This project builds on prior efforts to create teaching resources for high-school Advanced Placement Statistics teachers to use an open source statistics programming language called "R" in their classrooms. The project brings together datasets from a variety of STEM domains, and will develop exercises and assessments to teach students how to program in R and learn the underlying statistics concepts.
This project will examine the relationships among the factors that influence the implementation of the Exploring Computer Science (ECS), a pre-Advanced Placement curriculum that prepares students for further study in computer science. This study elucidates how variation in curricular implementation influences student learning and determines not only what works, but also for whom and under what circumstances.
This study explores the following issues in 9 schools across 3 neighborhoods: (1) How student engagement in STEM is enabled and constrained by the school's relations with its external community; (2) The similarities and differences in partnerships across different types of schools in three different urban neighborhoods by mapping networks, and assessing the costs and benefits of creating, maintaining, and dissolving network ties; and (3) How to model school and network decisions, relations, and resources using an operations research framework.