Student Retention and Graduation at EWU Before and After the Pandemic

Faculty Mentor

Xiuqin Baine

Document Type

Oral Presentation

Start Date

10-5-2023 9:55 AM

End Date

10-5-2023 10:15 AM

Location

PUB 317

Department

Mathematics

Abstract

The aim of this research is to identify key factors that contribute to the retention and graduation of students at Eastern Washington University (EWU), and attempt to see why EWU retention and graduation rates have been falling for the past several years. This is an issue that all colleges have faced since the pandemic but EWU has suffered more in the Spokane area and has been suffering since before the pandemic. The study will examine EWU student data from Summer 2006 to Fall 2023. The main method of analysis will be logistic regression to predict if a student will be retained, however the analysis will also be supplemented with statistical methods such as multiple linear regression, model selection, and principal component analysis. Initially, research was done on the prediction of student success as determined by meeting a GPA threshold. Results were exceptionally poor but in researching it, student retention was found to be a viable predictor. The findings will be presented in the conclusion, with the goal of assisting EWU to understand which student factors have the greatest impact on student retention and graduation rates.

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May 10th, 9:55 AM May 10th, 10:15 AM

Student Retention and Graduation at EWU Before and After the Pandemic

PUB 317

The aim of this research is to identify key factors that contribute to the retention and graduation of students at Eastern Washington University (EWU), and attempt to see why EWU retention and graduation rates have been falling for the past several years. This is an issue that all colleges have faced since the pandemic but EWU has suffered more in the Spokane area and has been suffering since before the pandemic. The study will examine EWU student data from Summer 2006 to Fall 2023. The main method of analysis will be logistic regression to predict if a student will be retained, however the analysis will also be supplemented with statistical methods such as multiple linear regression, model selection, and principal component analysis. Initially, research was done on the prediction of student success as determined by meeting a GPA threshold. Results were exceptionally poor but in researching it, student retention was found to be a viable predictor. The findings will be presented in the conclusion, with the goal of assisting EWU to understand which student factors have the greatest impact on student retention and graduation rates.