Date of Award
Doctor of Philosophy (PhD)
Computational Modeling & Simulation Engineering
Modeling and Simulation
Frederic D. McKenzie
Ahmed K. Noor
There has been an increase in the use of virtual reality (VR) technology in the education community since VR is emerging as a potent educational tool that offers students with a rich source of educational material and makes learning exciting and interactive. With a rise of popularity and market expansion in VR technology in the past few years, a variety of consumer VR electronics have boosted educators and researchers’ interest in using these devices for practicing engineering and science laboratory experiments. However, little is known about how such devices may be well-suited for active learning in a laboratory environment. This research aims to address this gap by formulating a utility framework to help educators and decision-makers efficiently select a type of VR device that matches with their design and capability requirements for their virtual laboratory blueprint. Furthermore, a framework use case is demonstrated by not only surveying five types of VR devices ranging from low-immersive to full-immersive along with their capabilities (i.e., hardware specifications, cost, and availability) but also considering the interaction techniques in each VR device based on the desired laboratory task. To validate the framework, a research study is carried out to compare these five VR devices and investigate which device can provide an overall best-fit for a 3D virtual laboratory content that we implemented based on the interaction level, usability and performance effectiveness.
In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
"A Utility Framework for Selecting Immersive Interactive Capability and Technology for Virtual Laboratories"
(2019). Doctor of Philosophy (PhD), Dissertation, Computational Modeling & Simulation Engineering, Old Dominion University, DOI: 10.25777/vxvt-y991