Using factors of low income, parents' levels of education, and family composition as determinants of educationally at-risk status, study investigated differences between first generation, undergraduate college students from families in lowest quintile of income in the U.S, One group consisted of students from single-parent households and the other of students from two-parent households. Data were from CIRP 2003 College Student Survey (CSS) and its matched data from the Freshman Survey (Student Information Form - SIF). Differences examined included student inputs, involvements, outcomes, and collegiate environments. Included is portrait of low income, first generation college students who successfully navigated U.S. higher education. The number of cases dropped from 15,601 matched SIF/CSS cases to 308 cases of low income, first generation college students (175 from single-parent households and 133 from two-parent households). Most of the 308 attended private, 4-year colleges. Data yielded more similarities than differences between groups. Statistically significant differences (p < .05) existed in 9 of 100 variables including race/ ethnicity, whether or not English was first language, and concern for ability to finance education as freshman. Data were not generalizable to all low income, first generation college students because of lack of public, 4-year and 2-year colleges and universities in dataset. Graduating seniors' average expected debt in June 2003 was $23,824 for students from single-parent households and $19,867 for those from two-parent households. 32% from single-parent households and 22% from two-parent households expected more than $25,000 of debt. Variables used on SIF proved effective tools to develop derived variables to identify low income, first generation college students from single-parent and two-parent households within CIRP database. Methodology to develop derived variables is explained.

<p dir="ltr">This dissertation aims to understand the academic outcome disparity between underrepresented minorities in higher education when compared to other racial groups. It seeks to address the social inequities in learning, college integration, and completion rate. The focus was narrowed to a specific marginalized community that represents first-generation underrepresented minority (FGURM) students, that is, students whose parents have not obtained a post-secondary degree and identified as belonging to the following racial or ethnic group: Blacks, Hispanics/Latinos, American Indians/Alaska Natives, Native Hawaiian/Pacific Islanders, and two or more races in the United States.</p><p dir="ltr">The overall objective was to explore with predictive models how demographic factors, pre-college academic performance, socioeconomic status, targeted programs aimed at fostering integration into campus communities, and support systems can increase the likelihood of academic success within this group. Predictive models based on supervised machine learning algorithms like Random Forest in combination with ensemble learning techniques like bagging and boosting was used to assess various predictors of successful academic outcomes. To address issues like incomplete and imbalanced data, a combination of case deletion and imputation methods, such as K-Nearest Neighbor (KNN), Linear Regression, and the Synthetic Minority Over-sampling Technique - Edited Nearest Neighbors (SMOTEENN), were utilized.</p><p dir="ltr">The results suggested that pre-college academic achievements, assessed through standardized test scores (ACT/SAT), along with demographic factors such as age, gender, and ethnicity, are significant predictors of cumulative grade point average (CGPA). Furthermore, a combination of test score and CGPA was identified as a strong predictor of graduation outcome. The research further showed that student involvement particularly in academic related organizations is vital for academic achievement. Other forms of student involvement, such as participation in cultural identity groups, service-oriented and recreational groups, were also significant predictors of positive academic outcomes. Moreover, specific academic disciplines, such as engineering and nursing, were recognized as significant predictors of graduation, especially for both male and female students.</p><p dir="ltr">This study concluded that improving K-12 education to boost college preparedness, especially for FGURM students, is vital for enhanced standardized test scores and academic success in college. Additionally, universities can enhance institutional commitment and attachment by creating a sense of belonging through programs focused on cultural and ethnic diversity, service, advocacy, and recreation as well as providing encouragement and opportunities for FGURM to participate in learning activities outside the traditional classroom setting, which can ultimately enhance FGURM students' academic achievement.</p>