Innovative AI Gaming Strategies for Enhanced English Language Skills: A Mixed-Methods Study on Adaptive Game-Based Learning in EFL Contexts

Abstract

Through adaptive gaming environments that customize instruction and engagement, recent developments in artificial intelligence (AI) have revolutionized the study of the English language. To improve vocabulary retention, reading comprehension, and communicative competence among EFL learners, this study presents a novel hybrid framework that combines metacognitive feedback with AI-based adaptive gaming. We used a mixed-methods approach to evaluate both qualitative and quantitative learning experiences, using pre- and post-tests, in-game analytics, and semi-structured interviews. Adaptive feedback was found to be the primary factor driving skill growth, and results show notable gains in motivation, accuracy, fluency, and general engagement. The findings offer factual proof that AI-gamified settings can promote student identity and self-regulation while concurrently improving a variety of EFL abilities. Future research on long-term impacts, scalability, and ethical considerations in AI-driven language acquisition is suggested by these findings, which also have implications for teacher preparation, instructional design, and sustainable AI-assisted curricula.