Personalized Online Learning Can Mitigate Racial Disparities in Math Achievement

• In Event: Advancing Equity in Mathematics Education: Innovative Approaches for Diverse Learners

Abstract

The racial achievement gap in the U.S., driven by structural inequalities in education, is a critical issue. This study examined whether a widely-adopted personalized online learning platform (IXL) could help mitigate the Black-White achievement gap in math. Using a pretest-posttest design, we first studied schools with a high percentage of Black students (HPB) and found improved math performance among grade cohorts that used IXL. Across all schools, higher levels of IXL usage were associated with greater learning gains; this effect was especially pronounced in HPB schools. These findings suggest that IXL can both enhance academic performance among Black students and potentially reduce racial disparities in education. Overall, this study shows that scalable, technology-based interventions can promote educational equity.

Authors

• Anjie Cao, Stanford University

• Christina C Schonberg, IXL Learning

• Bozhidar M. Bashkov, IXL Learning

• Mary Hargis, IXL Learning