Testing the robustness and performance of spatially consistent interfaces
Open accessAbstract
Relative spatial consistency - that is, the stable arrangement of objects in a 2D presentation - provides several benefits for interactive interfaces. Spatial consistency allows users to develop memory of object locations, reducing the time needed for visual search, and because spatial memory is long lasting and has a large capacity these performance benefits are enduring and scalable. This suggests that spatial consistency could be used as a fundamental principle for the design of interfaces. However, there are many display situations where the standard presentation is altered in some way: e.g., a window is moved to a new location, scaled, or rotated on a mobile or tabletop display. It is not known whether the benefits of spatial organization are robust to these common kinds of view transformation. To assess these effects, we tested user performance with a spatial interface that had been transformed in several ways, including different degrees of translation, rotation, scaling, and perspective change. We found that performance was not strongly affected by the changes, except in the case of large rotations. To demonstrate the value of spatial consistency over existing mechanisms for dealing with view changes, we compared user performance with a spatially-stable presentation (using scaling) with that of a 'reflowing' presentation (widely used in current interfaces). This study showed that spatial stability with scaling dramatically outperforms reflowing. This research provides new evidence of spatial consistency's value in interface design: it is robust to the view transformations that occur in typical environments, and it provides substantial performance advantages over traditional methods.
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Scarr et al. found that users were able to quickly locate items in spatially stable views that had undergone a uniform spatial transformation.
“Scarr et al. [2013] examined the robustness of users' spatial memory to various forms of spatial transformation (including scaling) and found that users were able to quickly locate items in spatially stable views that had undergone a uniform spatial transformation.”
From Supporting Novice to Expert Transitions in User Interfaces (2015) · cites this paper as Scarr et al. [2013]
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Self-citation
- Authors
- Scarr, J., Cockburn, A., Gutwin, C., & Malacria, S.
- Affiliations
- University of Canterbury (NZ)
- University of Saskatchewan (CA)
- Venue
- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2013-04-27
- Pages
- 3139-3148
- OpenAlex
- W2105123831
- Cited by
- 50
- References
- 35
- Citations by year
- 2026: 6 · 2025: 2 · 2024: 4 · 2023: 2 · 2022: 1 · 2021: 3 · 2020: 6 · 2019: 1 · 2018: 9 · 2017: 3 · 2016: 2 · 2015: 5 · 2014: 4 · 2013: 1 · 2012: 1
- FWCI
- 3.16
- Type
- conference paper
- Language
- en
- Open access
- green
- inria.hal.science
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- HAL (submittedVersion, other-oa)
- Libraries and Cultural Resources (University of Calgary) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Interactive and Immersive Displays
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Data Visualization and Analytics
- Keywords
- spatial consistency, spatial memory, visual search, view transformation, scaling, rotation, perspective shift, interface design, object location memory, mobile displays, tabletop displays
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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