Cited by 108Usability and User Interface DesignInnovative Human-Technology InteractionData Visualization and Analytics

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VISAR: A Human-AI Argumentative Writing Assistant with Visual Programming and Rapid Draft Prototyping

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Zhang, Zheng, Gao, Jie, Dhaliwal, Ranjodh Singh, Li, Toby Jia-Jun·2023·Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology

DOI 10.1145/3586183.3606800

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Abstract

In argumentative writing, writers must brainstorm hierarchical writing goals, ensure the persuasiveness of their arguments, and revise and organize their plans through drafting. Recent advances in large language models (LLMs) have made interactive text generation through a chat interface (e.g., ChatGPT) possible. However, this approach often neglects implicit writing context and user intent, lacks support for user control and autonomy, and provides limited assistance for sensemaking and revising writing plans. To address these challenges, we introduce VISAR, an AI-enabled writing assistant system designed to help writers brainstorm and revise hierarchical goals within their writing context, organize argument structures through synchronized text editing and visual programming, and enhance persuasiveness with argumentation spark recommendations. VISAR allows users to explore, experiment with, and validate their writing plans using automatic draft prototyping. A controlled lab study confirmed the usability and effectiveness of VISAR in facilitating the argumentative writing planning process.

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Authors: Zhang, Z., Gao, J., Dhaliwal, R. S., & Li, T. J.-J.
Affiliations: University of Notre Dame (US)
ORCID: Zhang, Zheng
Gao, Jie
Dhaliwal, Ranjodh Singh
Li, Toby Jia-Jun
Venue: Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology
Publisher: ACM
Published: 2023-10-29
Pages: 1-30
DOI: 10.1145/3586183.3606800
OpenAlex: W4385438855
Cited by: 108
References: 50
Citations by year: 2026: 30 · 2025: 54 · 2024: 21 · 2023: 3
FWCI: 25.06
Type: conference paper
Language: en
Open access: bronze
doi.org
Licence: www.acm.org/publications/policies/copyright_policy#Background (vor, 366 d)
Locations: ACM Symposium on User Interface Software and Technology (UIST) (publishedVersion)
arXiv (Cornell University) (submittedVersion, cc-by)
arXiv (Cornell University) (cc-by)
Funders: NSF (National Science Foundation) (CCF-2211428)
Topics: Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Data Visualization and Analytics
Keywords: argumentative writing, writing assistants, large language models, visual programming, writing planning, text editing, user autonomy, sensemaking

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VISAR: A Human-AI Argumentative Writing Assistant with Visual Programming and Rapid Draft Prototyping

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