Voice-Based Chatbots for English Speaking Practice in Multilingual Low-Resource Indian Schools: A Multi-Stakeholder Study

TL;DR

This study explores deploying voice-based chatbots for English speaking practice in low-resource Indian schools, revealing high demand, improved student confidence, and design challenges for sustainable integration.

Contribution

It provides empirical insights into multi-stakeholder perspectives and offers design recommendations for voice-enabled educational chatbots in multilingual, low-resource settings.

Findings

High demand for voice chatbots among students, teachers, and principals

Notable improvements in students' speaking confidence

Identified tensions between open-ended practice and curriculum assessment

Abstract

Spoken English proficiency is a powerful driver of economic mobility for low-income Indian youth, yet opportunities for spoken practice remain scarce in schools. We investigate the deployment of a voice-based chatbot for English conversation practice across four low-resource schools in Delhi. Through a six-day field study combining observations and interviews, we captured the perspectives of students, teachers, and principals. Findings confirm high demand across all groups, with notable gains in student speaking confidence. Our multi-stakeholder analysis surfaced a tension in long-term adoption vision: students favored open-ended conversational practice, while administrators emphasized curriculum-aligned assessment. We offer design recommendations for voice-enabled chatbots in low-resource multilingual contexts, highlighting the need for more intelligible speech output for non-native learners, one-tap interactions with simplified interfaces, and actionable analytics for educators. Beyond language learning, our findings inform the co-design of future AI-based educational technologies that are socially sustainable within the complex ecosystem of low-resource schools.