Convergence Accelerator Phase I (RAISE):
Skill-LeARn: Affordable Augmented Reality Platform for Scaling Up Manufacturing Workforce, Skilling, and Education 

Funded by NSF (Grant C-Accel #2033615)

Project period: 2020-2021

Collaborator: Purdue University 

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The NSF Convergence Accelerator supports team-based, multidisciplinary efforts that address challenges of national importance and show potential for deliverables in the near future. The broader impact/potential benefit of this Convergence Accelerator Phase I project will be immediately applicable to the manufacturing sector, which has a multiplier effect on the economy and jobs. Automation is splitting the American labor force into two worlds: a relatively small number of highly educated professionals earning good wages, and less-educated workers who are left with businesses that pay low wages. Although we have had technology breakthroughs, the overall productivity growth is slow partly due to a workforce that lacks critical new competencies, such as procedural instruction learning, digital fluency, and other essential skills. The current and future workforce needs to be geared up for a culture of constant change. Companies have been relying on the age-old way of one-on-one Worker Apprenticeship model to train their new workforce. However, the recent need for larger scale and rapid training has created a bottleneck in terms of time and cost, especially for small and medium enterprises (SMEs). As a learning scientist, I work with mechanical and electrical engineers, psychologists, computer scientists, and education researchers toward accomplishing a goal of creating a scalable low-cost solution for (re)skilling the workforce.

Press release: 

https://www.ics.uci.edu/community/news/view_news?id=1898

Representative Publications

Glenn, T., Raja, P., Payne, K., Vagholkar, D., Huang, J., Peppler, K., Ramani, K. (under review). IoT Maker: Creating High-Level Electro-Mechanical Devices Through Live Programming for Youth. International Journal of Child-Computer Interaction. 

Peppler, K., Huang, J., Richey, C. M., Ginda, M., Börner, K., Quinlan, H., Hart, A. J. (2020). Key principles for workforce upskilling via online learning: A learning analytics study of a professional course in additive manufacturing. arXiv preprint. https://arxiv.org/abs/2008.06610

Ipsita, A., Dong, Y., Erickson, L., Huang, J., Bushinski, A. K., Vilanueva, M. A., Saradhi, S., Peppler, K., Redick, S. T., Ramani, K. (2022). Towards modeling of virtual reality welding simulators to promote accessible and scalable training. The ACM CHI Conference on Human Factors in Computing Systems 2021.

Villanueva, A., Liu, Z., Zhu, Z., Du, X., Huang, J., Peppler, K., Ramani, K. (2021). RobotAR: An augmented reality compatible teleconsulting robotics toolkit for augmented makerspaces experiences. The ACM CHI Conference on Human Factors in Computing Systems 2021.