Keywords
Video Game Experience, Virtual Environments, Cognitive Skills, Artificial Intelligence
Abstract
This research empirically investigated the Video Game Experience Measure (VGEM), which captures general aspects of video game experience in a five-factor model, tapping factors such as frequency and intensity of gameplay, and self-reported confidence in specific game-related skills as well as more general self-efficacy. The VGEM captures facets of video game experience that have been represented in prior research, and which have individually been found to relate to players’ gameplay performance. These factors of individuals’ video game experience have been found to introduce notable variance in game-based experimentation, but the extent to which each aspect impacts performance has been sparsely researched. This study used well-established basic cognitive research tasks to investigate whether the VGEM is able to discriminate between individuals’ prior experience along different factors or dimensions of video gameplay, and whether the measure is able to account for variance in cognitive task performance on three cognitive tasks, including Fitts’ Law task, a measure of hand-eye coordination and reaction time, Task-Switching and Mixing task, a measure of cognitive flexibility, and Stroop task, a measure of attention and cognitive inhibition. Additionally, demographic factors such as sex and age are investigated as they relate to cognitive task performance. This study’s participants were undergraduate students at the University of Central Florida who volunteered to participate through the UCF Psychology SONA system recruitment system in exchange for course credit, the final dataset contained 295 participants. Results showed that the Video Game Experience Measure factors explained a significant proportion of the variance in cognitive task performance in this sample and were generally more predictive of performance than demographic factors. Findings from this research demonstrate that the Video Game Experience Measure may be used to more accurately account for variance in novel game-based task performance in experimental study samples, provide insight into factors related to aspects of video game experience, and elucidate differences between, in addition to non-players, types of players that emerge from combinations of demographic, motivational, and experiential factors.
Completion Date
2024
Semester
Summer
Committee Chair
Jentsch, Florian
Degree
Doctor of Philosophy (Ph.D.)
College
College of Engineering and Computer Science
Department
School of Modeling, Simulation, and Training
Degree Program
Modeling and Simulation
Format
application/pdf
Identifier
DP0028480
URL
https://purls.library.ucf.edu/go/DP0028480
Language
English
Release Date
8-15-2025
Length of Campus-only Access
1 year
Access Status
Doctoral Dissertation (Campus-only Access)
Campus Location
Orlando (Main) Campus
STARS Citation
Williams, Jessica L., "Informing a Comprehensive Player Profile Model Through the Development of a Video Game Experience Measure to Support Theory of Mind in Artificial Social Intelligence" (2024). Graduate Thesis and Dissertation 2023-2024. 275.
https://stars.library.ucf.edu/etd2023/275
Accessibility Status
Meets minimum standards for ETDs/HUTs
JWilliams
Restricted to the UCF community until 8-15-2025; it will then be open access.