A Methodology for Selecting and Refining Man-Computer Languages to Improve Users' Performance

Abstract

This report describes a methodology (supported by a software package) to model, measure, analyze, and evaluate user's performance in a message communication system environment. The theses of the report are: (1) that models of users and services can be accurately used as predictors in selecting a language form, for an application, which will result in high users' performance, and (2) that such a language form is only an approximation (in terms of yielding optimal user's performance) due to within variances of user and service-classes, hence individual, on-line regulation of language constructs is necessary to further improve performance. This report develops appropriate models and algorithms, and states hypotheses relating the interactive effects of users, services, language forms, and other variables important in man-machine discourse. An experiment design is presented, which tests the major hypotheses.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1974
Accession Number
AD0787684

Entities

People

  • John F. Heafner

Organizations

  • University of Southern California

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Communication Systems
  • Computer Languages
  • Data Science
  • Databases
  • Factor Analysis
  • Information Processing
  • Information Science
  • Knowledge Management
  • Message Processing
  • Network Science
  • Sampling
  • Statistical Algorithms
  • Statistical Analysis
  • Statistical Sampling
  • Statistics
  • Training

Fields of Study

  • Computer science

Readers

  • Database Systems and Applications
  • Psychometric Testing or Psychological Assessment.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.