The problem that guided this study was a socio-constructivist view of education via online learning. Based in the extant literature, a deficiency existed that directly correlated online learning closing the academic achievement gap between student populations. In other words, schools invested in technology; however, few empirical data sets existed that established a connection between technology integration and the academic achievement of different student groups. The purpose of this pooled regression analysis study was to determine whether the method of class instruction effected academic achievement gaps between three subpopulations based on gender, race, and SES. Specifically, this study examined whether gender, race, and SES could predict semester grades within and across traditional, blended, and online course instructional methods. The dependent variable for this study was student success in the form of an end-of-unit test grade designed to evaluate student understanding of the curriculum. The independent variables included student gender, ethnicity, and SES. Quantitative data were collected through an analysis of Public Education Information Management System (PEIMS) data and student end-of-unit exam grades. The research suggests one combined interaction, [gender x race] in the traditional learning environment, is statistically significant while several independent interactions are significant. Those independent interactions are TAKS scores, …