| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | August 24, 2021 |
| Latest Amendment Date: | June 26, 2023 |
| Award Number: | 2128749 |
| Award Instrument: | Standard Grant |
| Program Manager: |
David Corman
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | October 1, 2021 |
| End Date: | August 31, 2023 (Estimated) |
| Total Intended Award Amount: | $39,998.00 |
| Total Awarded Amount to Date: | $39,998.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
220 PAWTUCKET ST STE 400 LOWELL MA US 01854-3573 (978)934-4170 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
1 University Ave. Lowell MA US 01854-3692 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | FW-HTF Futr Wrk Hum-Tech Frntr |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
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.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
This planning grant investigated the design of applications for Augmented Reality (AR) systems with the objectives of engaging a multi-disciplinary group of content developers, stakeholders and AR system users from varied backgrounds. The research utilized a physical system that incorporated a table-top conveyor belt, two types of objects that were conveyed on the belt, multiple sensing devices at various locations of the system, and an embedded computing system that processed the sensor data. This system represents some of the features of cyber-physical systems and supports the design of controlled experiments that users can experience through the AR interaction.
The outcomes of this research include a novel design of the AR system software that resides on top of the Unity game engine and supports the rendering of audio, video and text-based information created by authors seeking to enhance the user’s AR experience with just-in-time informatics. Referred to as a No-Code AR System (NCARS), this allows content developers to be agnostic to the complex coding requirements that are often a barrier to user-specific application design.
A second outcome that promotes the goal of engaging authors, users, system and software engineers is in representing the NCARS structure and behavior using model-based systems engineering approaches and the systems modeling language. This graphical representation of the system design and its functions can be accessible to experts from other domains who are interested in creating applications and using the AR system.
The third outcome of this research was the collaboration sought with potential AR system users and engaging them in focus groups. Focus groups conducted before and after they interacted with the AR system provided data on the user’s prior experience with technology and recommendations for improving the AR system support while conducting experiments with the physical systems and associated task-based scenarios that were designed by researchers. These recommendations were reported back to the software engineers by the social scientist who conducted the focus groups. A key outcome was identifying the need and potential approach for integrating an interactive conversation with the user as they conduct the AR assisted tasks, eventually supporting a collaborative mode of conversation among all AR users as they conduct the tasks simultaneously.
A key goal of the research was to engage a group of interdisciplinary researchers as collaborators in the human-centric design of AR applications. This has been accomplished by forming an inter-institutional team that involves health sciences, engineering and computer science researchers at University of Massachusetts Lowell, University of the District of Columbia, University of Detroit Mercy and Vanderbilt University.
Last Modified: 12/22/2023
Modified by: Kavitha Chandra
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