EAGER: Centering Community Colleges in Research for Education/Workforce Development in STEM domains - AI, quantum computing, machine learning, and biotech (EAGER: CCCR)

About This Grant

To remain competitive in STEM, the United States must increase its workforce development with a specific and increasingly urgent focus on domains such as AI, quantum computing, machine learning, and biotech. Community colleges are a critical and underused resource for workforce pathway programs to these technology-dependent jobs. However, community colleges are the least likely to receive the critical funding to research, develop, implement, and scale these programs, particularly this in EPSCoR (Established Program to Stimulate Competitive Research) jurisdictions. This EAGER project will develop a scalable approach to increase the skills, self-efficacy, and interest of community college faculty to successfully develop competitive proposals for federal funding. With a specific focus on EPSCoR jurisdictions, this project has the potential to provide opportunities for all parts of the country to participate in and benefit from scientific and technological research and education. Community colleges face ongoing challenges in obtaining federal funding (as lead higher education institutions or even as significant partners) to research, test, and develop effective education/workforce pathways and programs. Their missions are historically focused on teaching and upskilling, and faculty typically lack the institutional resources and supports to pursue research projects. Most community colleges do not have existing Sponsored Project Offices (SPOs) critical to helping faculty with the administrative proposal development and submission components. This EAGER project will 1) test a coaching/mentorship model to increase the number and quality of NSF research proposals submitted by community college faculty; and 2) provide resources, traditionally offered by an SPO to facilitate the proposal administrative and submission tasks. The project activities also investigate successful practices for future scaling to other community college faculty in EPSCoR jurisdictions. The work is informed by ongoing, mixed-methods formative evaluation. Each participant is expected to develop a competitive proposal, aligned with the mission of the NSF CISE directorate, and focused on one of the prioritized domains of AI, quantum computing, machine learning, and/or biotech. The approach will include group and individual virtual experiences, including 1:1 coaching, interactive webinars, and development templates that occur before and after a 2.5- day In Person Development Intensive featuring expert panelists, interactive hands-on workshops, and one-on-one in-person mentor meetings. 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.