IntelliLearn: An AI-Driven Framework for Personalized Education

Abstract: With the introduction of intelligent and adaptive personalized learning systems, artificial intelligence (AI) has completely changed the educational landscape. Due to variations in learning styles, speeds, and comprehension levels, the standardized teaching methods used in traditional educational institutions do not work for all students. AI makes personalization possible by using sophisticated algorithms to examine student behavior, performance, and preferences. The architecture, methods, advantages, difficulties, applications, and potential future research areas of AI-enabled personalized learning systems are all covered in this paper. To help educators make data-driven decisions, the system also incorporates predictive analytics, performance tracking dashboards, and real-time feedback mechanisms. By offering tailored guidance, IntelliLearn boosts academic performance, increases student motivation, and improves learning efficiency. IntelliLearn shows great promise for transforming contemporary education through intelligent personalization and scalable AI-powered learning environments, despite issues with algorithmic fairness, data privacy, and implementation complexity.

Keywords: Artificial Intelligence, Education, Personalized Learning, Adaptive Learning Systems, Machine Learning, EdTech.