Language Learning Through Games: A Computational Linguistics Perspective

Résumé

Game-based learning has emerged as a powerful approach for second language acquisition, especially for English as a Second Language (ESL) learners. This article explores how digital games, augmented by natural language processing (NLP) and speech technologies, can facilitate language learning in multilingual contexts. We adopt an interdisciplinary perspective bridging computational linguistics, game-based learning theory, and AI-driven language pedagogy. The study follows an IMRaD structure. In the Introduction, we review theoretical foundations of game-based language learning, highlighting engagement, motivation, and contextualized practice afforded by games. We also discuss how NLP techniques (e.g. speech recognition, chatbots) enable interactive, personalized language practice. The Methodology describes the design of an interactive ESL learning game incorporating NLP (for feedback and dialogue) and outlines a simulated experiment comparing it with traditional instruction. The Results (simulated for illustrative purposes) indicate that the game-based approach yields higher vocabulary retention, greater learner engagement, and improved oral proficiency than conventional methods, aligning with prior empirical findings. A sample comparison of outcomes is presented in a table. The Discussion interprets these results, noting the positive implications for computational linguistics (e.g., NLP-driven adaptive feedback), second language acquisition (e.g., increased meaningful interaction), and educational technology (e.g., scalable immersive learning tools). We also address challenges such as ensuring accurate language processing and integrating games into curricula. The article concludes that NLP-enhanced games offer an effective, engaging medium for ESL learning, meriting further research and development.