CAREER: Leveraging the Virtualness of Virtual Reality for More-Effective Training
职业:利用虚拟现实的虚拟性进行更有效的培训
基本信息
- 批准号:2021607
- 负责人:
- 金额:$ 27.32万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-08-08 至 2023-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This research takes a new approach to computer-based virtual reality (VR) training by leveraging the virtualness of VR to provide training solutions not possible in the real world. The aim is to develop VR techniques that are more effective and more time-efficient for training than real-world exercises and VR systems that emulate them. To demonstrate the general effectiveness of these new VR training techniques, the research focuses on two training domains: (1) Robotic operating room tasks for non-surgeon team members, including preoperative setup, intraoperative tasks, and postoperative cleanup. (2) Pre-shift inspections of off-highway trucks, which include walk-around inspections, mounting the vehicle, and in-cab inspections. Formative expert reviews, studies comparing the new techniques to traditional VR training versions, and real-world validation studies will be used to determine the effectiveness and efficiency of the techniques. Educational activities include a graduate VR course, research experiences for undergraduates, a summer research program for underrepresented high school students, an annual VR summer camp for high and middle school students, and the creation of online video tutorials for VR development to support formal and informal learning.A new framework for designing and analyzing VR training techniques has been developed to facilitate this research, the Framework for Altering Fidelity to Influence Memory. It connects two concepts, system fidelity and working memory. System fidelity is the objective degree of exactness with which real world experiences are reproduced by a VR system. Working memory is the temporal activation of short-term or long-term perceptual, cognitive, and motor memory networks in the mind of the human user. The premise of the framework is to manipulate an aspect of system fidelity to help a stage of working memory, which in turn should improve the effectiveness of training. Six novel VR techniques, based on approaches identified with this framework, will be developed and investigated: (1) causation signaling, (2) sensory accents, (3) situational dramatization, (4) error instigation, (5) object conjuration, and (6) regulated biomechanics. For example, the causation signaling method is to purposefully alter time and physics to convey the cause-and-effect relationship between an event and its consequence. Time warping is a causation signaling technique in which the training scenario can be fast-forwarded after an error to the resulting consequence and then rewound back to the decision point just before the error. This technique will convey to the user the cause-and-effect relationship between the error and resulting consequence, in addition to allowing the user to correct the mistake.
这项研究采用了一种基于计算机的虚拟现实 (VR) 培训的新方法,利用 VR 的虚拟性提供现实世界中不可能的培训解决方案。目的是开发比现实世界的练习和模拟它们的 VR 系统更有效、更省时的 VR 技术。为了证明这些新的 VR 培训技术的总体有效性,该研究重点关注两个培训领域:(1)非外科医生团队成员的机器人手术室任务,包括术前设置、术中任务和术后清理。 (2)非公路卡车班前检查,包括巡视检查、装车检查和驾驶室内检查。形成性专家评审、新技术与传统 VR 训练版本的比较研究以及现实世界的验证研究将用于确定这些技术的有效性和效率。 教育活动包括研究生 VR 课程、本科生研究经验、针对代表性不足的高中生的暑期研究计划、针对高中生和中学生的年度 VR 夏令营,以及为 VR 开发创建在线视频教程以支持正式和非正式活动为了促进这项研究,我们开发了一个用于设计和分析 VR 训练技术的新框架,即改变保真度以影响记忆的框架。 它连接了两个概念:系统保真度和工作记忆。系统保真度是 VR 系统再现现实世界体验的客观精确程度。工作记忆是人类用户头脑中短期或长期感知、认知和运动记忆网络的时间激活。该框架的前提是操纵系统保真度的一个方面来帮助工作记忆的一个阶段,从而提高训练的有效性。基于该框架确定的方法,将开发和研究六种新颖的 VR 技术:(1) 因果信号,(2) 感官重音,(3) 情境戏剧化,(4) 错误煽动,(5) 物体召唤,以及(6)调节生物力学。 例如,因果信号方法是有目的地改变时间和物理来传达事件与其后果之间的因果关系。 时间扭曲是一种因果信号技术,其中训练场景可以在错误之后快进到结果结果,然后回退到错误之前的决策点。除了允许用户纠正错误之外,该技术还将向用户传达错误与结果之间的因果关系。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Ryan McMahan其他文献
Ryan McMahan的其他文献
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{{ truncateString('Ryan McMahan', 18)}}的其他基金
Collaborative Research: Advancing Quantum Education by Adaptively Addressing Misconceptions in Virtual Reality
合作研究:通过适应性地解决虚拟现实中的误解来推进量子教育
- 批准号:
2302816 - 财政年份:2023
- 资助金额:
$ 27.32万 - 项目类别:
Standard Grant
CCRI: Planning-C: Capturing and Logging Ecological Virtual Experiences and Reality (CLEVER)
CCRI:Planning-C:捕捉和记录生态虚拟体验和现实(CLEVER)
- 批准号:
2232448 - 财政年份:2023
- 资助金额:
$ 27.32万 - 项目类别:
Standard Grant
Collaborative Research: CCRI: Planning: InfraStructure for Photorealistic Image and Environment Synthesis (I-SPIES)
合作研究:CCRI:规划:真实感图像和环境合成的基础设施 (I-SPIES)
- 批准号:
2120240 - 财政年份:2021
- 资助金额:
$ 27.32万 - 项目类别:
Standard Grant
CAREER: Leveraging the Virtualness of Virtual Reality for More-Effective Training
职业:利用虚拟现实的虚拟性进行更有效的培训
- 批准号:
1552344 - 财政年份:2016
- 资助金额:
$ 27.32万 - 项目类别:
Continuing Grant
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