Measures of Information Complexity and the Implications for Automation Design

Abstract

Information complexity associated with automation aids is a bottleneck that limits their use. While automation systems are designed to bring new functions to users and increase their capacities, automation also creates new tasks associated with acquiring and integrating information from displays. For example, a complex display increases information load to human operators and reduces usability. Thus, the efficiency of an automation system largely depends on the complexity of displayed information. To evaluate the costs and benefits of an automation aid, it is important to understand how much information is shown on the display, how users look at multiple information sources to build and maintain situation awareness, and whether the information is displayed in a compatible way so it can be integrated and understood easily without the user having to make internal conversions or calculations. In this paper, we present a set of measures to assess information complexity. The metrics count information complexity as the combination of three basic factors: numeric size, variety, and relation; each factor is evaluated by the functions at three stages of brain information processing: perception, cognition, and action. Ideally, these measures provide an objective method to evaluate automation systems for acquisition and design prototypes.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2004
Accession Number
ADA428690

Entities

People

  • Jing Xing

Organizations

  • Federal Aviation Administration

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Cognition
  • Cognitive Complexity
  • Cognitive Workload
  • Color Coding
  • Computer Programming
  • Computers
  • Data Displays
  • Human Systems Integration
  • Human-Computer Interaction
  • Human-Computer Interfaces
  • Information Processing
  • Information Theory
  • Operating Systems
  • Personality
  • Psychology
  • Task Performance And Analysis
  • User Interface

Fields of Study

  • Computer science

Readers

  • Computer Science.
  • Instructional Design and Training Evaluation.
  • Systems Analysis and Design