AI Tutors in the Indian Classroom: A Comparative Study of Language Learning through Adaptive Technology

Abstract

The integration of Artificial Intelligence (AI) tutors into Indian classrooms marks a transformative shift in language education, aligning with the vision of NEP 2020 for personalized and inclusive learning. This study comparatively examines the effectiveness of AI-based adaptive learning platforms in enhancing English language proficiency among middle school students in urban private and rural government schools. Using a mixed-method approach, data were collected from 200 learners through pre- and post-language assessments, engagement surveys, and teacher interviews conducted over a three-month intervention period. Results reveal significant improvement in reading comprehension and vocabulary acquisition in both groups, with private school learners demonstrating higher digital engagement, while government school students benefited more in foundational grammar skills. The study also highlights challenges such as limited infrastructure, teacher apprehension, and inconsistent internet access, which impede the scalability of AI-assisted learning in rural settings. Overall, the findings affirm that AI tutors can supplement traditional pedagogy by providing individualized feedback and adaptive pacing, though their success relies on teacher facilitation and contextual adaptation. This comparative evaluation underscores the potential of AI-driven language learning to bridge educational divides, provided equitable access and teacher training are ensured.