AI-POWERED ADAPTIVE LEARNING: ENHANCING PERSONALIZED EDUCATION IN NIGERIA SECONDARY SCHOOLS

Abstract

This study examines the impact of AI-powered adaptive learning on students’ academic achievement and engagement in secondary schools in Nigeria. It also explores the moderating effects of gender and technology acceptance using the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. A quantitative survey research design was adopted, and data were collected from secondary school students in private schools with access to the uLesson AI adaptive learning tool. A structured questionnaire, consisting of the Adaptive Learning Engagement Scale (ALES) (r = .75) and the Technology Acceptance and Academic Performance Scale (r =.78), was used to gather responses. Descriptive and inferential statistics, including multiple regression analysis, were employed to analyze the data. Findings indicate a significant positive relationship between AI-powered adaptive learning and students’ academic achievement and engagement. Also, technology acceptance (UTAUT factors) significantly influenced students’ learning outcomes, with performance expectancy and effort expectancy emerging as key predictors. While gender had a notable effect on academic performance, its impact on engagement was not statistically significant. The study highlights the importance of integrating AI-driven learning tools with Supportive technology acceptance strategies to enhance student outcomes. It is recommended that educators and policymakers promote AI adoption, provide necessary training, and develop policies that foster a technology-friendly learning environment in Nigerian secondary schools.