Edu-Vision: An AI-Powered Multimodal Educational Assistant for Intelligent Content Understanding and Personalized Tutoring

Abstract: Edu-Vision is an advanced AI-powered educational assistant designed to understand, interpret, and teach educational content from multiple formats including PDF files, Word documents, PowerPoint presentations, images, diagrams, and scanned notes. The system integrates large language models, optical character recognition, vision-language models, and real-time internet retrieval to deliver explanations, summaries, quizzes, flashcards, study plans, and personalized tutoring support. The implementation combines file-specific extraction modules, tutoring pipelines powered by language models, and diagram analysis using a vision encoder-decoder model. The platform also includes context- aware document indexing, page-by-page explanation, accessibility-oriented features such as braille-ready output and audio-friendly quizzes, and adaptive tutoring based on subject and learner needs. By following Universal Design for Learning principles, Edu-Vision improves inclusivity and supports flexible, student-centered learning. The project demonstrates how multimodal AI can transform educational assistance into an interactive, accessible, and personalized learning experience.

Keywords: Multimodal Learning, Educational Assistant, OCR, Large Language Models, Vision-Language Model, Personalized Tutoring, Universal Design for Learning.