Predictors of Success at Infantry Training Battalion Using Countermovement Jump Metrics

Abstract

The enlisted infantry community, all of whom acquire their training at Infantry Training Battalion (ITB), comprises approximately 15% of the Marine Corps. It is therefore concerning when, on average, 12.9% of the Marines who attend ITB fail to graduate. The majority are dropped from ITB training for four reasons: MOS Specific Physical Standards (MSPS) assessment failures, academic failure, medical injuries, and administrative issues. Of the four reasons, MSPS accounts for the majority of the failures (35.7%), followed by Academics (34.39%), Medical (23.35%), and the remainder (6.47%) for Administrative. These statistics warrant investigation to determine what metrics can be utilized to mitigate failures. In 2019, ITB introduced a new curriculum that includes a newly developed MOS Specific Physical Standards (MSPS) assessment and force platforms to measure human kinetics and biomechanics through a Countermovement Jump (CMJ) test. Data from multiple sources applied to econometric and machine learning models revealed that cognitive ability, demographics, physical performance, and CMJ performance are significant predictors of success at ITB. The most significant predictor turns out to be an interaction of cognitive ability and CMJ, indicating the complementarity of brain and brawn in determining success at ITB. Continued CMJ data collection and analysis could provide valuable insights into prediction-based schoolhouse training models.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2021
Accession Number
AD1150730

Entities

People

  • Cody E. Pennington

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • Biomedical
  • Engineered Resilient Systems
  • Human Systems

DTIC Thesaurus Topics

  • Attrition
  • Basic Training
  • California
  • Data Mining
  • Data Science
  • Data Sets
  • Doctrine
  • Education
  • Factor Analysis
  • Information Science
  • Knowledge Management
  • Machine Learning
  • Military Research
  • Military Science
  • Military Training
  • Motor Skills
  • Predictive Modeling
  • Regression Analysis
  • Statistical Analysis
  • Students
  • Training
  • United States
  • Warfare

Readers

  • Canine Service Warrior Training Program for Wounded Warriors in the Veterinary Industry, Supported by Donors.
  • Instructional Design and Training Evaluation.
  • Regression Analysis.

Technology Areas

  • AI & ML