PERSONALIZED ADAPTIVE TUTORING SYSTEM USING PYTHON

This project presents a Personalized Adaptive Tutoring System that enhances learning by integrating
Bayesian Knowledge Tracing (BKT) with Generative Artificial Intelligence to dynamically model and
adapt to each learner’s knowledge state. Unlike traditional e-learning platforms that follow a fixed curriculum,
the proposed system continuously analyzes learner performance to generate personalized lessons, quizzes, and
explanations in real time, ensuring improved engagement and knowledge retention. Developed as a web-based
platform using frameworks such as Django or Flask, the system ensures accessibility and scalability while
utilizing a structured knowledge graph to represent relationships between concepts and guide learning paths.
Additionally, a Retrieval-Augmented Generation (RAG) approach is employed to ground AI-generated content
in trusted educational sources, minimizing errors and enhancing reliability.