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PromptCanvas: Composable Prompting Workspaces Using Dynamic Widgets for Exploration and Iteration in Creative Writing

Title data

Amin, Rifat Mehreen ; Kühle, Oliver Hans ; Buschek, Daniel ; Butz, Andreas:
PromptCanvas: Composable Prompting Workspaces Using Dynamic Widgets for Exploration and Iteration in Creative Writing.
In: ACM Transactions on Interactive Intelligent Systems. (5 June 2026) .
ISSN 2160-6455
DOI: https://doi.org/10.1145/3817049

Official URL: Volltext

Project information

Project title:
Project's official title
Project's id
Computergestützte Schreibwerkzeuge
525037874

Project financing: Deutsche Forschungsgemeinschaft

Abstract in another language

We introduce PromptCanvas, a UI concept that transforms prompting into a composable, widget-based experience on an infinite canvas. Users can generate, customize, and arrange interactive widgets that represent various facets of their text, offering greater control over AI-generated content. PromptCanvas allows to create widgets through system suggestions, user prompts, or manual input, providing a flexible environment tailored to individual needs. This enables deeper engagement with the creative process. In two lab studies, PromptCanvas outperformed both the conversational user interface (lab study 1) and the structured baseline, Wordcraft (lab study 2) on the Creativity Support Index. Participants found that it reduced cognitive load, while at the same time providing better performance. Qualitative feedback revealed that the visual organization of thoughts and easy iteration encouraged new perspectives and ideas. The field study (N=10) also confirmed these results, showcasing the potential of dynamic, customizable interfaces to improve collaborative writing with AI.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Dynamic UI; Prompting; LLM; human-AI co-creation; creativity support; metacognition; cognitive load; dynamic widgets; creative writing
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science IX > Chair Applied Computer Science - Univ.-Prof. Dr. Daniel Buschek
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 09 Jun 2026 05:52
Last Modified: 09 Jun 2026 05:52
URI: https://eref.uni-bayreuth.de/id/eprint/97886