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This study evaluated the impact of predictor variables on certificate, associate, or bachelor's degree completion for first-time community college students pursuing science, technology, engineering, and mathematics (STEM) degrees.
Using binary logistic regression, this study applied Crisp and Nora's theoretical model of persistence and transfer to first-time community college STEM students. The study used binary logistic regression to assess whether demographic variables, pre-collegiate variables, environmental pull factors, and academic experiences significantly predicted whether first-time STEM students completed a certificate, associate, or bachelor's degree within six-years of entering a community college. Four out of the 19 variables under this study, significantly predicted certificate, associate, or bachelor's degree completion for first-time community college STEM students.
The findings from this study indicated that gender, ethnicity, enrollment into high school calculus, and STEM GPA during college significantly predicted certificate, associate, or bachelor's degree completion for first-time community college STEM students. Further, the findings suggest that female STEM students were more likely than males to complete a certificate or degree; Hispanic students were as likely to complete a degree as White students, but their enrollment numbers in STEM fields of study were much lower. Conversely, Black/African American students were less likely to complete a certificate or degree than their White counterparts. Additionally, students with higher STEM GPAs and students who completed calculus during high school were more likely to complete a certificate, associate, or bachelor's degree. Finally, enrollment in basic skills courses was not statistically significant in predicting certificate or degree completion.
The findings associated with the present study indicate academic differences between the general community college student population and the community college STEM student population. As a result, the findings of this study have implications for policy and practice in STEM programs throughout community colleges nationwide.
Advisor: | Rabitoy, Eric |
Commitee: | |
School: | California State University, Fullerton |
School Location: | United States -- California |
Source: | DAI-A 76/12(E), Dissertation Abstracts International |
Source Type: | DISSERTATION |
Subjects: | Community college education, Higher education |
Keywords: | Binary Logistic Regression, Community College, First-Time Students, STEM, Two-Year Colleges |
Publication Number: | 3663987 |
ISBN: | 978-1-339-08614-9 |