Develop an AI-Based Multilingual Tutor/Chatbot for Student Interaction

Abstract

The rapid growth of Artificial Intelligence (AI) and Natural Language Processing (NLP) has created new opportunities for developing intelligent and inclusive educational systems. However, language barriers continue to limit access to digital learning resources, particularly for students who are more comfortable learning in regional and native languages. This research proposes the development of an AI-based multilingual tutor/chatbot for personalized student interaction and academic support. The proposed system integrates multilingual Natural Language Processing, Machine Translation, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and speech technologies to enable students to interact with the tutor using English and Indian regional languages, with a primary focus on Kannada-English interaction.

The proposed tutor will be grounded in curriculum-specific resources such as syllabi, textbooks, lecture notes, question banks, and other approved educational materials. Student queries will be processed through language identification, semantic understanding, information retrieval, and AI-based response generation to provide contextually relevant and curriculum-aligned explanations. The system will additionally support personalized learning by identifying students' learning requirements, generating topic-wise explanations, practice questions and quizzes, and providing immediate feedback. Voice-based interaction through speech-to-text and text-to-speech technologies will further improve accessibility for students who prefer spoken communication. The proposed framework aims to address challenges associated with low-resource Indian languages, code-mixed language interaction, contextual understanding, and hallucination in generative AI-based educational systems. The effectiveness of the system will be evaluated using NLP performance measures, response relevance, translation quality, question-answering accuracy, user satisfaction, and student learning outcomes. The proposed multilingual AI tutor is expected to provide an accessible, scalable, and personalized learning environment and contribute towards inclusive, mother-tongue-supported and technology-enabled higher education.