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 ID: 167570
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Slide1
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, ColoradoSlide2
Background
U.S. Employment in STEM Demographics
National Science Foundation, 2009Slide3
Background
Persistence in STEM:
Higher Education Research Institute, 2010
Percentage of 2004 STEM aspirants who
completed STEM degrees within five yearsSlide4
Previous ResearchAcademic preparation
Financial need
Joining a pre-professional or departmental club
Family support, role models, and mentorsStructured research programsSlide5
Conceptual Model
Adapted from Nora, Barlow, Crisp (2005)
Pre-College Factors &
Pull-Factors
Initial Commitments
Academic & Social Experiences
Persistence
Educational Aspirations
Formal/Informal Academics with Faculty
Social Experiences
Campus Climates
Validating Experiences
Mentoring Experiences
Educational Goal
Institutional Commitment
Reenrollment in Higher Education Institution
Pre-College Ability
Psychosocial Factors
Financial Assist/Need
Encouragement & Support
Environmental Pull Factors
Final CommitmentsSlide6
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?
If so, are these differences moderated by college experiences?
What factors contribute to the STEM major persistence of URM students? Slide7
Data
Data Source and Sample:
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”):Students followed through with first-year intentions to major in STEM field (1), student switched to another major (0)
STEM persistence, by raceSlide8
Analyses
Hierarchical Generalized Linear Modeling (HGLM)
Appropriate for multi-level data with dichotomous outcome
Two stages of analyses:
1. HGLM analysis of student-level predictors of STEM persistence for all-student sample, focusing on significance of race effects2. HGLM analysis of student and institution-level predictors of STEM persistence for URM students only
Significant predictors reported as delta-p (
Δ
-p) statisticsSlide9
Results: Research Question 1Are there significant differences in the proportion of URM students (versus Whites/Asians) who follow through on STEM major intentions?
Model 1
Model 2
Race Main Effects
Native American
No
No
Latino/a
Yes (-)
No
Black/African American
Yes (-)
No
Blocks of variables included in the model:
Gender,
mother’s ed.
X
X
College
Experiences
X
Latinos,
Blacks significantly less likely to persist in STEM (vs. Asians & Whites) when only demographics are considered
Effect is moderated by college experiencesSlide10
Results: Research Question 2What 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%Slide11
Results: Research Question 2What factors uniquely contribute to the STEM major persistence of URM students?
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
Only significant predictors shownSlide12
DiscussionExperiences in college and college contexts can have a significant influence on student persistence in STEM majors, above and beyond high school preparation
Sponsored Research Programs (MARC, MBRS, etc.)
Studying with other students
Institutional Selectivity
Proportion of students majoring in STEMSlide13
Contact Information
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.
Papers and reports are available for download
from project website:
http://heri.ucla.edu/nih
Project e-mail:
herinih@ucla.edu
Faculty and Co-PIs:
Sylvia
Hurtado
Mitchell Chang
Monica Lin
Gina Garcia
Felisha
Herrera
Postdoctoral Scholars:
Kevin Eagan
Josephine
Gasiewski
Administrative Staff:
Aaron Pearl
Graduate Research Assistants:
Christopher Newman
Minh Tran
Jessica
Sharkness
Cindy
Mosqueda
Juan
Garibay