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Type of Document Dissertation Author Harrell II., Ivan L. Author's Email Address iharrell@reynolds.edu URN etd-03232006-142946 Title Using Student Characteristics to Predict the Persistence of Community College Students in Online Courses Degree Doctor of Philosophy Department Educational Leadership and Policy Studies, Department of Advisory Committee
Advisor Name Title Beverly L. Bower Committee Chair Joy Gaston-Gayles Committee Member Richard Tate Committee Member Robert Schwartz Committee Member Keywords
- Computer Experience
- Demographics
- Community College
- Persistence
- Retention
- Withdrawal
- Course Withdrawal
- Attrition
- Online
- Web-based
- Student Characteristics
- Locus of Control
- Learning Style
- Computer Access
Date of Defense 2005-03-17 Availability unrestricted Abstract This study examined how student characteristics could be used to predict whether or not a community college student would persist in an online course. The research question guiding the study was, “Which student characteristics can be used to best predict the persistence of community college students in online courses?” The student characteristics examined were learning style, locus of control, computer experience and access, previous online experience and demographics.
A survey instrument consisting of two previously developed instruments and a Computer Experience scale that was created by the researcher specifically for this study, was administered to online students at one Florida community college for the pilot study and five additional Florida community colleges for the full study. Confirmatory and exploratory factor analysis were conducted on the computer experience scale to determine if there was an underlying hidden structure. Stepwise logistic regression was completed to determine the student characteristics that were significant predictors of online persistence, as well as an equation that could be used to predict whether or not a community college student would persist in an online course.
Confirmatory and exploratory factor analysis revealed that the Computer Experience scale consisted of three underlying subscales. The researcher named the three subscales based on the similarities of the variables that were associated with each factor: Factor one (basic computer skills); Factor two (Internet/email skills); Factor three (interactive computing skills).
Three of the initial 25 predictor variables were found to be significant predictors of community college online persistence: GPA, auditory learning style, basic computer skills. An increase in both auditory learning style and basic computer skills was associated with a decrease in the odds of course persistence. On the other hand, an increase in GPA was associated with an increase in the odds of course persistence. Additionally, an equation to predict whether or not an online community college student would persist in an online course was developed. Implications for community college administrators as well as recommendations for future studies are also provided in the study.
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