Date of Award


Access Type

Dissertation - Open Access

Degree Name

Doctor of Philosophy in Aviation


College of Aviation

Committee Chair

Dothang Truong, Ph.D.

First Committee Member

David Cross, Ph.D.

Second Committee Member

Robert L. Thomas, Ph.D.


Immersive simulation technology has been incorporated into numerous training environments, including medicine, engineering, and marketing. The aviation industry, in particular, has a history of embracing technology to enhance training and has especially regulated the requirements of devices for flight training. Virtual reality (VR) is the newest technology being adapted for training purposes. Many educational institutions training providers are incorporating virtual environments (VE) and VR systems into curricula and training programs to expand educational opportunities, enhance learning, promote deep cognitive learning, and leverage the abilities of a generation of students who have adopted technology from an early age.

As VR is adopted for educational purposes, researchers are conducting experiments to learning with the VE occurs at an equal or greater level than in the real world. However, research surrounding students’ perceptions of the technology and intentions to use it for training has been neglected. This is especially true in the realm of aviation and flight training. The goal of this research was to determine the factors that influence aviation students’ intention to use VR for flight training. An extended Technology Acceptance Model (TAM) was developed that incorporates elements of the Theory of Planned Behavior (TPB); factors derived from relevant, validated extended TAMs; and new factors that are theorized to impact use intention. These factors are related to aviation education, the use of VR technology in training environments, and using VR for flight training. The new model may explain flight students’ acceptance of VR for flight training as well as their intent to use the technology.

A quantitative research method with a cross-sectional survey design was utilized. Descriptive statistical analysis, a confirmatory factor analysis (CFA), and a structural equation modeling (SEM) process were employed. Data were collected from aviation students enrolled in FAA-approved Part 141 pilot schools in early 2020 using a survey design. Results indicated a good model fit to answer the three research questions of the study. There were 14 hypotheses in the original model. Although one was removed, an additional relationship was discovered, validated, and added to the model. Nine of the hypotheses were supported. Eight of the nine predictor factors of the model were determined to directly or indirectly impact behavioral intention (BI). The original TAM factors had the strongest relationships. Relationships between factors particularly relevant to VR technology and aviation training were also supported.

The results of the study fill a gap in the research surrounding the use of VR for flight training and the influencing factors of behavioral intention. The model may also be modified for other educational and training environments as well as other forms of immersive simulation technology.