AI in Education: Personalized Learning Systems and Their Impact on Student Performance and Engagement

Abstract

This research investigates the effect of AI-based personalized learning systems on students' performance, engagement, and participation, as well as challenges and ethical issues related to AI implementation in education. Adopting a quantitative research approach, data were gathered from 268 university instructors from all provinces of Pakistan using a self-administered questionnaire. Correlation analysis indicated a high positive correlation between AI-based learning and student performance (r = 0.74, p < 0.001), whereas regression analysis indicated significant influence on participation and engagement (β = 0.72, p < 0.001). Moreover, chi-square findings validated that accessibility problems (χ² = 12.76, p < 0.001) and data privacy issues (χ² = 15.89, p < 0.001) are significant challenges. The results indicate that AI improves learning outcomes but needs meticulous implementation to overcome barriers of access, ethics, and the working of teachers. This research adds to the increasing body of research on AI-based education and highlights the importance of inclusive, ethical, and regulated adoption of AI in higher education.