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Cognitive Processes and Traits Related to Graphic Comprehension

Cognitive Processes and Traits Related to Graphic Comprehension

Angela M. Zoss
Copyright: © 2014 |Pages: 17
ISBN13: 9781466643093|ISBN10: 1466643099|EISBN13: 9781466643109
DOI: 10.4018/978-1-4666-4309-3.ch005
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MLA

Zoss, Angela M. "Cognitive Processes and Traits Related to Graphic Comprehension." Innovative Approaches of Data Visualization and Visual Analytics, edited by Mao Lin Huang and Weidong Huang, IGI Global, 2014, pp. 94-110. https://doi.org/10.4018/978-1-4666-4309-3.ch005

APA

Zoss, A. M. (2014). Cognitive Processes and Traits Related to Graphic Comprehension. In M. Huang & W. Huang (Eds.), Innovative Approaches of Data Visualization and Visual Analytics (pp. 94-110). IGI Global. https://doi.org/10.4018/978-1-4666-4309-3.ch005

Chicago

Zoss, Angela M. "Cognitive Processes and Traits Related to Graphic Comprehension." In Innovative Approaches of Data Visualization and Visual Analytics, edited by Mao Lin Huang and Weidong Huang, 94-110. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-4309-3.ch005

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Abstract

The subject of how visualizations and graphics in general can be understood by their viewers draws on theories from many fields of research. Such theories might address the formal structure of the visualization, the style and graphic design skills of the creator, the task driving the viewer’s interaction with the visualization, the type of data being represented, or the skills and experiences of viewer. This chapter focuses on this last question and presents a set of interrelated constructs and viewer traits that contribute to (or interfere with) a viewer’s ability to analyze a particular data visualization. The review covers spatial thinking skills, cognitive styles, mental models, and cognitive load in its discussion of theoretical constructs related to graphic comprehension. The review also addresses how these cognitive processes vary by age, sex, and disciplinary background–the most common demographic characteristics studied in relation to graphic comprehension. Together, the constructs and traits contribute to a diverse and nuanced understanding of the viewers of data visualizations.

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