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With the rapid development of artificial intelligence, particularly generative AI, AI literacy is regarded as an essential competency for individuals and society. This research systematically organizes domestic and international literature and, through content analysis, addresses core issues in this field, including conceptual definitions, research approaches, developmental trajectories, core content, methodological theories and evaluation systems. The essence of artificial intelligence literacy has evolved into a multidimensional structure that encompasses knowledge, skills, mindset, attitudes and ethics. Three dominant research approaches are identified: the interdisciplinary-integration-oriented approach, the social-function-oriented approach, and the measurement-and-evaluation-oriented approach. Existing research has covered implementation strategies for multiple groups, the role of institutions such as libraries, and disparity studies. Both domestic and international competency frameworks are constructed around the “knowledge-skills-attitudes”, yet significant differences exist in group-specific and cultural perspectives. Current research faces several limitations, including inadequate validation of assessment tools, difficulty balancing generalizability and specificity, the knowledge-action gap stemming from reliance on self-report scales, lack of longitudinal and dynamic studies, andscarcity of cross-cultural applicability testing. Future studies should strengthen longitudinal research and measurement method innovation, prioritize developing culturally responsive frameworks, and address equity issues in literacy education.
, authors=Wenjuan Yu, Junping Hu, Hongbin Gao, authorsList=Wenjuan Yu, Junping Hu, Hongbin Gao, authorCompany=null, correspAuthors=Hongbin Gao, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1288943097602220976, articleId=1288943097166013358, tenantId=1146029695717560320, journalId=1149652312894775300, language=CN, title=人工智能素养:内涵取向、核心议题与框架审视, columnId=1288943042333880741, journalTitle=科普研究, columnName=专题, runingTitle=null, highlight=null, articleAbstract=
随着人工智能技术的迅猛发展,特别是生成式人工智能的突破性应用,人工智能素养已演变为关乎个体发展与社会竞争力的核心素养。本研究通过对中外文献进行系统梳理并结合内容分析法,旨在回应人工智能素养的内涵界定、研究取向、发展脉络、核心内容、方法理论及评价体系等核心问题。人工智能素养的内涵已演变为一个超越单纯技术操作的,包含知识、技能、思维、态度与伦理的多维复合结构。学界形成了以学科融入、社会功能与测量评估为代表的三大研究取向;相关研究已系统覆盖多群体的素养实施策略、图书馆等机构的角色探究以及差异研究等内容。国内外人工智能素养框架围绕“知识—技能—态度”3个核心维度构建,但也存在群体与文化视角上的显著差异。目前还存在评估工具信效度验证不足、普适性与特异性难以平衡、依赖自我报告式量表导致的知行鸿沟、缺乏动态纵向研究以及跨文化适用性检验匮乏等问题。未来研究应加强纵向研究与测量方法创新,重视文化回应性框架的开发,并关注素养教育的公平性议题。
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于文娟,中国科普研究所博士后,研究方向:人工智能素养、开放科学、高等教育管理等,E-mail:yuwenjuan@cast.org.cn。
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于文娟,中国科普研究所博士后,研究方向:人工智能素养、开放科学、高等教育管理等,E-mail:yuwenjuan@cast.org.cn。
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