Ensuring effectiveness of training programs has been a dominant theme in the training industry, and is constantly evolving with the steady incorporation of emerging technology. This field study offers an investigation into the intersection between the applied and research world, and examines the practicality of recommended best practices for implementing synthetic learning environments (SLEs) in the military. Specifically, cognitive load has been identified as a significant factor in influencing the effectiveness of training programs. Research on this topic has focused on utilizing the affordances of SLEs to decrease cognitive load imposed by the material and system in order to allow for more cognitive resources to be allocated towards schema construction and automation. Therefore, this study was derived from a need to ensure that the introduction of SLEs into training programs did not hinder learning or training transfer by comparing the performance outcome measures from two SLEs, Virtual BattleSpace 3 (VBS3) and the Military OpenSimulator Enterprise Strategy (MOSES). Based on concepts of cognitive load, it was possible that any group differences could be explained by the varying levels of cognitive load imposed by either system. Furthermore, the specific system could influence the strength of the effect of cognitive load on performance measures. A conditional process analysis model was constructed from the theorized relationships, and the bootstrap method was used to analyze the model. Research findings indicated no support, and discussions delved into possible explanations for results of the study, limitations, and recommendations for future research. While the analyses were nonsignificant, this was the first study investigating the difference between the VBS3 and MOSES platform, and indicated no difference in impacting performance. Additionally, because MOSES is a free, open source platform, this study could support industries that are looking for cost-effective methods to expand training programs in the direction of SLEs.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-6882 |
| Date | 01 January 2018 |
| Creators | Goh, Joelene |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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