Artificial Cognitive Systems and Aviation training

Open Access
Article
Conference Proceedings
Authors: Abner Del Cid FloresDimitrios ZiakkasBrian G Dillman

Abstract: The research objectives are to (1) provide a complete assessment of extended reality technologies and (2) discuss the viability of these technologies for use in US college aviation training programs.The field of educational services is one of the many that can benefit from utilizing extended reality technology due to its versatility. Learning and general performance of student pilots and flight trainees can benefit from applying extended reality technologies in flight training, which can be advantageous when using these technologies. We examine the utilization of XR technologies by looking at them from an educational theoretical framework and analyzing their applicability across several industries and simulations in Purdue Artificial Intelligence Laboratory. A comprehensive literature review resulted in four subtopics, which are as follows: educational theoretical foundation, XR technologies across industries; XR technologies in education; and XR technologies in aviation.Results show that the use of XR technologies has the potential for enhancing learning and performance in safe flight instruction environments, a possible reduction in student pilot turnover mainly due to the elimination of the fear factor involved during initial training when compared to flying in the actual airplane, and an overall low cost for both flight training organizations and trainees due to the high levels of portability. These findings led us to propose using XR technologies as having the potential to enhance learning and performance in safe flight instruction environments.A comprehensive understanding of the possibilities offered by XR technology is necessary for the continuation of aeronautical psychology research offered in Purdue AI laboratory.

Keywords: XR technologies, aviation training, artificial cognitive systems, aviation management

DOI: 10.54941/ahfe1002838

Cite this paper:

Downloads
381
Visits
1189
Download