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Embry-Riddle Scholarly Commons · Journal article (JAAER)
Implementing Artificial Intelligence and Machine Learning into Advanced Qualification Programs
Attribution
This is the abstract and citation. Full text lives at Embry-Riddle Scholarly Commons — we link out rather than host. All credit to the authors and Embry-Riddle Aeronautical University.
Abstract
Verbatim from Embry-Riddle Scholarly Commons. Not paraphrased, not summarized.
Since its start, the Advanced Qualification Program (AQP) has encouraged new and innovative strategies for training airline crewmembers. The foundation of AQP is to train crew the way they fly and to find new and innovative ways to increase safety through training. By using data collected through the AQP process, training methods can be refined and improved. New technologies, such as artificial intelligence (AI) and machine learning can make data analysis and training more effective and efficient. This paper will explore these concepts and how AI and machine learning could be implemented in the AQP process to make training more effective and make pilots, crewmembers, and passengers safer.
Author
- Herr, Jennifer R Embry-Riddle Aeronautical University
Keywords
- AQP
- Advanced Qualification Program
- Machine Learning
- Artificial Intelligence
- Adaptive Learning
- Aviation Safety and Security
- Curriculum and Instruction
- Management and Operations
Citation: Herr, Jennifer R (2021). Implementing Artificial Intelligence and Machine Learning into Advanced Qualification Programs. Embry-Riddle Aeronautical University. Embry-Riddle Scholarly Commons ID oai:commons.erau.edu:jaaer-1890. https://commons.erau.edu/jaaer/vol30/iss1/6 ↗