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Computer Science > Software Engineering

Title: Generating User Experience Based on Personas with AI Assistants

Authors: 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.
Comments: 3 Pages, Accepted at the ICSE2024 Doctoral Symposium
Subjects: Software Engineering (cs.SE); Human-Computer Interaction (cs.HC)
DOI: 10.1145/3639478.3639810
Cite as: arXiv:2405.01051 [cs.SE]
  (or arXiv:2405.01051v1 [cs.SE] for this version)

Submission history

From: Yutan Huang [view email]
[v1] Thu, 2 May 2024 07:03:16 GMT (79kb)

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