Community college online course retention and grade predictors
Simon Y. Liu, The George Washington University, United States
The George Washington University . Awarded
This study investigated factors predicting students' retention and final grades in a community college online course. Community colleges serve diverse segments of society through a flexible and open access policy. By their very nature, community colleges provide a good fit with online learning. Unfortunately, studies suggest that online course dropout rates are high. The costs of course dropouts are borne by students, community colleges, and the society. There is, therefore, a vital need to better understand factors influencing community college online course retention and final grade.
A review of literature concluded that learning outcomes are influenced by an array of factors with complex interactions among them. Among these factors, psychological, technological, and social readiness have emerged as common concepts from previous studies and formed the basis of this dissertation study. This study employed the Learner Autonomy Profile (LAP) to measure the psychological readiness, the Online Technologies Self-Efficacy Scale (OTSES) to measure the technological readiness, and the Social Presence and Privacy Questionnaire (SPPQ) to measure the social readiness.
Data for this study were collected from volunteers enrolled in Eastern Community College online courses in the fall of 2006. This study used SPSS Version 14.0 to analyze survey data collected from 108 subjects. The conventional cut-off level of .05 was adopted. The results of binary and ordinal logistic regression analyses suggested that psychological readiness and social readiness were significant predictors of course retention and final grade in the online environment. However, the relationships between technological readiness and course retention and final grade were insignificant.
Based on the findings, this study proposes recommended actions for community colleges and online educators to improve the likelihood of student success in an online learning environment. Actions include early identification of at-risk students and effective interventions such as building effective blended learning programs, offering attentive psychological advising and counseling, providing timely technical support, and developing integrated social and learning communities. It is hoped that future work will move toward the development and testing of a comprehensive community college action plan for student retention.
Liu, S.Y. Community college online course retention and grade predictors. Ph.D. thesis, The George Washington University.
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