Doctoral Dissertations

Orcid ID

Date of Award


Degree Type


Degree Name

Doctor of Philosophy


Higher Education Administration

Major Professor

Terry T. Ishitani

Committee Members

Norma T. Mertz, Jimmy G. Cheek, Gary J. Skolits


Community colleges are an essential element of the American postsecondary landscape and workforce preparation. In 2017, over six-million students, which represented roughly one-third of the total undergraduate enrollment in the United States, were enrolled in community colleges. In the past ten years, the importance of community colleges in the economic need for greater postsecondary credential attainment has been underscored by state policies and national initiatives. The wide variation in both the nature of community colleges and the students they serve makes examining the outcomes of these institutions difficult and oftentimes imprecise.

Assessing the performance of community colleges and determining what factors positively or negatively relate to their outcomes remains incompletely investigated. Statistical models of community college outcomes have failed to account for the distinctive characteristics of community colleges and have studied these institutions in isolation from their environments. Many of the limitations within literature may be attributed to insufficient data availability at the times of those studies. Adequate data, however, have recently become available that allow for the exploration of community college outcomes in a deeper and more meaningful way.

This dissertation study investigated how institutional and state characteristics of community colleges determine award rates. This was accomplished by accounting for salient variables, by leveraging three national datasets, and by using a more appropriate analytical method for the study of community colleges at the national level.

The results of ordinary least squares and multilevel regressions revealed variation between the institutional characteristics that significantly predict community college award rates once differences between states are taken into consideration. Moreover, variation was also observed in the institutional characteristics that significantly predict the award rates for all entering, first-time, and not-first-time students. In general, however, degree of urbanization, institutional type, and the proportions of part-time students, non-degree-seeking students, racial minority students, and female students emerged as consistent significant predictors across all statistical models.

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