NeuroQuest: A Multi-Agent AI Framework for Adaptive Learning Through Intelligent Knowledge Creation

The increasing integration of artificial intelligence in education has led to the development of adaptive learning systems capable of enhancing knowledge delivery and comprehension. This paper proposes a multi-agent AI framework, NeuroQuest, advancing the domain by synthesizing real-time academic content into structured, multimodal formats, including PDFs, presentations, and podcasts. Unlike conventional AI-based tools primarily focusing on information retrieval, NeuroQuest employs a collaborative agentic approach using OpenAI’s Swarm framework to search, refine, and generate highly structured educational outputs. A user evaluation study comprising students and professors demonstrated high satisfaction levels in content clarity, readability, and multimodal accessibility. While users highlighted the platform’s strengths in organizing and synthesizing knowledge effectively, response speed emerged as a trade-off requiring further optimization. These findings establish NeuroQuest as a promising AI-driven academic tool that bridges the gap between information retrieval and structured knowledge synthesis.