Name
Abstract | ||
|---|---|---|
ABSTRACTInteraction enables users to navigate large amounts of data effectively, supports cognitive processing, and increases data representation methods. However, there have been few attempts to empirically demonstrate whether adding interaction to a static visualization improves its function beyond popular beliefs. In this paper, we address this gap. We use a classic Bayesian reasoning task as a testbed for evaluating whether allowing users to interact with a static visualization can improve their reasoning. Through two crowdsourced studies, we show that adding interaction to a static Bayesian reasoning visualization does not improve participants’ accuracy on a Bayesian reasoning task. In some cases, it can significantly detract from it. Moreover, we demonstrate that underlying visualization design modulates performance and that people with high versus low spatial ability respond differently to different interaction techniques and underlying base visualizations. Our work suggests that interaction is not as unambiguously good as we often believe; a well designed static visualization can be as, if not more, effective than an interactive one. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3411764.3445176 | Conference on Human Factors in Computing Systems |
Keywords | DocType | Citations |
Data Analysis, Reasoning, Problem Solving, Decision Making, Interaction Design, Human-Subjects Quantitative Studies | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Abigail Mosca | 1 | 12 | 2.14 |
| Alvitta Ottley | 2 | 0 | 1.01 |
| Remco Chang | 3 | 983 | 64.96 |