SBIR Phase I: Virtual and Augmented Reality Enabled Personalized Manufacturing Training

该SBIR第一阶段项目将研究在制造和材料测试培训项目中应用虚拟现实（VR）和增强现实（AR）技术的可行性，以提高学术成就，加速学位进度，并促进更有效地使用昂贵的实验室设备。 根据2014年的统计数据，在美国，只有不到40%的学生进入STEM领域的大学，完成STEM学位。即使是那些完成学业的人，大多数人（超过60%）也需要比4年的名义时间长几年。为学生提供支持VR和AR的个性化制造实验室是一种很有前途的方法，可以提高学生的参与度，为他们未来的职业生涯做好准备，并拓宽学生的创新前景。正如美国理事会最近关于竞争力的报告所描述的那样，先进制造业对就业的乘数效应最大。为了使美国在这一领域获得竞争力，迫切需要一支训练有素的劳动力队伍，能够开发新的材料测试协议和制造工艺。该SBIR项目旨在开发技术，使教育部门能够利用VR和AR来加速培训。拟议的软件将通过试点测试进行评估。该项目所产生的技术和见解可能会在生命科学等其他领域得到应用。该研究的关键技术创新包括开发一种新型的高保真模块化虚拟对象模型，基于证据中心设计的定制任务模型，以及灵活地将联合收割机对象模型与任务模型相结合以快速开发适合于虚拟现实（VR）和增强现实（AR）的活动的方法装置.这些创新可以显著降低内容创建成本，并可能消除课堂教育和实践培训之间的界限，提供有效和无缝的教育体验。从长远来看，这些创新也可以广泛应用于其他领域的培训。该SBIR项目的总体目标是评估拟议的内容创建和学习分析系统的可行性，并将其应用于创建用于制造课程的创新内容。拟议的系统和内容将通过与工程专业学生的试点测试进行评估，以收集丰富的数据集，包括视频，传感器时间序列数据和模拟事件日志。数据分析将寻求学生成果（内容知识，参与度，对工程的态度，对学习工程的自我效能，产品的可用性的变化）和教师成果（对产品有用性的态度）的变化的证据。

This SBIR Phase I project will research the feasibility of applying virtual reality (VR) and augmented reality (AR) technologies in manufacturing and material testing training programs to increase academic achievement, accelerate progress toward degree and foster more effective use of expensive lab-equipment. According to 2014 statistics, in the United States, less than 40% of students entering college in STEM fields finish with a STEM degree. And even for those who finish, a majority (over 60% ) take several years longer than the nominal time of 4 years. Providing students with VR and AR enabled personalized manufacturing labs is a promising way to increase students' engagement and better prepare them for future careers as well as broaden students' outlook on innovation. As described in the recent US council report on competitiveness, advanced manufacturing has the largest multiplier effect on jobs. In order for the US to gain competitiveness in this sector, there is a pressing need for a trained workforce that is able to develop new materials testing protocols and manufacturing processes. This SBIR project aims to develop technologies that enable the education sector to leverage VR and AR to accelerate training. Proposed software will be evaluated through pilot testing. Technology and insights resulting from this project may find applications in other domains such as life sciences.Key technical innovations in this proposed research include the development of a novel high-fidelity modular virtual object model, customized task models based on evidence centered design, and methods to flexibly combine object models with task models to rapidly develop activities suitable for virtual reality (VR) and augmented reality (AR) devices. These innovations may significantly reduce the content creation cost and potentially dissolve the boundary between classroom education and hands-on training, providing an effective and seamless educational experience. In the long term, these innovations may also be applied broadly to training in other domains. The overarching goal of this SBIR project is to evaluate the feasibility of the proposed system for content creation and learning analytics and apply them to create innovative content for use in manufacturing courses. The proposed system and content will be evaluated via pilot testing with engineering students to collect rich datasets comprising videos, sensor time series data and simulation-event logs. Data analysis will seek evidence for changes in both students outcomes (changes in content knowledge, engagement, attitude towards engineering, self-efficacy towards learning engineering, usability of the product) and instructor outcomes (attitudes about the usefulness of the product).