Abstract

This pilot study examines the impact of combined immersion and embodiment on learning and emotional outcomes. The results are intended to better enable U.S. Army senior leaders to decide if dismounted infantry Soldiers would benefit from a more immersive simulation-based training capability. The experiment's between-subject design included a sample of 15 participants randomly assigned to one of three system configurations representing different levels of combined immersion and embodiment. The control group was a typical desktop, and the two experimental groups were a typical configuration of a Virtual Reality headset (VR) and a novel configuration using VR supported by an omnidirectional treadmill (ODT) for full body exploration and interaction. Unique from similar studies, this pilot study allows for an analysis of the Infinadeck ODT's impact on learning outcomes and the value of pairing tasks by type with various levels of immersion. Each condition accessed the same realistically modeled geospatial virtual environment (VE), the UCF Virtual Arboretum, and completed the same pre and post VE-interaction measurement instruments. These tests included complicated and complex information. Declarative information involved listing plants/communities native to central Florida (complicated tasks) while the situational awareness measurement required participants to draw a sketch map (complex task). The Kruskal-Wallis non-parametric statistical test showed no difference between conditions on learning outcomes. The non-parametric Spearman correlation statistical test showed many significant relationships between the system configuration and emotional outcomes. Graphical representations of the data combined with quantitative, qualitative, and correlational data suggest a larger sample size is required to increase power to answer this research question. This study found a strong trend which indicates learning outcomes are affected by task type and significant correlations between emotions important for learning outcomes increased with combined immersion and embodiment.

Notes

If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu

Graduation Date

2023

Semester

Spring

Advisor

Harrington, Maria

Degree

Master of Science (M.S.)

College

College of Engineering and Computer Science

Department

School of Modeling, Simulation, and Training

Degree Program

Modeling & Simulation

Format

application/pdf

Identifier

CFE0009567; DP0027580

URL

https://purls.library.ucf.edu/go/DP0027580

Language

English

Release Date

May 2023

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

Download

Share

COinS