The University of Hawai ʻ i at Mānoa ACCESS TO SUCCESS: LEADING INDICATORS WORKGROUP

 First Time freshmen of Fall 2003 o n = 1,809 o Enough history to examine first term retention through degree completion  Transfer students entering in Fall 2009 o n = 1,804 o Currently studying retention

 Data Collection, Causal Modeling, Results

 Created a longitudinal database with over 100 data elements theoretically related to retention & graduation (see handout for list of variables): o Demographic o Geographic Origin o Pre-Collegiate Experiences o Academic and Course Experiences o Campus Experience o Financial Aid o Interaction Variables o Additional Variables from LI Research!

Gender Age Ethnicity Residency Geographic Origin High School GPA & Rank SAT AP CLEP Educational Goals Transfer GPA # Transfer Credits Major Credit Load Credits Earned First Term GPA Distance Education Dual Enrollment High Failure Rate Courses Courses Taken (including Math & English) On Campus Employment Housing Student Life Activities Athletics STAR Usage Average Class Size Need Based Aid Non-need Based Aid Pell Grant Work Study % of Aid Met Ethnicity by Geographic Origin Employment by Housing High School GPA by First Term GPA Residency by Need Based Aid Ratio of Successful Adds to Drops Retention & Degree Completion Demographics Pre-College Academic Campus Experience Financial Need Interactions

Credits Earned Yr. 1 Dual Enrollment Geographic Origin Ethnicity High School GPA First Term GPA Enrollment in College Level Math Year 1 Strongest Weakest Degree Completion These variables account for approximately 34% of the variance in a student’s likelihood of completing a degree (Pseudo R Square =.344). *Wald statistic (sig.) The Wald test statistic was used to indicate strength of the variable instead of the coefficient, standardized beta. Because of the nature of the logistic regression, the coefficient is not easily interpretable to indicate strength (<.001)* (<.001)* (<.001)* (<.001)* (.001)* (.001)* (.013)*

 Variables significant in predicting degree completion of freshmen: o “Expected” predictors emerging from model: Ethnicity (Asian students 2x greater odds) Geographic Origin (1.9x greater odds for HI students) First Term GPA (1.5x greater odds per grade point increase) o Not-so obvious predictors: >= 24 Credits Earned in Year 1 (Odds Ratio = 6x) Dual Enrollment (Odds Ratio = 2x) Enrollment in College-Level Math in Year 1 (Odds Ratio = 1.5x) Prior Credits Earned (Odds Ratio = 1.5x)

 73% of observations correctly classified o Sensitivity: 76% o Specificity: 70%

1 st Term GPA On Campus Employment Declared Major Geographic Origin Distance Education Ethnicity Need-Based Aid Strongest Weakest Transfer Student Retention These variables account for approximately 26% of the variance in a student’s likelihood of completing a degree (Pseudo R Square =.258). *Wald statistic (sig.) The Wald test statistic was used to indicate strength of the variable instead of the coefficient, standardized beta. Because of the nature of the logistic regression, the coefficient is not easily interpretable to indicate strength (<.001)* (<.001)* (<.001)* (<.001)* (.003)* (.008)* (.045)*

 Engaging the students in understanding o Positive Psychology i.e How taking 15 credits will help students graduate in 4 years Showing students the cost implications of delaying their studies The power of a phone call  Targeted interventions o Use at-risk forecasting data to predict and inform o Focus on at-risk students on the “threshold”

 Florida State University o 85% retention rate in 2000 up to 91% in 2009 o Retention Task Force started at the very top level o Main efforts were in IR and Advising  U of Nevada at Reno o 76% in 2005 up to 80% in o Retention Task Force started at the very top; same focus as FSU o Quantified data in terms of $/revenue. o Covered in Media nationally

 Facilitate credit momentum o “Do it in 4” Project o Students missing credit milestones are called in for advising  Drive enrollment in Math & English in students’ first year o Automatic (pre)registration for first year students o Examine course pressure points; course wait listing  Mandatory advising in first semester on campus o Mandatory declaration of major by second year on campus  New opportunities for on-campus employment: o Undergraduate Research, Student Success Fellowships, Legislative Internships  Fast track transfer policies o Automatic admit for UH System students o Transfer programs like “Ka’ie’ie”

Mānoa Institutional Research Office Dr. Ron Cambra Assistant Vice Chancellor for Undergraduate Education John Stanley Institutional Analyst