arXiv:2606.00038cs.CYcs.AI2026-06

提出五阶段AI素养发展模型,助高校学生从被动回避到主动批判使用AI。

Beyond Tool Adoption: A Practical Five-Stage Developmental Continuum for AI Literacy in Higher Education

  • 构建五阶段发展模型:从不参与、盲目使用到批判评估与改进。
  • 330余名学生参与实践,观察到从被动到主动的素养提升趋势。
  • 适合教育者设计分层课程,推动AI素养从工具使用走向深度理解。

人工智能素养已成为高校毕业生的核心能力。然而,学生对AI工具的参与常呈现两极分化:或因恐惧、信任缺失、伦理顾虑或资源不足而回避,或盲目依赖导致表面流畅实则误解。现有框架虽定义了素养维度,但缺乏诊断学习起点与进展路径的指导。本文提出五阶段AI素养发展连续体:0)尚未参与,1)无批判使用,2)有意识使用,3)批判评估,4)持续改进。该模型与UNESCO、OECD等国际框架对齐,为教学提供可操作路径。在北卡罗来纳州立大学的实践案例中,2024秋季至2026春季期间,通过学分课程与高强度工作坊,覆盖超330名参与者。由于未采用验证量表或对照组,结果为观察性实践反馈:参与者行为显示出从非参与或盲目使用向有意识参与转变;持续且学科嵌入式体验更促进批判评估与改进型实践。论文主张,AI素养不应仅限于工具采纳,而应视为在专业与社会语境中理解、评估并负责任地应用AI系统的成长性能力。

原文摘要 · Abstract (English)

Artificial intelligence (AI) literacy is increasingly recognized as a foundational competency for all university graduates. Yet students' engagement with AI tools often clusters at two extremes: avoidance driven by fear, mistrust, ethical concern, or lack of access, and uncritical reliance that produces fluent output while masking misunderstanding. Existing AI literacy frameworks provide valuable competency definitions, but most offer limited guidance for diagnosing where learners begin and how they progress toward responsible, critical engagement. This paper proposes a five-stage AI Literacy Continuum: 0) Not Yet Engaged, 1) Uncritical Use, 2) Informed Use, 3) Critical Evaluation, and 4) Improvement --that describes developmental orientations toward AI use in higher education. The continuum complements dimensional frameworks by providing educators with a practical diagnostic and instructional pathway aligned with international frameworks, including UNESCO and OECD. We present a design-based implementation case from North Carolina State University, where credit-bearing courses and intensive hands-on workshops engaged more than 330 participants between Fall 2024 and Spring 2026. Because the implementation did not use a validated pre/post instrument or comparison group, we frame the findings as observational and practice-based: participants exhibited behaviors consistent with movement from non-engagement or uncritical use toward informed engagement, while sustained and discipline-embedded experiences produced stronger evidence of critical evaluation and improvement-oriented practice. We discuss curricular pathways, opportunity considerations, assessment strategies, and argue that AI literacy should be understood not as tool adoption alone but as a developmental capacity to understand, evaluate, and responsibly apply AI systems in disciplinary and societal contexts.

AI素养教育发展五阶段模型

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