A study of the non-academic factors influencing four-year degree completion among African Americans and Latinos at a public research university

Increasing national emphasis on college completion and affordability has prompted institutional efforts to focus on increasing efficient degree attainment within four-years. Traditional predictors of four-year graduation, Scholastic Achievement Test (SAT) scores and high school grade point average (...

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Bibliographic Details
Main Author: Wasielewski, Miguel Vincent
Format: Others
Published: 2014
Subjects:
Online Access:http://hdl.handle.net/2152/24785
Description
Summary:Increasing national emphasis on college completion and affordability has prompted institutional efforts to focus on increasing efficient degree attainment within four-years. Traditional predictors of four-year graduation, Scholastic Achievement Test (SAT) scores and high school grade point average (GPA) may disproportionately negatively impact the enrollment of African American and Latino students who are more likely to receive lower scores on these metrics. This study sought to identify quantifiable non-academic metrics that can assist to predict bachelor's degree attainment in four years for African Americans and Latinos who do not meet typical standardized testing and scoring predictors. A regression analysis was performed on CIRP Freshmen Survey data for University of Texas at Austin students first enrolled in fall 2008 to assess the strength of Freshmen Survey constructs and student-level financial aid to predict graduation within a four-year timeframe. The results showed that the combined consideration of select variables increased the accuracy of prediction by over seven percentage points; moreover, two factors, holding a positive self-concept and likelihood of college involvement, demonstrated statistical significance within the model. While there are several study limitations, the findings offer support for further exploration of a model for predicting four-year graduation that considers non-academic data elements. === text