数智时代教师身份认同的研究脉络与演进趋势——基于中外核心文献的系统性回顾

Research Trajectories and Trends of Teacher Identity in the Digital Age—A Systematic Review of Core Chinese and International Literature

摘要: 随着人工智能技术越来越多地融入教育教学，教师传统的角色定位受到冲击，数智时代教师身份认同问题日益凸显。本研究基于CNKI与WOS核心数据库(2015~2026)，采用系统性文献回顾(Systematic Review)方法，并辅助以CiteSpace进行主题聚类，分析了国内外教师数智时代身份认同的研究脉络与趋势。研究发现，国内外相关研究最初关注身份危机以及技术适配，转向对教师内在心理与教学观念的探讨，再发展为目前人机协同环境下身份重构与互动关系重建的演变过程。数字化转型促使教师不断重构专业角色。教师不仅是教学内容的设计者，更是人机协同环境下，通过具体教学决策与行为调整，实现算法反馈与师生情感共鸣相平衡的关键主体。基于此，本文提出，未来研究应超越宽泛的理论探讨，通过真实的课堂人机分工实证、基于情感视角的叙事研究，以及针对本土政策驱动环境的中长期追踪，将抽象的身份认同研究转化为具体的教师发展与支持路径。

Abstract: With the increasing integration of artificial intelligence into education and teaching, the traditional role positioning of teachers has been challenged, making the issue of teachers’ identity in the digital age increasingly prominent. Based on the CNKI and WOS core databases (2015~2026), this study employed a systematic literature review method, supplemented by CiteSpace for thematic clustering to analyze the research trajectories and trends of teachers’ identity in the digital age domestically and internationally. The findings reveal an evolutionary process in related research: it initially focused on identity crises and technological adaptation, then shifted toward the exploration of teachers’ internal psychology and teaching beliefs, and has now developed into the reconstruction of identity and interactive relationships within human-machine collaborative environments. Digital transformation compels teachers to continuously reconstruct their professional roles. Teachers are not only the designers of teaching content, but also the key agents capable of achieving a balance between algorithmic feedback and teacher-student emotional resonance through specific teaching decisions and behavioral adjustments in human-machine collaborative environments. Based on this, this paper proposes that future research should move beyond broad theoretical discussions, and transform abstract identity research into specific teacher development and support pathways through empirical investigations of human-machine division of labor in real classrooms, narrative research from an emotional perspective, and longitudinal tracking within local policy-driven environments.