Predicting the Productive Capacity of Air Force Aerospace Ground Equipment Personnel Using Aptitude and Experience Measures

Abstract

This study investigated the effects of mechanical aptitude and job experience on the job performance of 204 Air Force Aerospace Group Equipment (AGE) mechanics. Job performance was expressed as productive capacity (PC), which is derived from estimated performance times on job tasks. PC measures were derived for 50 tasks typically performed by airmen in the specialty. Aptitude measures took the form of Mechanical percentile composite scores on the Armed Services Vocational Aptitude Battery (ASVAB). A second-order logistic model was used to regress PC on aptitude and experience at the task level and at the overall job, or aggregate, level. Model R(2)s were generally low. For the tasks, R(2)s ranged from .01 to .13, and for the aggregate model the R2 was about .16. Generally, experience was a significant predictor but aptitude was not. There was also no indication of an aptitude/experience interaction. These results were verified through forward stepwise regression. There was some evidence that airmen may experience some skill degradation on production-type tasks at around the six year point as they transition to supervisory roles.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1993
Accession Number
ADA262391

Entities

People

  • Robert S. Faneuff

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Computational Science
  • Data Science
  • Databases
  • Enlisted Personnel
  • Factor Analysis
  • Information Science
  • Knowledge Management
  • Mathematical Models
  • Personnel Management
  • Production
  • Psychology
  • Regression Analysis
  • Reliability
  • Statistical Algorithms
  • Statistical Inference
  • Task Performance And Analysis

Readers

  • Computational Modeling and Simulation
  • Occupational Health and Safety.
  • Psychometric Testing or Psychological Assessment.

Technology Areas

  • Space