Advanced manufacturing in fiber optics and photonics is undergoing an ambitious revitalization to enhance industrial capacity for a 21st-century high-tech economy. Two major challenges are to create new technology infrastructures and develop digital learning tools, which can help address the severe lack of technicians and engineers.
Groups at MIT, Clemson University, and The University of Arizona are leading the creation of digital learning simulations for workforce training in advanced manufacturing. By targeting knowledge gaps in both industry and government identified by the public-private Manufacturing USA institutes, this effort aims to rapidly reskill and upskill the current manufacturing workforce.
We present a three-pronged digital learning approach using (i) desktop virtual reality (VR) tool-training simulations, (ii) interactive web simulations using a novel methodology for photonics data visualization, and (iii) application-focused digital games to increase engagement for technician and engineering audiences. A holistic approach of interleaving all three learning modes may drive student motivation by connecting procedural skills acquisition with observations of real-world technology implementation, such as low-power cloud computing. This work presents formative assessment interviews and summative research for optics and photonics online learning content teaching into specific technology application areas. Additionally, in-classroom observations of technician and engineering students during blended-learning boot camps demonstrate the viability of these interactive games and simulations for future training.
Applications-grounded content in fiber optics and integrated photonics has the potential to encourage on-the-job training of industry veterans by adapting to their learning needs and schedule constraints. A sustained focus on contemporary applications will promote awareness of leading-edge industry innovation.
Education
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Workforce Training for Optics and Photonics Manufacturing Using Desktop VR Simulations, Data Visualization, and Game-Based Learning
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EV
Erik Verlage
MIT
GS
Glenda Stump
Massachusetts Institute of Technology
SR
Saif Rayyan
Massachusetts Institute of Technology
BU
Bhargav Upadhyay
Clemson University
JB
Jeff Bertrand
Clemson University
KM
Kapil Madathil
Clemson University
AK
Alan Kost
SS
Sajan Saini
Massachusetts Institute of Technology
GW
George Westerman
Massachusetts Institute of Technology
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Lionel Kimerling
Massachusetts Institute of Technology