BIG DATA ANALYTICS IN EDUCATION: TRANSFORMING STUDENT LEARNING AND INSTITUTIONAL PRACTICES

Abstract

Big Data Analytics (BDA) is revolutionizing education by transforming how student learning and institutional practices are analyzed and optimized. This paper explores the significant impact of BDA on the education sector, focusing on its potential to enhance student performance, personalize learning experiences, and improve institutional decision-making. Through real-time data collection and analysis, educational institutions can identify trends, predict outcomes, and address challenges related to student retention, academic success, and resource management.

The application of BDA enables educators to tailor instructional strategies based on individual learning patterns, promoting a more personalized and effective learning experience. Furthermore, the integration of BDA helps in identifying at-risk students early, allowing for timely interventions that improve academic outcomes. In higher education, BDA assists institutions in curriculum development, resource allocation, and operational efficiency, aligning practices with both student needs and industry demands.

However, the widespread adoption of BDA in education also raises concerns regarding data privacy, ethical considerations, and the digital divide. This review critically examines these challenges while also highlighting the benefits of data-driven decision-making. It discusses key case studies and models where BDA has successfully enhanced educational practices, providing insights into best practices for integrating these technologies into learning environments.

BDA presents transformative opportunities for education, fostering personalized learning, improving institutional processes, and addressing challenges in real-time. The review emphasizes the need for ethical frameworks and robust data governance to ensure equitable and secure implementation of BDA in education.