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.
- Question: How do students, teachers, and principals experience voice-based chatbots for English speaking practice in low-resource schools?
- Setting and data: Four low-resource schools in Delhi, involving students, teachers, and principals over a six-day period.
- Method: Field study combining observations and interviews
Spoken English proficiency is a powerful driver of economic mobility for low-income Indian youth, yet opportunities for spoken practice remain scarce in schools.
- In four low-resource schools in Delhi, voice-based chatbots for English practice were linked to notable gains in student speaking confidence.
- Students, teachers, and principals all showed high demand for voice-based conversational English practice.
- Students favored open-ended conversational practice with the chatbot, while school administrators emphasized curriculum-aligned assessment.
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