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An exploration of a testing procedure for the aviation industry

Resource type
Thesis type
(Project) M.Sc.
Date created
2023-12-06
Authors/Contributors
Author: Lai, Liwei
Abstract
In the aviation industry, pilot training is paramount, necessitating robust and precise assessment methodologies. Despite the shift towards Competency-based Training and Assessment (CBTA) recommended by the International Civil Aviation Organization (ICAO), there is a notable absence of comprehensive statistical models to substantiate the evaluation process. This project explores the application of an enhanced Many-Facet Rasch Model (MFRM) employing Bayesian estimation techniques and presents a novel approach for quantifying pilot competency scores, ensuring a more granular and accurate assessment of pilot capabilities. By analyzing simulated data, the research assesses the viability of this statistical approach in operational settings. Potential applications and limitations of this methodology within the aviation industry are discussed.
Document
Extent
28 pages.
Identifier
etd22805
Copyright statement
Copyright is held by the author(s).
Permissions
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Supervisor or Senior Supervisor
Thesis advisor: Swartz, Tim
Thesis advisor: Parker, Gary
Language
English
Download file Size
etd22805.pdf 754.39 KB

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