Predictive Statistical Modeling of Naval Reserve Officers Training Corps Attrition

Abstract

Attrition and the retention of talent is a concern for all organizations, but especially in the military. It is important to understand what factors influence attrition so that organizational leadership can optimize its purpose. This research examines attrition within Naval Reserve Officer Training Corps (NROTC) between 2013 and 2020. Using data provided by Naval Education Training Command (NETC), predictive statistical models aim to demonstrate what types of demographic, academic, and performance-based factors are important to predicting attrition among NROTC midshipmen. Modeling NROTC attrition behavior could enhance the NROTC Scholarship selection process, improve and organize attrition tracking in NROTC, and inform NETC on where resources should be allocated in order to improve program function. Furthermore, methods for tracking and predicting attrition, and for defining variable importance toward prediction, serve to inform other programs in decision-making processes surrounding attrition and talent retention.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2020
Accession Number
AD1127105

Entities

People

  • Zachary H. Swenson

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • Ground and Sea Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Attrition
  • California
  • Data Analysis
  • Data Mining
  • Data Sets
  • Department Of Defense
  • Education
  • Information Science
  • Machine Learning
  • Minority Groups
  • Navy
  • Neural Networks
  • Nuclear Powered Submarines
  • Physical Fitness
  • Predictive Modeling
  • Reserve Officer Training Corps
  • Schools
  • Spreadsheet Software
  • Statistical Analysis
  • Students
  • Supervised Machine Learning
  • Training

Readers

  • Computational Modeling and Simulation
  • Naval Personnel Management