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Effects of Individual Differences in Working Memory on Plan Presentational Choices
Nava Tintarev1, Judith Masthoff2
1Department of Computing and Informatics, Faculty of Science and Technology, Bournemouth University Poole, UK.
Frontiers in Psychology
|December 1, 2016
Summary
Individual differences in working memory impact visualization effectiveness. Emphasizing plan steps improves performance, but only when accounting for user working memory capacity in decision support systems.
Area of Science:
- Human-computer interaction
- Cognitive psychology
- Information visualization
Background:
- Decision support systems require effective visualization interfaces.
- Individual user differences, particularly working memory, can influence visualization effectiveness.
- Presenting plans (sequences of actions) is crucial in domains like semi-autonomous logistics.
Purpose of the Study:
- To investigate the role of working memory in visualization design for decision support.
- To explore different presentational choices for visualizing plans (interactivity, aggregation, layout, emphasis).
- To develop and apply a novel methodology for evaluating visualization effectiveness.
Main Methods:
- Literature review on individual differences and visualization evaluation metrics.
- Experimental investigation of presentation variants (interactivity, aggregation, layout, emphasis).
- Dual-task paradigm measuring performance in task interleaving and situational awareness.
Main Results:
- Individual working memory capacity is a significant factor in visualization effectiveness.
- Emphasizing plan steps via highlighting borders can enhance primary task performance.
- The benefit of emphasis is contingent on controlling for individual working memory variations.
Conclusions:
- Visualization design for decision support must consider individual user differences, especially working memory.
- Tailoring presentation strategies based on working memory can optimize decision-making and processing.
- A layered-evaluation approach using dual-task paradigms provides robust insights into visualization effectiveness.
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