Developing a UXR Point of View for Cognitive Accessibility in Mobile Learning with Generative AI
arXiv:2605.31149v1 Announce Type: cross Abstract: This study investigates how UX research (UXR) principles, combined with Large Language Model (LLM)-supported analysis, can be used to improve the quality of requirements for mobile learning systems designed for learners with cognitive disabilities. Using the UXR Point-of-View (PoV) pyramid as a methodological framework, the study progressed through four stages: foundational structuring of psychological, behavioral, and design layers; structured validation using the DeLone and McLean Information Systems Success Model and Quality Function Deploym
The proliferation of generative AI and the increasing focus on inclusive design in education make the integration of UXR and LLMs for accessibility in mobile learning particularly relevant.
This research provides a framework for leveraging AI to improve educational outcomes for cognitively impaired learners, addressing a critical need for accessible technology solutions.
The methods for developing accessible educational software will evolve to incorporate AI-driven UXR, potentially leading to more effective and personalized learning experiences for disabled individuals.
- · Learners with cognitive disabilities
- · Ed-tech companies focused on accessibility
- · UX Researchers
- · Generative AI developers
- · Traditional, one-size-fits-all educational software
- · Organizations slow to adopt AI-driven UXR
Improved design and functionality of mobile learning systems for individuals with cognitive disabilities.
Increased participation and academic success rates for cognitively disabled learners in digital educational environments.
Broader societal integration and economic opportunities for individuals with cognitive disabilities, fostered by more accessible education and training.
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