Navigating the Digital-AI Frontier: A Comparative Thematic Synthesis of Global Digital Learning Skills Frameworks for Inclusive Primary Education

Abstract

In the era of generative artificial intelligence (GenAI) and post-pandemic educational restructuring, primary education urgently requires a redefined conception of digital learning skills—one that is explicitly inclusive of students with special educational needs (SEN). This study provides a comparative thematic synthesis of four authoritative international frameworks: the European DigComp 2.2, ISTE Standards for Students, UNESCO AI Competency Framework for Students (2024), and the Digital Intelligence (DQ) Global Standards. Guided by Social Constructivism, Connectivism, Self-Regulated Learning (SRL), and Universal Design for Learning (UDL), the analysis reveals a decisive paradigm shift from technical-procedural tool usage toward a holistic matrix of cognitive, socio-emotional, and ethical competencies. Five thematic clusters are identified across all frameworks: information and data literacy, communication and collaboration, digital content creation, safety and well-being, and computational problem-solving. A critical cross-cutting finding is the systematic absence of explicit SEN provisions in every framework examined—constituting a structural gap in global digital education policy. A widening “Usage-Training Gap,” wherein approximately 86% of primary students engage with AI tools daily while fewer than half receive formal guidance, disproportionately disadvantages learners with SEN. The study proposes a five-domain conceptual matrix that integrates accessibility and UDL as a foundational dimension, positioning digital learning skills as a mediating variable between technological infrastructure and inclusive academic outcomes. Recommendations address policymakers, special education practitioners, and curriculum designers, emphasizing a shift from physical access equity (Divide 1.0) to skill agency equity (Divide 2.0).