A Statistical Analysis Utilizing Detailed Institutional Data Academic Performance and Persistence of Undergraduate Students at a Land-Grant Institution: A Statistical Analysis Utilizing Detailed Institutional Data Fran Hermanson, Vicki McCracken, and Diem Nguyen Washington State University INTRODUCTION GRADUATION PROFILE KEY FINDINGS High School GPA is a significant predictor of first semester college GPA and positively affects the probability of graduation (both five and six year). SAT/ACT is a solid (positive) predictor of first semester WSU GPA but does not significantly impact the probability of graduation. Varsity Athlete status increases the odds of student graduation, and is linked to higher GPAs. Federal Pell Grant eligibility is associated with lower WSU GPAs and probabilities of completing the degree, indicating financial constraints negatively impact student success. Students who take Biology/Chemistry/Math all in the first semester have significantly lower first semester GPAs but graduate at similar rates as their counterparts. Despite differences in graduation rates by race/ethnic groups, the race/ethnicity variables are not significant in the multiple regression/logistical analyses. Non-continuous enrollment significantly lowers the probability of graduation. Washington residents had lower first semester GPAs, but had higher probabilities of graduating. Improving student success in postsecondary education is a key federal, state, and university objective that is inseparable from the focus on increasing student access. In Washington State, about 59 percent of college students graduate within six years. At Washington State University (WSU), a six-year graduation rate is approximately 68 percent. These statistics raise concerns about the retention and graduation of college students and the need for improving student success at WSU. This study uses WSU institutional data to analyze factors associated with academic performance and persistence of WSU students and provide some policy implications for improving the retention and graduation rates. STATISTICAL MODELS 1. Performance Model Yi is the WSU GPA of student i for the first semester. Xi is a vector of explanatory variables including: race/ethnicity, gender, age, residency, HSGPA, SAT/ACT, Pell eligibility, full/part- time status, whether a varsity athlete, affiliation with Greek system or Honors College, simultaneously taking Biology/Chemistry/Math, and if in a STEM (Science, Technology, Engineering, and Math) discipline. 2. Graduation Model Zi is a binary random variable, whose value equals 1 if student i graduated by the 6th (or 5th) year and 0 if not; and Pi is the graduation probability for student i. Xi is a vector of explanatory variables with additional predictors: first semester GPA (adjusted), transferred credits, and stop-out. SELECTED RESULTS IMPLICATIONS The empirical results suggest an admission process selecting students based on individual potential for success should consider factors in addition to high school GPA and SAT/ACT. Retention efforts should identify students based on other risk factors (in addition to high school GPA and SAT), such as financial aid, residency, housing, enrollment status, running-start, etc. METHODOLOGY This study applies statistical techniques to determine factors affecting student performance and graduation at WSU. OLS regression is used for the first-semester performance model with GPA as the response variable and logistic regression is used for the graduation model with a binary response . The survival analysis method is used to take into account the longitudinal nature of the student progression and the censoring data problem. Pre-college and post-enrollment variables, student demographics, and institutional characteristics are examined in both performance and graduation models. DATA Analysis based on institutional data for 2 cohorts of students that entered WSU (Pullman campus) as new freshmen in fall 2002 and fall 2003. Detail included information about the student prior to enrolling and then at the end of 1st semester, 2nd semester, and subsequent semesters until 12th semester. Analyzed dataset consisted of 5841 students, of which 1894 are censored (had not graduated by the 12th semester), accounting for over 32 percent of the 2 cohorts.