AdaPT uses LLMs to help teachers adapt existing lesson plans for diverse student needs and different educational contexts, aiming to promote educational equity.

In plain terms

High-quality lesson plans often don't fit different student groups or regions due to educational inequality. Teachers usually modify existing plans, but current AI tools focus on creating new content, which adds work. There's a critical need to quickly adapt lessons for diverse student learning profiles. The researchers developed AdaPT, a system that uses Large Language Models (LLMs) to transform existing lesson plans. LLMs are advanced AI programs that can understand and generate human-like text. AdaPT provides an interactive interface where teachers input student profiles, see structured lesson representations, get explanations for why changes are made, and can iteratively refine the adapted content. They evaluated AdaPT with teachers and experts, and results show that the system effectively supports teachers' workflows and helps customize lessons. This could help address educational inequality by making high-quality instruction more accessible.