Using Universal Design for Learning and Artificial Intelligence to Support Students with Disabilities

Abstract

This paper explores whether Universal Design for Learning (UDL) can be combined with Artificial Intelligence (AI) to create a more inclusive pedagogy for students with disabilities. Two graduate level courses in Student Affairs with a combined enrollment of 37 students completed an AI-based assignment and provided survey data and artifacts of learning to assess student perception and academic impact. The sample reported higher than average rates of disabilities with over 30% reporting a learning disability and 43% reporting qualifying for disability services. The assignment was designed with principles of UDL to specifically consider the unique needs of students with learning disabilities, especially those with difficulty reading or writing, for whom AI may be particularly helpful. Therefore, following UDL standards, students were given multiple options to demonstrate learning by critiquing an AI output by rewriting the output, commenting on the output, or providing a video critique of the output. Interestingly, students were roughly evenly distributed in their selection of the assessment options, suggesting that the options are well-utilized and may be related to the high representation of disability in the classroom sample. Students reported overall satisfaction with an AI-based assignment with UDL options built-in.