@inproceedings{e5528366e1494eca8ec89a7e3aa57edb,
title = "EduX-RAG: Retrieval Augmented Generation Framework for Cross-Lingual Educational Chatbots",
abstract = "Developing cross-lingual educational chatbots presents significant challenges when handling dynamic language switching and content retrieval across different languages. We introduce EduX-RAG, a framework that integrates Retrieval-Augmented Generation (RAG) with prompt engineering to enable cross-lingual conversations in educational chatbots. EduX-RAG addresses the complexities of managing multilingual content and cross-lingual queries within a single interaction. We validate the effectiveness of EduX-RAG using 13 languages, including high- and low-resource languages and commonly confused language pairs. Deployed in a fully functional educational chatbot, EduX-RAG demonstrates strong cross-lingual retrieval capabilities with a high answer rate of 92\%, even when query and material languages differ. Overall, EduX-RAG delivers robust cross-lingual capabilities, achieving a Language Identification Accuracy of 90\%, Material Citation Accuracy of 99\%, and a Response Similarity Score of 70\%.",
keywords = "chatbot, education, LLM, prompt-engineering, RAG",
author = "Johanne Medina and Soon Gyo-Jung and Joni Salminen and Aldous, \{Kholoud Khalil\} and Jansen, \{Bernard J.\}",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025 ; Conference date: 25-11-2025 Through 28-11-2025",
year = "2025",
doi = "10.1109/FLLM67465.2025.11390969",
language = "English",
series = "2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "465--473",
editor = "Kai Erenli and Christian Guetl and Yaser Jararweh and Jim Jansen",
booktitle = "2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025",
address = "United States",
}