LLMs in EduGame: A Web-based Interactive English Learning Game

Abstract

This paper introduces the development of a web-based educational word-guessing game aimed at enhancing English language learning through interactive gameplay. Leveraging large language models (LLMs) to generate contextual hints, semantic scores, and word lists, the game fosters an engaging and dynamic learning environment. Building upon a previous metaverse-based implementation, this web approach improves accessibility, scalability, and deployment ease. The system architecture incorporates modern web technologies like React, Node.js, and Tailwind CSS to ensure a seamless user experience, while addressing key challenges such as LLM integration, real-time feedback, and progressive hinting mechanisms. Preliminary results suggest improved usability and broader adoption potential across diverse educational settings. This paper contributes to the field by demonstrating how web-based platforms, combined with LLMs, can offer scalable, effective, and gamified learning experiences, highlighting the potential for further advancements in language education technology.