# Are LLMs Useful in the Poorest Schools? TheTeacher.AI in Sierra Leone

arXiv: https://arxiv.org/abs/2310.02982 · HTML: https://mlsanity.com/paper/2310.02982/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Oct 2023.

## Built on by (most cited first, 4 of 4)

- [The GPT Surprise: Offering Large Language Model Chat in a Massive Coding Class Reduced Engagement but Increased Adopters Exam Performances](https://mlsanity.com/paper/2407.09975/) (2024)
- [Generative AI for Education (GAIED): Advances, Opportunities, and Challenges](https://mlsanity.com/paper/2402.01580/) (2024)
- [Large Language Models Meet User Interfaces: The Case of Provisioning Feedback](https://mlsanity.com/paper/2404.11072/) (2024)
- [Learning by Teaching: Engaging Students as Instructors of Large Language Models in Computer Science Education](https://mlsanity.com/paper/2508.05979/) (2025)

## Abstract (arXiv)

Education systems in developing countries have few resources to serve large, poor populations. How might generative AI integrate into classrooms? This paper introduces an AI chatbot designed to assist teachers in Sierra Leone with professional development to improve their instruction. We describe initial findings from early implementation across 122 schools and 193 teachers, and analyze its use with qualitative observations and by analyzing queries. Teachers use the system for lesson planning, classroom management, and subject matter. Usage is sustained over the school year, and a subset of teachers use the system more regularly. We draw conclusions from these findings about how generative AI systems can be integrated into school systems in low income countries.