Useful junk?: the effects of visual embellishment on comprehension and memorability of charts
Abstract
Guidelines for designing information charts (such as bar charts) often state that the presentation should reduce or remove 'chart junk' - visual embellishments that are not essential to understanding the data. In contrast, some popular chart designers wrap the presented data in detailed and elaborate imagery, raising the questions of whether this imagery is really as detrimental to understanding as has been proposed, and whether the visual embellishment may have other benefits. To investigate these issues, we conducted an experiment that compared embellished charts with plain ones, and measured both interpretation accuracy and long-term recall. We found that people's accuracy in describing the embellished charts was no worse than for plain charts, and that their recall after a two-to-three-week gap was significantly better. Although we are cautious about recommending that all charts be produced in this style, our results question some of the premises of the minimalist approach to chart design.
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Bateman et al. (2010) found that long-term recall of more detailed charts was better than for simpler versions, with participants judging the embellished charts to be easier to remember and enjoyable.
“Long-term recall of the more detailed charts turned out to be better than for the simpler versions in that study, with participants judging the embellished charts to be easier to remember and to be enjoyable (Bateman et al., 2010).”
From Understanding Cognitive Load in Digital and Online Learning: a New Perspective on Extraneous Cognitive Load (2022) · cites this paper as Bateman et al., 2010
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Correll, M. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300418 · Cited by 150 · see citing works
Boy, J., Pandey, A. V., Emerson, J., Satterthwaite, M., Nov, O., & Bertini, E. (2017) · Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3025453.3025512 · Cited by 104 · see citing works
Good Game Feel: An Empirically Grounded Framework for Juicy Design
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- Authors
- Bateman, S., Mandryk, R. L., Gutwin, C., Genest, A., McDine, D., & Brooks, C.
- Affiliations
- University of Saskatchewan (CA)
- Venue
- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2010-04-10
- Pages
- 2573-2582
- OpenAlex
- W2120326355
- Cited by
- 404
- References
- 0
- Citations by year
- 2026: 16 · 2025: 44 · 2024: 30 · 2023: 28 · 2022: 25 · 2021: 44 · 2020: 39 · 2019: 30 · 2018: 22 · 2017: 24 · 2016: 19 · 2015: 24 · 2014: 23 · 2013: 16 · 2012: 10
- FWCI
- 9.88
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Funders
- Natural Sciences and Engineering Research Council of Canada
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Data Visualization and Analytics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- bar charts, chart design, data visualization, interpreting accuracy, long-term recall, minimalist design
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