人工智能赋能湘西乡土数学建模教学的实证研究——以吉首中小学为例

Empirical Research on AI-Empowered Local-Context Mathematical Modeling Teaching in Xiangxi—A Case of Primary and Secondary Schools in Jishou

摘要: 针对湘西民族地区初中数学建模教学本土素材匮乏、课程资源短缺、学生建模素养薄弱的现实问题，本研究基于建构主义与情境认知理论，构建“乡土素材挖掘–人工智能转化–课堂实践验证”资源开发体系，搭建自然地理、民族文化、特色产业三类乡土建模资源库。选取吉首市某中学102名初二学生开展准实验，实验组实施人工智能赋能乡土情境建模教学，对照组采用常规教学。结果显示，实验组学生数学建模能力、学习兴趣提升显著优于对照组，学困生获益最明显。研究表明，融合生成式人工智能与湘西乡土元素的建模资源，可降低建模学习门槛，激发内在学习动机，兼顾数学核心素养与民族文化认同感培育，可为湘西同类民族地区乡土数学课程建设提供可借鉴的实践案例。

Abstract: Aiming at the problems of insufficient local materials, scarce curriculum resources and students’ weak modeling literacy in junior high-school mathematical modeling teaching in Xiangxi ethnic areas, this study constructs a resource-development system of “local material excavation - AI-enabled transformation - classroom practical verification” based on constructivism and situated cognition theories, and builds a resource library including physical geography, ethnic culture and characteristic industries. A quasi-experiment was conducted on 102 eighth-grade students at a middle school in Jishou City. The experimental group adopted AI-empowered local-context mathematical modeling teaching, and the control group received conventional teaching. The results reveal that the experimental group has significantly better improvement in mathematical modeling competence and learning interest, especially for low-achieving students. Research indicates that modeling resources combining generative AI and Xiangxi local elements reduce modeling learning barriers, boost intrinsic motivation, cultivate mathematical core competencies and ethnic cultural identity, and offer practical cases for local math curriculum construction in similar ethnic areas of Xiangxi.