The Impact of Large Language Models on K-12 Education in Rural India: A Thematic Analysis of Student Volunteer's Perspectives
Journal:
arXiv
Published Date:
May 6, 2025
Abstract
AI-driven education, particularly Large Language Models (LLMs), has the
potential to address learning disparities in rural K-12 schools. However,
research on AI adoption in rural India remains limited, with existing studies
focusing primarily on urban settings. This study examines the perceptions of
volunteer teachers on AI integration in rural education, identifying key
challenges and opportunities. Through semi-structured interviews with 23
volunteer educators in Rajasthan and Delhi, we conducted a thematic analysis to
explore infrastructure constraints, teacher preparedness, and digital literacy
gaps. Findings indicate that while LLMs could enhance personalized learning and
reduce teacher workload, barriers such as poor connectivity, lack of AI
training, and parental skepticism hinder adoption. Despite concerns over
over-reliance and ethical risks, volunteers emphasize that AI should be seen as
a complementary tool rather than a replacement for traditional teaching. Given
the potential benefits, LLM-based tutors merit further exploration in rural
classrooms, with structured implementation and localized adaptations to ensure
accessibility and equity.
