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.
@article{arxiv.2405.01051,
title = {Generating User Experience Based on Personas with AI Assistants},
author = {Yutan Huang},
journal= {arXiv preprint arXiv:2405.01051},
year = {2024}
}
Comments
3 Pages, Accepted at the ICSE2024 Doctoral Symposium