Mathematics & Science Achievement in Texas Urban Schools: A Multilevel Multinomial Logistic Regression Analysis

Abstract

In Texas urban schools, there has been a persistent gap in academic performance in mathematics and science. Discussions about student performance often overlook sociocultural factors contributing to these disparities. This study examines mathematics and science achievement in Texas urban schools using a multilevel multinomial logistic regression analysis and the conceptual framework of the opportunity gap. Data from the Texas Education Agency for the 2018-2019 school year was analyzed to examine relationships between student achievement and within- and between-school characteristics. The findings reveal significant disparities in science achievement (i.e., Biology) and mathematics achievement (i.e., Algebra I). Female students outperform males in Algebra I but underperform in Biology. Students eligible for free or reduced lunch (FRL) consistently underperform in both subjects. Course tracking also plays a critical role, with students on accelerated tracks showing higher achievement, while those in off-track courses are more likely to underperform. School-level factors, such as the proportion of FRL-eligible, Black, or Latinx students, further contribute to lower achievement outcomes across mathematics and science. These results highlight the need for targeted interventions, equitable resource allocation, and culturally responsive teaching practices to address persistent achievement gaps in urban education settings.