S.3583 - Innovations in Mentoring, Training, and Apprenticeships Act115th Congress (2017-2018)
|Sponsor:||Sen. Heller, Dean [R-NV] (Introduced 10/11/2018)|
|Committees:||Senate - Commerce, Science, and Transportation|
|Latest Action:||Senate - 10/11/2018 Read twice and referred to the Committee on Commerce, Science, and Transportation. (All Actions)|
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Summary: S.3583 — 115th Congress (2017-2018)All Information (Except Text)
Introduced in Senate (10/11/2018)
Innovations in Mentoring, Training, and Apprenticeships Act
This bill requires the National Science Foundation (NSF) to award competitive grants to community colleges to develop or improve associate degree and certificate programs in STEM (science, technology, engineering, and mathematics, including computer science) fields in which there is a significant workforce demand in their region and a need to strengthen the global competitiveness of affected companies.
The NSF shall award competitive grants to universities partnering with employers or employer consortia that commit to offering apprenticeships, internships, research opportunities, or applied learning experiences to university students in identified four-year STEM degree programs.
The NSF shall award competitive grants to institutions of higher education or nonprofit organizations to conduct research on student outcomes and determine best practices and scalability of computer-based and online courses for technical skills training.
The NSF Directorate of Social, Behavioral & Economic Sciences, in coordination with the Department of Labor, shall support research to improve the efficiency of skilled technical labor markets in the United States.
The NSF shall commission research that compares and contrasts skilled technical workforce development between the United States and other developed countries.
The NSF National Center for Science and Engineering Statistics shall coordinate with other relevant federal statistical agencies in exploring the feasibility of expanding its surveys to include the collection of objective data on certain skilled technical workers who use significant levels of STEM knowledge in their jobs.