2019 — 2020 |
Clegg, Benjamin [⬀] Cleary, Anne (co-PI) [⬀] Rhodes, Matthew Ortega, Francisco (co-PI) [⬀] Heggestad, Eric (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Fw-Htf-P: Optimizing Long-Term Human Performance in Future Work @ Colorado State University
Wearable systems, for example smart watches and smart glasses, are important emerging technologies for the future of work. When such systems are coupled with automation that supports and guides performance, they offer tremendous opportunities for American companies, but also might create challenges for their workers. Optical, see-through displays from wearable devices like smart glasses or head-mounted displays can project images while still allowing the user to see through them. The resulting blend of digital elements with the person's view of the real world is a form of augmented reality. This type of dynamic integration of new forms of information with our environment provides an opportunity to enable major innovations in the workplace. However, the ability to use these devices to constantly and seamlessly inform and guide people as they perform their jobs will impact what these individuals are learning. A key issue is how people can remain engaged in the tasks in ways that allow them to learn what is necessary for them to enhance performance and outcomes and also enrich their working lives. What people need to avoid is becoming passive, unquestioning recipients of external support. This research tackles the issue of how to optimize support and assistance to increase human capacities and improve immediate outcomes, while still allowing the durable, robust learning that ultimately produces skilled, experienced workers.
The core objective of this award is to advance the use of automation support for performance in future work by incorporating principles from the science of learning to produce superior long-term outcomes. This approach will provide a foundation for determining when and how external assistance would provide the best aid to humans. The work aims towards a new theoretical framework, as well as for guidelines for practitioners and developers. An initial study of performance in an exemplar furniture assembly task will use augmented reality to examine the interaction between current ongoing performance and long-term learning. The investigators will also organize a broad, multidisciplinary workshop to foster future interest in the area and develop new collaborations. The ultimate goal of this planning project is to develop the necessary research personnel, research infrastructure, and foundational work to expand the opportunities for studying future technology, future workers, and future work at the level of a FW-HTF full research proposal.
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.
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