GUIComp: A GUI Design Assistant with Real-Time, Multi-Faceted Feedback
Not on the map. Why?
Abstract (arXiv)
Users may face challenges while designing graphical user interfaces, due to a lack of relevant experience and guidance. This paper aims to investigate the issues that users with no experience face during the design process, and how to resolve them. To this end, we conducted semi-structured interviews, based on which we built a GUI prototyping assistance tool called GUIComp. This tool can be connected to GUI design software as an extension, and it provides real-time, multi-faceted feedback on a user's current design. Additionally, we conducted two user studies, in which we asked participants to create mobile GUIs with or without GUIComp, and requested online workers to assess the created GUIs. The experimental results show that GUIComp facilitated iterative design and the participants with GUIComp had better a user experience and produced more acceptable designs than those who did not.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Jan 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2022: 1; 2023: 2; 2024: 3; 2025: 2; 2026: 3.
11 papers.
- 2024UICrit: Enhancing Automated Design Evaluation with a UICritique Datasetcited by 21
- 2024UIClip: A Data-driven Model for Assessing User Interface Designcited by 14
- 2022Predicting and Explaining Mobile UI Tappability with Vision Modeling and Saliency Analysiscited by 9
- 2025Generative Interfaces for Language Modelscited by 5
- 2025Synthetic Heuristic Evaluation: A Comparison between AI- and Human-Powered Usability Evaluationcited by 2
- 2023Reimagining Application User Interface (UI) Design using Deep Learning Methods: Challenges and Opportunitiescited by 1
- 2023Pairwise GUI Dataset Construction Between Android Phones and Tabletscited by 1
- 2026From Answer Givers to Design Mentors: Guiding LLMs with the Cognitive Apprenticeship Modelcited by 1
- 2024From Metrics to Meaning: Time to Rethink Evaluation in Human-AI Collaborative Designcited by 0
- 2026LikeThis! Empowering App Users to Submit UI Improvement Suggestions Instead of Complaintscited by 0
- 2026Design Theater: Evaluating the Gap Between User-Facing Design Reasoning and Implementation in Generative UI Toolscited by 0
- 2026Design Theater: Evaluating the Gap Between User-Facing Design Reasoning and Implementation in Generative UI Tools24 Jul 2026
- 2026LikeThis! Empowering App Users to Submit UI Improvement Suggestions Instead of Complaints4 Mar 2026
- 2026From Answer Givers to Design Mentors: Guiding LLMs with the Cognitive Apprenticeship Model27 Jan 2026
- 2025Generative Interfaces for Language Models26 Aug 2025
- 2025Synthetic Heuristic Evaluation: A Comparison between AI- and Human-Powered Usability Evaluation3 Jul 2025
- 2024UICrit: Enhancing Automated Design Evaluation with a UICritique Dataset11 Jul 2024
- 2024UIClip: A Data-driven Model for Assessing User Interface Design18 Apr 2024
- 2024From Metrics to Meaning: Time to Rethink Evaluation in Human-AI Collaborative Design30 Jan 2024
- 2023Pairwise GUI Dataset Construction Between Android Phones and Tablets7 Oct 2023
- 2023Reimagining Application User Interface (UI) Design using Deep Learning Methods: Challenges and Opportunities23 Mar 2023
- 2022Predicting and Explaining Mobile UI Tappability with Vision Modeling and Saliency Analysis5 Apr 2022