生成式人工智能素养量表（GLAT）研究述评
DOI:
https://doi.org/10.70693/cjst.v1i4.1768Keywords:
生成式人工智能量表；ALS ；GLAT；跨文化评估；文献计量法Abstract
生成式人工智能的快速发展对素养评估提出新挑战。现有研究多依赖自陈式量表，且缺乏跨文化验证。基于此，本研究采用CiteSpace工具与文献计量方法，对2021-2025年间中英文文献进行可视化与定性分析。结果表明：研究理论基础从“信息素养”向“AI素养”演进；热点聚焦于“学评融合”“人机协同”等主题；现有量表虽形成“认知-技能-情感-伦理”四维结构，但存在跨文化等值性验证不足、评估缺乏标准化等问题。本研究提出“认知-技能-情感-伦理-评估-跨文化”六维度量表，为跨文化场景下的量表设计提供理论支撑。
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