{"id":9345,"date":"2025-12-08T08:00:34","date_gmt":"2025-12-08T14:00:34","guid":{"rendered":"https:\/\/www.everylearnereverywhere.org\/?p=9345"},"modified":"2025-12-08T08:26:36","modified_gmt":"2025-12-08T14:26:36","slug":"implementing-ai-for-every-learner-considerations-for-accessibility-in-higher-education","status":"publish","type":"post","link":"https:\/\/www.everylearnereverywhere.org\/es\/blog\/implementing-ai-for-every-learner-considerations-for-accessibility-in-higher-education\/","title":{"rendered":"Implementing AI for Every Learner: Considerations for Accessibility in Higher Education"},"content":{"rendered":"

With AI tools increasingly shaping everything from assignment design to student services, institutions face a pivotal moment: Adopt AI in ways that expand access or repeat historic patterns of exclusion for the 3.5 million U.S. college students who live with a disability.<\/p>\n

That AI is rapidly evolving is a common observation, but it\u2019s important to remember, says Rolando M\u00e9ndez, Director of Education of Teach Access, that the field of accessibility in higher education is also \u201cactively updating and advancing.\u201d<\/p>\n

Keeping up with the intersection of those two domains was the topic of Making AI Work for All: Enhancing Accessibility for Students in Higher Education<\/a>, a webinar featuring M\u00e9ndez presented October 15, 2025 by Every Learner Everywhere, Teach Access, and the Northwest Higher Education Accessibility Technology Group (NWHeat). M\u00e9ndez outlined definitions of disability, ableism, and accessibility, then highlighted examples of how AI can both introduce barriers and expand access. The presentation ranged from the practical \u2014 including a framework for practical prompt design \u2014 to institutional considerations of policy and personnel.<\/p>\n

M\u00e9ndez was one of the contributors to Where AI Meets Accessibility: Considerations for Higher Education<\/a>, a toolkit published by Every Learner and Teach Access earlier in 2025, and many of the ideas he presented are also outlined there.<\/p>\n

Built-in accessibility<\/h2>\n

About 1.3 billion people globally or one in four U.S. adults live with a disability. M\u00e9ndez emphasized that disability is a spectrum, and can be visible, invisible, permanent, temporary, or situational.<\/p>\n

But oftentimes, technology treats people with disabilities as a problem to \u201cfix\u201d rather than a design challenge to meet. When people with disabilities are excluded from AI development or underrepresented in training data, bias can enter systems invisibly. This results in AI tools that misinterpret language, generate inaccessible materials, or perpetuate harmful stereotypes.<\/p>\n

\u201cOne size does not fit all,\u201d M\u00e9ndez said. \u201cWhat is accessible to one person with a disability is not necessarily accessible to someone else with the same or a different disability.\u201d<\/p>\n

To make AI and other digital learning tools inclusive, accessibility must be built in. That means involving people with disabilities in the design and testing processes that shape their use in education. When educators and developers collaborate with students and professionals with disabilities, they create systems that reflect real-world diversity and serve a broader range of learners.<\/p>\n

AI as a tool for access<\/h2>\n

Despite the risk of creating more barriers to inclusion, M\u00e9ndez said, AI holds tremendous promise for improving accessibility in higher education. With thoughtful use, it can support students with disabilities: For example:<\/p>\n