B2: Learning Environments with Augmentation and Robotics for Next-gen Emergency Responders (LEARNER)

美国国家科学基金会融合加速器支持使用启发，基于团队的，多学科的努力，解决国家的重要性的挑战，并将产生交付价值的社会在不久的将来。更广泛的影响和潜在的社会效益，这个融合加速器第二阶段项目将产生基于技术的学习解决方案，可以支持和增强应急响应（ER）人员的性能和安全。学术研究人员，核心技术开发人员，利益相关者以及由行业和政府领导人组成的咨询委员会将聚集在一起，评估与人类增强技术（HAT）使用相关的机遇和挑战，这些技术可以改变ER工作的基础，使用启发的解决方案寻找过程，并以一种可转移到其他工作环境的方式。这将涉及开发和评估LEARNER（面向下一代应急响应人员的增强和机器人学习环境），这是一个具有物理，增强和虚拟现实组件的混合现实学习环境，供用户学习使用两种HAT类有效工作：动力外骨骼（EXO）和头戴式AR界面（AR）。我们的努力将有助于更好地将融合工作概念化，从而促进对人类与技术相互作用的理解;有助于为人类及其环境量身定制，优化和不断适应的系统;以及教育和终身学习，以创造必要的劳动力。我们的努力也将成为其他研究团体的典范，这些研究团体可以从工程，计算机科学，学习科学和人力资源开发等传统学科界限中受益。我们将通过领导一个国家人才生态系统理事会，一个合作智库组织，支持关于利用先进技术进行劳动力学习的科学研究活动，并组织关于技术驱动的学习科学和教育进步的Learn-X专题讨论会。人力资源开发。我们将开发和评估LEARNER的功能原型-一个创新的可访问的，模块化的，个性化的和可扩展的学习平台，以加速ER工作人员的技能和再技能，特别是在新兴的增强技术上，这些技术具有改变工作性质和提高效率、健康和福祉的巨大潜力。LEARNER将提供一个独特的训练模式，将生理学，神经学和行为学的学习标记纳入实时情景演变。拟议的虚拟和物理用户界面和交互技术将推进人机交互领域提供一个多感官的方法ER模拟和同步虚拟交互与物理环境和工作工件。此外，我们计划将这些HAT投入使用并开发一个有效的学习平台，这具有巨大的变革潜力，因为EXO和AR将使用户能够通过他们新扩展的身体和感知能力，在个人和团队层面制定新的工作策略。最后，我们的工作将通过创建一个可扩展和可复制的平台来促进学习，该平台将提高创新和新兴HAT的集成和采用速度，从而使不同工业部门的未来劳动力受益。我们的跨学科方法融合并增强了学习科学，计算机科学，虚拟和增强现实，人为因素，认知心理学和系统工程等学科的现有知识，以创建LEARNER平台，该平台集成了培训课程设计，创新和新兴技术实施，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The NSF Convergence Accelerator supports use-inspired, team-based, multidisciplinary efforts that address challenges of national importance and will produce deliverables of value to society in the near future.The broader impact and potential societal benefits of this Convergence Accelerator Phase II project will be to generate technology-based learning solutions that can support and augment the performance and safety of emergency response (ER) personnel. Academic researchers, core-technology developers, stakeholders, and an advisory board constituted of leaders from industry and government will come together to assess opportunities and challenges related to the use of human augmentation technologies (HATs) that can transform the process of foundational, use-inspired solution-finding for ER work, and in a way that is transferable to other work contexts as well. This will involve the development and evaluation of LEARNER (Learning Environments with Augmentation and Robotics for Next-gen Emergency Responders), a mixed-reality learning environment with physical, augmented, and virtual reality components, for users to learn to work effectively with two HAT classes: powered exoskeletons (EXO) and head-worn AR interfaces (AR). Our effort will contribute to better conceptualize convergence work that can foster the understanding of reciprocal human-technology interactions; contribute to systems that are tailored, optimized, and continuously adapted for humans and their environments; and education and lifelong learning to create the requisite workforce. Our effort will also serve as a model for other research communities that can benefit from working across traditional disciplinary boundaries in engineering, computer science, learning sciences, and human resource development. We will share our methods, learnings and findings with the ER community and the wider world by leading a National Talent Ecosystem Council, a collaborative think-tank organization, to support scientific research activities on workforce learning with advanced technologies and organizing Learn-X symposiums on the topic of technology-driven advances in learning-sciences and educational/human resource development.We will develop and evaluate a functional prototype of LEARNER – an innovative accessible, modular, personalized, and scalable learning platform to accelerate skilling and reskilling of ER workers, particularly on nascent augmentation technologies that have significant potential to change the very nature of work and improve efficiency, health, and well-being. LEARNER will provide a unique training paradigm by incorporating physiological, neurological, and behavioral markers of learning into real-time scenario evolution. The proposed virtual and physical user interfaces and interaction techniques will advance the human-computer interaction field by providing a multisensory approach for ER simulation and synchronized virtual interactions with physical environments and work artifacts. Furthermore, our plan to field these HATs and develop an effective learning platform has significant transformative potential as EXOs and AR will enable users to formulate new work strategies at the individual and team levels enabled by their newly extended physical and perceptual capabilities. Finally, our work will advance learning by creating a scalable and replicable platform that will increase the speed of integration and adoption of innovative and emerging HATs that benefit the future workforce across diverse industrial sectors. Our transdisciplinary approach converges and enhances the existing knowledge from the disciplines of learning science, computer science, virtual and augmented realities, human factors, cognitive psychology, and systems engineering to create the LEARNER platform that integrates training course design, innovative and emerging technology implementation, and new techniques of work.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.