Exploring AI-Driven Adaptive Learning Systems for Personalized Education in Nigerian TVET Institutions to Enhance Student Engagement and Skill Acquisition Outcomes

The emergence of Artificial Intelligence (AI) in education has revolutionized learning methodologies, particularly through the implementation of adaptive learning systems. This paper explores the impact of AI-driven adaptive learning systems on student engagement and skill acquisition outcomes in Nigerian Technical and Vocational Education and Training (TVET) institutions. Traditional educational practices often follow a one-size-fits-all approach, failing to cater to the diverse learning needs of students, thereby contributing to high dropout rates and inadequate skill development. AI technologies offer personalized learning experiences that align educational outcomes with industry demands, addressing the skills mismatch highlighted by the World Bank. However, the successful integration of these systems faces significant barriers, including insufficient infrastructure, limited funding, and resistance to change among educators. Additionally, concerns regarding data privacy and ethical implications pose challenges to stakeholder acceptance of AI in educational contexts. Recommendations include enhancing institutional infrastructure, providing targeted training for educators, and establishing clear policies to safeguard data privacy. Furthermore, fostering collaboration between educational institutions and industry can ensure curriculum alignment with labor market needs. By addressing these challenges, AI-driven adaptive learning systems have the potential to transform the educational landscape in Nigeria, equipping students with relevant skills and enhancing their engagement and motivation. Ultimately, the adoption of these innovative technologies could lead to improved educational outcomes and better prepare graduates for the demands of the modern workforce.