Feasibility Study for Predicting Human Reliability Growth through Training and Practice

Abstract

This report examines the feasibility of developing a stand alone, quantitative Human Reliability Growth Model (HRGM) that predicts the impact of training variable on soldier performance. Such a model would incorporate learning curve fitting techniques to predict the impact of training variables on performance and would be based on empirical data from the behavioral and social science literature and available government data bases. This report describes the effort to collect empirical data on the effects of learning and practice on human performance. In addition, the report contains a review of the theoretical literature involving human learning and practice in which the nature and application of learning curves and curve fitting techniques are derived and summarized. The results of this effort reveal that, out of approximately 3,000 research titles and abstracts reviewed, only 27 articles meet minimal criteria for use in developing the HRGM. It was concluded that, although a theoretical basis for developing an HRGM exists, the data could not support its development. Human learning and practice, Human reliability growth, Learning curve fitting techniques, Human performance modeling, Training and performance literature, Training and performance review.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1992
Accession Number
ADA252371

Entities

People

  • John C. Lowry
  • Michael M. Copenhaver
  • Virginia A. Rappold

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Applied Psychology
  • Cognition
  • Control Systems
  • Databases
  • Doctrine
  • Experimental Design
  • Flight Simulators
  • Flight Training
  • Human Factors Engineering
  • Information Processing
  • Military Training
  • Motor Skills
  • Psychology
  • Students
  • Trainees
  • Training Devices

Readers

  • Computational Modeling and Simulation
  • STEM Education
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.