EducateAI: Leveling Up - Building AP-CSA Teacher Capacity for Project-Based Learning

College Board will develop and nationally disseminate teacher professional learning (PL), lesson plans, and other instructional resources that will make up a new Advanced Placement Computer Science A (AP-CSA) course offering to increase the participation of students from groups historically underrepresented in Computer Science (CS). One pathway to broadening participation in CS that already has a national reach and provides a considerable opportunity is the AP-CSA program. The new course offering will include relevant Artificial Intelligence (AI) topics based on a review of college curricula and advance the NSF EducateAI initiative while preparing a larger and more diverse pool of computer science professionals to meet the country’s growing demand. The revised course will be built upon a project-based learning pedagogy (PBL), which has repeatedly demonstrated improvements in content knowledge; critical thinking and problem-solving skills; communication, collaboration & team building; discipline-specific skills; motivation; and persistence. Significantly, PBL has also been shown to increase participation and persistence by students from groups historically underrepresented in CS careers. This project seeks to increase the capacity of high school teachers for improving students’ exam outcomes, self-efficacy, and persistence. The Research Practice Partnership (RPP) will develop and test a new PBL AP-CSA course and provide resources and skill building for teachers to implement this new course. The RPP problem of practice is to improve enrollment, retention, and exam participation of students from groups underrepresented in computing in AP CSA courses by making improvements to current course pedagogy, content, and the gaps in teacher preparation for equitable teaching approaches. The project’s strategic vision begins with supporting classroom experiences that encourage students to persist in the course once enrolled (through PBL), and that simultaneously foster a school culture that increases broader student interest in AP-CSA. These two strategies will lead to the long-term outcome of broadening participation in CS professions and CS teaching. This inclusion will shift the perspectives and reduce biases (especially in the AI fields) and lead to a more equitable application and accessibility of CS education. The research focus will be on learning how instructor and student identities (i.e., racial/ethnic, gender, social economic status, and the intersection thereof) moderate these processes in order to understand if the PBL AP-CSA course is more efficacious for certain types of teachers and/or students. The research design uses field experiments with random assignment to condition, allowing the team to draw causal (versus correlational) conclusions. The project’s research and evaluation data will contribute to the field’s knowledge regarding the intersection of these elements, and it generates data and findings to inform future AP courses (e.g., AP- Computer Science Principles). The project will prepare 150+ teachers, and lead to the full dissemination of the products to more than 3,000 AP-CSA students nationwide. 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.