Date of Award

3-2021

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Operational Sciences

First Advisor

Raymond R. Hill, PhD

Abstract

The initiative to reduce the Air Forces serious pilot shortage lead to the Pilot Training Next (PTN) program. Under PTN, student pilots progress at an individual rate while making increased use of simulator-based training resources. A previous thesis used data from the first PTN class to conceptualize and prototype a student training flight scheduler. This scheduler did not consider training events required to bring students back to achieved levels of performance if in fact that student performance had regressed. This thesis examines three classes of PTN student data to determine whether student regression in training progression can be detected. A visual and two machine learning-based methods are examined and found to not predict training regression in PTN student pilots.

AFIT Designator

AFIT-ENS-MS-21-M-160

DTIC Accession Number

AD1131027

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