HUMAN FACTORS PREDICTION VALIDATION.

Abstract

This study concerned the predictive accuracy of personnel and training projections research conducted during new development cycles, and the development of an administrative tool for decision-making processes associated with allocating resources to future human factors research. Two measures of projection accuracy, termed Regret and Discrepancy were formulated. Data on a sample of projections made during the 5-year period 1959 to 1964 were collected. These data were analyzed to provide measures of accuracy (Discrepancy and Regret) and enumerate various possible predictor variables. Limitations within the data prevented collection of Regret scores. A validity index (to predict Discrepancy) was derived using curve fitting and multiple linear regression. Four important factors - types of projections, point-in-time (within the RDT and E cycle), system size, and number of replications of the research - were discovered. A final multiple regression formula (validity index) based on these four factors was produced and found to have a correlation of .66 with measured Discrepancy. Suggestions for refinement and utilization of the validity index, for further work with the Regret model of the index, and for improvement of reports of future human factors projections are included. (Author)

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1967
Accession Number
AD0819210

Entities

People

  • Lawrence E. Langdon
  • Richard S. Gebhard
  • Robert A. Wood
  • Victor J. Hernandes

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Accuracy
  • Curve Fitting
  • Education
  • Students
  • Trainees
  • Training
  • Validation

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computational Modeling and Simulation
  • Instructional Design and Training Evaluation.