Date of Award

Summer 2012

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

STEM and Professional Studies

Program/Concentration

Occupational and Technical Studies

Committee Director

Philip A. Reed

Committee Member

Carmen P. Burrows

Committee Member

John M. Ritz

Abstract

The purpose of this study was to identify academic factors that might predict online course success for community college students. Online course success was a focus of national research and debate as studies consistently indicated lower success rates in online courses as compared to traditional courses; however, research that identified academic predictors to guide the development of policies and services that support student success in online courses was limited.

A random sample of 20 online course sections held at one multi-campus, urban community college resulted in 491 enrollees being examined for seventy-eight factors that might predict online course success. Factors present prior to online course enrollment included GPA; test scores; developmental coursework in reading, writing, and mathematics; college-level coursework in specific disciplines; and enrollment history. Factors present during the semester of online course enrollment included student status, current enrollment measures such as total number of courses attempted, total credits, and course duration. Demographic factors included gender, age, race/ethnicity, financial aid status, and geographic proximity to campus.

Data extracted from the student registration system included demographic characteristics, course rosters, test scores, and enrollment history. Data were grouped into three blocks prior to analysis: demographics, academic factors prior to online enrollment, and academic factors during online enrollment. An unordered logistical regression evaluated the predictive value of these factors for online course success.

Results of the logistical regression analysis indicated that the predictor model did not provide a statistically significant improvement over the constant-only model; the addition of variables did not improve the ability to predict the outcome, online course success. Continued analysis identified four statistically significant predictors of online course success in community college students. For factors measured prior to enrollment, cumulative college GPA was a positive predictor of online course success. For demographic factors, geographic proximity to campus was a negative predictor of online course success. For factors present during enrollment, total courses attempted (during the semester studied) was a positive predictor, and total credits attempted (during the semester studied) was a negative predictor of online course success.

The researcher concluded that online course success in community college students was a complex issue that could not be explained by academic factors alone and suggested that future studies attempting to predict online course success in community college students be comprehensive in addressing the multitude of academic, social, and other factors that may influence online course success. Additional suggestions for further study included evaluating the relationship individual factors have to online course success and seeking out student perspectives regarding online courses to determine other factors that contribute to successful and unsuccessful online course experiences for community college students.

DOI

10.25777/ed9c-gq86

ISBN

9781267649492

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