Generative AI in Education: Pedagogical, Theoretical and Methodological Perspectives in Nigerian Tertiary Institutions

Abstract

The emergence of generative artificial intelligence (GenAI) represents a paradigm shift in educational technology, offering unprecedented opportunities for transforming teaching, learning, and research in Nigerian tertiary institutions. This paper examines the integration of generative AI in higher education from pedagogical, theoretical, and methodological perspectives, with specific focus on the Nigerian context. The study explores how large language models, AI image generators, and multimodal AI systems are reshaping educational practices, while analyzing the theoretical foundations including constructivism, connectivism, and the TPACK framework that underpin AI-enhanced pedagogy. Methodologically, the paper investigated research approaches for studying GenAI implementation, including design-based research, mixed methods approaches, and participatory action research. Despite the transformative potential of generative AI, Nigerian tertiary institutions face significant challenges including infrastructural deficits, digital literacy gaps, ethical concerns regarding academic integrity, and policy vacuums. The paper proposes a comprehensive framework for sustainable integration of generative AI in Nigerian higher education, emphasizing the need for contextualized policies, capacity building, ethical guidelines, and collaborative partnerships. The study concludes that successful implementation of generative AI requires alignment with local educational realities, cultural contexts, and sustainable development goals to maximize benefits while mitigating risks.