The RPPforCS project connects the teams through virtual meetings (webinars), in-person meetings, and meetings of the R-EWG. Here you will find information about the participating grant teams, project activities, and resources from the project.
Searchable RPP Database and Maps
This database allows you to search through our existing community of projects on a range of characteristics. You can use this resource to find people who are geographically close to you, working on a similar problem of practice, working with a similar student or teacher population, and more!
The first map of the embedded “RPPforCS Projects Map”, "Projects by Research Team" shows the dispersion of project PIs across the country. The second map, "Projects by Implementation Location" demonstrates the distribution of projects by the proposed state of implementation. The “RPPforCS District Maps” insert provides a map of US school districts within which one or more NSF: CSforAll RPPs are operating, as well as tables of demographic data for these districts. All of these maps have a set of demographic data associated with projects and/or locations that can be filtered upon.
At this time these features are only available for viewing on your desktop. Sorry for any inconvenience!
RPP Project Database
The RPPforCS searchable database allows you to search through our existing community of projects on a range of characteristics. You can use this resource to find people who are geographically close to you, working on a similar problem of practice, working with a similar student or teacher population, and more! The database will automatically update itself with your chosen filters shortly after selecting them.
If you are looking for potential BPC partners, then you may find the following filters the most useful:
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The “District Population” filters allow you to search for projects by the populations of the districts that they are known to be operating in. Note that these are not necessarily the target population, but may provide insight into the environment that a project is operating in.
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The “Urban/Rural Class” filter allows you to search for projects by the US Census designation of projects’ district partners.
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The “Keywords” filter allows you to search for projects by key areas of focus, such as pathways programs or PD delivery.
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The “State of Implementation” filter allows you to search for projects by state. Only states with at least one project are listed.
Advancing AI and Data Science Education in the US through Collaborative Coordination
The New York City Foundation for Computer Science Education
Leigh DeLyser
CSforALL will convene a workshop of Computer Science (CS) education, Artificial Intelligence (AI), Machine Learning (ML), and Data Science (DS) leaders to explore education pathways to careers in AI and AI-related fields. The workshop will be followed by a report with guidance for decision makers regarding implementation of these important topics, and recommendations for policy that will ensure equitable implementation across the landscape.
Examining Transfer Between Programming Languages in Computer Science
WestEd
Yvonne Kao
This project seeks to understand how to help students connect concepts they learned in one programming language to related concepts in a new programming language. Many studies in computer science education have examined how students perform when their coursework transitions from one programming language to another. This project broadly aims to develop and use such a computer science-specific theory in the context of middle school students as they engage with three different block-based programming languages.
A Continuous Coaching Model for High School Computer Science Teachers
University of West Florida
Sikha Bagui
This proposal will explore a continuous support coaching model, based on Knight’s instructional coaching model, for increasing the pool of future educators without deep pre-existing content knowledge, who will be prepared to coach and teach AP Computer Science Principles (AP-CSP). The coaching model, offered by the University of West Florida’s computer science faculty, will be focused on the pedagogy of computer science, implemented using a constructivist pedagogical approach.
Building High-Quality K-12 Computer Science Education Research
The New York City Foundation for Computer Science Education; North Carolina State University
Leigh DeLyser
The project will first frame prior research against the CAPE framework to identify barriers researchers face when conducting high-quality research inequitable K-12 computing education. Using results from that effort and input from experts, the researchers will develop recommendations and resources for expanding coverage of equitable, high-quality K-12 computing education research. Finally, the research team will design and test workshops to train researchers in equitable K-12 CER methods and practices.
Computational Modeling for Integrating Science and Engineering Design
SRI International; Vanderbilt University
Satabdi Basu
CMISE will investigate how different types of computational modeling activities promote integrated student learning of science and engineering. CMISE will have immediate impacts on STEM + Computing offerings for the Metro Nashville Public School district where the project will be conducted; broadly it will also help strengthen and grow a diverse STEM workforce by bringing authentic and compelling science and engineering opportunities to fifth and sixth grade students.
Designing Inclusive CT Metrics to Broaden Participation in Computer Science
Northeastern University
Casper Harteveld
This project addresses three critical needs in computer science education: (1) improving computational thinking metrics to support automated assessment of computational thinking; (2) providing students with real-time feedback that helps them monitor their progress in computational thinking and programming to build confidence in their skills; and (3) creating context-sensitive assessment and feedback tools that promote inclusivity and encourage students to learn about computer science, computational thinking, and programming.
RPPforCS Project Maps
The first tab, "Projects by Research Team" shows the dispersion of NSF: CSforAll RPPs across the country. By toggling the filters on the right-hand side of the map you can filter the view by which Grade Band a project is targeting as well as the type of curriculum that the projects will be using. Note that points are staggered to allow overlapping projects to be visible.
The second tab, "Impact Area" demonstrates the distribution of NSF: CSforAll RPPs by the proposed state of implementation. As with the first map you can filter down by Grade Band and Curriculum Used. Mousing over or clicking on a state will display all grade bands being targeted by RPPs in that state, all curricula being used by RPPs in that state, and a list of all projects operating in that state.
RPPforCS District Maps
This set of maps details the districts that NSF: CSforAll RPPs are known to be partnered with and the overall demographics of students in those districts. These demographics do not necessarily represent the specific student subgroups (if any) being targeted by NSF: CSforAll RPPs, however. It should also be noted that projects will frequently only work directly with a subset of schools within a district, and a project's presence in a district on this map does not imply that they are working with every school in a given district.
All of these tabs can be filtered by searching for a project's name, by state, or by districts' urban/rural status as defined by the US Census.
The first tab "RPPforCS Continental District Map" displays all known public school districts partnered with one or more NSF: CSforAll RPPs.
The second and third tabs "District Race/Ethnicity Demographics vs. State Demographics" and "District Race/Ethnicity Demographics vs. National Demographics" provide details for each RPP-partnered school district's student demographics compared to their state or national student demographics, respectively. They also provide information on which projects are operating in each district. The "Examine by" drop-down menu in the top right of each tab can be used to select what demographic group to display data for.
The last tab "Other Demographic Information" shows district-level student data for the percentage of students eligible for free/reduced lunch as well as the percentage of those who are English as a second language/limited English proficiency students. Any blank rows indicate that there is currently no data for a given district.