PERSONALIZED LEARNING VIA AI EDUCATIONAL HUB

Abstract

Personalized learning has become a critical requirement in modern digital education environments where learners possess diverse interests, learning speeds, and knowledge backgrounds. Traditional e-learning platforms often follow a one-size-fits-all model that fails to address individual learner needs, resulting in low engagement, poor retention rates, and ineffective knowledge acquisition. This project proposes EduMorph AI, an intelligent educational hub designed to deliver adaptive and personalized learning experiences through artificial intelligence– driven recommendation techniques. The system integrates a hybrid recommendation mechanism that combines content-based filtering and collaborative filtering to recommend relevant courses and learning resources to users. Contentbased filtering utilizes Term Frequency–Inverse Document Frequency (TF-IDF) and cosine similarity to analyze course descriptions, topics, and metadata, while collaborative filtering employs Truncated Singular Value Decomposition (SVD) to analyze user–course interaction patterns and identify latent learning preferences. This hybrid strategy improves recommendation accuracy and effectively handles cold-start problems for new users or courses. Additionally, the platform incorporates Explainable Artificial Intelligence (XAI) to provide transparent reasoning behind each recommendation through interpretable explanations and reason codes, thereby improving user trust and learning motivation. The proposed system is implemented as a web-based educational platform that allows learners to access courses, receive personalized suggestions, track learning progress, and interact with a centralized educational hub. Experimental evaluation demonstrates that the hybrid recommendation model significantly improves recommendation relevance and learner engagement compared to conventional recommendation approaches. The EduMorph AI framework therefore provides an efficient, scalable, and learner-centric solution for next-generation digital education systems.