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This study analyzes the impact of the Chicago Alliance for Equity in Computer Science (CAFÉCS) Research Practice Partnership (RPP) on the Chicago Public School (CPS) Office of Computer Science (OCS). Using a qualitative analysis drawing on data from leadership team meetings, published articles and presentations, and evaluation reports from 11 years of the partnership, we utilized a framework developed by the CAFÉCS leadership team to document the impact on district (1) Programs, (2) Research, (3) Organizational Structures, and (4) Policies leading to (5) Equitable Results for students, condensed as PROSPER. In particular, we explore the role of the RPP in supporting a 500% increase in graduating students who completed at least one high school computer science (CS) course between 2016 and 2020 in Chicago Public Schools (CPS). This study adds to the existing literature on assessing the impact of RPPs through the development of the PROSPER Framework, which may be a useful tool to help RPPs examine impacts on partner districts. 

This study compares the characteristics and professional development (PD) experiences between teachers who began teaching Exploring Computer Science before and after the enactment of a CS graduation requirement in the Chicago Public Schools. The post-requirement teachers were less likely to have a CS background, but their experience in the ECS PD and their level of confidence at the end of the PD were equivalent to the early adopters. 

Prior research has shown that students pursuing Exploring Computer Science (ECS) as their first elective course were more likely to pursue another computer science course in high school, as compared to students who took a traditional course as the first course. This study investigated whether the results are consistent when students are pursuing ECS to fulfill the Chicago Public Schools' graduation requirement. ECS is designed to foster deep engagement through equitable inquiry around computer science concepts. It is hypothesized that students who are fulfilling a graduation requirement will pursue additional computer science coursework at rates similar to students who were pursuing ECS as an elective course. 

Prior research has shown that students pursuing Exploring Computer Science (ECS) as their first elective course were more likely to pursue another computer science course in high school, as compared to students who took a traditional course as the first course. This study investigated whether the results are consistent when students are pursuing ECS to fulfill the Chicago Public Schools' graduation requirement. ECS is designed to foster deep engagement through equitable inquiry around computer science concepts. It is hypothesized that students who are fulfilling a graduation requirement will pursue additional computer science coursework at rates similar to students who were pursuing ECS as an elective course. 

This study investigated patterns in the development of computational thinking and programming expertise in the context of the Exploring Computer Science (ECS) program, a high school introductory CS course and professional development program designed to foster deep engagement through equitable inquiry around CS concepts. Prior research on programming expertise has identified three general areas of development — program comprehension, program planning, and program generation. The pedagogical practices in ECS are consistent with problem solving approaches that support the development of programming expertise. The study took place in a large urban district during the 2016–17 school year with 28 ECS teachers and 1,931 students. A validated external assessment was used to measure the development of programming expertise. The results indicate that there were medium-sized, statistically significant increases from pretest to posttest, and there were no statistically significant differences by gender or race/ethnicity. After controlling for prior academic achievement, performance in the ECS course correlated with performance on the posttest. With respect to specific programming concepts, the results also provide evidence on the progression of the development of programming expertise. Students seem to develop comprehension and planning expertise prior to expertise in program generation. In addition, students seem to develop expertise with concrete tasks prior to abstract tasks. 

A key strategy for broadening CS participation in the Chicago Public Schools (CPS) has been the enactment of a high school CS graduation requirement. The Exploring Computer Science (ECS) curriculum and professional development (PD) program serve as a core foundation for supporting enactment of this policy. The CAFECS researcher-practitioner partnership provides support for ECS implementation in CPS. An important part of the sustainability of the ECS PD model in CPS is the development of local workshop facilitators. Potential facilitators have generally been selected based on the CAFECS team's personal familiarity with active ECS teachers. Once selected, teachers engage in a two-year apprenticeship program to become facilitators. However, in the three years since the enactment of the policy, the number of ECS teachers and students has grown significantly. This rapid expansion of the CS teaching force has strained the ability to confidently identify new facilitators from a large pool of teachers and ensure consistency of workshop implementation. As a result, CAFECS is exploring how to supplement the ECS Facilitator Development Model through a proactive recruitment model and explicit support for the mentoring process. 

This study investigated patterns in the development of computational thinking practices in the context of the Exploring Computer Science (ECS) program, a high school introductory CS course and professional development program designed to foster deep engagement through equitable inquiry around CS concepts. Past research indicates that the personal relevance of the ECS experience influences students' expectancy-value towards computer science. Expectancy-value is a construct that is predictive of career choices. We extended our research to examine whether expectancy-value influences the development of computational thinking practices. This study took place in the context of two ECS implementation projects across two states. Twenty teachers, who implemented ECS in 2016–17, participated in the research. There were 906 students who completed beginning and end of year surveys and assessments. The surveys included demographic questions, a validated expectancy-value scale, and questions about students' course experiences. The assessments were developed and validated by SRI International as a companion to the ECS course. Overall, student performance statistically increased from pretest to posttest with effect size of 0.74. There were no statistically significant differences in performance by gender or race/ethnicity. These results are consistent with earlier findings that a personally relevant course experience positively influences students' expectancy for success. These results expanded on prior research by indicating that students' expectancy-value for computer science positively influenced student learning.