作者：杨玉芹,张颖,孙丹儿,何闻萌,魏艳涛*

出版刊物：Humanities & Social Sciences Communications

出版时间：2025年

内容摘要：

As artificial intelligence (AI) becomes increasingly integrated into various fields, the need to enhance learners’ AI literacy is more urgent than ever. Despite its growing importance, a comprehensive review of AI literacy education research has been lacking. This study addresses that gap by mapping the current landscape, tracing its evolution, and identifying key themes through a bibliometric analysis of research from 2014 to 2024, utilizing Cite Space for data visualization and analysis. This study systematically selected 335 relevant articles from databases, including Web of Science Core Collection, Scopus, and Science Direct, following PRISMA guidelines. Our methodology involved keyword co-occurrence mapping to trace the development paths and thematic evolution within the field. By examining publication trends and thematic clusters, we provide insights into the progression and focal points of AI literacy education research over the past decade. The study reveals three key insights. First, AI literacy education research has shifted from an exploratory phase to rapid growth, with a marked increase in publications. Second, four distinct developmental trajectories have emerged, emphasizing the interdisciplinary nature of the field and its connections to information, digital, and algorithmic literacy. Third, nine prominent research themes have been identified, with data literacy, machine learning, AI literacy, the technology acceptance model, and computational thinking as focal points. These themes highlight AI’s evolving role, particularly in education, and shifts in research priorities. This review provides a comprehensive understanding of AI literacy education’s evolution and its implications for education, ethics, and society. As AI continues to influence modern education and industry, this analysis serves as a valuable resource for researchers, educators, and policymakers navigating the complex intersection of AI and literacy.

随着人工智能日益融入各领域，提升学习者的AI素养变得尤为迫切。尽管其重要性不断凸显，当前仍缺乏对AI素养教育研究的系统性综述。为弥补这一空白，本研究通过文献计量分析方法，对2014年至2024年相关研究进行全景式梳理与演化脉络追踪，并利用CiteSpace工具开展数据可视化分析。研究依据PRISMA准则，系统筛选自Web of Science核心合集、Scopus及Science Direct数据库的335篇文献，通过关键词共现网络分析，揭示该领域的发展路径与主题演进。在考察发文趋势与主题聚类的基础上，本研究进一步梳理近十年来AI素养教育研究的进展脉络与核心议题。研究发现：第一，AI素养教育研究已从探索阶段进入快速增长期，研究成果数量呈现显著上升趋势；第二，该领域形成四条清晰的发展路径，体现了其跨学科特性以及与信息素养、数字素养、算法素养等领域的内在关联；第三，当前研究聚焦于九大核心主题，其中数据素养、机器学习、AI素养、技术接受模型和计算思维成为重点研究方向，这些主题不仅反映了人工智能在教育等领域的角色演变，也显示出研究重点的阶段性转移。本综述为理解AI素养教育的演进规律及其对教育、伦理与社会发展的影响提供了系统性参考。随着人工智能持续影响现代教育和产业格局，本研究可为研究者、教育工作者和政策制定者提供应对AI与素养教育复杂关联的重要参照。