Improving Community College Graduation Rates by Identifying Predictors that Matter
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Date
2020-05
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Abstract
Hundreds of thousands of students across the country begin their postsecondary education at community colleges each year, but less than half graduate. The goal of this research was to identify key predictors of credential completion for first-time, first-year postsecondary students at community colleges. Integrated Postsecondary Education Data System (IPEDS) data from 2015 was used for the present study. A total of five linear regression models were developed to analyze the graduation rates at two-year public sector institutions. The models provide insight into statistical significance of relationships between demographics, endowment assets, dual-credit, instructor-type, and federal-grant scholarship. The analysis found that there is a statistically significant relationship among specific demographic groups. Across all models, the presence of a dual-credit program has a statistically significant relationship to graduation rates.
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Keywords
predictors, community college, statistical analysis