A Phase-Wise Machine Learning-based Performance Evaluation in Flight Simulation Training

Flight training is the crucial part of aviation industry. This study advances the field of flight training by combining tolerance-based performance labelling with machine learning classification to classify the pilot student performance in different phases of flight. The main contribution of the study is that it allows the flight instructor to give meaningful feedback, tailor remedial instruction, and make better decisions about pilot student performance and progression. Moreover, this study promotes the application of machine learning models in aviation education and highlights their significance in resolving the difficulties related to pilot training.