Developing a UXR Point of View for Cognitive Accessibility in Mobile Learning with Generative AI
This work addresses the problem of poorly defined requirements in mobile learning for learners with cognitive disabilities, offering an incremental improvement in the UXR process for this specific domain.
This study developed a UXR Point-of-View (PoV) framework, supported by LLM analysis, to improve requirements for mobile learning systems for learners with cognitive disabilities. It found that many usability and engagement issues stem from ambiguous requirements, and the resulting Cognitive Accessibility UXR Playbook provides a structured way to embed accessibility principles into measurable requirements.
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 Deployment (QFD); insight consolidation through the development of nine Cognitive Accessibility UXR Play Cards; and stakeholder-specific PoV articulation to support interdisciplinary communication. LLM-supported synthesis was integrated to assist in theme clustering, requirement refinement, and hypothesis formulation under human oversight. Findings suggest that many usability and engagement challenges in mobile learning originate from ambiguous or under-specified requirements rather than interface design alone. By embedding cognitive accessibility principles into measurable and technically traceable requirements, the proposed Cognitive Accessibility UXR Playbook provides a structured pathway for aligning theory, system architecture, and stakeholder strategy.