NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 9 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Kopp, Jason P.; Shaw, Emily J. – Journal of College Student Retention: Research, Theory & Practice, 2016
Retention research rarely differentiates between students dismissed from an institution for poor academic performance versus students leaving by choice. As a proxy for studying academic dismissal, this study investigated differences between students leaving college in academic jeopardy after the first year (<2.00 grade point average) and those…
Descriptors: Dropouts, College Students, Academic Achievement, School Holding Power
Peer reviewed Peer reviewed
Direct linkDirect link
Mengo, Cecilia; Black, Beverly M. – Journal of College Student Retention: Research, Theory & Practice, 2016
Violence against university students has significant impact on their mental health. The impact of violence on students' academic performance has received little attention. The primary purpose of this study is to examine the impact of sexual and physical/verbal violence on the academic performance of college students. Data from 74 case files of…
Descriptors: Violence, Victims, Grade Point Average, Dropouts
Peer reviewed Peer reviewed
Direct linkDirect link
Kerby, Molly B. – Journal of College Student Retention: Research, Theory & Practice, 2015
Theoretical models designed to predict whether students will persist or not have been valuable tools for retention efforts relative to the creation of services in academic and student affairs. Some of the early models attempted to explain and measure factors in the "college dropout process." For example, in his seminal work, Tinto…
Descriptors: Predictor Variables, Models, School Holding Power, Academic Persistence
Peer reviewed Peer reviewed
Direct linkDirect link
Davidson, Cody; Wilson, Kristin – Journal of College Student Retention: Research, Theory & Practice, 2013
The purpose of this article is to trace the development of the Tinto framework for student integration and to critically analyze the application of the framework with nontraditional student populations. Specifically, the terms "academic" and "social integration" have become synonymous with student retention and, by extension,…
Descriptors: Academic Persistence, Social Integration, Nontraditional Students, Predictor Variables
Peer reviewed Peer reviewed
Direct linkDirect link
Campbell, Corbin M.; Mislevy, Jessica L. – Journal of College Student Retention: Research, Theory & Practice, 2013
Along with the massification of higher education and increasing costs, the pressure on institutions to retain all students to degree completion has been mounting. Early identification of students who are at risk of leaving an institution may help institutions to target and retain these students. This study investigated whether freshmen behaviors,…
Descriptors: Identification, At Risk Students, School Holding Power, Enrollment
Peer reviewed Peer reviewed
Direct linkDirect link
Schatzel, Kim; Callahan, Thomas; Davis, Timothy – Journal of College Student Retention: Research, Theory & Practice, 2013
Results from the analyses of data from 463 former college students between the ages of 25 and 34 years old identify those most likely to reenroll in higher education in the near future. Those who intend to reenroll are more likely to be members of minority groups, younger, single, and recently laid-off, have earned more credits, and hold strong…
Descriptors: Dropouts, Stopouts, Enrollment, Withdrawal (Education)
Peer reviewed Peer reviewed
Direct linkDirect link
Ma, Yanli; Cragg, Kristina M. – Journal of College Student Retention: Research, Theory & Practice, 2013
While some students drop out early in their academic career, others drop out close to completion. What similarities and differences exist between these early and late dropouts? Using a sample 3,520 first-time, full-time (FTFT) students seeking a bachelor's degree at a state university, this study employs multinomial logistic regression to model…
Descriptors: Dropouts, College Transfer Students, Undergraduate Students, Regression (Statistics)
Peer reviewed Peer reviewed
Direct linkDirect link
Delen, Dursun – Journal of College Student Retention: Research, Theory & Practice, 2012
Affecting university rankings, school reputation, and financial well-being, student retention has become one of the most important measures of success for higher education institutions. From the institutional perspective, improving student retention starts with a thorough understanding of the causes behind the attrition. Such an understanding is…
Descriptors: Higher Education, Student Attrition, School Holding Power, Prediction
Peer reviewed Peer reviewed
Direct linkDirect link
Glynn, Joseph G.; Sauer, Paul L.; Miller, Thomas E. – Journal of College Student Retention: Research, Theory & Practice, 2006
The model presented used available data to predict whether or not a student will drop out at some time during his or her college career. The model successfully identified students who would or would not drop out approximately 80% of the time. Logistic regression analysis was employed to predict chances of attrition for matriculating freshmen soon…
Descriptors: Student Attrition, Models, Dropouts, Probability