Educational Big Data Analytics for Futuristic Smart Learning Using Deep Learning Techniques

This paper proposes a deep learning-based analytical framework for processing educational big data to enable personalized content recommendation, predictive analytics for student performance, and adaptive learning pathways across educational settings including K-12. The focus is primarily on the technical architecture and data analytics methodology rather than evaluation of AI systems or measurement of learning outcomes.

The goal is to use the massive amounts of data created by digital education systems to develop intelligent and adaptable learning environments that are particularly suited to each student’s requirements. The rapid digitization of education systems has led to the proliferation of educational big data, presenting unprecedented opportunities to reshape learning environments into intelligent, responsive spaces that adapt to the needs of individual learners. This paper explores the integration of adv

Source

Framework Categories

Tool Types

Tags