DataGOAT – Building Counter Structures to Combat Systemic Racism in STEM Education & Sport Through Data Literacy
College sports are inextricably linked with university campuses, but athletics is often separated from academic enterprises. This is especially true for those sports with the largest public audiences—Division 1 football and men’s basketball—where Black men are over-represented relative to the larger student body. These elite athletes constantly review statistics, calculate trajectories, and make projections—all data science pursuits. But unlike their classmates in music, engineering, or medicine, athletes cannot earn credit for this work; indeed, they are often encouraged to pursue non-STEM majors that do not disrupt their team schedules. This divide between athletics and academics is founded upon the exploitation of young Black men within the billion-dollar enterprises of college basketball and football, as well as racialized stereotypes that portray athletes, especially Black men, as dumb jocks. Because of these stereotypes, even athletes and coaches do not perceive themselves as STEM practitioners, despite the fact that important STEM skills are deeply embedded in elite athletics. The DataGOAT (Greatest Of All Time) project will build counter structures to combat this systemic racism by formalizing academic engagement with data science through sport, combating “dumb jock” stereotypes unjustly linked with Black men, and facilitating educational models and career pathways from sport to STEM.
Our project will create STEM curricular opportunities and technical interventions that can be integrated into existing educational programs, teach athletes data science content and proficiency, and empower them through critical data literacy. We do not aspire to draw athletes away from the sport that inspires them, their peers, and society at large. Instead, we situate STEM learning in counter structures that address systemic racism while harnessing this interest in athletics data. DataGOAT is a transformative higher education infrastructure merging data science with intercollegiate athletics. It includes coursework, internships, and a data analysis tool, aiming to promote racial equity in STEM, especially for Black male athletes. Through deep ethnographic work and collaborative design with athletes at two Division 1 universities, DataGOAT centers the voices of athletes and counters racist stereotypes hindering Black male athletes’ STEM engagement. By leveraging athletes’ data practices, the infrastructure supports their well-being and fosters critical data literacy. Our study assesses the design and impact of DataGOAT on critical data literacy development, STEM course uptake, and pipelines.
Keywords: collegiate sports, critical data literacy, co-design, life-relevant learning, data science education
Duration:
10/01/2024 - 03/31/2028
Partnering Organization(s):
National Science Foundation
Total Award Amount:
$3,431,745.00