AIED For Self-Learning in Nigeria: Implications for Curriculum and Instruction

The advent of Artificial Intelligence in Education (AIED) has opened new pathways for self directed learning, particularly in contexts where access to qualified and competent teachers remains uneven. This paper examines the implications of AIED-supported self-learning for curriculum design and instructional practice, making Nigeria as a case of study. Drawing on a structured review of AIED literature, self-directed learning theory, and empirical studies from Nigerian educational contexts, the paper identifies three core tensions: the promise of personalized adaptive systems versus infrastructural deficits; the demand for learner autonomy versus the preference for teacher-directed instruction; and the urgency of AI literacy versus the need for ethical governance frameworks. The analysis suggests that Nigeria's curriculum must shift from content-coverage models toward competency-based, AI augmented frameworks, while instruction must move toward blended facilitation that positions the teacher as a learning architect rather than a sole knowledge source. The paper concludes with a research agenda addressing theoretical and empirical gaps in AIED supported self-learning in Nigeria.