NSF Award
2128950
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. <br/>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. <br/>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.<br/><br/>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.
