ABSTRACT
Extended reality has long been utilized in the games industry and is emergent for pilot training in the military and commercial airline sectors. This paper follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to present a systematic quantitative literature review (SQLR) on the use of extended reality in flight simulators. It also encompasses recent studies of teaching and learning in immersive, virtual environments in non-aviation disciplines. The review identified 39 papers spanning all areas of the virtuality continuum across academic, commercial, and military aviation sectors, as well as engineering and medicine. The SQLR found that extended reality in flight simulators is being introduced in the commercial and military aviation sectors. However, within academia, hardware constraints have hindered the ability to provide positive empirical evidence of simulator effectiveness. While virtual reality may not replace traditional flight simulators in the near future, the technology is available to supplement classroom training activities and some aspects of simulator procedure training with promising cognitive learning outcomes. However, its usefulness as a mechanism of skills transfer to the real world has not been evaluated, highlighting numerous research opportunities.
ABSTRACT
Research into expertise is relatively common in cognitive science concerning expertise existing across many domains. However, much less research has examined how experts within the same domain assess the performance of their peer experts. We report the results of a modified think-aloud study conducted with 18 pilots (6 first officers, 6 captains, and 6 flight examiners). Pairs of same-ranked pilots were asked to rate the performance of a captain flying in a critical pre-recorded simulator scenario. Findings reveal (a) considerable variance within performance categories, (b) differences in the process used as evidence in support of a performance rating, (c) different numbers and types of facts (cues) identified, and (d) differences in how specific performance events affect choice of performance category and gravity of performance assessment. Such variance is consistent with low inter-rater reliability. Because raters exhibited good, albeit imprecise, reasons and facts, a fuzzy mathematical model of performance rating was developed. The model provides good agreement with observed variations.
