Post-secondary online learning in the U.S.: an integrative review of the literature on undergraduate student characteristics (original) (raw)
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Persistence and Dropout in Higher Online Education: Review and Categorization of Factors
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Online learning is becoming more popular with the maturity of social and educational technologies. In the COVID-19 era, it has become one of the most utilized ways to continue academic pursuits. Despite the ease and benefits offered by online classes, their completion rates are surprisingly low. Although several past studies focused on online dropout rates, institutions and course providers are still searching for a solution to this alarming problem. It is mainly because the previous studies have used divergent frameworks and approaches. Based on empirical research since 2001, this study presents a comprehensive review of factors by synthesizing them into a logically cohesive and integrative framework. Using different combinations of terms related to persistence and dropout, the authors explored various databases to form a pool of past research on the subject. This collection was also enhanced using the snowball approach. The authors only selected empirical, peer-reviewed, and conte...
Online learning continues to grow at post-secondary institutions across the United States, but many question its efficacy, especially for students most at-risk for failure. This paper engages that issue. It examines recent research on the success of community college students who take online classes and explores similar comparisons using 656,258 student records collected through the Predictive Analytics Reporting (PAR) Framework. In particular, the research investigated retention rates for students in three delivery mode groups – students taking only onground courses, students taking only online courses, and students taking some courses onground and some courses online at five primarily onground community colleges, five primarily onground four-year universities, and four primarily online institutions. Results revealed that taking some online courses did not result in lower retention rates for students enrolled in primarily onground community colleges participating in the PAR Framework. Moreover, although retention rates were lower for such students taking only online courses than for similar students taking only onground or blending their courses, much of the difference could be explained by extraneous factors. Essentially no differences in retention between delivery mode groups were found for students enrolled in primarily onground four-year universities participating in the PAR Framework, while at participating primarily online institutions, students blending their courses had slightly better odds of being retained than students taking exclusively onground or exclusively online courses. No differences between the latter groups were found at these institutions. Patterns of retention were similar regardless of gender across institutional categories, and were mostly similar regardless of Pell grant status with the exception of fully online students at traditional community colleges. Age, however, did differentially affect delivery mode effects. Older students taking only online courses were retained at higher rates than younger students taking only online courses at both primarily onground community colleges and primarily online institutions. The results suggest that, despite media reports to the contrary, taking online courses is not necessarily harmful to students' chances of being retained, and may provide course-taking opportunities that otherwise might not be available, especially for nontraditional students.
Retention, Progression and the Taking of Online Courses
Online learning continues to grow at post-secondary institutions across the United States, but many question its efficacy, especially for students most at-risk for failure. This paper engages that issue. It examines recent research on the success of community college students who take online classes and explores similar comparisons using 656,258 student records collected through the Predictive Analytics Reporting (PAR) Framework. In particular, the research investigated retention rates for students in three delivery mode groups – students taking only onground courses, students taking only online courses, and students taking some courses onground and some courses online at five primarily onground community colleges, five primarily onground four-year universities, and four primarily online institutions. Results revealed that taking some online courses did not result in lower retention rates for students enrolled in primarily onground community colleges participating in the PAR Framework. Moreover, although retention rates were lower for such students taking only online courses than for similar students taking only onground or blending their courses, much of the difference could be explained by extraneous factors. Essentially no differences in retention between delivery mode groups were found for students enrolled in primarily onground four-year universities participating in the PAR Framework, while at participating primarily online institutions, students blending their courses had slightly better odds of being retained than students taking exclusively onground or exclusively online courses. No differences between the latter groups were found at these institutions. Patterns of retention were similar regardless of gender across institutional categories, and were mostly similar regardless of Pell grant status with the exception of fully online students at traditional community colleges. Age, however, did differentally affect delivery mode effects. Older students taking only online courses were retained at higher rates than younger students taking only online courses at both primaily onground community colleges and primarily online institutions. The results suggest that taking courses online is not terribly harmful, especially when considering the access to higher education they provide for an older population in particular.
Assessing Student Retention in Online Learning Environments: A Longitudinal Study
In their initial study, authors Boston, Ice, and Gibson (2011) explored the relationship between student demographics and interactions, and retention at a large online university. Participants in the preliminary study (n = 20,569) included degree-seeking undergraduate students who completed at least one course at the American Public University System (APUS) in 2007. Two notable findings from the study were (1) the importance of transfer credit, and (2) the consistency of activity in predicting continued enrollment. Interestingly, the latter finding was confirmed upon the analysis of longitudinal data from the current study. Further related to the latter finding-yet unexpected, was the existence of new literature that, although subtle, affirms the importance for online institutions to conduct ongoing research on these topics. Readers of the current study are encouraged to refer to the preliminary study toward a comprehensive understanding of these nuances. Though informative, the researchers wished to validate the original study findings through longitudinal evaluation of retention.
