The DOI matches its Crossref record, with a small difference in title or year.
Designing as reflective conversation with the materials of a design situation
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“Thus, researchers have voiced the need to support design space thinking in creativity support tools, stating various benefits of offering designers the ability to leverage an understanding of the design space in creative processes [7, 10, 23, 32, 55, 57].”
From Luminate: Structured Generation and Exploration of Design Space with Large Language Models for Human-AI Co-Creation (2024) · cites this paper as [55]
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Citations
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Suh, S., Chen, M., Min, B., Li, T. J.-J., & Xia, H. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642400 · Cited by 148
Mixed-Initiative Creative Interfaces
Deterding, S., Hook, J., Fiebrink, R., Gillies, M., Gow, J., Akten, M., Smith, G., Liapis, A., & Compton, K. (2017) · Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems · doi:10.1145/3027063.3027072 · Cited by 117
Zhang, C., Yao, C., Wu, J., Lin, W., Liu, L., Yan, G., & Ying, F. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3501914 · Cited by 114
Thinking with diagrams in architectural design
Do, E. Y.-L., & Gross, M. D. (2001) · Artificial Intelligence Review · doi:10.1023/a:1006661524497 · Cited by 109
When and How to Use AI in the Design Process? Implications for Human-AI Design Collaboration
Lee, S.-Y., Law, M., & Hoffman, G. (2025) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2024.2353451 · Cited by 97
Mixed-initiative content creation
Liapis, A., Smith, G., & Shaker, N. (2016) · Computational Synthesis and Creative Systems · doi:10.1007/978-3-319-42716-4_11 · Cited by 71
A Meta-analysis of the Effect of Multimedia Technology on Creative Performance
Liu, M., Pang, W., Guo, J., & Zhang, Y. (2022) · Education and Information Technologies · doi:10.1007/s10639-022-10981-1 · Cited by 25
Tech-Art-Theory: Improvisational Methods for HCI Learning and Teaching
Kang, L., & Jackson, S. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3449156 · Cited by 14
Varieties of inner speech and creative potential
de Rooij, A. (2022) · Imagination, Cognition and Personality · doi:10.1177/02762366211070999 · Cited by 14
Representational transformations: Using maps to write essays
Binks, A., Toniolo, A., & Nacenta, M. A. (2022) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2022.102851 · Cited by 12
“This explicit representation helps users discover new arguments and responses: seeing the arguments arranged visually provides feedback to the writer about what is there and what is missing, an example of representational talkback (Sch ¨ on, 1992; Yamamoto et al., 1998).”
BackgroundCeci n’est pas une chaise: Emerging practices in designer-AI collaboration
van der Burg, V., Akdag Salah, A., Chandrasegaran, S., & Lloyd, P. (2022) · Proceedings of DRS · doi:10.21606/drs.2022.653 · Cited by 10
Metadata
- Authors
- Schön, D. A.
- Venue
- Knowledge-Based Systems
- Publisher
- Elsevier BV
- Published
- 1992-03
- Volume
- 5
- Issue
- 1
- Pages
- 3-14
- ISSN
- 0950-7051
- Cited by
- 368
- References
- 0
- Language
- en
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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