Proposes a five-stage developmental continuum (Not Engaged, Uncritical Use, Informed Use, Critical Evaluation, Improvement) for AI literacy at NC State; the continuum doubles as a diagnostic tool for moving students beyond fluent-but-uncritical tool adoption. Found that reaching higher stages requires discipline-embedded experiences. AI Literacy, Higher Ed, Ethics, Faculty Development, Student Experience.
Key Findings
The paper proposes a five-stage AI Literacy Continuum — Not Yet Engaged, Uncritical Use, Informed Use, Critical Evaluation, and Improvement — describing developmental orientations toward AI use in higher education.The continuum responds to two problematic extremes observed in students: avoidance driven by fear, mistrust, ethical concern, or lack of access, and uncritical reliance that produces fluent output while masking misunderstanding.It complements dimensional competency frameworks by providing educators a practical diagnostic and instructional pathway aligned with international frameworks, including those of UNESCO and OECD.A design-based implementation case at North Carolina State University engaged more than 330 participants between Fall 2024 and Spring 2026 through credit-bearing courses and intensive hands-on workshops.Because no validated pre/post instrument or comparison group was used, the findings are 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.Stage-specific assessment strategies are proposed, from identifying hallucinated content, appropriate use cases, and articulating AI limitations at early stages, to designing evaluation protocols or demonstrating systematic improvement of AI performance on disciplinary tasks at later stages.The Continuum as a Diagnostic Tool
The five stages are explicitly intended as a diagnostic device, not just a description: educators can locate where learners begin and design instruction that moves them toward responsible, critical engagement. The framework's practical value lies in pairing each stage with observable behaviors and appropriate assessment, so that AI literacy is treated as a developmental capacity to understand, evaluate, and responsibly apply AI systems in disciplinary and societal contexts — rather than as tool adoption alone.
Implications for AI in Education
The continuum gives Curriculum Design and Faculty Development a shared vocabulary for sequencing AI literacy instruction, and its alignment with international frameworks supports institutional uptake. The NC State case suggests that movement along the continuum is most visible when experiences are sustained and embedded in disciplines, implying that one-off workshops may shift students from non-engagement toward informed use, while deeper stages require ongoing, context-rich opportunities. The authors' framing of their evidence as observational and practice-based also models appropriate epistemic humility for institutions adopting the framework, and their discussion of equity considerations reminds educators that access and disposition shape where students enter the continuum.
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Liu & Levy (2026). Beyond Tool Adoption: A Practical Five-Stage Developmental Continuum for AI Literacy in Higher Education. arXiv:2606.00038.