The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Filtering and Informing the Design Space: Towards Design-Space Thinking
Abstract
Building on the concept “prototypes that filter the design space,” we establish how other kinds of design artifacts and activities (e.g., sketching, tests, concept posters, metaphors, design tools) are equally critical in filtering the design space. We also suggest a parallel term, “informing the design space,” to define how design artifacts and activities expand the design space. We focus on a 16-month, full-scale media architecture design project and zero in on seven of its component events, and use design-space schemas to shed light on the dynamics of the design space with respect to informing and filtering the design space. Our concluding contribution is to propose design-space thinking as a sub-discipline of design research. We argue that this research perspective serves to address the creative aspects of the design process, the generative potential of design-space thinking, and the tools that support design-space thinking and research.
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“the capacity to instantly produce tens to hundreds of outputs is especially conducive to assisting users in developing a comprehensive understanding of the design space [32, 39]”
From Luminate: Structured Generation and Exploration of Design Space with Large Language Models for Human-AI Co-Creation (2024) · cites this paper as [32]
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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 [32]
In the citing paper
“Design spaces have commonly been represented with Cartesian spaces where possible variations reside within the dimensions of a design, and variations reflect different values on those dimensions [7, 32, 45, 57].”
From Luminate: Structured Generation and Exploration of Design Space with Large Language Models for Human-AI Co-Creation (2024) · cites this paper as [32]
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Cited by
Sorted by citations
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
IdeationWeb: Tracking the Evolution of Design Ideas in Human-AI Co-Creation
Shen, H., Shen, L., Wu, W., & Zhang, K. (2025) · Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713375 · Cited by 24
Metadata
- Authors
- Halskov, K., & Lundqvist, C.
- Affiliations
- Digital Design and Information Studies, Aarhus University, Denmark
- ORCID
- Halskov, Kim
- Venue
- ACM Transactions on Computer-Human Interaction
- Published
- 2021-01-20
- Volume
- 28
- Issue
- 1
- Pages
- 1-28
- ISSN
- 1073-0516
- 1557-7325
- Cited by
- 38
- References
- 2
- Language
- en
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