A Quantum-Inspired Adaptive AI Tutor for Personalized Learning: A Quiz-Driven Knowledge Framework

Adaptive learning systems aims to prepare materials based on user needs, but many of them are still depend on strict rules and fixed content. To overcome the limitations of traditional online tutoring system, our proposed work introduces a Quantum-inspired tutor system. The purpose of this proposed system is to update each learner’s pace through quiz driven updates and its dynamically generated content. Learner understanding is modeled as a probability distribution over knowledge levels-conceptually similar to a quantum state. After each quiz, this distribution is updated, and several teaching strategies such as hints, examples, and explanations, are evaluated in parallel. One of them is selected using probabilistic sampling, echoing quantum-style collapse. This helps the system to balance exploration with targeted feedback. Multilingual contents, learner profiles and modular deployment are included in our work. Our work offers a scalable and interpretable foundation for intelligent tutoring system in software and programming education for learners.