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作所有大学毕业生的一项基础能力。然而，学生对人工智能工具的参与往往集中于两个极端：因恐惧、不信任、伦理担忧或缺乏获取途径而产生的回避，以及不加批判的依赖——后者虽能产出流畅的输出，却掩盖了理解上的不足。现有的人工智能素养框架提供了有价值的能力定义，但多数在指导如何诊断学习者起点以及他们如何向负责任、批判性参与迈进方面所提供的指引有限。本文提出一个人工智能素养五阶段发展连续体：0) 尚未参与，1) 不加批判的使用，2) 知情使用，3) 批判性评价，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。它通过为教育工作者提供一套与联合国教科文组织（UNESCO）和经济合作与发展组织（OECD）等国际框架相一致的实用诊断与教学路径，从而补充了维度型框架。我们呈现了来自北卡罗来纳州立大学的一项基于设计的实施案例，该案例在2024年秋季至2026年春季期间，通过学分课程和密集型实践工作坊吸引了超过330名参与者。由于该实施未使用经过验证的前/后测工具或对照组，我们将研究结果界定为基于观察与实践的：参与者表现出的行为与从非参与或不加批判的使用向知情参与的转变相一致，而持续的、嵌入学科的经历则产生了批判性评价和以改进为导向实践的更强证据。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仅被理解为工具采纳，而应被视为一种理解、评价并负责任地在学科与社会语境中应用人工智能系统的发展性能力。