Big Data Analytics for Personalized Learning on e-Learning PlatformsAbstract

Abstract

This research aims to explore the potential of big data in improving learning personalization on e-learning platforms. By analyzing data on student behavior, learning outcomes, and preferences, a big data-based e-learning system can provide recommendations for materials, learning paths, and interventions tailored to individual needs. The integration of machine learning and deep learning strengthens the system's ability to predict learning needs, provide adaptive recommendations, and detect learning problems early, which in turn increases student motivation, engagement, and learning outcomes.

Despite the many benefits gained, the implementation of big data in education also faces several challenges, including data privacy issues, data integration, infrastructure limitations, and high implementation costs. This research shows that despite these challenges, with the right policies and investments in infrastructure, the use of big data can improve the learning process, creating a more adaptive and relevant learning experience for every student.