Physical and Cognitive Effects of Virtual Reality Integrated Training

Stone, Richard; Watts, Kristopher Patrick; Zhong, Peihan; Wei, Chen-Shuang

doi:10.1177/0018720811413389

Cited by 51 publications

(70 citation statements)

References 29 publications

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“…Based on results of transfer of training with virtual reality and welding [6,7], and based on discussion with the local Sheriff's department, a reduction in number of bullets needed to train police officers of 50% could be considered a conservative amount. While real-world application and virtual application are not a direct comparison, it has been proven to provide a positive transfer of training and is something that could be done in the future.…”

Section: Discussionmentioning

confidence: 99%

“…Instructional technology directs cognitive learning processes. Augmented reality and virtual reality have been proven to be effective instructional technologies with the ability to display a transfer of training demonstrated in previous work with their use of virtual reality integrated weld training [6,7].…”

Section: Transfer Of Trainingmentioning

confidence: 99%

“…A lot of devices have been developed to mitigate environmental impact and hardware impact on accuracy, but few exist to assist in training humans with handguns. The human factors that effect aim include: (1) fatigue [2], (2) experience [3,4], (3) body sway [1], (4) heart rate [9], and (5) arm tremors [7].…”

Section: Introductionmentioning

confidence: 99%

“…Before the ARCTiC LawE, there was only one exoskeleton that is designed for handgun training-the MAXFAS, a mobile arm exoskeleton for firearm aim & Thomas M. Schnieders tms@iastate.edu Richard T. Stone rstone@iastate.edu stabilization [7], designed and validated by Dan Baechle as part of his Master of Science research at the University of Delaware. Much of Baechle's research focused on manufacturing the exoskeleton out of carbon fiber and developing an algorithm that allowed for an intended motion while suppressing natural tremors.…”

Section: Introductionmentioning

confidence: 99%

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ARCTiC LawE: An Upper-Body Exoskeleton for Firearm Training

et al. 2017

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The Armed Robotic Control for Training in Civilian Law Enforcement, or ARCTiC LawE, is an upperbody exoskeleton designed to assist civilian, military, and law enforcement personnel in accurate, precise, and reliable handgun techniques. This exoskeleton training utilizes a laser-based handgun with similar dimensions, trigger pull, and break action to a Glock Ò 19 pistol, common to both public and private security sectors. The paper aims to train and test subjects with no handgun training/experience both with and without the ARCTiC LawE and compare the results of accuracy, precision, and speed. Ultimately, the exoskeleton greatly impacts sensory motor learning, and the biomechanical implications are confirmed via both performance and physiological measurements. The researchers believe the ARCTiC LawE is a viable substitute for training with live-fire handguns in order to reduce the cost of training time and munitions. They also believe the ARCTiC LawE will increase accuracy and precision for typical law enforcement and military live-fire drills. Additionally, this paper increases the breadth of knowledge for exoskeletons as a tool for training.

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Section: Discussionmentioning

confidence: 99%

Section: Transfer Of Trainingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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ARCTiC LawE: An Upper-Body Exoskeleton for Firearm Training

et al. 2017

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“…Nevertheless, the real aim of a training effectiveness analysis is to show the pertinence and usefulness of a VR/MR tool as part of a training programme with specific aims [8,25,27,42]. In line with that, the effectiveness assessment is the process by which researchers could identify the shortfalls and the possible customizations of training tool for satisfying the needs of an organization [20,30,43].…”

Section: Introductionmentioning

confidence: 99%

Empirical evidence, evaluation criteria and challenges for the effectiveness of virtual and mixed reality tools for training operators of car service maintenance

Borsci

Lawson

Broome

2015

Computers in Industry

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A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription. AbstractThe debate on effectiveness of virtual and mixed reality (VR/MR) tools for training professionals and operators is long-running with prominent contributions arguing that there are several shortfalls of experimental approaches and assessment criteria reported within the literature. In the automotive context, although car-makers were pioneers in the use of VR/MR tools for supporting designers, researchers started only recently to explore the effectiveness of VR/MR systems as mean for driving external operators of service centres to acquire the procedural skills necessary for car maintenance processes. In fact, from 463 journal articles on VR/MR tools for training published in the last thirty years, we identified only eight articles in which researchers experimentally tested the effectiveness of VR/MR tools for training service operators' skills. To survey the current findings and the deficiencies of these eight studies, we use two main drivers: i) a well-known framework of organizational training programmes, and ii) a list of eleven evaluation criteria widely applied by researchers of different fields for assessing the effectiveness of training carried out with VR/MR systems. The analysis that we present allows us to: i) identify a trend among automotive researchers of focusing their analysis only on car service operators' performance in terms of time and errors, by leaving unexplored important pre-and post-training aspects that could affect the effectiveness of VR/MR tools to deliver training contents -e.g., people skills, previous experience, cibersickness, presence and engagement, usability and satisfaction and ii) outline the future challenges for designing and assessing VR/MR tools for training car service operators.

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