Decision making with visualizations: a cognitive framework across disciplines
By Lace M. K. Padilla, Sarah H. Creem-Regehr, Mary Hegarty, Jeanine K. Stefanucci. 2018
285 citations recorded by the source corpus.
Visualizations—visual representations of information, depicted in graphics—are studied by researchers in numerous ways, ranging from the study of the basic principles of creating visualizations, to the cognitive processes underlying their use, as well as how visualizations communicate complex information (such as in medical risk or spatial patterns). However, findings from different domains are rarely shared across domains though there may be domain-general principles underlying visualizations and their use. The limited cross-domain communication may be due to a lack of a unifying cognitive framework. This review aims to address this gap by proposing an integrative model that is grounded in models of visualization comprehension and a dual-process account of decision making. We review empirical studies of decision making with static two-dimensional visualizations motivated by a wide range of research goals and find significant direct and indirect support for a dual-process account of decision making with visualizations. Consistent with a dual-process model, the first type of visualization decision mechanism produces fast, easy, and computationally light decisions with visualizations. The second facilitates slower, more contemplative, and effortful decisions with visualizations. We illustrate the utility of a dual-process account of decision making with visualizations using four cross-domain findings that may constitute universal visualization principles. Further, we offer guidance for future research, including novel areas of exploration and practical recommendations for visualization designers based on cognitive theory and empirical findings.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Management Science and Operations Research
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Citations in the corpus
- FairSight: Visual Analytics for Fairness in Decision Making (2019, methodology): “We propose FairDM framework that facilitates the contemplative decision-making process [31] with a set of tasks to achieve fairer decision making.”
- The effects of over-reliance on AI dialogue systems on students' cognitive abilities: a systematic review (2024, background): “…the cognitive and neurological foundations of the process and highlights the diversity of approaches in analyzing decision-making strategies, bridging the gap between rational choice theory’s normative ideals and the practical adaptations identified by descriptive theories (Padilla et al., 2018).”