Transcript Making a Difference in Science Education for

Making a Difference in
Science Education
for Underrepresented Students:
The Impact of Undergraduate Research Programs
Kevin Eagan
Gina Garcia
Felisha Herrera
Juan Garibay
Sylvia Hurtado, Principal Investigator
Mitchell Chang, Principal Investigator
Higher Education Research Institute, UCLA
2010 AIR Annual Forum
Chicago, Illinois
Introduction
• Graduate enrollment in science and engineering has
been increasing
• However, URM enrollment continues to lag behind
– Proportion of URMs in graduate programs during 20062007 academic year
• American Indian 0.4%
• Black 4.9%
• Latina/o 3.6%
• STEM completion rates remain low (esp. for URMs)
– Huang, Taddese, & Walter (2000)
– Higher Education Research Institute (2010)
Purpose
• To examine the effects of undergraduate
research programs on students’ intentions to
enroll in graduate school through the use of
advance statistical techniques on multiinstitutional data.
– Propensity score matching
Background
• Graduate School Enrollment
– Prior academic achievement
– Race/socioeconomic status
– Parent education
– Institutional selectivity
– Level of involvement
– Student faculty interaction
Background
• Benefits of undergraduate research programs
Retrospective Analyses
Single Time Point
Longitudinal
Hurtado, Cabrera, Lin,
Arellano, & Espinosa (2009)
Lopatto (2004)
Russell, Hancock, &
McCullough (2007)
Maton & Hrabowski (2004)
Barlow & Villarejo (2004)
Hunter, Laursen, & Seymour
(2006)
Bauer & Bennett (2003)
Hathaway, Nagda, &
Gregerman (2002)
MacLachlan (2006)
Seymour, Hunter, Laursen,
& Deantoni (2004)
Conceptual Framework
Social and Cultural Capital
• Capital inherited through social position and
family background
• Social capital acquired in college complements
the capital that students bring with them
Science Identity
• Fostering knowledge growth
• Opportunities to display scientific knowledge &
practices
• Acknowledgement of being a science person
Research Questions
1. What pre-college experiences and characteristics of
entering college students predict their likelihood of
participating in a structured undergraduate research
program during college?
2. After accounting for students’ chances of participating
in an undergraduate research program, what effect
does participation in such a program have on students’
intention to enroll in graduate/professional school,
particularly in a STEM field?
Methods: Sample
• CIRP Longitudinal Sample (n=4,212)
– 2004 Freshman Survey (TFS)
– 2008 College Senior Survey (CSS)
• Targeted institutions:
– Strong reputations in STEM graduation rates
– Undergraduate research programs funded by NSF
and NIH
– Minority-serving institutions
Methods: Variables
• DV: 3-part variable representing post-college intentions:
– Enroll in graduate/professional STEM program
– Enroll in graduate/professional non-STEM program
– No intentions to pursue graduate/professional degree
• IVs
–
–
–
–
–
–
–
–
Undergraduate research participation
Science identity
Career focus in 2008
College GPA
College experiences
Pre-college preparation
Demographics
Institutional characteristics
Methods: Analyses
• Missing data
• Propensity score matching
– Discussion of the counterfactual
– Estimation of the propensity score related to
participation in an undergraduate research
program
– Multinomial hierarchical generalized linear
modeling
Methods: Analyses
• Issues of selection bias/endogeneity
• Counterfactual framework
– “a potential outcome, or the state of affairs that
would have happened in the absence of the
cause” (Guo & Fraser, 2010, p. 24)
– Comparing a “treated” individual with a “nontreated” individual
• Propensity score estimation
Methods: Analyses
• Reweighting of the data with derivations of
the propensity score
– Average treatment effect
– Average treatment of the untreated (ATU) effect
– Average treatment of the treated (ATT) effect
• Multinomial hierarchical generalized linear
modeling
Limitations
• Secondary data analysis
• Limited DV: intentions and combination of
graduate and professional school
• Unobservable variables affecting
undergraduate research participation
• Weighting adjustment using propensity score
rather than matching by propensity score
Findings: Predictors of Participating in
Undergraduate Research Programs
• Major: Physical sciences (10.77%), Life
sciences (7.34%), Health sciences (4.90%)
• Race: Black (5.71%)
• Participated in pre-college research program
(4.03%)
• Degree aspiration in 2004: Ph.D. (3.54%)
• Composite SAT score (100-point change):
2.27%
Findings: Effects of Undergraduate Research
Program Participation on Graduate/Professional
School Enrollment Intentions
Intend to Enroll in a STEM
Graduate/Professional Program
Log
Delta-P odds S.E.
Sig.
Intend to Enroll in a non-STEM
Graduate/Professional
Program
Log
Delta-P Odds S.E. Sig.
Average treatment effect (ATE)
Average treatment for the
untreated (ATU)
Average treatment for the
treated (ATT)
7.84%
0.39 0.16
*
4.96%
0.23
0.17
7.95%
0.40 0.16
*
5.98%
0.28
0.18
6.91%
0.34 0.15
*
-0.45%
-0.02
0.15
Unadjusted multinomial HGLM
8.38%
0.42 0.14
**
1.77%
0.08
0.15
***
1.80%
Simple mean comparison
13.50%
Discussion
• Confirmation of results from prior studies
– “Effect” is much more modest than prior studies
might suggest
• UG research programs attract students who
already identify as scientists
• Average treatment of the untreated (ATU)
effect
– Expand the reach of these programs
– Ensure programs not only harvest talent but
develop it, too
Conclusion and Directions for
Future Research
• Follow these students into graduate school
and examine matriculation patterns
• Investigate via qualitative methods the quality
of students’ research experiences
• UG research programs as wise investments
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: [email protected]
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.