Toward a Learner-Oriented Community College Online Course Dropout Framework
Simon Liu, Joel Gomez, Badrul Khan, Cherng-Jyh Yen, George Washington University, United States
International Journal on E-Learning Volume 6, Number 4, ISSN 1537-2456 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC USA
Community colleges serve diverse segments of society through a flexible and open access. By their very nature, community colleges provide a good fit with online learning. Unfortunately, online course dropout rates are high. The costs of course dropout are borne by students, community colleges, and the society. There is, therefore, a vital need to better understand factors influencing community college online course dropout. A review of studies on conventional and online learning dropout models and a survey of 30 community colleges on online self-assessment practices conclude that there is no single indicator that can effectively predict online course dropout. On the other hand, there are several learner controllable indicators that, taken collectively, are potential predictors of online course dropout. Among them, psychological, technological, and social factors have emerged as common and widely-used predictive concepts. This article proposes a framework along these three dimensions to describe, organize, and explain learner-oriented factors influencing community college online course dropout. This proposed framework, when applied as part of a comprehensive retention strategy, has the potential for contributing to the reduction of the dropout rate in community college online learning programs.
Liu, S., Gomez, J., Khan, B. & Yen, C.J. (2007). Toward a Learner-Oriented Community College Online Course Dropout Framework. International Journal on E-Learning, 6(4), 519-542. Waynesville, NC USA: Association for the Advancement of Computing in Education (AACE).
© 2007 Association for the Advancement of Computing in Education (AACE)
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Simon Liu, Joel Gomez, Badrul Khan & Cherng-Jyh Yen, George Washington University, United States
International Journal on E-Learning Vol. 6, No. 4 (October 2007) pp. 519–542
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