Emily An Plcy380 0201 Fall 2025 10/3/2025
1. Pérez Perez, F. (2024). AI and accessibility in education. Consortium for School Networking & CAST. https://www.cosn.org/wp-content/uploads/2024/09/Blaschke_Report_2024_lfp .pdf
2. Every Learner Everywhere. (2024). Where AI meets accessibility: Advancing equity in digital learning. https://www.everylearnereverywhere.org/wp-content/uploads/Where-AI-Meets-Accessibility-Final.pdf
3. Gibson, R. (2024, September 10). The impact of AI in advancing accessibility for learners with disabilities. EDUCAUSE Review. https://er.educause.edu/articles/2024/9/the-impact-of-ai-in-advancing-accessi bility-for-learners-with-disabilities ‘
4. Pitts, G., Marcus, V., & Motamedi, S. (2025, June 3). Student perspectives on the benefits and risks of AI in education [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2505.02198 5. Pérez Perez, F. (2024). AI and accessibility in education. Consortium for School Networking. https://www.cosn.org/wp-content/uploads/2024/09/Blaschke_Report_2024_lfp .pdf
6. Nicholson-Benn, H. (2023, October 25). Generative AI and accessibility in education. National Centre for AI (Jisc). https://nationalcentreforai.jiscinvolve.org/wp/2023/10/25/generative-ai-and-acc essibility-in-education/
7. Zhang, W., Chinta, S. V., Wang, Z., Yin, Z., Hoang, N., Gonzalez, M., Le Quy, T., & Vidyadhari, S. (2024, July 26). FairAIED: Navigating fairness, bias, and ethics in educational AI applications [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2407.18745
8. University of Maryland’s Robert H. Smith School of Business. (2024, April 23). University of Maryland’s Smith School of Business launches Center for Artificial Intelligence in Business. PR Newswire. https://www.prnewswire.com/news-releases/university-of-marylands-smith-sch ool-of-business-launches-center-for-artificial-intelligence-in-business-3021252 80.html
9. UNESCO. (2025, September 25). What you need to know about AI and the right to education. https://www.unesco.org/en/articles/what-you-need-know-about-ai-and-right-ed ucation
10. Klimova, B., & Pikhart, M. (2025). Exploring the effects of artificial intelligence on student and academic well-being in higher education: A mini-review. Frontiers in Psychology, 16, 1498132. https://doi.org/10.3389/fpsyg.2025.1498132
11. Georgieva, M., Webb, J., Stuart, J., Bell, J., Crawford, S., & Ritter-Guth, B. (2025, June 24). AI ethical guidelines for higher education. EDUCAUSE Working Group. https://library.educause.edu/resources/2025/6/ai-ethical-guidelines
12. Barnard College CEP. (2024). Student guide to generative AI. https://cep.barnard.edu/student-guide-generative-ai
13. Cornell University Center for Teaching Innovation. (2024). AI and accessibility in teaching and learning. https://teaching.cornell.edu/generative-artificial-intelligence/ai-accessibility
14. Roschelle, J., & Weaver, D. J. (2024, February 20). How AI for education can address digital equity. Digital Promise. https://digitalpromise.org/2024/02/20/how-ai-for-education-can-address-digital-equity/
15. Perry, A. (2024). AI and the digital divide [Video]. TEDxWellington College HZ Youth. YouTube. https://www.youtube.com/watch?v=SsyEFSUyFBI 16. Association of American Colleges and Universities. (2025, January 22). Higher education leaders navigate AI disruption. https://www.aacu.org/newsroom/higher-education-leaders-navigate-ai-disrupti on
Reflection Prompts
What did you learn about your issue from this challenge?
I learned that the main problem with AI and accessibility in higher education isn’t just about students having computers or internet anymore. Now it’s more about making sure the AI tools schools use are fair and work with things like screen readers. Schools have to check that AI doesn’t have bias and that it fits with ideas like Universal Design for Learning so all students can use it.
What was successful or least successful? Why?
I found some good guides and policies from places like EDUCAUSE and Cornell that gave clear steps for using AI responsibly. That part was really helpful. But it was harder to find actual programs or studies that show how to handle problems like digital fatigue or stress from using too much tech. Those issues are important, but there aren’t many tested solutions yet.
What might you do differently?
Next time, I’d try to look for more real data, like comparing how different colleges handle AI rules and training. I’d also focus more on how teachers get trained, especially newer or non-tenured faculty, since if teachers don’t know how to use AI fairly, students can’t benefit from it either.
How will this challenge help you moving forward?
This helped me learn the words and ideas people use when talking about AI ethics and fairness. I can use this when I work on future projects so I remember to make things accessible and fair for everyone. It showed me that my tech skills can actually connect to social change.
What questions do you have after completing this challenge?
I wonder how students will know if the AI tools they’re using are actually fair or trustworthy. I also wonder what happens to schools that don’t have the money or resources to keep up with new AI tools, will their students fall behind compared to others?