The Significance of Interactions: Understanding Gender, Ethnicity/race, and Socioeconomic Status as Related to the Likelihood of Bachelor’s Degree Completion
Although access to a postsecondary education has increased exponentially since 1970, access to a bachelor’s degree has not grown as swiftly. Moreover, while national longitudinal trend data highlight improvements in bachelor’s degree completion in the aggregate, they disguise important disparities in bachelor’s degree completion across groups. Specifically, these data mask inequality in bachelor’s degree attainment across and within groups, particularly groups defined by gender, ethnicity/race, and socioeconomic status.
Conceptual models accompanying research on bachelor’s degree completion have included both student- and institution-level characteristics. Although these models have shed light on disparities in completion with respect to gender, ethnicity/race, and socioeconomic status, few predictive models incorporate the interaction of these demographic constructs. Since gaps in bachelor’s degree completion persist both within and across groups, additional consideration of interactions may prove helpful for future retention efforts.
Using Tinto’s conceptual model of student departure, this dissertation examines a model of bachelor’s degree completion, focusing on the interaction of gender, ethnicity/race, and socioeconomic status. Framed by critical race feminist theory, this research acknowledges variance in privilege and marginalization by gender, ethnicity/race, and socioeconomic status, as well as the interaction of these characteristics. Logistic regression analyses are used to identify likelihood of degree completion within six years using the Beginning Postsecondary Students data set.
Descriptive analyses show that gender, ethnicity/race, socioeconomic status groups are related to bachelor’s degree completion and suggest that these variables may interact to predict bachelor’s degree completion. Nonetheless, none of the interactions were statistically significant in the logistic regression analyses. This research highlights the differences in conceptual and statistical interactions, and how additional research may be needed both theoretically and empirically. Implications for policy and practice incorporating a critical race feminist theoretical approach and statistical interactions are also presented.