Publication Type
Journal Article
Version
acceptedVersion
Publication Date
1-2026
Abstract
Design studies aim to develop visualization solutions for real-world problems across various application domains. Recently, the emergence of large language models (LLMs) has introduced new opportunities to enhance the design study process, providing capabilities such as creative problem-solving, data handling, and insightful analysis. However, despite their growing popularity, there remains a lack of systematic understanding of how LLMs can effectively assist researchers in visualization-specific design studies. In this paper, we conducted a rnulti-stage qualitative study to fill this gap, which involved 30 design study researchers from diverse backgrounds and expertise levels. Through in-depth interviews and carefully-designed questionnaires, we investigated strategies for utilizing LLMs, the challenges encountered, and the practices used to overcome them. We further compiled the roles that LLMs can play across different stages of the design study process. Our findings highlight practical implications to inform visualization practitioners, and also provide a framework for leveraging LLMs to facilitate the design study process in visualization research.
Keywords
Design Study; Large Language Models (LLMs); Qualitative Study; Visualization
Discipline
Graphics and Human Computer Interfaces
Research Areas
Intelligent Systems and Optimization
Areas of Excellence
Digital transformation
Publication
IEEE Transactions on Visualization and Computer Graphics
Volume
32
Issue
1
First Page
287
Last Page
297
ISSN
1077-2626
Identifier
10.1109/TVCG.2025.3634820
Publisher
Institute of Electrical and Electronics Engineers
Citation
RUAN, Shaolun; SHENG, Rui; WEN, Xiaolin; WANG, Jiachen; ZHANG, Tianyi; WANG, Yong; DWYER, Tim; and Jiannan LI.
Qualitative study for LLM-assisted design study process: Strategies, challenges, and roles. (2026). IEEE Transactions on Visualization and Computer Graphics. 32, (1), 287-297.
Available at: https://ink.library.smu.edu.sg/sis_research/11063
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/TVCG.2025.3634820