ADAPTIVE INTELLIGENT LEARNING SYSTEM USING LARGE LANGUAGE MODELS AND LANGCHAIN

Abstract: The rapid evolution of Artificial Intelligence (AI) has revolutionized educational technology, enabling personalized and adaptive learning experiences. This System proposes the development of an Intelligent Educational Agent (IEA) that integrates OpenAI’s GPT-4.1 Turbo through the LangChain framework and employs Retrieval- Augmented Generation (RAG) to deliver contextually rich, dynamic, and learner-centric educational support. Unlike traditional chatbots that depend on single embeddings and static datasets, the proposed IEA adopts a multi-embedding hybrid retrieval mechanism, facilitating semantic understanding across diverse educational resources, including textbooks, lecture materials, and research notes.
A student difficulty tracking module is incorporated to monitor learner performance through metrics such as response accuracy, completion time, and hint usage. These insights enable the agent to classify learners into beginner, intermediate, and advanced categories, generating personalized responses, adaptive quizzes, and progressive content suited to each learner’s cognitive level. Furthermore, the system employs feedback-driven continuous improvement, refining retrieval and content generation strategies based on user interaction patterns.
Experimental evaluations demonstrate that the IEA enhances contextual understanding, engagement, and learning retention by offering customized learning pathways and real-time adaptation. This System establishes a novel framework for multi-source, AI-driven educational assistance, bridging the gap between static content delivery and intelligent, adaptive pedagogy. Future extensions may include multimodal learning integration, multilingual capabilities, and advanced pedagogical modelling, marking a significant contribution to the next generation of intelligent educational technologies.

Keywords: Intelligent Educational Agent, Lang Chain, Large Language Models, Retrieval-Augmented Generation (RAG), GPT-4.1Turbo, Adaptive Learning, Personalized Education, Hybrid Retrieval, Semantic Search, Multi- Embedding.