Open Educational Resources and Generative AI: Towards a Framework for Responsible Integration
Abstract
Generative artificial intelligence is challenging traditional approaches to the production, adaptation, circulation, and governance of educational resources. This article asks how generative artificial intelligence and Open Educational Resources can be responsibly integrated in higher education and lifelong learning. The study adopts a qualitative framework-development design organised in two phases: an integrative analysis of international artificial intelligence and OER frameworks, and a stakeholder-informed co-creation phase comprising expert validation and a participatory workshop. Data sources included a documentary framework review matrix, expert validation transcripts, panel synthesis notes, workshop group outputs, graphical materials, and facilitator notes. The stakeholder-informed phase involved five international experts, four national informants, and 81 workshop participants from educational, governmental, civil society, and open-knowledge backgrounds. Data were analysed through abductive thematic synthesis, source-to-theme mapping, and iterative framework refinement. The findings show that: (a) artificial intelligence and open educational resources continue to evolve through partially separate policy and practice spheres, creating gaps in equity, interoperability, provenance, trust, legal clarity, and institutional capacity; (b) responsible implementation depends on human agency, openness beyond licensing, quality assurance, collective governance, capacity-building, and infrastructure choice; (c) co-creation translated these gaps into practical institutional priorities; and (d) the OE-AI Framework offers a seven-pillar architecture for aligning AI-mediated innovation with openness, educational autonomy, and public value. The article contributes a governance-oriented framework for educational communities, policymakers, and institutional leaders seeking to integrate AI and OER as a public-good educational challenge.