Refining the Process of the Commandant's Education Board

reportActive / Technical Report | Accesssion Number: AD1213588 | Open PDF

Abstract:

As warfare becomes increasingly complex, the Marine Corps needs to better equip its warriors. One of the ways the Marine Corps does this is through graduate education programs (GEP). The Commandants Education Board assesses candidates based on their desire, career timing, and aptitude. Aptitude is broken into competitiveness and competency. Desire is assessed via a survey. Competitiveness is assessed via fitness reports (FITREP). However, the Marine Corps has no effective method of assessing competency in the field for which a Marine is attending a GEP. This thesis used data from the Marine Corps Total Force Data Warehouse, specifically the Marine-1 and Master Brief Sheet data, to find predictors for FITREP performance of Marines filling 88xx billets. These predictors were taken from before the Marine entered into a Marine Corps GEP. This study focused on the following predictors: source of entry, time in service, primary military occupational specialty (PMOS), level of previous education (undergraduate versus graduate), and undergraduate major subject (STEM or liberal arts). This study found that source of entry, PMOS, and STEM had no predictive power in determining a Marines performance. It also found that greater time in service and some graduate education had a slightly positive correlation to performance. This thesis recommends discontinuing vetting Marines for STEM undergraduates and giving preference to Marines with previous graduate education.

Author(s):
Niewoehner, Brent J.
Author Organization(s):
NAVAL POSTGRADUATE SCHOOL MONTEREY CA
Funding Organization(s):
NAVAL POSTGRADUATE SCHOOL MONTEREY CA, MONTEREY, CA
Document Type:
Technical Report/Master's Thesis
Publication Date:
2023 Jun 01
Pagination:
66

Security Markings

DOCUMENT & CONTEXTUAL SUMMARY

Distribution Code:
A - Approved For Public Release
Distribution Statement: Public Release.
Copyright: Not Copyrighted

RECORD

Collection: TRECMS
Subject Terms
Descriptor(s):
supervised machine learning, students, military education, united states naval academy, machine learning, warfare, algorithms, california, data sets, operations research, reserve officer training corps, service academies, united states, classification, data analysis, data mining, education
Keyword(s):
FITREPS(FITNESS REPORTS), MCTFS(MARINE CORPS TOTAL FORCE SYSTEM), CEB(COMMANDANTS EDUCATION BOARD), CCLEB(COMMANDANTS CAREER LEVEL EDUCATION BOARD), CPIB(COMMANDANTS PROFESSIONAL INTERMEDIATE-LEVEL EDUCATION BOARD), GEP(GRADUATE EDUCATION PROGRAM), STEM(SCIENCE, TECHNOLOGY, ENGINEERING, MATH), RESERVE OFFICER TRAINING CORPS
Subject Categories:
Military Sciences; Behavioral and Social Sciences; Behavioral and Social Sciences
Modernization Areas:
Autonomy; Cyber; AI and Machine Learning
Communities of Interest:
; ; ; ;
Descriptor(s):
supervised machine learning, students, military education, united states naval academy, machine learning, warfare, algorithms, california, data sets, operations research, reserve officer training corps, service academies, united states, data analysis, data mining, education, engineering
Creation Date:
2023 Oct 24
Update Date:
2023 Nov 09