Abstract
AbstractThis correlational, quantitative dissertation in practice explored the influence of the timing of algebra 1, taking advanced math courses, taking AP math courses, math credits earned, math self-efficacy, math identity, and socioeconomic status (SES) on the decision by girls to choose computer science education or career pathway at the post-secondary level. The variables of SES, race/ethnicity, region, locale, and school control were also included as controls in the analyses. Data from the publicly available, nationally representative High School Longitudinal Study of 2009 (HSLS:09) was used to explore the strength and directions of relationships between the predictor variables and the outcome variable. Three research questions were explored through examining the bivariate correlations between variables, and multivariate regression models. The statistical software IBM SPSS v 28.0 was used to filter and analyze the data. The overall findings suggest math self-efficacy and math identity play a key role in girls choosing to participate in computer science. Race/ethnicity is also significant as the data suggests the predictor variables have varying effects by race/ethnicity. Proposed solutions highlight the importance of seeing students as individuals and of educators crafting strategies to increase the participation by girls in computer science (CS) that are respectful and understanding of the influence of race/ethnicity and of the culture of the individual school and community.
Keywords: HSLS:09, STEM, algebra, mathematics, math self-efficacy, math identity, post-secondary education, Computer Science, female students, girls.