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Predicting graph reading performance: A cognitive approach
conference contribution
posted on 2023-05-23, 08:42 authored by Huang, W, Hong, S-H, Eades, PPerformance and preference measures are commonly used in the assessment of visualization techniques. This is important and useful in understanding differences in e®ectiveness between di®erent treatments. However, these measures do not answer how and why the di®erences are caused. And sometimes, performance measures alone may not be sensitive enough to detect di®erences. In this paper, we introduce a cognitive approach for visualization e®ectiveness and e±ciency assessment. A model of user performance, mental e®ort and cognitive load (memory demand) is proposed and further mental e®ort and visualization e±ciency measures are incorporated into our analysis. It is argued that 1) combining cognitive measures with traditional methods provides us new insights and practical guidance in visualization assessment. 2) analyzing human cognitive process not only helps to understand how viewers interact with visualizations, but also helps to predict user performance in initial stage. 3) keeping cognitive load induced by a visualization low allows more memory resources to be available for high level complex cognitive activities. A case study conducted supports our arguments.
History
Publication title
Conferences in Research and Practice in Information TechnologyVolume
60Editors
K Misue, K Sugiyama and J TanakaPagination
1-10Department/School
School of Information and Communication TechnologyPublisher
Australian Computer Society, Inc.Place of publication
AustraliaEvent title
Asia-Pacific Symposium on Information Visualization (APVIS 2006)Event Venue
Tokyo, JapanDate of Event (Start Date)
2006-02-01Date of Event (End Date)
2006-02-01Rights statement
Copyright 2006, Australian Computer Society, Inc. This pa- per appeared at Asia-Paci¯c Symposium on Information Visu- alization (APVIS 2006), Tokyo, Japan, February 2006. Confer- ences in Research and Practice in Information Technology, Vol. 60. K. Misue, K. Sugiyama and J. Tanaka, Ed. Reproduction for academic, not-for pro¯t purposes permitted provided this text is included.Repository Status
- Restricted