ABSTRACT
Even prior to the COVID-19 pandemic, online learning had become a fundamental part of post-secondary education. At the same time, empirical evidence from the last decade documents higher dropout online in comparison to face-to-face courses for some students. Thus, while online learning may provide students access to post-secondary education, concerns about academic momentum and degree attainment dominate the higher education online learning landscape. Because course completion is often used as a measure of effectiveness, there is a strong need for institutions to be able to predict the potential persistence of online students to direct efforts towards ameliorating dropout. Yet currently, a widely tested and validated archetypical predictive model of retention and success does not exist for undergraduate online learning. This integrative review of the literature examines evidence gathered over the last decade, organizing and summarizing major findings, to help identify potential undergraduate student characteristics for inclusion in such a model. The body of literature collected in this review suggests ten factors for consideration.
ABSTRACT
This study details the prevalence of community college students’ reports of serious health events both before and after the onset of the COVID-19 pandemic in spring 2020. Survey responses from a representative sample of students within the largest community college at the City University of New York highlighted serious health challenges. Findings indicated that serious health challenges (including illness/injury/disability/mental health) were a significant factor in predicting students’ outcomes during the spring 2020 term. However, health-related events that occurred prior to the onset of the pandemic had a substantially and significantly larger correlation with course outcomes than those that occurred after the onset of the pandemic. This suggests that serious health issues may be a major barrier to student progress at community colleges, even outside of the conditions of a global pandemic, and that the pandemic may have only exacerbated this significant but often overlooked preexisting issue. [ FROM AUTHOR] Copyright of American Behavioral Scientist is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Even prior to the COVID-19 pandemic, online learning had become a fundamental part of post-secondary education. At the same time, empirical evidence from the last decade documents higher dropout online in comparison to face-to-face courses for some students. Thus, while online learning may provide students access to post-secondary education, concerns about academic momentum and degree attainment dominate the higher education online learning landscape. Because course completion is often used as a measure of effectiveness, there is a strong need for institutions to be able to predict the potential persistence of online students to direct efforts towards ameliorating dropout. Yet currently, a widely tested and validated archetypical predictive model of retention and success does not exist for undergraduate online learning. This integrative review of the literature examines evidence gathered over the last decade, organizing and summarizing major findings, to help identify potential undergraduate student characteristics for inclusion in such a model. The body of literature collected in this review suggests ten factors for consideration.