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，学生对人工智能工具的参与往往集中在两个极端：因恐惧、不信任、伦理关切或缺乏机会而回避，以及不加批判地依赖，这虽能产生流畅的输出，却掩盖了理解不足。现有的人工智能素养框架提供了有价值的能力定义，但多数框架在诊断学习者起点及其如何迈向负责任、批判性参与方面指导有限。本文提出了一个五阶段人工智能素养连续体：0）尚未参与，1）不加批判的使用，2）知情使用，3）批判性评估，以及4）改进——该连续体描述了高等教育中人工智能使用的发展取向。该连续体补充了维度框架，为教育工作者提供了与包括联合国教科文组织和经合组织在内的国际框架相一致的实用诊断与教学路径。我们介绍了北卡罗来纳州立大学的一个基于设计的实施案例，其学分课程和密集型实践研讨会在2024年秋季至2026年春季期间吸引了超过330名参与者。由于实施过程中未使用经过验证的前/后测试工具或对照组，我们将研究结果界定为观察性和基于实践的：参与者表现出的行为与非参与或不经批判的使用向知情使用的转变一致，而持续且嵌入学科的经验则产生了更强有力的批判性评估和以改进为导向实践的证据。我们讨论了课程路径、机会考量、评估策略，并主张人工智能素养不应仅被理解为工具采纳，而应被视为一种理解、评估和负责任地将人工智能系统应用于学科及社会情境的发展能力。