Abstract
Algebra is considered a gateway course that helps to close the achievement gap between ethnic and socioeconomic subgroups. Using a predictive correlational design, this research investigated whether demographic, school-related, and previous test score variables could be used to predict Algebra I and Algebra II success. Demographic predictor variables included age, gender, ethnicity, and status regarding disability, giftedness, retention, suspension, and mobility. School predictor variables included Title I status and school grade. Test scores included seventh grade reading and mathematics state assessment scores. Univariate analyses of variance (ANOVA) were computed to determine significance and effect size (eta squared value). Multiple regression analyses were used to determine prediction models for both the Algebra I and II end of course assessment scores. Finally, standardized beta coefficients were plotted to determine the effect of the variables on Algebra I and Algebra II success over time. The demographic and school-related variables in isolation were not strong enough to predict Algebra I and Algebra II success; however, in combination, the demographic, school-related, and previous test score variables did produce a significant prediction model that was stronger than prediction by test score alone.