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Related Experiment Videos

An evaluation method of computer usability based on human-to-computer information transmission model.

K Ogawa1

  • 1Human Interface Laboratories, Nippon Telegraph and Telephone Corporation, Kanagawa, Japan.

Ergonomics
|May 1, 1992
PubMed
Summary

This study introduces a new computer usability evaluation method using information transmission rates. The device independent information transmission rate (RDI) and computer independent information transmission rate (RCI) efficiently assess software and device usability.

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Area of Science:

  • Human-Computer Interaction
  • Information Theory
  • Usability Engineering

Background:

  • Traditional usability evaluation methods can be complex and time-consuming.
  • A need exists for objective, quantifiable measures of computer usability.
  • Existing models often lack device or system independence.

Purpose of the Study:

  • To propose a novel method for evaluating and predicting computer usability.
  • To introduce information transmission measures for quantifying usability.
  • To establish device and computer independent rates for usability assessment.

Main Methods:

  • Developed a human-to-computer information transmission model with three levels: device, software, and task content.
  • Defined device independent information (DI) and computer independent information (CI) measures.

Related Experiment Videos

  • Introduced device independent information transmission rate (RDI = DI/T) and computer independent information transmission rate (RCI = CI/T), where T is task completion time.
  • Main Results:

    • The proposed RDI and RCI rates provide a quantitative assessment of usability.
    • Experiments on three different systems confirmed the method's efficiency.
    • The rates allow for relative evaluation of software and device operations across diverse computer systems.

    Conclusions:

    • The RDI and RCI rates offer an efficient and objective approach to computer usability evaluation.
    • This information transmission-based method enhances the prediction and understanding of user interaction.
    • The approach is applicable to various computer systems and tasks, facilitating comparative usability studies.