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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | University of Detroit Mercy |
| Country | United States |
| Start Date | Oct 01, 2021 |
| End Date | Sep 30, 2025 |
| Duration | 1,460 days |
| Number of Grantees | 2 |
| Roles | Principal Investigator; Co-Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2122349 |
As computing plays an increasingly important role in all industries, the demand for skills in information technology and software have skyrocketed while the associated training infrastructure has not kept pace. The need for a workforce with a background in computing is particularly important for the economy of the greater Detroit area, which is driven by the automotive and manufacturing sectors.
However, two primary limitations that inhibit the penetration of computer science in Detroit-area high schools are: (1) a lack of teachers who have sufficient preparation and confidence to teach the material, and (2) students who lack the awareness and interest to undertake such courses when they are available. Researchers from University of Detroit Mercy and Michigan State University are partnering to broaden participation and increase access to quality computer science instruction for high school students in Detroit.
This project will increase the awareness and interest of students underrepresented in computer science and educate high school teachers to deliver high-quality computer science instruction.
The project will use a sustainable multi-pronged approach to build the capacity of underserved high schools to offer CS curriculum in the metro-Detroit area. The components of the project include: (a) training of incumbent high school teachers through a unique co-teaching model with university faculty, (b) summer intensive CS experiences for high school teachers, (c) co-design of activities and lessons with teachers that bring issues of social and racial justice into their high school CS courses, and (d) adaptation and dissemination of curriculum that integrates technology, computational thinking, and career exposure into core required academic courses.
Using mixed-methods approaches, the project will collect a rich set of data to examine how the project influences teacher learning (such as pedagogical content knowledge and self-efficacy) and student outcomes (such as AP Exam pass rates, attitudes, and post-graduation destinations). Results from this project will help discover how to support high school computer science teachers to offer high-quality computer science instruction that better engages students and improves student learning and impacts student future career paths.
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.
University of Detroit Mercy
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