The aviation industry faces increasing pilot training demands, and reliance on conventional Full Flight Simulators (FFS) limits training capacity. Virtual Reality (VR) offers scalable, remote training opportunities, but its role as a complement to FFS requires empirical validation. In collaboration with Singapore Airlines (SIA) instructor pilots, we developed a VR training prototype for a visual approach into Gimhae International Airport, emphasizing Competency-Based Training and Assessment (CBTA)-based Threat and Error Management (TEM). An empirical study with 39 SIA Boeing 737-MAX 8 type-rated first officers evaluated VR against FFS. An equivalence analysis showed that VR achieved performance outcomes comparable to FFS in 13 of the 16 Observable Behaviors (OBs) and across 4 Competencies. In addition, a comparative analysis indicated measurable performance improvements when VR was used to supplement FFS training. Our results suggest VR can meaningfully complement FFS in targeted competency areas, with future work required to assess its broader integration across additional scenarios and performance metrics.

In cooperative games that involve team-mates that are controlled by either a computer or another human player, is there a difference in how humans assign credit or blame? There has been some related work on computers as team-mates and credit/blame assignment, but there does not seem to have been work to show whether the belief that a team-mate is human or not affects this. A qualitative study was conducted, in which 16 participants played variations of a team-based game with one of four kinds of team-mates: human (real or perceived) or AI (real or perceived). The two main findings of this research are that the perception of whether a team-mate is human or computer results in different credit/blame assignment and results in inaccurate skill assessment.

Although there has been research suggesting that people will treat computers socially and even consider computers as team-mates, there does not seem to have been any research looking specifically at how the perception of team-mate identity affects game enjoyment and team-mate preference in real-time cooperative games. In order to study this question, a quantitative study was conducted in which 40 participants played a real-time, goal-oriented, cooperative game. During the study, all participants played the game twice: once with an AI team-mate and once with a "presumed" human team-mate (i.e., an AI team-mate that they believed was a human team-mate). Thus, the team-mate performance and behaviors were essentially the same for both conditions. Participants in the study showed a much higher preference for the "presumed" human team-mate, indicating significantly higher levels of enjoyment and cooperation during the game sessions with that team-mate. The results suggests that perceived identity is a strong moderator of game enjoyment.