Episodic memory refers to an individual's memory for events that they have experienced in the past along with the associated contextual details. In order to more closely reflect the way that episodic memory functions in the real world, researchers and clinicians test episodic memory using virtual environments. However, these virtual environments introduce new interfaces and task demands that are not present in traditional methodologies. This dissertation investigates these environments through the lenses of Presence and Cognitive Load theories in order to unravel the ways that basic technological and task differences may affect memory performance. Participants completed a virtual task under High and Low Immersion conditions intended to manipulate Presence and Single-Task, Ecological Dual-Task and Non-Ecological Dual-Task conditions intended to manipulate cognitive load. Afterward they completed a battery of memory tasks assessing spatial, object, and feature binding aspects of episodic memory. Analysis through 2x3 ANOVA showed that performance for spatial memory is greatly improved by manipulation of Presence, where performance for object memory is improved by germane cognitive load. Exploratory analyses also revealed significant gender differences in spatial memory performance, indicating that improving Presence may offset the higher levels in male performance traditionally seen on spatial tasks. These results have practical implications for clinical memory assessment, as well as training paradigms and may serve to highlight the differences in the ways that memory is studied in the laboratory versus the way that it is employed in day-to-day life. Future studies based on this research should focus on linking these differences in memory performance to visuospatial and verbal strategies of memorization and determining whether the effects observed in this study replicate using other manipulations of presence and cognitive load.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-7453 |
| Date | 01 January 2019 |
| Creators | Barclay, Paul |
| 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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