Document Type


Date of Degree

Spring 2011

Degree Name

PhD (Doctor of Philosophy)

Degree In

Educational Policy and Leadership Studies

First Advisor

Paulsen, Michael B

First Committee Member

Bills, David B

Second Committee Member

Liddell, Debora L

Third Committee Member

Pascarella, Ernest T

Fourth Committee Member

Tarvydas, Vilia M


The purpose of this study was to integrate traditional student success models with theories which focus on nontraditional students to create a model of early community college student success. The researcher sought to understand the pre-college behaviors, attitudes, and attributes, from both cognitive and noncognitive domains, which influence the success of first-time community college students enrolled in a developmental mathematics course. First-time community college students enrolled in Elementary Algebra (N=385) were surveyed on their educational goals, prior academic achievement, anticipated interactions during the first semester, and items from the Noncognitive Questionnaire (NCQ) (Sedlacek, 2004). Institutional data supplemented the survey variables as well as provided all dependent variables.

Factor analyses were conducted to reduce the number of anticipatory variables. Descriptive statistics were reported for all dependent and independent variables. Both linear regression and logistic regression were utilized to examine the six research questions. Variables were entered into the regression equations in five blocks: demographics, college plans, prior mathematics achievement, anticipated experiences and interactions, and noncognitive variables. The model proved to be statistically significant in explaining each of the six dependent measures of student success. Moreover after controlling for the first four blocks of independent variables, six of the eight noncognitive variables reached statistical significance in its relationship to at least one dependent variable, with at least one significant finding regarding the effects of noncognitive variables on each of the six outcome measures.

The findings of the study suggest noncognitive variables are useful in predicting student success and persistence at least early in the community college experience. Future researchers, policymakers, and administrators will gain insights into the application of noncognitive variables with a population of community college students.


Community College, Developmental Mathematics, Noncognitive Variables, Student Persistence, Student Success


vii, 268 pages


Includes bibliographical references (pages 259-268).


Copyright 2011 David Arthur Keller