A Nigerian Artificial Intelligence Adoption Framework for Education Using the Barrett Model: A Values-Driven, Data Protection–Embedded, Language-Inclusive Blueprint for Teaching and Learning

Abstract

Artificial intelligence (AI) offers significant opportunities to enhance teaching and learning in Nigeria, yet existing scholarship and policy lack a unified, values-driven adoption framework. Key gaps include the absence of a coherent policy spine, limited operationalisation of the Nigeria Data Protection Act (NDPA) and Regulation (NDPR), weak standards for language equity and accessibility, and the absence of pilot-ready guidance. This paper proposes a comprehensive adoption framework structured by the Barrett Model’s seven levels of organisational consciousness. Using a design-synthesis approach, the study integrates Nigeria-focused policy analyses, higher-education governance models, multilingual pilot strategies, and Africa-wide lessons on responsible AI. The framework introduces: cross-cutting principles for data protection and teacher safeguards; a seven-level Barrett-aligned structure with decision gates and measurable KPIs; an operating model for governance, Education Management Information System (EMIS)/National Education Management Information System (NEMIS) interoperability, and vendor oversight; a pilot blueprint and compliance pack; a programme for language equity and accessibility; a monitoring and assurance plan; a phased implementation roadmap; and a risk register. To our knowledge, this is the first system-wide AI in education framework explicitly adapted to Nigeria through the Barrett Model. It provides a values-based, operational, and legally compliant pathway for ethical AI adoption, with broader relevance for low- and middle-income countries.

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