Award Abstract # 2122349
Collaborative Research: Moving beyond access, increasing teacher knowledge to teach rigorous equity-focused high school computing

NSF Org: CCF
Division of Computing and Communication Foundations
Recipient: UNIVERSITY OF DETROIT MERCY
Initial Amendment Date: August 13, 2021
Latest Amendment Date: July 14, 2022
Award Number: 2122349
Award Instrument: Standard Grant
Program Manager: Stephanie Gage
sgage@nsf.gov
 (703)292-4748
CCF
 Division of Computing and Communication Foundations
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: October 1, 2021
End Date: September 30, 2025 (Estimated)
Total Intended Award Amount: $652,181.00
Total Awarded Amount to Date: $672,181.00
Funds Obligated to Date: FY 2021 = $652,181.00
FY 2022 = $20,000.00
History of Investigator:
  • Richard Hill (Principal Investigator)
    hillrc@udmercy.edu
  • Jocelyn Bennett Garraway (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Detroit Mercy
4001 W MCNICHOLS RD
DETROIT
MI  US  48221-3038
(313)927-1000
Sponsor Congressional District: 13
Primary Place of Performance: University of Detroit Mercy
4001 W MCNICHOLS
Detroit
MI  US  48221-3038
Primary Place of Performance
Congressional District:
13
Unique Entity Identifier (UEI): ZAX4T6ANZ3J1
Parent UEI: ZAX4T6ANZ3J1
NSF Program(s): CSforAll-Computer Sci for All,
Special Projects - CNS
Primary Program Source: 01002223DB NSF RESEARCH & RELATED ACTIVIT
01002122DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 023Z, 7218
Program Element Code(s): 134Y00, 171400
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Lapetina, Andrew and Hill, Richard and Yadav, Aman and Lachney, Michael and Allen_Kuyenga, Madison "A Co-Instructional Model to Develop High School CS Teachers in Historically Underrepresented Communities: Building Capacity with a Purpose" , 2024 https://doi.org/10.1145/3653666.3656067 Citation Details

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