GGrantIndex
← Search

Building a sustainable national network for developing and disseminating Sports Content for Outreach, Research, and Education in data science

$1,100,000FY2022EDUNSF

Carnegie Mellon University, Pittsburgh PA

Investigators

Abstract

This project aims to serve the national interest by exploring approaches to engage and prepare the next generation of data scientists through sports analytics. This collaborative effort will create a national network of academic and sports industry partners to develop modules paired with data, code, example problems. All materials will be housed on the Integrated Statistics Learning Environment (ISLE) platform, which will be freely accessible to students and faculty. Industry partners from over 50 sports teams and leagues will work with educators to create authentic modules that will focus on introducing foundational data science topics via sports applications. Resources will be primarily geared towards undergraduate students and will cover a wide array of men’s and women’s sports including baseball, basketball, hockey, tennis, cricket and much more. The project will also offer professional development opportunities for faculty and work to engage a diverse collection of institutions and students with an additional goal of broadening participation in the data science workforce. This collaboration brings together educators from five institutions (Carnegie Mellon University, Baylor University, St. Lawrence University, University of Pittsburgh and the United States Military Academy) together with sports industry professionals to create authentic curricular materials. Industry partners will lead the development of each module with guidance from a team of expert educators. As a result, educators will better understand skills and approaches used by sports analytics professionals, and will also have access to case studies build from real-world data. Each module will be reviewed and refined to ensure clarity and accessibility for undergraduates at varying educational stages and within multiple disciplines. Modules will showcase multiple steps for working with data: deciding how to collect and wrangle data, building and assessing appropriate models, and communicating the results. Project materials will be hosted on an Integrated Statistics Learning Environment (ISLE) platform, which will provide user data to help the network better understand how the modules are used, identify areas for improvement, and explore engagement across subgroups of students and educators. Evaluation and knowledge generation will focus on exploring three key ideas: 1) incorporating industry partners into the creation of education materials at scale, 2) exploring the directed module structure utilized in the project; and 3) analyzing user data to explore the engagement of students and educators via the ISLE platform. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. 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.

View original record on NSF Award Search →