What Matters in College for Retaining Aspiring Scientists

What Matters in College for Retaining Aspiring Scientists and Engineers? Mitchell Chang Jessica Sharkness Christopher Newman Sylvia Hurtado Higher Education Research Institute, UCLA 2010 AERA Annual Meeting Friday, April 30 – Tuesday, May 4 Denver, Colorado

Background ¡ U. S. Employment in STEM Demographics 3. 9% 4. 5% White 17. 2% Asian American Black Latino 77. 3% National Science Foundation, 2009

Background ¡ Persistence in STEM: Percentage of 2004 STEM aspirants who completed STEM degrees within five years 50. 0% 42. 0% 40. 0% 33. 0% 30. 0% 18. 4% 20. 0% 22. 1% 10. 0% White Asian American Higher Education Research Institute, 2010 Black Latino

Previous Research ¡ ¡ ¡ Academic preparation Financial need Joining a pre-professional or departmental club Family support, role models, and mentors Structured research programs

Conceptual Model Pre-College Factors & Pull-Factors Initial Commitments Pre-College Ability Final Commitments Persistence Formal/Inform al Academics with Faculty Psychosocial Factors Financial Assist/Need Academic & Social Experiences Educational Aspirations Encouragement & Support Environmental Pull Factors Social Experiences Educational Goal Campus Climates Institutional Commitment Validating Experiences Mentoring Experiences Adapted from Nora, Barlow, Crisp (2005) Reenrollment in Higher Education Institution

Research Questions ¡ Among all students who started college with an interest in majoring in a STEM field, are there significant differences in the proportion of URM students (versus Whites and Asians) who follow through on these intentions? l ¡ If so, are these differences moderated by college experiences? What factors contribute to the STEM major persistence of URM students?

Data ¡ Data Source and Sample: l Longitudinal data: 2004 CIRP Freshman Survey & 2008 CIRP Senior Survey ¡ ¡ ¡ 3, 670 students overall 1, 634 URM students (812 Latino, 626 Black, 196 Native American) Dependent Variable (“STEM persistence”): l Students followed through with first-year intentions to major in STEM field (1), student switched to another major (0) STEM persistence, by race 100% 80% 73. 5% 62. 8% 58. 9% 56. 5% White Native American Latino/a Black/ African American 60% 40% 20% 0% Asian/ Pacific Islander

Analyses ¡ Hierarchical Generalized Linear Modeling (HGLM) l ¡ Two stages of analyses: l l ¡ Appropriate for multi-level data with dichotomous outcome 1. HGLM analysis of student-level predictors of STEM persistence for all-student sample, focusing on significance of race effects 2. HGLM analysis of student and institution-level predictors of STEM persistence for URM students only Significant predictors reported as delta-p (Δ-p) statistics

Results: Research Question 1 Are there significant differences in the proportion of URM students (versus Whites/Asians) who follow through on STEM major intentions? Model 1 Model 2 No No Latino/a Yes (-) No Black/African American Yes (-) No Race Main Effects Native American Blocks of variables included in the model: Gender, mother’s ed. X College Experiences ¡ X X Latinos, Blacks significantly less likely to persist in STEM (vs. Asians & Whites) when only demographics are considered ¡ Effect is moderated by college experiences

Results: Research Question 2 What factors contribute to the STEM major persistence of URM students? ¡ Only significant predictors shown Student-Level Predictors Delta-P High School Academic Preparation/Pre-College Characteristics Math + Verbal SAT score (100 -pt increments) 6. 8% Academic Self-Concept 1. 0% Social Self-Concept -0. 8% Aspire to medical degree (vs. Bachelor’s) -11. 5% College Experiences Participated in undergrad research program 17. 4% Studied with other students 13. 6% Joined club/org. related to major 9. 3% Faculty interaction (factor) -6. 8% Worked full-time while in school -9. 7%

Results: Research Question 2 What factors uniquely contribute to the STEM major persistence of URM students? ¡ Only significant predictors shown Institution-Level Predictors Delta-P Institutional Characteristics Institutional Selectivity (100 -pt increments) -13. 0% Percent of students majoring in STEM (10 -point increments) 5. 57% Model Statistics Explained variance at Level 2 0. 69 Baseline probability of STEM major persistence 0. 58

Discussion ¡ Experiences in college and college contexts can have a significant influence on student persistence in STEM majors, above and beyond high school preparation l l Sponsored Research Programs (MARC, MBRS, etc. ) Studying with other students Institutional Selectivity Proportion of students majoring in STEM

Contact Information Faculty and Co-PIs: Sylvia Hurtado Mitchell Chang Postdoctoral Scholars: Kevin Eagan Josephine Gasiewski Administrative Staff: Aaron Pearl Graduate Research Assistants: Monica Lin Cindy Mosqueda Christopher Newman Juan Garibay Gina Garcia Minh Tran Felisha Herrera Jessica Sharkness 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 R 01 GMO 71968 -01 and R 01 GMO 71968 -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.