Automated Test Outline Development: Research Findings

Abstract

The Automated Test Outline (ATO) research and development effort was designed to explore and resolve both technical and logistical problems associated with using occupational survey data to derive weighted subject matter areas for Specialty Knowledge Test (SKT) outlines. Issues discussed included: the process for selecting appropriate subsets of tasks from a full task inventory for mailout to subject-matter experts in order to obtain task-level testing importance ratings; interrater and test-retest reliability indices for testing importance ratings in 28 Air Force specialties; the validity of the ATO procedure, as measured by the SKT teams' adherence to the computed testing importance weights for each duty-level outline area and each task; and the relationship between field-validated testing importance and a variety of routine available task factors, such as field-recommended training emphasis, task learning difficulty, average grade of members performing, and percent members performing and average percent time spent by members performing at the E-5 and E-6/7 paygrade levels. Air Force enlisted personnel; Specialists job analysis; Occupational analysis; Task analysis; Test development. (EDC)

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1989
Accession Number
ADA215401

Entities

People

  • Johnny J. Weissmuller
  • Martin J. Dittmar
  • William J. Phalen

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Administrative Personnel
  • Air Force
  • Air Force Facilities
  • Availability
  • Command And Control
  • Construction
  • Corporations
  • Enlisted Personnel
  • Fabrication
  • Governments
  • Job Analysis
  • Learning
  • Management Personnel
  • Manpower
  • Personnel Management
  • Standards
  • Training

Readers

  • Instructional Design and Training Evaluation.
  • Occupational Health and Safety.
  • Regression Analysis.