人机协同”机制下教师角色转型、学生主体性重构及伦理安全边界等关键问题，为生成式人工智能融入基础教育提供理论参照与实践范式。

Abstract: The breakthrough development of generative artificial intelligence (GenAI) offers a new paradigm for transforming high school mathematics education. Addressing practical challenges in traditional mathematical autonomous learning—such as lack of personalization, delayed feedback, and scarce resources—this study constructs a three-dimensional theoretical framework of “cognitive scaffolding-affective support-metacognitive development”. It proposes a “Four-Stage Spiral” strategy model for leveraging GenAI to enhance high school students’ autonomous learning in mathematics: 1) intelligent diagnosis and path planning, 2) dynamic interaction and deep inquiry, 3) reflective construction and transferable innovation, and 4) community collaboration and symbiotic development. A one-semester quasi-experimental teaching practice was conducted at a key high school. The results indicated that the experimental group significantly outperformed the control group in terms of self-directed learning efficacy, higher-order thinking skills, and mathematics achievement (p < 0.01). Furthermore, the study explores critical issues within the “Human-AI Collaboration” mechanism, including the transformation of the teacher’s role, the reconstruction of student agency, and ethical safety boundaries. This research aims to provide a theoretical reference and practical model for integrating GenAI into basic education.