Advancing Educational Accessibility: The LangChain LLM Chatbot's Impact on Multimedia Syllabus-Based Learning

Abstract

A chatbot is a computer program using artificial intelligence to simulate conversation with users, providing information or performing tasks in natural language. Traditional chatbots in education help navigate course details, but often lack subtle understanding and context. The Large Language Model (LLM) model, computationally intensive and slower than Generative Pre-trained Transformer, generates answers solely from course material, limiting responses to user input. In our work we have proposed a chat history view option, a multimodal syllabus upload capability, improved querying capabilities, and the ability to recall past responses for enhanced performance. Our chatbot leverages the powerful LangChain LLM to overcome these limitations. Our research uses Lang Chain’s LLM to power AI-driven educational chatbots, analyzing course materials to tailor responses for personalized student learning. This paper delves into the design, architecture, and evaluation of this chatbot, showcasing its impact on engagement, comprehension, and accessibility, and ultimately paving the way for a future of universally inclusive education. Evaluations show our LLM-powered approach achieves high accuracy, generating clear, precise answers, exceeding the abilities of traditional educational chatbots.