The Journal of Aviation/Aerospace Education & Research (JAAER) is a double-blind, peer-reviewed scholarly publication that provides a free, open-access platform for educators and researchers in Aviation and Aerospace Academia and Industry. We publish innovative scholarship on the integration and discovery of scientific knowledge and its application to Aviation and Aerospace. Our journal has an esteemed panel of reviewers from well-respected academic, industry, and government institutions.
We invite submissions covering all dimensions of Aviation/Aerospace research and education; more specifically, we encourage submissions in original research, industrial application and design integration, education and workforce development, and reviews of important issues in Aviation and Aerospace. Our journal is inter- and cross-disciplinary in nature, covering a wide scope of areas.
- Aviation Safety
- Aviation Psychology, Human Factors and Ergonomics
- Aviation/Aerospace Systems Design, integration, and Optimization
- Modeling and Simulation in Aviation
- Data Analytics and Statistical Analysis
- Aviation Business
- Aviation Education and Workforce Development
- Flight Training
- Aviation Maintenance
- Aviation Meteorology
- Diversity and Sustainability in Aviation
- Commercial Space Operations
- Uncrewed Aircraft Systems (UAS)
- Social and Legal Issues in Aviation
Volume 33, Number 4
Special Issue: Artificial Intelligence in Aviation
Aviation Training & Technology
Guest Editors' Introduction to Special Issue: Artificial Intelligence in Aviation
Carla A. Hackworth Ph.D., Yongxin (Jack) Liu Ph.D., and Chien-tsung Lu Ph.D.
Articles
Computational Cognitive Modeling of Pilot Performance in Pre-flight and Take-off Procedures
Rongbing Xu M.A.Sc, Shi Cao Ph.D., Suzanne K. Kearns Ph.D., Ewa Niechwiej-Szwedo Ph.D., and Elizabeth Irving Ph.D.
Identifying Aircraft Damage Mitigating Factors with Explainable Artificial Intelligence (XAI): An Evidence-Based Approach to Rule-Making for Pilot Training Schools
Ryan Zierman B.S., A&P and Burak Cankaya D.Eng.
Machine Learning - Hail Awareness Spatial Analysis Toolkit (HASAT)
Haoruo Fu M.S., Joseph P. Hupy Ph.D., Chien-tsung Lu Ph.D., and Zhenglei Ji M.S.
An Exploratory Single-Case Study Unveiling the Promise of Artificial Intelligence in Aviation Education
Jorge L. D. Albelo Ph.D. and Stacey McIntire M.S., M.A.
A New Trajectory in UAV Safety: Leveraging Reinforcement Learning for Distance Maintenance Under Wind Variations
Xiaolin Xu M.S. and Jeffrey Sun
Human-AI Teams in Aviation: Considerations from Human Factors and Team Science
Jenna Korentsides M.S., Joseph R. Keebler PhD, Crystal M. Fausett PhD, Sabina M. Patel M.S., and Elizabeth H. Lazzara PhD
Low-Resource Automatic Speech Recognition Domain Adaptation – A Case-Study in Aviation Maintenance
Nadine Amin M.S., Tracy L. Yother Ph.D., and Julia Rayz Ph.D.
An Enhanced Deep Autoencoder for Flight Delay Prediction
Desmond B. Bisandu PhD, Dan Andrei Soviani-Sitoiu MSc, and Irene Moulitsas PhD
Artificial Intelligence in Aviation: A Path Analysis
Leila Halawi DBA, Mark D. Miller Ed.D., and Sam J. Holley Ph.D.
