The study utilized a quantitative multiple regression research design looking at the association between home technology use to complete school work and student achievement scores as measured on an online diagnostic assessment. Despite a tremendous amount of literature studying the potential effect of home use of technology on student achievement, there is no consensus on whether that effect is positive or negative (Fairlie & Robinson, 2013; Vigdor, Ladd, & Martinez, 2014). This study sought to gain a better understanding of the association of home technology use on student achievement. The study controlled for the independent variables of race/ethnicity, socioeconomic status, English as a new language status, and disability status since these variables were identified by several researchers as a possible influencing factor on student achievement. The primary data source was a student survey that was administered to sixth, seventh, and eighth grade students attending the study's targeted middle school. Demographic, socioeconomic, and student achievement data were added to the student survey data set. Statistical analysis was performed using formulas built into the SPSS software program. Descriptive statistics including means, standard deviations, skewness, kurtosis, sample size, and ranges are reported. A dichotomous non-disadvantaged, disadvantaged minority, variable was created by grouping all students who reported their race/ethnicity as White or Asian into the non-disadvantaged group and students who reported any other race/ethnicity were placed into the disadvantaged minority group. This grouping of students by race/ethnicity is common among studies in the social sciences. A Pearson's r correlation matrix was created for all variables used in the study, and significant relationships between variables were identified. Factor scores were created by combining highly correlated variables. Cronbach alpha coefficients are reported for each identified component factor. Exploratory factor analysis was run to further verify the factor score that was used for all multivariate analyses. Hierarchical linear modeling was run to identify the potential unique effect of the home technology use for school work (HTS) factor score on the dependent ELA and math achievement variables while controlling for several demographic and socioeconomic variables. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]