Collaborative Research: FW-HTF-P: Participatory Design Process for Co-Creating Augmented Reality Based Education and Training Systems

这项调查探讨了人工智能辅助增强现实（AR）系统在加强STEM教育，改善代际沟通和跨学科知识共享方面的作用。未来的科学和工程教育工作要求学习者获得强大的学科基础，设计技能和系统思维技能，同时实现他们在解决大型，复杂的社会问题中的作用。专业劳动力中的成人学习者成熟，在某个领域拥有强大的设计和生产技能，需要支持将其技能转移到新的工作环境中。这些进步对于解决我们面临的人才缺口是必要的。这项调查将利用商业AR设备，并探索充分利用这些功能所必需的系统和过程基础。在这个规划阶段，我们将组建一个由教育工作者，主题专家和社会技术系统工程师组成的综合团队，以设计STEM教育和劳动力培训环境中的工作流程。将设计一个原型系统，以协助拟订要求和系统结构，并充分探讨可扩展部署的技术选择。AR设备已用于教育和培训活动。这项调查的重点是开发AR内容所需的系统和流程，并将新功能整合到STEM教育和劳动力培训中。这些能力将为高中生掌握科学实验室活动提供新的途径，高级研究生快速掌握新的内容领域，为在涉及机械的环境中工作的新员工提供培训，指导和支持，培训和支持提供者和患者的健康和康复计划，支持医疗服务并提供创新的医疗保健提供模式。由于新技能的半衰期约为两年，而超过42%的人预计会在两年内从事需要新技能的工作，因此，这一制度的实施将使工人能够相对容易地从一种工作环境转移到另一种工作环境。该团队从一个强大的AR系统框架开始，该框架将支持内容数据库、指定指令序列的工具、多功能的演示模式集合和会话交互。提出了一种新的大学，工业和社区利益相关者之间的合作模式。该团队将调整和实施的工具，从预先行动研究，社区为基础的预先行动研究，和德尔菲方法，以磨练研究问题和设计工作流程流程。这个奖项反映了NSF的法定使命，并已被认为是值得的支持，通过评估使用基金会的智力价值和更广泛的影响审查标准。

This investigation explores the role of AI-Assisted Augmented Reality (AR) systems in strengthening STEM education, improving inter-generational communications, and sharing knowledge across disciplines. Future work in science and engineering education demands that learners acquire strong disciplinary foundations, design skills, and systems-thinking skills while realizing their roles in addressing large, complex, societal problems. Adult learners in the professional workforce are mature, have strong design and production skills in a domain, and need support to transfer their skills to new work contexts. Such advances are necessary to address the talent-gap that confronts us. This investigation will utilize commercial AR devices and explore the systems and process foundations that are necessary to fully utilize such capabilities. In this planning phase, we will assemble an integrative team of educators, subject-matter experts and socio-technical systems engineers to design workflow processes in STEM education and workforce training contexts. A prototype system will be designed to aid in the process of formulating requirements, systems architecture and fully explore the technology options for scalable deployment. AR devices have been used in education and training activities. This investigation focuses on the systems and processes that are necessary to develop the AR content and integrate the new capabilities into STEM education and workforce training. The capabilities will offer new avenues for high-school students to master their science-lab activities, advanced graduate students to quickly master new content areas, provide training, orientation and support for new employees who work in environments that involve machinery, train and support providers and patients in health and rehabilitation programs, support medical services and offer innovative modes for health care delivery. Given that the half-life of new skills is about two years, and over 42% of the people are expected to be in jobs that require new skills in two years, the availability of such systema will make enable workers to move from one context of work to another with relative ease. The team is starting with a robust AR system framework that will support a content database, tools for specifying sequences of instruction, a versatile collection of presentation modalities, and conversational interaction. A novel model for collaborations between university, industry and community stakeholders is proposed. The team will adapt and implement tools from Participatory Action Research, Community-Based Participatory Research, and the Delphi Method to hone research questions and design workflow processes.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.