Using Generative AI to Support Math Learning for Students with Disabilities

Presenter: Ramon Baez

Group Members: Patrick Anthony Reed, Jonathan Patrick Costigan

Faculty Sponsor: Hao Loi

School: Quinsigamond Community College

Research Area: Computer Science

Session: Poster Session 2, 11:30 AM - 12:15 PM, Auditorium, A57

ABSTRACT

Pre-algebra is a fundamental building block for numeracy skills, yet students with disabilities often encounter barriers in traditional learning environments. These challenges can stem from difficulties in processing visual information, limited access to adaptive resources, or the need for personalized instructional approaches. This research explores the integration of Generative AI as an assistive tool, utilizing retrieval-augmented generation (RAG) to enhance accessibility and improve math learning outcomes for students who benefit from auditory-based instruction.


The study focuses on leveraging Generative AI to develop a system that provides real-time feedback, delivers personal audio-based explanations, and breaks down equations step by step to aid students struggling with math comprehension. Additional features, such as Automatic Question Generation (AQG), help create tailored practice problems, in addition to text-to-speech functionality, further supporting students by making mathematical concepts more accessible. By incorporating these assistive technologies, this research aims to close learning gaps, enhance engagement, and build mathematical confidence among students with disabilities.

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