Measuring The Impact of AI-Based Learning Analytics on Student Performance and Institutional Decision-Making: A Study of Educational Institutions in South Punjab

Abstract

This study investigates the impact of AI-based learning analytics on student performance and institutional decision-making in higher education institutions in South Punjab, Pakistan. Using a quantitative research design, data were collected from 300 respondents comprising students, faculty members, and administrators across public and private universities. Descriptive, correlation, and regression analyses were employed to examine the relationships between AI-based learning analytics, student performance, and institutional decision-making. The findings reveal that AI-based learning analytics significantly enhance student academic outcomes by providing personalized feedback and adaptive learning opportunities. Similarly, AI systems were found to strengthen institutional decision-making by improving administrative efficiency, evidence-based planning, and strategic resource management. The results highlight the transformative potential of AI-driven analytics as both a pedagogical and managerial tool, bridging the gap between learning and governance. Despite these positive outcomes, the study acknowledges limitations related to geographic scope and reliance on self-reported data. It concludes that AI adoption in education can create more data-informed, transparent, and efficient institutions if integrated strategically and ethically.