Development and Comparison of TACAMO Icon Design Formats

Abstract

The purpose of this study was to develop and evaluate a set of icons for the next generation message processing system for the TACAMO airborne strategic communications platform. An icon set for a proposed interface was developed through the use of an icon production method test, that is, potential users designed candidate icons that were meaningful to them. These icons were then refined for discriminability via Input from a user survey. To determine if well-developed icons with alphanumeric labels yield a significant performance advantage over the same icons without labels, an experiment involving trained users was conducted using a response time model. Subtractive logic was used to measure icon identification times as a function of whether they were or were not labeled. When speed of performance and rate of errors were compared, labeling of Icons resulted in significantly longer response times, yet did not result in fewer errors for the tested icon set. It is recommended that the unlabeled set of icons be used for TACAMO's next generation message processing system, and that the Icon production method be used more widely to involve users in interface design. TACAMO, Icons, Human-computer interaction, Symbols, Labels, Software interface design, System Design, Direct manipulation interface.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1992
Accession Number
ADA252917

Entities

People

  • William D. Sanders

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Human Systems
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Applied Psychology
  • Cognitive Systems Engineering
  • Computer Programming
  • Computers
  • Engineering
  • Human Factors Engineering
  • Human Systems Integration
  • Information Processing
  • Message Processing
  • Motor Skills
  • Network Science
  • Operating Systems
  • Operations Research
  • Production Engineering
  • Psychology
  • Surveys
  • United States

Readers

  • Database Systems and Applications
  • Human-Computer Interaction (HCI).
  • Neural Network Machine Learning.