Thinking Graphically: Connecting Vision and Cognition during Graph Comprehension

Abstract

Task analytic theories of graph comprehension account for the perceptual and conceptual processes required to extract specific information from graphs. Comparatively, the processes underlying information integration have received less attention. We propose a new framework for information integration that highlights visual integration and cognitive integration. During visual integration, pattern recognition processes are used to form visual clusters of information; these visual clusters are then used to reason about the graph during cognitive integration. In three experiments the processes required to extract specific information and to integrate information were examined by collecting verbal protocol and eye movement data. Results supported the task analytic theories for specific information extraction and the processes of visual and cognitive integration for integrative questions. Further, the integrative processes scaled up as graph complexity increased, highlighting the importance of these processes for integration in more complex graphs. Finally, based on this framework, design principles to improve both visual and cognitive integration are described.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2008
Accession Number
ADA480055

Entities

People

  • Deborah A. Boehm-davis
  • J. Gregory Trafton
  • Raj M. Ratwani

Organizations

  • United States Naval Research Laboratory

Tags

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Coding
  • Cognition
  • Cognitive Science
  • Comprehension
  • Computer Graphics
  • Computer Programming
  • Extraction
  • Eye
  • Eye Movements
  • Human Factors Engineering
  • Human-Machine Interaction
  • Pattern Recognition
  • Psychology
  • Reasoning
  • Recognition
  • Thinking

Fields of Study

  • Computer science
  • Psychology

Readers

  • Artificial Intelligence
  • Human-Computer Interaction (HCI).
  • Systems Analysis and Design

Technology Areas

  • AI & ML