Kevin Eagan Sylvia Hurtado Mitchell Chang Higher Education Research Institute UCLA ASHE 2010

1. What Matters in STEM: Institutional Contexts That Influence STEM Bachelor’s Degree Completion Rates Kevin Eagan Sylvia Hurtado Mitchell Chang Higher Education Research Institute UCLA ASHE 2010 Indianapolis, IN

2. Introduction

3. Introduction • Research has focused on individual students’ • background characteristics • prior preparation • introductory courses • undergraduate research experiences • extracurricular activities • But has not closely examined • the context of students’ experiences • the structure of opportunity

4. Research Questions 1. What individual pre-college and college entry characteristics and experiences predict STEM students’ likelihood to complete a STEM bachelor’s degree within five years of entering college? 2. What institutional characteristics and programs account for variations across institutions in students’ average probability of completing a STEM bachelor’s degree within five years of entering college? 3. Do the effects of students’ background characteristics, such as race, vary across institutions? If so, can institutional characteristics and programs enhance or mitigate these effects?

5. Methods • Data • 2004 CIRP Freshman Survey • 2009 Best Practices Survey • 2009 National Student Clearinghouse enrollment and completion data • Sample • 55,178 STEM aspirants who began college in 2004 • 237 four-year colleges and universities

6. Methods • Dependent variable • 3-part categorical variable: (1) earned a STEM degree, (2) earned a non-STEM degree, (3) did not earn a degree • Independent variables • Student-level: race, gender, HS curriculum, prior achievement, STEM identity and career goals, high school activities • Institution-level: HBCU, control, selectivity, presence of undergraduate research opportunities, STEM retention programs, formalized student-faculty interaction

7. Methods • Analyses • Missing data: multiple imputation • Cross-tabs: Institutional STEM completion rates x Best Practices • Multinomial Hierarchical Generalized Linear Modeling

8. Limitations • Examining STEM aspirants • Best Practices Survey – multiple respondents per institution • Analysis of five-year completion data

9. Results Five-Year STEM Completion Rates by Race

10. Results Five-Year STEM Completion Rates by Extent of Undergraduate Research Opportunities

11. Results • STEM Degree vs. No Degree • Undergraduate research opportunities (+)* • Selectivity (+) • Black, Latino, Native American (-) • High school GPA (+) • Years of HS math, chemistry, biology (+) • Sex: Female (+) • Hours per week spent studying in HS (+)

12. Results • STEM Degree vs. Non-STEM Degree • STEM retention programs (+)* • HBCU vs. PWI (+)* • Black, Latino vs. White (-) • Asian American vs. White (+) • High school GPA (+) • Years of HS chemistry, math (+) • STEM career goal (+) • Expectation of changing major (-) • Sex: Female (-)

13. Discussion • The role of selectivity • The role of HBCUs in STEM education • Variation in the effect of race • Persistent significance of prior academic preparation in predicting STEM completion

14. Contact Information Faculty and Co-PIs: Sylvia Hurtado Mitchell Chang Postdoctoral Scholars: Kevin Eagan Josephine Gasiewski Administrative Staff: Aaron Pearl Monica Lin Graduate Research Assistants: Christopher Newman Minh Tran Jessica Sharkness Tanya Figueroa Gina Garcia Felisha Herrera Cindy Mosqueda Juan Garibay Papers and reports are available for download from project website: http://heri.ucla.edu/nih Project e-mail: herinih@ucla.edu Acknowledgments: This study was made possible by the support of the National Institute of General Medical Sciences, NIH Grant Numbers 1 R01 GMO71968-01 and R01 GMO71968-05 as well as the National Science Foundation, NSF Grant Number 0757076. This independent research and the views expressed here do not indicate endorsement by the sponsors.