Development of a Methodology for Assessing Aircrew Workloads.

Abstract

The adaptability of industrial methods for setting job and time standards to workload assessment requirements was investigated. Methods considered included direct and indirect time study, synthetic time systems, standard data systems, information content analysis, work sampling and job evaluation. Conventional methods were found to be deficient in accounting for task time variability, divided-attention effects, and cognitive demands which are regarded as critical to effective air crew workload assessment. A combination of synthetic time and standard data system methodologies was proposed as an effective approach to the problem. Three experiments were conducted to evaluate the feasibility of developing a Synthetic Data System(SDS) consistent with workload assessment needs. Swithing, communication and perceptual-mediational tasks were paired with tracking to create divided-attention demands characteristic of pilot workloads. Regression analyses showed that significant amounts of variance in task time requirements and error rates could be accounted for in terms of task and man-machine interface design variables. Development of an SDS on the basis of the performance of aircrew members in aircraft simulators is recommended.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1981
Accession Number
ADA114364

Entities

People

  • David M. Ings
  • David R. Payne
  • James R. Buck
  • James W. Barany
  • Mark L. Lehto

Organizations

  • Purdue University

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Human Systems
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Analysis Of Variance
  • Cognitive Workload
  • Computational Science
  • Computer Programs
  • Computer Simulations
  • Data Science
  • Human Behavior
  • Human Factors Engineering
  • Information Processing
  • Information Science
  • Job Analysis
  • Measurement
  • Personnel Management
  • Psychology
  • Regression Analysis
  • Task Performance And Analysis

Readers

  • Instructional Design and Training Evaluation.
  • Regression Analysis.