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, combatting“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