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Understanding cognitive differences in processing competing visualizations of complex systems.

机译:了解处理复杂系统的竞争可视化过程中的认知差异。

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摘要

Node-link diagrams are used represent systems having different elements and relationships among the elements. Representing the systems using visualizations like node-link diagrams provides cognitive aid to individuals in understanding the system and effectively managing these systems. Using appropriate visual tools aids in task completion by reducing the cognitive load of individuals in understanding the problems and solving them. However, the visualizations that are currently developed lack any cognitive processing based evaluation. Most of the evaluations (if any) are based on the result of tasks performed using these visualizations. Therefore, the evaluations do not provide any perspective flow the point of the cognitive processing required in working with the visualization.;This research focuses on understanding the effect of different visualization types and complexities on problem understanding and performance using a visual problem solving task. Two informationally equivalent but visually different visualizations - geon diagrams based on structural object perception theory and UML diagrams based on object modeling - are investigated to understand the cognitive processes that underlie reasoning with different types of visualizations. Specifically, the two visualizations are used to represent interdependent critical infrastructures. Participants are asked to solve a problem using the different visualizations. The effectiveness of the task completion is measured in terms of the time taken to complete the task and the accuracy of the result of the task. The differences in the cognitive processing while using the different visualizations are measured in terms of the search path and the search-steps of the individual.;The results from this research underscore the difference in the effectiveness of the different diagrams in solving the same problem. The time taken to complete the task is significantly lower in geon diagrams. The error rate is also significantly lower when using geon diagrams. The search path for UML diagrams is more node-dominant but for geon diagrams is a distribution of nodes, links and components (combinations of nodes and links). Evaluation dominates the search-steps in geon diagrams whereas locating steps dominate UML diagrams. The results also show that the differences in search path and search steps for different visualizations increase when the complexity of the diagrams increase.;This study helps to establish the importance of cognitive level understanding of the use of diagrammatic representation of information for visual problem solving. The results also highlight that measures of effectiveness of any visualization should include measuring the cognitive process of individuals while they are doing the visual task apart from the measures of time and accuracy of the result of a visual task.
机译:节点链接图用于表示具有不同元素以及元素之间关系的系统。使用像节点链接图这样的可视化来表示系统,可以为个人理解系统和有效管理这些系统提供认知帮助。使用适当的视觉工具,可以减轻个人理解问题和解决问题的认知负担,从而有助于完成任务。但是,当前开发的可视化缺少任何基于认知处理的评估。大多数评估(如果有)都是基于使用这些可视化文件执行的任务的结果。因此,评估没有提供任何视角流来处理可视化工作所需的认知处理点。本研究着重于使用可视化问题解决任务来理解不同可视化类型和复杂性对问题理解和性能的影响。研究了两个信息等效但在视觉上不同的可视化效果-基于结构对象感知理论的Geon图和基于对象建模的UML图-了解不同类型的可视化是推理基础的认知过程。具体来说,这两种可视化用于表示相互依赖的关键基础架构。要求参与者使用不同的可视化解决问题。根据完成任务所花费的时间和任务结果的准确性来衡量任务完成的有效性。根据个人的搜索路径和搜索步骤来衡量使用不同可视化工具时认知处理的差异。这项研究的结果强调了不同图表在解决同一问题上的有效性的差异。在geon图中,完成任务所花费的时间明显更少。使用geon图时,错误率也大大降低。 UML图的搜索路径更以节点为主导,而Geon图的搜索路径则是节点,链接和组件(节点和链接的组合)的分布。评估主导了geon图中的搜索步骤,而定位步骤主导了UML图。结果还表明,当图表的复杂性增加时,不同可视化的搜索路径和搜索步骤的差异也会增加。;本研究有助于确立认知水平的理解,对于使用信息的图形表示来解决视觉问题,这一点至关重要。结果还强调,任何可视化效果的衡量标准都应包括衡量个人在执行视觉任务时的认知过程,而不是时间和视觉任务结果的准确性。

著录项

  • 作者

    Chakrabarty, Madhavi Mukul.;

  • 作者单位

    New Jersey Institute of Technology.;

  • 授予单位 New Jersey Institute of Technology.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 190 p.
  • 总页数 190
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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