AI-Driven LMS Personalization: A Blazor-Based Framework

The goal of this paper is to look at how we can use AI to personalize learning platforms in a way that improves the experience for students. Rather than a one-size-fits-all approach, the idea is to use machine learning to tailor content and recommendations to each individual user. The machine learning algorithms in the proposed framework will dynamically adapt to the changes pertaining to the learning experience based on the individual user's interactions. So as you interact with the system, it gets smarter about what kinds of things you might be interested in or find helpful and the specific proposal involves building this type of personalized AI into a learning management system using Blazor components. Blazor allows content to be dynamically updated in real-time, which suits this personalized approach. We present a practical use case of the University of Tetova. By this study, we would like to underline the potential of AI-driven personalization in LMS environments and the advantages of using Blazor for real-time, modular system integration.