The Prediction of Performance, Progress, and Persistence of First-Time in College Students with the Texas Common Application

The purpose of this study was to examine data collected by the State of Texas Common Application for Admission in order to predict first time in college students’ progress, performance, and persistence in the first semester of college. Research is clear that student background and pre-college characteristics are associated with college success. At the institution utilized in this study, assured or automatic admissions or criteria are set with minimum standards for two of these pre-college characteristics: standardized test score and high school percentage rank. Institutions across the State of Texas utilize similar uniform admissions standards. This study utilizes multiple regression to explore if other variables gathered from the State of Texas Common Application for Admission add to the prediction of student success over the assured admissions criteria alone. Previous research has explored archival data or institutional databases for similar prediction studies. This study is unique in its assessment of the State of Texas Common Application for Admissions’ data which has been in use for over 10 years with little to no evaluation. Less common pre-college variables will be included such as type of high school curriculum, parent educational background, and date of admission. Further, the dependent variables used in this study provide a comprehensive view of first semester student success and persistence with three measures: first semester quality credit hours completed (progress), first semester grade point average (performance), and retention to the second semester (persistence). The population for this study was approximately 4500 first time in college students admitted in fall 2009 at a four-year public emerging research institution in Texas. Findings indicate that additional variables collected by the Texas Common Application do enhance the prediction of progress, performance, and persistence in the first semester of college, but the variables account for less than 15 percent of the variation in the dependent variables. In addition, differences are found in how these variables predict when gender, race, and family income are considered. This study provides valuable information for enrollment managers and university administrators interested in understanding the entering abilities of first-year students and identifying students who may be at risk for first semester attrition.