Edutrack: AI based Personalized Learning Through Secure Analytics

To Provide individualized, adaptable learning environments, EduTrack, an AI-powered learning platform, seeks to revolutionize higher education. EduTrack incorporates state-of-the-art technology to enhance academic performance and student engagement. It is built on the MERN stack and employs Python-based microservices for machine learning. The platform features a hybrid video recommendation engine, adaptive learning pathways, real-time AI chatbot, and extensive performance statistics. This report highlights the research gaps that EduTrack fills, especially in the areas of scalability, personalization, and real-time learner support—areas where existing AI platforms often fail. Teachers and students have their own dashboards with EduTrack. While students may access study materials, performance tracking, and AI-driven assistance, teachers can post resources, give tests, and monitor their progress. A learning style detection engine that can provide content in a personalized manner, an AI chatbot that can answer questions in real time using Gemini or OpenAI, a hybrid video recommendation system that blends collaborative and content-based filtering, and a test performance analyzer that can adapt learning paths to each user's needs are some of its primary features. EduTrack uses algorithms like Random Forest, SVD, Decision Trees, and NLP to deliver a personalized learning experience. Learning analytics and digital identity systems can be combined to give teachers data-driven insights that raise student performance and engagement. By combining intelligent digital learning with traditional models, EduTrack aims to create a flexible, effective, and inclusive learning environment for a variety of educational needs.