Educationally At-risk College Students From Single-parent and Two-parent Households: an Analysis of Differences Employing Cooperative Institutional Research Program Data.
Description: 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.
Date: August 2005
Creator: Brown, Peggy Brandt
Item Type: Thesis or Dissertation
Partner: UNT Libraries