Aviation Commons^™

An Exploratory Study Of Us Navy T-45c Simulation Training, Aaron D. Judy Ed.D., Tom Gollery Ed.D.

Journal of Applied Social Science Research and Practice

Flight training is costly and workload intensive. According to a recent Government Accountability Office (GAO) report, the US Navy and US Air Force predict a 25% shortage of fighter pilots by 2023 (GAO, 2018). The military needs empirical research to determine the effectiveness of flight simulation training and whether simulation training can decrease the overall training time for student pilots. The purpose of this study was to compare intermediate and advanced military student pilots’ scores on the T-45C OFT simulator training events and scores on the T-45C aircraft training events in four training domains; the intervention in this study included …

Does The Use Of Simulation Significantly Impact Students’ Perceptions Of Their Air Traffic Control Knowledge And Skill?, Meron Lindenfeld, Jeanne Radigan, Michael Figuccio

Journal of Aviation Technology and Engineering

Simulation has served as an instructional supplement in education and training within various fields such as nursing, business, and flight training. Prior research studies have documented its usefulness. Simulation-based lessons have also been used for air traffic control (ATC) training, but little research has been conducted on the usefulness of simulation in this application. This study measured the level of influence that ATC simulation had on students’ perception of their ATC knowledge and skill level and their commitment to a career in ATC.

Data were collected by surveying students at four institutions of higher education after they completed ATC courses …

Automatic Gaze Classification For Aviators: Using Multi-Task Convolutional Networks As A Proxy For Flight Instructor Observation, Justin Wilson, Sandro Scielzo, Sukumaran Nair, Eric C. Larson

International Journal of Aviation, Aeronautics, and Aerospace

In this work, we investigate how flight instructors observe aviator scan patterns and assign quality to an aviator's gaze. We first establish the reliability of instructors to assign similar quality to an aviator's scan patterns, and then investigate methods to automate this quality using machine learning. In particular, we focus on the classification of gaze for aviators in a mixed-reality flight simulation. We create and evaluate two machine learning models for classifying gaze quality of aviators: a task-agnostic model and a multi-task model. Both models use deep convolutional neural networks to classify the quality of pilot gaze patterns for 40 …