EDUCATIONAL INFORMATION SYSTEMS: LEVERAGING DATA SCIENCE FOR PERSONALIZED LEARNING

Abstract

The integration of data science into educational information systems (EIS) is revolutionizing personalized learning environments. By harnessing large datasets, learning algorithms, and artificial intelligence (AI), educational institutions can now deliver tailored learning experiences that cater to the individual needs of students. This article explores how data science can enhance educational information systems, with a focus on adaptive learning, student performance prediction, and curriculum customization. Key themes include the role of machine learning models in predictive analytics, the integration of learning management systems (LMS) with data-driven insights, and the future potential of AI in fostering more efficient, inclusive, and personalized education. This paper aims to offer insights for educational stakeholders to leverage data science in optimizing learning outcomes and achieving educational goals.