Generating User Experience Based on Personas with AI Assistants
Yutan Huang
Abstract
Traditional UX development methodologies focus on developing "one size fits all" solutions and lack the flexibility to cater to diverse user needs. In response, a growing interest has arisen in developing more dynamic UX frameworks. However, existing approaches often cannot personalise user experiences and adapt to user feedback in real-time. Therefore, my research introduces a novel approach of combining Large Language Models and personas, to address these limitations. The research is structured around three areas: (1) a critical review of existing adaptive UX practices and the potential for their automation; (2) an investigation into the role and effectiveness of personas in enhancing UX adaptability; and (3) the proposal of a theoretical framework that leverages LLM capabilities to create more dynamic and responsive UX designs and guidelines.