近十年人工智能赋能数学教育研究——基于CiteSpace知识图谱的演进分析

Research on Artificial Intelligence Empowering Mathematics Education in the Past Decade—An Evolutionary Analysis Based on CiteSpace Knowledge Graph

摘要: 人工智能赋能数学教育的研究在中国已历经近十年探索，如何系统厘清这十年间研究的趋势及整体发展？运用内容分析法和文献统计法，借助CiteSpace知识图谱可视化软件进行研究表明：(1) 人工智能赋能数学教育现阶段及未来将处于一个较热的研究时期。(2) 该领域不同时期划分以下四个热点主题：学段分层研究、技术赋能研究、素养培养研究、学科基础研究。(3) 作者合作网络与机构合作网络处于一个低密度的状态，网络结构松散，该领域尚未形成专业核心的研究群。(4) 大多数研究停留于技术应用的表面的描述，对人工智能赋能数学教育的深层教育理论挖掘与运用不足。基于此给出建议，为数学教育学科推动人工智能技术与数学教育深度融合适配的研究与实践，提供了清晰的演进参照与优化方向。

Abstract: Research on AI-empowered mathematics education in China has undergone nearly a decade of exploration. To systematically clarify the trends and overall development of this research, this study employed content analysis and bibliometric methods, using CiteSpace for knowledge-map visualization. The findings reveal that: (1) AI-empowered mathematics education is currently in a relatively active research phase and is expected to remain so in the foreseeable future. (2) Four key thematic clusters have emerged across different stages: grade-level stratification studies, technology-enabled research, competency development studies, and foundational disciplinary research. (3) Author and institutional collaboration networks exhibit low density and loose structures, suggesting the absence of a specialized core research community in this field. (4) Most studies remain at a descriptive level, focusing on technological applications, while deeper engagement with educational theories in AI-empowered mathematics education is still insufficient. Based on this, recommendations are proposed, which provide a clear evolutionary reference and optimization direction for the adaptive research and practice of promoting the in-depth integration of artificial intelligence technology and mathematics education in the mathematics education discipline.