LAUSR

Globally, students with visual disabilities face significant challenges in accessing and learning mathematics, particularly when solving mathematical equations and expressions. These challenges result from the inherent complexity and abstract nature of mathematical content. Additionally, braille codes are inconsistent across regions, collaborative math platforms are unavailable, and accessible mathematics literature is scarce. Assistive technologies, artificial intelligence, and educational resources have improved accessibility for students with visual disabilities. However, these students still face significant challenges when navigating, exploring, and solving mathematical equations and expressions. These challenges contribute underrepresentation of these students in the science, technology, engineering, and mathematics disciplines. To address these limitations, this study proposes a novel solution to assist students with visual disabilities in learning mathematical expressions interactively with flexible navigation. This study proposes an algorithmic approach for converting input mathematical expressions into content MathML expressions, parsing those expressions into semantic elements, and then providing a structural overview of these expressions. Moreover, interactive keyboard keys were designed to provide flexible navigation through speech feedback, so that users can interact more effectively with expressions. Python libraries were utilized to implement the proposed solution. An empirical evaluation was conducted by 15 instructors and 94 students with visual disabilities and validated by Cronbach’s alpha. Results indicate that the proposed solution improved mathematics accessibility and learning. This study lays a foundation for future research on the integration of advanced technologies in special education.