Abstract: Personalized learning is important because every student learns at a different speed and has different goals. Many learners face difficulty while studying online due to a lack of guidance, unclear explanations, and no immediate feedback. To solve this problem, this project presents an LLM Powered Chatbot for Personalized Learning. The system works as a virtual tutor that interacts with learners through a web application. It allows users to enter a learner profile such as name, knowledge level, learning goal, and learning style. Based on these details, the chatbot generates customized responses that are easier to understand. The system also provides additional learning tools such as quiz generation and learning roadmap creation. Quizzes help learners test their knowledge, and roadmaps provide a structured plan for learning a topic step by step. The proposed system uses a locally hosted LLM (via Ollama) to generate answers, ensuring privacy and reducing dependency on cloud services. The results show that the chatbot improves the learning experience by giving clear explanations, supporting self-assessment, and helping learners follow a structured learning path.

Keywords: Large Language Model (LLM), Personalized Learning, Chatbot, Virtual Tutor, MCQ Generation, Learning Roadmap, Flask, Ollama, Education Technology


Downloads: PDF | DOI: 10.17148/IJARCCE.2026.151135

How to Cite:

[1] Vinay C, K Sharath, "LLM POWERED CHATBOT FOR PERSONALIZED LEARNING," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2026.151135

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