EVALUATING THE IMPACT OF AI-DRIVEN LEARNING MANAGEMENT SYSTEMS ON TEACHING AND LEARNING IN HIGHER EDUCATION

Abstract

This study examines the effects of Artificial Intelligence (AI)-based Learning Management Systems (LMS) on teaching and learning in tertiary education. With challenges like large class sizes, diverse learning needs, and adapting to evolving educational environments, AI technologies in LMS are becoming increasingly popular to address these issues. AI-powered LMS offers personalized learning paths, automated processes, and real-time feedback, transforming education. The objective of this paper is to evaluate the impact of AI-based LMS on teaching capabilities, student engagement, and performance. Using a mixed-methods research approach, data were collected through surveys (quantitative) and interviews (qualitative), alongside usage analytics from the LMS. Results show that AI-based LMS are moderately effective in improving learning outcomes and engagement, although challenges remain in instructor adoption, content customization, and technological support. The study highlights the need for continuous professional development for educators, robust technical infrastructure, and ethical considerations in AI use. Best practice guidelines for integrating AI in education are provided, aiming to improve teaching practices and student learning experiences.