Geographic and Racial Disparities in Gifted Identification in Texas Before and After COVID-19

• In Event: Supporting Diverse Gifted Learner Needs

Abstract

This study examines how COVID-19 influenced racial/ethnic representation in gifted and talented (GT) programs across Texas school districts. Using hierarchical linear modeling (HLM) and Civil Rights Data Collection data from 2017–18, 2020–21, and 2021–22, we analyzed demographic divergence between GT-identified and general student populations. Kullback–Leibler Divergence (KLD), Jensen–Shannon Divergence (JSD), and race-specific representation indices were used to assess disparities. Results show that rural districts consistently exhibited greater divergence than suburban, town, and urban districts. Districts with higher proportions of Black students also had larger representation gaps. Although divergence decreased slightly over time, the improvement was broadly distributed. Findings underscore the need for equity-focused identification policies and targeted supports, particularly in rural districts.

Authors

• Vicky Weiqing Ji, University of North Texas

• Candie Aguilar, University of North Texas

• Travis D. Hill, University of North Texas

• Jaret Hodges, University of North Texas