Session 10: Factors of Significance for Graduating at a Private College

Presentation Type

Oral

Student

Yes

Track

Methodology

Abstract

This research project examined factors that influence odds of graduating at a small, rigorous, private college in the Midwest. De-identified data from the college’s database for the 2013 to 2016 cohorts was collected by the Institutional Research office and provided to the researcher. Several statistical and machine learning techniques were utilized to develop predictive models, including logistic regression and neural network analyses. Fields included include number of major changes, time spent relaxing, satisfaction, and exam preparation techniques. Control variables included distance from home, high school gpa, and religious affiliation. The methods of analysis will be compared and contrasted and results will be discussed.

Keywords: graduation rates, logistic regression, higher education

Start Date

2-8-2022 2:30 PM

End Date

2-8-2022 3:25 PM

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Feb 8th, 2:30 PM Feb 8th, 3:25 PM

Session 10: Factors of Significance for Graduating at a Private College

Pheasant Room 253 A/B

This research project examined factors that influence odds of graduating at a small, rigorous, private college in the Midwest. De-identified data from the college’s database for the 2013 to 2016 cohorts was collected by the Institutional Research office and provided to the researcher. Several statistical and machine learning techniques were utilized to develop predictive models, including logistic regression and neural network analyses. Fields included include number of major changes, time spent relaxing, satisfaction, and exam preparation techniques. Control variables included distance from home, high school gpa, and religious affiliation. The methods of analysis will be compared and contrasted and results will be discussed.

Keywords: graduation rates, logistic regression, higher education