Bridging Gaps in Understanding College Graduation Rates

As educational attainment increasingly becomes a prerequisite for economic mobility and societal advancement, understanding the factors influencing college graduation rates is important. The complexity of this issue is highlighted by disparities in completion rates across demographic groups and institutional types. While existing literature offers valuable insights into graduation rate predictors, there remains a gap in comprehensive predictive models that incorporate gender dynamics, acceptance rates, student ethnicity, and the prevalence of distance learning. To alleviate this disparity, data from The National Center for Education Statistics was used to predict whether 4-year public colleges in the US have a graduation rate exceeding 50%. Key factors were hypothesized based on current literature and were used as the dependent variables in the predictive model. Among these variables, after running the predictive model, gender and number of instructional staff, along with acceptance rate were crucial in the prediction of graduation rates.

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Publication Details

Published
2025-04-24
DOI
https://doi.org/10.1109/isdfs65363.2025.11011978
Primary Topic
Higher Education Research Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Bridging Gaps in Understanding College Graduation Rates

Derya Ucuz, Zachary J. Ridder, Serkan Varol, George Thompson
Higher Education Research Studies
article

Bridging Gaps in Understanding College Graduation Rates

Derya Ucuz, Zachary J. Ridder, Serkan Varol, George Thompson
article en

Abstract

As educational attainment increasingly becomes a prerequisite for economic mobility and societal advancement, understanding the factors influencing college graduation rates is important. The complexity of this issue is highlighted by disparities in completion rates across demographic groups and institutional types. While existing literature offers valuable insights into graduation rate predictors, there remains a gap in comprehensive predictive models that incorporate gender dynamics, acceptance rates, student ethnicity, and the prevalence of distance learning. To alleviate this disparity, data from The National Center for Education Statistics was used to predict whether 4-year public colleges in the US have a graduation rate exceeding 50%. Key factors were hypothesized based on current literature and were used as the dependent variables in the predictive model. Among these variables, after running the predictive model, gender and number of instructional staff, along with acceptance rate were crucial in the prediction of graduation rates.

University of Tennessee at Chattanooga (US)
Openalex Percentile: Top 86%
Higher Education Research Studies
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