The Student Experience With Varying Immersion Levels of Virtual Reality Simulation

Sharon L Farra1, Sherrill J Smith, Deborah L Ulrich

  • 1About the Authors Sharon L. Farra, PhD, RN, CNE, CHSE, is an associate professor, Wright State University College of Nursing and Health, Dayton, Ohio. Sherrill J. Smith, PhD, RN, CNL, CNE, and Deborah L. Ulrich, PhD, RN, ANEF, are professors, Wright State University College of Nursing and Health. The authors acknowledge the National League for Nursing for grant support in funding this research. In addition, they are grateful to Dr. Eric Hodgson for his deployment of the virtual reality simulation and graduate research assistant Kelly Hanlon. For more information, contact Dr. Farra at Sharon.farra@wright.edu.

Related Concept Videos

Student t Distribution01:31

Student t Distribution

The population standard deviation is rarely known in many day-to-day examples of statistics. When the sample sizes are large, it is easy to estimate the population standard deviation using a confidence interval, which provides results close enough to the original value. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
The Student t distribution was developed by William S. Goset (1876–1937) of the...
14.3K
Virtual Work01:20

Virtual Work

The principle of virtual work states that if a body is in static and dynamic equilibrium, then the sum of all the virtual work done by all external forces and couple moments for any given virtual displacement must be zero.
In static equilibrium, a body can experience an imaginary or virtual movement, such as displacement or rotation. The virtual work done by a force is equal to the dot product of force and virtual displacement in the direction of the force. When it comes to virtually rotating a...
1.4K
Gradually Varying Flow01:29

Gradually Varying Flow

Gradually varying flow (GVF) in open channels describes situations where water depth changes slowly along the channel due to factors like non-uniform bed slope, channel shape variations, or obstructions. This flow type occurs when the depth adjusts gradually to balance gravitational forces, shear forces, and energy requirements, resulting in a low rate of depth change.Characteristics of Gradually Varying FlowGVF is commonly observed in natural streams, rivers, and canals, where flow depth...
454
Rapidly Varying Flow01:24

Rapidly Varying Flow

Rapidly varying flow (RVF) in open channels is characterized by abrupt changes in flow depth over a short distance, with the rate of depth change relative to distance often approaching unity. These flows are inherently complex due to their transient and multi-dimensional nature, making exact analysis difficult. However, approximate solutions using simplified models provide valuable insights into their behavior.Key Features of Rapidly Varying FlowRVF is commonly observed in scenarios involving...
518
Microsoft Excel: Student's t-Test01:25

Microsoft Excel: Student's t-Test

Student's t-test in Microsoft Excel is a statistical method used to compare the means of two groups to determine if they are significantly different from each other. It's commonly used to evaluate hypotheses, such as testing whether a treatment has an effect compared to a control group. Excel provides built-in functions to perform t-tests, making it accessible for users needing to conduct basic statistical analysis.
To conduct a t-test in Excel, use the T.TEST function or the "Data...
1.7K
The Stanford Prison Experiment03:20

The Stanford Prison Experiment

The famous and controversial Stanford Prison Experiment, conducted by social psychologist Philip Zimbardo and his colleagues at Stanford University, demonstrated the power of social roles, social norms, and scripts.
24.8K