Collaboration with Conversational AI Assistants for UX Evaluation: Questions and How to Ask them (Voice vs. Text)
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Abstract (arXiv)
AI is promising in assisting UX evaluators with analyzing usability tests, but its judgments are typically presented as non-interactive visualizations. Evaluators may have questions about test recordings, but have no way of asking them. Interactive conversational assistants provide a Q&A dynamic that may improve analysis efficiency and evaluator autonomy. To understand the full range of analysis-related questions, we conducted a Wizard-of-Oz design probe study with 20 participants who interacted with simulated AI assistants via text or voice. We found that participants asked for five categories of information: user actions, user mental model, help from the AI assistant, product and task information, and user demographics. Those who used the text assistant asked more questions, but the question lengths were similar. The text assistant was perceived as significantly more efficient, but both were rated equally in satisfaction and trust. We also provide design considerations for future conversational AI assistants for UX evaluation.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 8 of its 76 references that are in the map. First posted on arXiv 7 Mar 2023.
Builds on
8 of 76 references.
References · 8
- 2017Localizing Moments in Video with Natural Languagecited by 663
- 2014Translating Videos to Natural Language Using Deep Recurrent Neural Networkscited by 95
- 2021Towards a Science of Human-AI Decision Making: A Survey of Empirical Studiescited by 86
- 2022Human-AI Collaboration via Conditional Delegation: A Case Study of Content Moderationcited by 67
- 2022Rethinking Explainability as a Dialogue: A Practitioner's Perspectivecited by 52
- 2019Discovering the Sweet Spot of Human-Computer Configurations: A Case Study in Information Extractioncited by 11
- 2022Understanding Questions that Arise When Working with Business Documentscited by 6
- 2022"Merging Results Is No Easy Task": An International Survey Study of Collaborative Data Analysis Practices Among UX Practitionerscited by 3
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Citing papers per year: 2025: 6.
6 papers.
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