UXCascade: Scalable Usability Testing with Simulated User Agents
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866911392131448832 |
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| author | Holter, Steffen Koh, Eunyee Dogan, Mustafa Doga Chan, Gromit Yeuk-Yin |
| author_facet | Holter, Steffen Koh, Eunyee Dogan, Mustafa Doga Chan, Gromit Yeuk-Yin |
| contents | Simulated user agents are increasingly used in usability testing to support fast, iterative UX workflows, as they generate rich data such as action logs and think-aloud reasoning, but the unstructured nature of this output often obscures actionable insights. We present UXCascade, an interactive tool for extracting, aggregating, and presenting agent-generated usability feedback at scale. Our core contribution is a multi-level analysis workflow that (1) highlights patterns across persona traits, goals, and outcomes, (2) links agent reasoning to specific issues, and (3) supports actionable design improvements. UXCascade operationalizes this approach by listing agent goals, traits, and issues in a structured overview. Practitioners can explore detailed reasoning traces and annotated views, propose interface edits, and assess their impact across personas. This enables a top-down, exploration-driven analysis from patterns to concrete UX interventions. A user study with eight UX professionals demonstrates that UXCascade integrates into existing workflows, enabling iterative feedback during early-stage interface development. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_15777 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | UXCascade: Scalable Usability Testing with Simulated User Agents Holter, Steffen Koh, Eunyee Dogan, Mustafa Doga Chan, Gromit Yeuk-Yin Human-Computer Interaction Simulated user agents are increasingly used in usability testing to support fast, iterative UX workflows, as they generate rich data such as action logs and think-aloud reasoning, but the unstructured nature of this output often obscures actionable insights. We present UXCascade, an interactive tool for extracting, aggregating, and presenting agent-generated usability feedback at scale. Our core contribution is a multi-level analysis workflow that (1) highlights patterns across persona traits, goals, and outcomes, (2) links agent reasoning to specific issues, and (3) supports actionable design improvements. UXCascade operationalizes this approach by listing agent goals, traits, and issues in a structured overview. Practitioners can explore detailed reasoning traces and annotated views, propose interface edits, and assess their impact across personas. This enables a top-down, exploration-driven analysis from patterns to concrete UX interventions. A user study with eight UX professionals demonstrates that UXCascade integrates into existing workflows, enabling iterative feedback during early-stage interface development. |
| title | UXCascade: Scalable Usability Testing with Simulated User Agents |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2601.15777 |