Date of Award:

5-2020

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Education

Committee

Marla Robertson

Committee

Ryan Knowles

Committee

Aryn Dotterer

Abstract

Higher education institutions are facing low degree completion rates on an epidemic scale. The role of a bachelor degree completion in the well-being and future life of college students is of paramount importance, impacting physical and mental health, financial stability, relationship satisfaction and duration, safety, and community engagement.

Institutions must be critical of and act to address barriers to degree completion. In addition to an intrinsic investment in the success of their students, institutions may be motivated by institutional improvement, performance-based funding, and the ethical ambition to create an educated society. Understanding when and why students drop and stop out can range from simple to very complex. Large schools with a varied student population may need to assess tens to hundreds of variables to get an accurate understanding of student behavior.

Big data and student predictive analytics are valuable tools to understand the scope and patterns of low degree completion and serve as a common first step on the path to improve completion rates (Baer & Norris, 2016). This project introduces an Individual Analysis Model through which an institution can identify degree completion challenges, then evaluate the institutional resources available as well as static and adaptive data tools which may help leaders understand the issue. A demonstration case is used to show how the model works and provide concrete examples to the reader for reference.

Demonstration case using the Individual Analysis Model: Utah has one of the lowest female degree completion rates in the country, consistently 5-11% behind the national average. Within that data oddity, Utah Valley University (UVU) is consistently one of the lowest female degree completion rates within Utah. This anomaly has been consistent since the 1990s and is not improving at rates similar to their Utah peers. The author uses survival analysis to better understand the impact of change in marital status and change in dependents on students’ likelihood of degree completion.

Results of the research project reinforce the need for an Individual Analysis Model when examining unique student patterns of enrollment and degree completion. Findings indicate that female students are more likely to complete their degree than their male peers. Both male and female students who change marital status and continue enrollment accelerate their timeline to graduation. Male students who add a dependent during enrollment increase their likelihood of graduating where female students have a slight decrease in their likelihood of degree completion.

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