AI-ENHANCED MICROLEARNING IN LOW-RESOURCE EFL CLASSROOMS: A MIXED-METHODS STUDY FROM UZBEKISTAN

Abstract

The integration of artificial intelligence (AI) into English as a Foreign Language (EFL) education has attracted significant scholarly attention in recent years. However, limited research has explored its application in low-resource classroom contexts. This study investigates the effectiveness of combining AI tools with microlearning strategies in a vocational college in Uzbekistan. Using a mixed-methods design, data were collected from 25 students over four weeks through pre- and post-tests, classroom observations, and learner feedback. The results indicate statistically significant improvements in student engagement, vocabulary acquisition, and speaking confidence. The findings suggest that AI-enhanced microlearning provides a scalable and cost-effective solution for improving language learning outcomes in resource-constrained environments