MultiUX : A Human-AI Collaborative Tool to Facilitate Multiple Usability Test Video Analyses

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Authors: Luyao Shen, Qing Shi, Emily Kuang, Linjie Qiu, Shixu Zhou, Pan Hui, Mingming Fan
Cited by: 1
References: 32

Abstract

Analyzing multiple usability videos is essential for identifying common problems and prioritizing them. While existing tools assist in identifying problems within single videos, the manual process of comparing and categorizing them remains time-consuming. Inspired by prior work that suggested a human-AI collaborative approach could improve the efficiency and completeness of analyzing single videos compared to either humans or AI alone, we extended this approach to investigate its effectiveness in analyzing multiple videos. We designed MultiUX to assist in strategically analyzing multiple videos by comparing and categorizing problems across them, and optimizing the analysis sequence through video recommendations. MultiUX was compared to a baseline in a between-subjects study involving 20 UX evaluators. Results showed that MultiUX supported analyzing more videos and identifying more common problems that were encountered by more users in a given time. Additionally, MultiUX guided participants to analyze multiple videos more strategically.

Fields of Study & Subjects

Usability and User Interface Design Persona Design and Applications Innovative Human-Technology Interaction

Publication details

Journal / source
International Journal of Human-Computer Interaction
Publisher
Informa UK Limited
Volume
42
Issue
17
Pages
13930–13955
Publication date
2 January 2026
Language
EN