ARTIFICIAL INTELLIGENCE IN ENGLISH LANGUAGE EDUCATION: ADDRESSING VOCABULARY AND PRONUNCIATION CHALLENGES AMONG URBAN AND SEMIURBAN MARATHI-SPEAKING LEARNERS

Abstract

This study explores the potential of Artificial Intelligence (AI) technologies in addressing the persistent challenges of English vocabulary acquisition and pronunciation accuracy among Marathi-speaking learners in urban and semiurban regions of Maharashtra, India. Despite growing recognition of English as a vehicle for socio-economic mobility, learners in urban and semiurban areas often face structural disadvantages including limited access to qualified language instruction, restricted exposure to English in authentic contexts, and pedagogical methods that prioritize rote learning over communicative competence. These challenges are further compounded by linguistic discrepancies between Marathi and English, particularly in phonology and lexical structures. Through a critical analysis of existing AI-driven educational tools—such as NLP-based vocabulary trainers and speech-recognition-based pronunciation applications—this study investigates the role of personalized, adaptive technologies in supporting second language acquisition. The paper also engages with the ethical, infrastructural, and cultural implications of AI integration in language education, emphasizing the need for context-sensitive, accessible, and linguistically inclusive solutions. In doing so, it situates AI as both a pedagogical innovation and a necessary intervention to bridge the English language learning gap in India’s urban and semiurban educational landscape.