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Title: Safety first: Developing a model of expertise in collaborative robotics
Rapid advances in technology also come with increased training needs for people who engineer and interact with these technologies. One such technology is collaborative robots, cobots, which are designed to be safer and easier to use than their traditional robotic counterparts. However, there have been few studies of how people use cobots and even fewer identifying what a user must know to properly set up and effectively use cobots for their manufacturing processes. In this study, we interviewed nine experts in robots and automation in manufacturing settings. We employ a quantitative ethnographic approach to gain qualitative insights into the cultural practices of robotics experts and corroborate these stories with quantitative warrants. Both quantitative and qualitative analyses revealed that experts put safety first when designing and monitoring cobot applications. This study improves our understanding of expert problem-solving in collaborative robotics, defines an expert model that can serve as a basis for the development of an authentic learning technology, and illustrates a useful method for modeling expertise in vocational settings.  more » « less
Award ID(s):
1822872
NSF-PAR ID:
10248767
Author(s) / Creator(s):
; ; ;
Editor(s):
Ruis, Andrew R.; Lee, Seung B.
Date Published:
Journal Name:
Advances in Quantitative Ethnography: Second International Conference, ICQE 2020, Malibu, CA, USA, February 1-3, 2021, Proceedings
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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