🤖 AI Summary
This study addresses the growing misalignment between the rapid integration of generative artificial intelligence into classrooms and educators’ preparedness to use it responsibly. To bridge this gap, the authors propose the Responsible Artificial Intelligence Literacy in Education (RAIL-Ed) framework. Drawing on a systematic review of 67 studies and integrating perspectives from critical pedagogy, pragmatism, sociocultural theory, and human-centered traditions, RAIL-Ed uniquely positions ethics, equity, and agency as constitutive elements. The framework articulates an integrative, developmental, and dialectical model organized around six core pillars, accompanied by a three-stage maturity rubric. Designed to inform K–12 teacher education, curriculum design, and policy development, RAIL-Ed offers a theoretically grounded and empirically actionable foundation that aligns with AI literacy initiatives from UNESCO and the OECD/European Commission.
📝 Abstract
Generative artificial intelligence (GenAI) has entered classrooms faster than teachers have been prepared to use it well, producing a GenAI literacy lag in which technological diffusion outpaces educators' conceptual, pedagogical, and ethical readiness. Established AI literacy frameworks predate the widespread adoption of large language models and, while acknowledging ethics, position it as a discrete competency rather than a constitutive commitment, with equity and agency as supplementary design principles. Recent GenAI-specific efforts address isolated features but remain fragmented. We introduce the Responsible AI Literacy in Education (RAIL-Ed) framework, developed through a systematic review and qualitative framework analysis of 67 studies (2023-2025), grounded in critical, pragmatist, sociocultural, and human-centered traditions (Freire, Dewey, Vygotsky, Shneiderman). RAIL-Ed specifies six interdependent pillars: Technical Fluency, Critical Evaluation, Human-AI Collaboration, Contextual Awareness, Ethical Reasoning, and Empowered Agency, marked by three commitments. It is integrative: the absence of any pillar produces a characteristic pedagogical failure. It is developmental: a three-level rubric (Emerging, Competent, Advanced) specifies how each pillar matures across the K-12 teacher-preparation continuum. It is dialectical: the same generative affordance can deepen or displace learning depending on the literacy a teacher brings to it, making the cultivation of that literacy, not the adoption of the tool, the object of design. By treating ethics, equity, and agency as constitutive, RAIL-Ed offers a theoretically grounded basis for curriculum design, teacher education, and policy, aligned with the UNESCO AI Competency Framework for Teachers and the OECD/European Commission AILit Framework. The framework is conceptual, advancing falsifiable propositions for empirical validation.