Evaluation of the impact of AI-driven adaptive learning on foundational literacy in preschoolers in Nigeria

Abstract

This study evaluates the impact of AI-driven adaptive learning on foundational literacy development among preschool ers in Nigeria, set against a background of rapid technological transformation and persistent literacy gaps in early childhood education. The research aimed to evaluate how these personalised digital platforms influence early reading skills and engagement, while assessing the scope of digital infrastructure and teacher readiness across six Nigerian states: Kaduna State, Bauchi State, Abuja (Federal Capital Territory), Lagos State, Rivers State and Enugu State. Adopt ing a quantitative descriptive survey design, the study sampled 384 teachers and administrators using the "AI-Driven Adaptive Learning and Foundational Literacy Questionnaire" (ADALFLQ). The findings revealed that while AI-driven platforms significantly enhance letter recognition (x̄ = 3.10), phonemic awareness, and learner engagement (x̄ = 3.23), their overall effectiveness is critically hampered by low teacher preparedness (x̄ = 2.32), poor internet connectivity (x̄ = 2.49), and inadequate training (x̄ = 2.25). The study concluded that although AI-driven adaptive learning positively influences literacy outcomes, it cannot operate in a vacuum; thus, the difference in literacy scores between supportive and less supportive environments was not statistically significant at p > 0.05 due to systemic infrastructural deficits. Based on these results, it is recommended that the government and school proprietors prioritise robust digital infra structure, stable electricity, and comprehensive teacher professional development in AI integration.