Qualitative Study for LLM-assisted Design Study Process: Strategies, Challenges, and Roles

TL;DR

This study explores how large language models can assist visualization researchers in design studies, identifying strategies, challenges, roles, and practical implications through qualitative analysis of expert interviews.

Contribution

It provides a systematic understanding of LLM-assisted design study processes and proposes a framework for effective integration in visualization research.

Findings

Identified key strategies for using LLMs in design studies

Highlighted common challenges and solutions in LLM integration

Outlined roles of LLMs across different design study stages

Abstract

Design studies aim to create visualization solutions for real-world problems of different 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 multi-stage qualitative study to fill this gap, involving 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 and summarized the roles that LLMs can play across different stages of the design study process. Our findings highlight practical implications to inform visualization practitioners, and provide a framework for leveraging LLMs to enhance the design study process in visualization research.