用大模型模拟用户测试网页设计，加速迭代优化。
UXAgent: An LLM Agent-Based Usability Testing Framework for Web Design
- 用大模型代理模拟数千名虚拟用户交互网页。
- 输出行为次数、思维访谈和视频记录等多维度结果。
- 适合需要快速验证设计的用户体验研究者。
可用性测试是用户体验研究人员评估网页设计的重要方法，但存在设计难迭代、招募参与者困难等挑战。受大语言模型模拟智能体（LLM-Agent）研究启发，我们设计了UXAgent系统，帮助研究人员在真实用户测试前自动评估和优化可用性测试方案。该系统包含一个大模型代理模块和通用浏览器连接器模块，可生成数千名模拟用户对目标网站进行测试。结果以定性（如代理思考过程访谈）、定量（如操作次数）和视频录制等形式呈现，供研究人员分析。五位用户体验研究者参与的启发式评估显示，参与者认可系统的创新性，但也对大模型代理辅助可用性研究的未来发展表示关注。
原文摘要 · Abstract (English)
Usability testing is a fundamental yet challenging (e.g., inflexible to iterate the study design flaws and hard to recruit study participants) research method for user experience (UX) researchers to evaluate a web design. Recent advances in Large Language Model-simulated Agent (LLM-Agent) research inspired us to design UXAgent to support UX researchers in evaluating and reiterating their usability testing study design before they conduct the real human subject study. Our system features an LLM-Agent module and a universal browser connector module so that UX researchers can automatically generate thousands of simulated users to test the target website. The results are shown in qualitative (e.g., interviewing how an agent thinks ), quantitative (e.g., # of actions), and video recording formats for UX researchers to analyze. Through a heuristic user evaluation with five UX researchers, participants praised the innovation of our system but also expressed concerns about the future of LLM Agent-assisted UX study.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。