Improving the Prediction of Performance in Cyber Training
Abstract
The U.S. Army Cyber Center of Excellence seeks to maximize the likelihood that Soldiers classified into cyber-related military occupational specialties (MOS) will be successful. Currently, Soldiers must receive passing scores on two measures to be eligible for classification into the 17C occupation (Cyber Operations Specialist). The first is the Skilled Technical composite of the Armed Services Vocational Aptitude Battery (ASVAB) and the second is the Cyber Test. There is now interest in seeing whether adding a temperament measure would further improve prediction of important Soldier outcomes in this MOS. The Tailored Adaptive Personality Assessment System (TAPAS) is a prime candidate to use for this purpose. To investigate the potential of TAPAS to improve the existing system for classifying Soldiers into the 17C MOS, a method for collecting performance criterion data then periodically matching this to predictor and other administrative data was established. Data collection commenced in the summer of 2018; ARI will continue to update the analyses and results as more Soldiers progress through training.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 01, 2020
- Accession Number
- AD1160157
Entities
People
- Alexander P. Wind
- Deirdre J. Knapp
- Samuel J. Posnock
- Thomas Kiger
- William Taylor
Organizations
- Human Resources Research Organization
- U.S. Army Research Institute for the Behavioral and Social Sciences