Examining Training Eligibility Standards: Four Case Studies

Abstract

The objective of the study was to examine the feasibility of putting the determination of MOS training eligibility standards (i.e., AA composite cutoff score levels) on firmer empirical footing. The key to establishing defensible cutoff levels is the estimation of empirical relationships between student training performance and AA composite scores. Accordingly, the authors estimated training performance relationships and utilized the estimated parameters to examine the impact upon training performance of changes in training eligibility standards, with the aim of identifying defensible standards. The authors specified and estimated binary logistic models based on course-level pass I fail data and regression model using overall student average data for four MOS. These criteria or dependent variables were estimated as functions of AA governing composites and Soldier demographic variables. The authors found moderate correlations between student performance and AA composites, and relatively modest explanatory power of the estimated logistic and OLS regression models. The four MOS also illustrated the difficulties of the intended exploration. Advanced Individual Training (AIT) is closely managed; with data available it is not always possible to distinguish the better form the poorer students. In particular, it is difficult to accurately distinguish between failure to complete training due to academic versus non-academic reasons; there is not much variation in student training performance scores; and there would appear to be a lot of ongoing student remediation.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2004
Accession Number
ADA427358

Entities

People

  • Eric S. Williams
  • Peter M. Greenston

Organizations

  • U.S. Army Research Institute for the Behavioral and Social Sciences

Tags

Communities of Interest

  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Ammunition
  • Artillery
  • Attrition
  • Business Administration
  • Composite Materials
  • Data Analysis
  • Descriptive Analytics
  • Education
  • Job Training
  • Munitions
  • Organizational Structure
  • Personnel Selection
  • Social Sciences
  • Standards
  • Students
  • Training
  • Training Management

Fields of Study

  • Education

Readers

  • Psychometric Testing or Psychological Assessment.
  • Regression Analysis.