Personalized learning path Generator

Abstract

Personalized learning has become an important approach in modern education to address the diverse learning needs, abilities, and goals of individual learners. Traditional learning systems often follow a uniform curriculum, which may not effectively support learners with different skill levels and learning speeds. This paper presents a Personalized Learning Path Generator that dynamically creates customized learning paths based on learner profiles, skill assessments, interests, and performance data. The proposed system analyzes user inputs to identify knowledge gaps and recommends suitable learning resources in a structured and adaptive manner. By continuously monitoring learner progress and updating recommendations, the system enhances learner engagement, improves learning efficiency, and supports goal-oriented education. The proposed approach demonstrates the potential of intelligent educational systems in delivering effective and learner-centric learning experiences.