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Balu, Rekha; Porter, Kristin – MDRC, 2017
Many low-income young people are not reaching important milestones for success (for example, completing a program or graduating from school on time). But the social-service organizations and schools that serve them often struggle to identify who is at more or less risk. These institutions often either over- or underestimate risk, missing…
Descriptors: Low Income Groups, At Risk Students, Youth Programs, School Role
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Miller, Thomas E.; Tyree, Tracy; Riegler, Keri K.; Herreid, Charlene – College and University, 2010
This article describes the early outcomes of an ongoing project at the University of South Florida in Tampa that involves using a logistics regression formula derived from pre-matriculation characteristics to predict the risk of individual student attrition. In this piece, the authors will describe the results of the prediction formula and the…
Descriptors: Mentors, Student Attrition, Models, Multiple Regression Analysis
1989
The conference program and the texts of 24 papers presented at the conference are provided in this document. Selected papers include: "The Use of the College Student Experience Questionnaire in Policy and Program Development" (Karen Bauer and Dale Trusheim); "Predicting Freshman Performance as Admissions Criteria" (David Zubrow); "Has the Middle…
Descriptors: Academic Persistence, Database Design, Educational Planning, Enrollment
Lasher, William F.; And Others – 1980
Analytical techniques developed by the University of Texas at Austin to deal with problems of forecasting future enrollments, instructional workloads, and funding levels are considered. In order to project university enrollments, Texas public high school graduates were projected. In-migration rates were separated from survival rates,…
Descriptors: Academic Persistence, Budgeting, College Freshmen, Educational Finance
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Reyes, Maria Elena – Journal of College Student Retention, 2001
Focus groups comprised of Alaska Native students at the University of Alaska Fairbanks identified factors contributing to or serving as barriers to student academic success. Contributors included student persistence, financial support from native corporations, family support, employment, and availability of developmental classes. Barriers included…
Descriptors: Academic Persistence, Alaska Natives, College Students, Focus Groups
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Shah, Chandra; Burke, Gerald – Higher Education, 1999
A Markov chain is used to model the movement of undergraduates through the higher education system in Australia. Given the student's age on commencing a course of study, the model provides estimates of the probability of course completion, mean time for completion, and mean time spent in the higher education system. (Author/MSE)
Descriptors: Academic Persistence, Age, College Students, Enrollment Management