"AI-INTEGRATED LEARNING MANAGEMENT SYSTEMS (LMS) : IMPACT ON PRIMARY SCHOOL STUDENT'S ACADEMIC PERFORMANCE"

This study investigates the effectiveness of Artificial Intelligence (AI)-enhanced Learning Management Systems (LMS) in improving academic achievement, engagement, and critical thinking among primary school students. Despite growing adoption of AI tools in educational settings, findings reveal limited measurable benefits at the primary level. A mixed-method, cross-sectional design was employed with data collected from 120 students using academic assessments, LMS usage logs, classroom observations, and teacher interviews. Regression analysis showed weak relationships between AI tools—personalized learning, adaptive assessments, and intelligent feedback—and academic performance (R = 0.091, R² = 0.008), with no significant predictors (p > 0.05). Similarly, system log analyses found no significant correlations between LMS usage indicators (logins, time spent) and engagement, suggesting quantitative metrics alone cannot capture the multifaceted nature of engagement. A weak, non-significant positive correlation between personalized learning and critical thinking (r = 0.159, p = 0.082) was also observed. These findings align with existing critiques emphasizing the importance of pedagogical readiness, teacher training, and contextualized implementation in AI-driven education. The study highlights the need for multidimensional engagement measures and longitudinal mixed-method research to understand AI's long-term impact. While AI technologies hold promise, their effective integration in primary classrooms requires cautious optimism, professional development, and institutional support.