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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | Wested |
| Country | United States |
| Start Date | Aug 15, 2021 |
| End Date | Jul 31, 2024 |
| Duration | 1,081 days |
| Number of Grantees | 2 |
| Roles | Principal Investigator; Co-Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2122485 |
This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). This project will help middle school computer science (CS) students connect more deeply with CS content and promote inclusion and equitable participation in CS classrooms through data science. Data science is a new field that applies computer science and statistics to data sets with the goal of extracting useful information.
Data science skills have become necessary to make sense of complex social and scientific problems. Data science has mainly been taught in graduate and undergraduate programs, but more and more groups are aiming to teach data science in elementary, middle, and high school. Data science instruction can give computer science students the opportunity to solve authentic and socially relevant problems, increasing interest and motivation, particularly for learners who are members of historically underrepresented groups in science, technology, engineering, and mathematics (STEM).
Authentic and socially relevant problems also provide opportunities for students to engage in classroom discourse, a strategy that has demonstrated benefits for English learners in mathematics classes.
Computer Science Connections is a researcher-practitioner partnership (RPP) between WestEd and the Oakland Unified School District (OUSD). The partnership will use a design research approach to modify the data science content within OUSD’s middle school computer science curriculum to include more socially relevant problems and to incorporate classroom discourse strategies.
The OUSD team will design the new data science unit and establish a professional learning community (PLC) to prepare teachers to teach it. Using a combination of focus groups, surveys, and observations, the WestEd team will conduct research on teachers’ and students’ perceptions of data science and how it is currently taught in OUSD middle schools.
The team will also evaluate the effectiveness of the new data science unit in OUSD CS classrooms and how well the data science PLC prepares teachers to teach data science. The success of the partnership will be evaluated by an external advisory panel with expertise in computer science education, math education, data science education, and teacher professional development.
The RPP will provide information to the field on the successes and challenges of engaging in this work and a program that is evidence-based through rigorous efficacy research. This project is funded by the CS for All: Research and RPPs program.
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.
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