Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 0 |
| Since 2016 (last 10 years) | 0 |
| Since 2006 (last 20 years) | 4 |
Descriptor
| Intervention | 5 |
| Models | 5 |
| Academic Persistence | 3 |
| Higher Education | 3 |
| Regression (Statistics) | 3 |
| Student Attrition | 3 |
| College Freshmen | 2 |
| High Risk Students | 2 |
| Mentors | 2 |
| Prediction | 2 |
| Predictor Variables | 2 |
| More ▼ | |
Source
| College and University | 5 |
Author
| Miller, Thomas E. | 3 |
| Herreid, Charlene H. | 2 |
| Herreid, C. H. | 1 |
| Herreid, Charlene | 1 |
| Miller, T. E. | 1 |
| Riegler, Keri K. | 1 |
| Seidman, Alan | 1 |
| Tyree, Tracy | 1 |
Publication Type
| Journal Articles | 5 |
| Reports - Descriptive | 3 |
| Guides - Non-Classroom | 1 |
| Opinion Papers | 1 |
| Reports - Evaluative | 1 |
Education Level
| Higher Education | 4 |
Audience
Location
| Florida | 4 |
Laws, Policies, & Programs
Assessments and Surveys
| SAT (College Admission Test) | 1 |
What Works Clearinghouse Rating
Direct linkHerreid, Charlene H.; Miller, Thomas E. – College and University, 2009
This article is the fourth in a series of articles describing an attrition prediction and intervention project at the University of South Florida (USF) in Tampa. In this article, the researchers describe the updated version of the prediction model. The original model was developed from a sample of about 900 First Time in College (FTIC) students…
Descriptors: Prediction, Regression (Statistics), Researchers, Intervention
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
Miller, Thomas E.; Herreid, Charlene H. – College and University, 2009
This is the fifth in a series of articles describing an attrition prediction and intervention project at the University of South Florida (USF) in Tampa. The project was originally presented in the 83(2) issue (Miller 2007). The statistical model for predicting attrition was described in the 83(3) issue (Miller and Herreid 2008). The methods and…
Descriptors: Regression (Statistics), College Students, Higher Education, Student Attrition
Miller, T. E.; Herreid, C. H. – College and University, 2008
This article presents a project intended to produce a model for predicting the risk of attrition of individual students enrolled at the University of South Florida. The project is premised upon the principle that college student attrition is as highly individual and personal as any other aspect of the college-going experience. Students make…
Descriptors: Academic Persistence, Student Attrition, Admission (School), Regression (Statistics)
Peer reviewedSeidman, Alan – College and University, 1996
Recent research on college student attrition is examined for trends, and it is suggested that the common perspective on retention and attrition is too narrow; it should be viewed from three perspectives: within-course retention; program retention; and institutional retention rate. Recommended for retention (R) is early (E) identification (Id) plus…
Descriptors: Academic Persistence, College Administration, Dropout Characteristics, Dropout Prevention
