@inproceedings{5759827ffd4843a38af0852268d00b12,
title = "When to Give Feedback: Exploring Tradeoffs in the Timing of Design Feedback",
abstract = "Advances in AI have opened up the potential for creativity tools to computationally generate design feedback. In a future when designers can request feedback anytime on demand, how would the timing of these requests impact novices' creative learning processes? What are the tradeoffs of providing access to feedback throughout a design task (in-action) versus only providing feedback after (on-action)? We explored these questions through a Wizard-of-Oz study (N=20) using an interactive design probe, where participants could request feedback either throughout the design process or only after they complete a full draft. We found that in-action participants frequently request feedback, resulting in better improvements as indicated by a greater decrease in issues in their final design. However, we saw that in-action feedback can also risk users overly relying on feedback instead of engaging in more holistic self-evaluation. We discuss the implications of our insights on designing tools for creative feedback.",
keywords = "creativity support tools, empirical studies of design, feedback, human-AI collaboration, visual design",
author = "Jane, {L. E.} and Yen, {Yu Chun Grace} and Pan, {Isabelle Yan} and Grace Lin and Mingyi Li and Hyoungwook Jin and Mengyi Chen and Haijun Xia and Dow, {Steven P.}",
note = "Publisher Copyright: {\textcopyright} 2024 Owner/Author.; 16th Conference on Creativity and Cognition, C and C 2024 ; Conference date: 23-06-2024 Through 26-06-2024",
year = "2024",
month = jun,
day = "23",
doi = "10.1145/3635636.3656183",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "292--310",
booktitle = "C and C 2024 - Proceedings of the 16th Conference on Creativity and Cognition",
}