International Journal of Science, Engineering and TechnologyAuthors: Shanvi Deep, Priyanshu Roshan, Rishu Raj, Shubham Anand, Mr. Sohan Lal
Abstract: The abundance of online educational resources often overwhelms self-paced learners due to lack of structured guidance. This paper proposes an AI-Driven Personalized Learning Path Recommendation System that generates a complete week-by-week learning roadmap from a single userentered topic. The system automatically decomposes topics into subtopics, arranges them logically, estimates study duration, recommends high-quality resources (videos, documentation, tutorials), and supports realtime progress tracking. Built using the MERN stack (MongoDB, Express.js, React.js, Node.js) and integrated with GroqAI for fast, intelligent generation, the platform delivers personalized, actionable learning plans. Evaluation through user studies and system testing demonstrates high relevance, logical coherence, clarity, and practical usefulness. The system significantly reduces planning effort and improves learning structure for students and self-learners.
