DATA MINING APPROACH WITH LEARNING ANALYTICS FOR ASSESSMENT OF STUDENTS PERFORMANCE

Abstract

Abstract: In the realm of contemporary education, the confluence of extensive datasets and evolving data analytics techniques offers transformative avenues for student performance assessment. This research explores the synergy between data mining and learning analytics, aiming to craft a comprehensive framework. Beyond predicting academic outcomes, the study seeks to furnish educators with insights for tailored teaching strategies. This intersection holds promise for personalized and adaptive learning environments. The subsequent chapters delve into theoretical foundations, methodology, implementation, and the potential impact of this data-driven approach on assessing students' academic achievements.