Beyond Measures of Speed & Accuracy: Evaluating Visualization Perception, Reasoning & Decision-Making

Visualizations have long been used to support decision-making across various fields. By transforming complex data into graphical representations, such as charts, graphs, and maps, visualizations are generally reputed to make information more accessible and comprehensible for all. While prior work demonstrates that visualizations can improve speed and accuracy across comprehension and analytical tasks, there lacks research on how they can benefit decision-making. Decision-making is a complex task which involves risk comprehension and rational thinking but also various heuristics and external factors. While research has shown that individual traits and situational factors can impact performance with visualizations, they have not been explored in the context of decision-making. By focusing on three essential stages of the decision-making pipeline with visualization—perception, reasoning, and decision—I explore 1) how visualizations impact decision-making, and 2) how individual differences and situational factors mediate decision-making with visualizations. This thesis builds on the connection between perception, reasoning and decision to advance the understanding of how visualization can play a role in decision-making processes. By considering individual and situational factors such as working memory capacity and time pressure in visualization evaluation, this thesis expands beyond conventional evaluation metrics and challenges the one-size-fits-all approach. The research presented deepens our understanding of how people from diverse backgrounds and with different cognitive traits make decisions using charts and text. We provide evidence-based recommendations aimed at designing systems that are more accessible and effective for diverse users, leading to the development of better user-centric visual tools.

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science & Engineering

Year dc:date.available

2024

Author dc:creator

• Bancilhon, Melanie

Contributors dc:contributor

• William Yeoh
• Alvitta Ottley

• Data Visualization;Decision-Making;Human-Computer Interaction;Individual Differences
• Chemical Engineering
• Engineering

Statement dc:rights

• I have not registered my thesis with the U.S. Copyright Office, and do not intend to.

Language dc:language

English (en)

Identifier

https://openscholarship.wustl.edu/eng_etds/1085

OAI identifier oai:identifier

oai:openscholarship.wustl.edu:eng_etds-2156