Context-Aware AI for Real-Time Content and Quiz Recommendations in Student Learning Environments
Agon Memeti, Ibrahim Neziri, Neshat Ajruli, Krenar Huseini, Asri Nuhi, Aqim Iljazi · 2025
The paper presents a context-aware AI system designed to dynamically recommend course material and generate quizzes in real-time, based on the individual student interaction and performance. The proposed model integrates generative AI capability with a previously developed Learning Management System (LMS), using Blazor components for seamless user interface presentation and real-time system updates. Through the processing of contextual data such as enrolled courses, student activity, history, and participation patterns, the system acquires insight to generate intelligent content blocks and short quizzes tailored to the immediate needs of the learner. The artificial intelligence engine, which is built on large language models, is infused through guided questions that solicit recommended topics and related quiz items. Upon login by students, the dashboard includes an interactive "Subject explanation" panel, allowing real-time provision of AI-generated resources and quizzes, visually integrated using Blazor’s conditional rendering feature. This article describes the system design, implementation sequence, and deployment at the University of Tetova, illustrating how cognitive-aware AI can engage learners more and facilitate adaptive learning routes through autonomous, scalable learning augmentation.