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.

翻译：人工智能（AI）素养日益被视为所有大学毕业生应具备的基础能力。然而，学生对AI工具的参与往往集中在两个极端：一是因恐惧、不信任、伦理担忧或缺乏使用途径而回避；二是盲目依赖，虽能产生流畅的输出，却掩盖了理解上的不足。现有AI素养框架提供了有价值的定义，但多数在指导如何诊断学习者的起点以及如何向负责任、批判性参与进展方面存在局限。本文提出一个五阶段AI素养连续统：0）尚未参与，1）不加批判的使用，2）知情使用，3）批判性评估，4）改进——描述高等教育中AI使用的演进取向。该连续统补充了维度框架，为教育者提供了一个实用诊断与教学路径，与国际框架（包括联合国教科文组织与经合组织）保持一致。我们展示了来自北卡罗来纳州立大学的一项基于设计的实施案例，其中学分课程与密集实践工作坊在2024年秋季至2026年春季期间吸引了超过330名参与者。由于该实施未采用经过验证的前/后测工具或对照组，我们将发现界定为观察性且基于实践：参与者表现出从非参与或盲目使用向知情参与的转变行为，而持续且深入学科的体验则产生了更强的批判性评估与改进导向实践的证据。我们讨论了课程路径、机会考量、评估策略，并主张AI素养不应仅被理解为工具采纳，而应视为一种发展性能力，旨在理解、评估并负责任地在学科与社会语境中应用AI系统。