Date of Award
3-2022
Document Type
Thesis
Degree Name
Master of Science
Department
Department of Electrical and Computer Engineering
First Advisor
Mark G. Reith, PhD
Abstract
The United States military must continue to innovate and improve the way we fight and defend against our near-peer adversaries. Emerging technologies such as machine learning, artificial intelligence, and reverse engineering are paving the way for an increasingly complex security environment. A core tenant of winning in this new era of warfare is how we educate and train our military force. Many of the online trainings made available to service members today fall short in the implementation of existing learning theories.
AFIT Designator
AFIT-ENG-MS-22-M-076
DTIC Accession Number
AD1173313
Recommended Citation
Woods, Trenton M., "Examining the Effects of Learning Theory Implemented Within an Online and Self-Paced Learning Path" (2022). Theses and Dissertations. 5372.
https://scholar.afit.edu/etd/5372