Google believes that the best way for us to ensure both equity and excellence in computer science education is to support rigorous scientific research that improves our understanding of CS learning and teaching. As the CS education research community has grown and matured, it is also critically important to create greater opportunities for new voices to ask new questions.
CS-ER: Supporting Computer Science Education Research in K–12
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Call for proposals will be sent out in January and proposals will be due March 11, 2022.
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These are one-year awards, possibly best suited to pilot projects and proof of concept explorations.
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The funding level is between $50K and $120K per award.
Review Criteria
The focus for all grants is CS education research. We cannot fund capital projects, hiring, or publications. The proposed program must demonstrate:
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Research design: The proposed research should be grounded in a compelling, theoretically-informed problem statement that guides the data collection, measurement, and analysis plans.
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Equity: We want to see growth in areas of historically marginalized groups in computer science and will prioritize proposals that generate new data and/or lead to research-supported solutions to address the current challenges.
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Collaboration: Study design includes interdisciplinary and multi-institutional partners with plans for shared contributions, responsibilities, and levels of influence for all members.
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Scalability: Given that these are single-year research initiatives, proposals should demonstrate potential for scaling.
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Sustainability: Proposals should include a plan for further funding once Google's funding ceases.
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Dissemination: Proposals should include a dissemination plan detailing how the research findings will be shared with the broader CS education community. For example, practitioners, parents, and policy makers.
Research priority areas (but not limited to):
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Equity: What are the best methods for scaffolding CS concepts for students with academic deficiencies or disabilities?
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Implementation: How can districts and states verify the effectiveness of their computer science education implementations?
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Preservice Education: What exemplary and scalable models exist for incorporating computer science learning into teacher preparation programs?
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Developmental readiness. What are effective instructional strategies for identifying whether a student is developmentally ready to learn particular CS concepts?
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Engagement: How does early CS experience impact future interest in CS?
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Professional Development: What are the best practices for CS PD in terms of positively impacting student learning?
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Student Learning:
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What models of CS content delivery provide the largest impact on students learning (after school, in school discrete courses, in school integrated into other disciplines)?
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How do we measure effective CS teaching
Please indicate your interest in this form and more information on submitting a proposal will be sent to you directly. You can also reach out to sidniedavis@google.com directly with questions regarding this opportunity.