Campus Units
Education, School of
Document Type
Article
Publication Version
Published Version
Publication Date
7-6-2015
Journal or Book Title
Strategic Enrollment Management Quarterly
Volume
3
Issue
2
First Page
109
Last Page
131
DOI
10.1002/sem3.20064
Abstract
Improving student success and degree completion is one of the core principles of strategic enrollment management. To address this principle, institutional data were used to develop a statistical model to identify academically at-risk students. The model employs multiple linear regression techniques to predict students at risk of earning below a 2.0 grade point average (GPA) in their first semester of college. Data analysis from student cohorts starting in the Fall 2007 through Fall 2009 (N = 11,644) identified two groups of students—one predicted to earn less than a 2.0 and the other predicted to earn a 2.0 or higher. The first semester college GPA and retention rates of both groups of students were tracked to examine the accuracy of the model in predicting student success and subsequent retention rates. Multi-year analyses illustrates that the model can be used to identify students who are at risk of earning less than a 2.0 GPA. Additional analysis demonstrates there is a relationship between predicted and actual first semester GPA and retention rates. Since the data used to develop the model are commonly available at most institutions, this study provides a practical approach for the SEM research professional to identify potentially academically at-risk students, which subsequently can be used to assist students and improve student success and degree completion.
Copyright Owner
Wiley
Copyright Date
2015
Language
en
File Format
application/pdf
Recommended Citation
Gansemer-Topf, Ann M.; Compton, Jonathan I.; Wohlgemuth, Darin R.; Forbes, Gregory R.; and Ralston, Katerina S., "Modeling Success: Using Preenrollment Data to Identify Academically At-Risk Students" (2015). Education Publications. 37.
https://lib.dr.iastate.edu/edu_pubs/37
Included in
Educational Assessment, Evaluation, and Research Commons, Higher Education Commons, Student Counseling and Personnel Services Commons
Comments
This is the peer reviewed version of the following article: FULL CITE, which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving