AdaPT: Adaptive Lesson Plan Transformer for Cross-Regional and Differentiated Instruction
For teachers, this system addresses the gap in tools for adapting lesson plans to new contexts and student profiles, but the evaluation is small-scale and incremental.
AdaPT uses LLMs to adapt existing lesson plans for cross-regional and differentiated instruction, reducing teacher workload. User study with 9 teachers and expert evaluation with 3 specialists showed it supports teacher workflows and promotes educational equity.
Due to educational inequality, high-quality lesson plans often mismatch the needs of disparate educational contexts. Teachers typically modify existing lesson plans to fit new contexts, but current tools instead focus on generating content from scratch, creating additional workload. Moreover, a critical gap remains in supporting teachers to quickly adapt to new learning profiles. To bridge these gaps, we present AdaPT, a system leverages LLMs to support transformation of existing lesson plans for cross-regional and differentiated instruction. AdaPT features an interactive interface that allows teachers to input student profiles, offers structured lesson representation, provides explanations for lesson-plan transformations, automatically adapts lesson content for new contexts, and supports iterative, teacher-in-the-loop refinement. We evaluated AdaPT through a user study with 9 teachers and an expert evaluation with 3 specialists. Results show that AdaPT supports workflows of teachers and offers a promising pathway toward promoting educational equity.