AI Study Buddy: Personalized Learning Support through Artificial Intelligence
Abstract & Keywords
Artificial Intelligence (AI) is transforming modern education by providing intelligent and personalized learning experiences. This paper presents AI Study Buddy, an AI-powered educational assistant designed to improve students' learning through personalized tutoring, document-based question answering, intelligent quizzes, and conversational support. The system integrates Large Language Models (LLMs), Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG), vector databases, and speech technologies to provide accurate and context-aware responses. The proposed system enables students to upload study materials such as PDF documents, ask questions using text or voice, receive AI-generated explanations, summarize complex topics, generate quizzes, and monitor their learning progress. A modern web application built with React, TypeScript, Tailwind CSS, and FastAPI ensures an interactive and responsive user experience. The backend utilizes vector embeddings and semantic search to retrieve relevant educational content before generating AI responses. Experimental evaluation demonstrates that the AI Study Buddy significantly enhances learning efficiency, student engagement, and accessibility while reducing the time required to understand academic concepts. The system supports self-paced learning and can be extended for schools, colleges, and online education platforms. Keywords: Artificial Intelligence, Personalized Learning, AI Tutor, Large Language Models, Natural Language Processing, Retrieval-Augmented Generation, FastAPI, React, Vector Database, Educational Technology.
Author Affiliations
References Listing (3)
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