Assessing Large Language Models in Children's Education in Low-Resource Settings: Opportunities and Challenges

Ibomoiye Domor Mienye, George Rabeshi Obaido, Thabisile Obi

Published: 06 Mar 2025, Last Modified: 12 Apr 2025ICLR 2025 Workshop AI4CHL PosterEveryoneRevisionsBibTeXCC BY 4.0
Track: Tiny paper
Keywords: Children's Education, LLMs, Low-Resource Learning, Ethical AI in Education
TL;DR: This paper explores the role of large language models (LLMs) in children's education in low-resource settings, highlighting their opportunities, challenges, and proposed frameworks for ethical and inclusive AI deployment.
Abstract: Large language models (LLMs) offer scalable and adaptive learning solutions for children's education in low-resource settings. While they enhance engagement and accessibility, challenges such as bias, privacy risks, and infrastructure limitations remain. This paper reviews and highlights key issues and proposes strategies to ensure equitable and effective AI-driven education.
Submission Number: 29