Using Cognitive Fit Theory to Evaluate the Effectiveness of Information Visualizations: An Example Using Quality Assurance Data
Issue No. 05 - September/October (2010 vol. 16)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2010.21
Jay M. Teets , Coastal Carolina University, Conway
David P. Tegarden , Virginia Tech, Blacksburg
Roberta S. Russell , Virginia Tech, Blacksburg
Cognitive fit theory, along with the proximity compatibility principle, is investigated as a basis to evaluate the effectiveness of information visualizations to support a decision-making task. The task used in this study manipulates varying levels of task complexity for quality control decisions in a high-volume discrete manufacturing environment. The volume of process monitoring and quality control data produced in this type of environment can be daunting. Today's managers need effective decision support tools to sort through the morass of data in a timely fashion to make critical decisions on product and process quality.
Experimental design, information visualization, quality assurance, user interface evaluation.
R. S. Russell, D. P. Tegarden and J. M. Teets, "Using Cognitive Fit Theory to Evaluate the Effectiveness of Information Visualizations: An Example Using Quality Assurance Data," in IEEE Transactions on Visualization & Computer Graphics, vol. 16, no. , pp. 841-853, 2010.