Online Journal of Distance Learning Administration, 2016
Online course delivery continues to grow as a viable means of providing increased educational access to more students, but low student retention rates remain a major challenge. In this study, key institutional characteristics that influence student retention in postsecondary education are analyzed. These are student-faculty ratio, graduation rate, acceptance rate, enrollment rate, institutional aid rate, default rate, and institution type. Using multivariable regression analysis, our findings show that graduation rate, default rate, and college type were significantly associated with retention rate among online degreegranting institutions. Furthermore, graduation rate was found to be strongly positively linearly related with retention rate, while default rate was strongly negatively linearly related with retention rate. Overall these findings have direct implications on the planning and management of online instruction.
A Literature Review on the Definitions of Dropout in Online Higher Education
EDEN Conference Proceedings
Online higher education continues to grow, yet its high dropout rates remain a pressing and complex problem. However, there are many different definitions of dropout (and related concepts: attrition, persistence, and retention) in the literature, usually related to a temporal conception, and the issue is controversial. Inconsistent terminology is problematic because the ways dropout is defined determine how it is measured, tackled, and researched. This contribution seeks to remedy such issue by summarizing a scoping review of the recent literature on the theme, focusing on the key issue of online higher education students’ dropout conceptualization and definition. A scoping review between 2014 and 2018 yielded 138 articles and dissertations. Findings reveal a complex yet disorganized field, lacking standard definitions. Some concepts (e.g. completion) were defined clearly more often, while others (e.g. attrition and dropout) varied wildly; few papers employed previous definitions fr...
Comprehensive Assessment of Student Retention in Online Learning Environments
As the growth of online programs continues to rapidly accelerate, concern over the retention of the online learner is increasing. Educational administrators at institutions offering online courses, those fully online or brick and mortars, are eager to promote student achievement. Retention is critically important, not just for student success, but also for the success of these institutions of higher education. Models for understanding student persistence in the face-to-face environment are well established; however, many of the variables in these constructs are not present in the online environment or they manifest in significantly different ways. With attrition rates higher than in face-to-face programs, the development of models to explain online retention is considered imperative. This study moves in that direction by exploring the relationship between student demographics and interactions, and retention at a large online university. Analysis of data, which included an n of 20,569, provides an illustration of the importance of transfer credit and the consistency of activity in predicting continued enrollment.
Journal of Asynchronous Learning Network
There is well-documented evidence that online retention rates are lower than face-to-face retention rates; however, most past research on online retention focuses on student characteristics, with little knowledge existing on the impact of course type. This study uses a matched sample of 2,330 students at a large urban community college to analyze two key course-level factors which may be impacting online retention: the student's reason for taking the course (as an elective or a requirement) and course difficulty level. The results of this study indicate that the online modality increases dropout risk in courses that are taken as an elective or distributional requirement, particularly for lower-level courses. The findings suggest that in the online environment, the student's reason for course enrollment may be considered a risk indicator and that focused learner support targeted at particular course types may be needed to increase online persistence and retention.
Is the Second Time the Charm? Investigating Trends in Online Re-enrollment, Retention and Success
The Journal of Educators Online
Online education is becoming an increasingly important component of higher education. The Sloan Foundation 2010 Survey of Online Learning reports that more than 30% of all students take at least one online course during their college career. Because of this, attention is now turning to the quality of student outcomes that this instructional method provides. However, there is a huge gap in empirical investigations devoted to the link between technology and performance indicators such as grade performance, re-enrollment and course completion (Nora & Plazas Snyder, 2008). This study found that prior online course experience is strongly correlated with future online course success. In fact, knowing a student's prior online course success explains 13.2% of the variation in retention and 24.8% of the variation in online success in our sample, a large effect size. Students who have not successfully completed any previous online courses have very low success and retention rates, and students who have successfully completed all prior online courses have fairly high success and retention rates. Therefore, this study suggests that additional support services need to be provided to previously unsuccessful online learners, while students who succeed online should be encouraged to enroll in additional online courses in order to increase retention and success rates in online learning.
Factors impacting retention of online students
Online learning has continued to grow in recent years. However, retaining students in online courses and programs has posed a challenge. Whether the university is public, private, offers both face-to-face and online programs, or is 100% online, retaining students in online programs can be an issue. This study reflects the widespread desire at a large online for-profit university to improve student retention rates. The goal of the research was to provide further insight into why students may decide to drop out of online programs. Participants consisted of former undergraduate students at the university in the College of Education who dropped out without providing a specific reason for doing so. The study used a non-experimental mixed methods approach collecting data from university databases, an online survey, interviews, and classroom walk-throughs. Data analysis employed techniques such as frequency calculations, a MANOVA, and qualitative content analysis. Results from the MANOVA revealed statistically significant results when examining student Grade Point Average and last course grade. Furthermore, data collected from the online survey, interviews, and classroom walk-throughs revealed common reasons for why students may drop out of online programs.