Paper presented at the 2012 Annual Forum of the Association for Institutional Research

1. Priming the Pump or the Sieve:
Institutional Contexts and URM STEM
Degree Attainments
Sylvia Hurtado
Kevin Eagan
Bryce Hughes
Higher Education Research Institute, UCLA

2. A National Imperative
National Academies (2011) report Expanding
Underrepresented Minority Participation: America’s
Science and Technology Talent
 Establishes most of the growth in the new jobs will require
science and technology skills
 ―Those groups that are most underrepresented in S&E are
also the fastest growing the general population‖ (National
Academies, 2011, p. 3).
 In an effort to achieve long-term parity in a diverse
workforce, they recommend a near term, reasonable goal of
improving institutional efforts to double the number of
underrepresented minorities receiving undergraduate STEM
degrees.

3. A National Imperative
2012 President’s Council of Advisors on Science and Technology
(PCAST) report, Engage to Excel: Producing One Million
Additional College Graduates With Degrees In
Science, Technology, Engineering, And Mathematics
 Increasing the retention of STEM majors from 40% to 50%
would, alone, generate three-quarters of the targeted 1 million
additional STEM degrees over the next decade.
 Retaining more students in STEM majors is the lowest-
cost, fastest policy option to providing the STEM professionals
that the nation needs.
 Changing productivity levels means changing practices, and
mindsets from priming the sieve to priming the pump, or talent
development.

4. Purpose of the Study
• Identify the faculty and institutional
characteristics that contribute to higher rates
of STEM degree completion, particularly
among underrepresented groups, controlling
for students’ entering characteristics.
• Identify challenges and opportunities to prime
the pump and improve the use of ―evidence-
based‖ approaches.

5. Literature Review: Student-level
Characteristics
 Pre-college experiences
 Strong high school curriculum
 High test scores and grades
 Advanced courses in science and mathematics
 High aspirations for a STEM degree
 URM students less likely to access AP courses,
yet equally or more likely to aspire to a STEM
degree

6. Literature Review: Institutional-Level
Characteristics
 Faculty pedagogies
 STEM courses tend to utilize teacher-centered pedagogies
 Introductory STEM courses perceived as ―gatekeepers‖ to STEM
degrees
 Student-centered pedagogies key to retaining women and URM students
in STEM programs
 Minority-targeted STEM retention programs
 Generally improve probability of URM STEM degree completion
 Mixed results regarding improving URM academic performance
 Undergraduate research experiences
 Found to be one of the most effective contributors to increasing URM
STEM completion odds
 Benefits to students participating in undergraduate research may be
conditional depending on timing and duration
 Minority-serving institutions (MSIs)
 HBCUs in particular provide a unique atmosphere that supports Black
students’ degree attainment
 Research is beginning to demonstrate benefits for other URM students
attending other categories of MSIs

7. Literature Review: Are Selective
Institutions Better for URM Students?
 More selective universities have higher graduation rates
 URM students also graduate at higher rates from more
selective institutions
 More recent studies have found conditions that indicate
this benefit does not apply across the board
 Wider usage of multilevel modeling in higher education
research has shown single-level modeling overstates the
effects of selectivity
 Selectivity was found to be negatively related to four-year
retention of women of color in STEM
 Biomedical and behavioral science students attending more
selective institutions were slightly but significantly less likely
to be retained in these programs to their fourth year
 Yet many recent multilevel studies continue to confirm
selectivity positively predicts higher probability of
graduation

8. Percentage of 2004 STEM Aspirants Who Completed STEM
Degrees in Four, Five, and Six Years, by Race/Ethnicity
60
52.4
50 46.6
43
40.4
40 38.5
35.8
29.6 29
30
24 24.3 24.9
22 21.8
20.2
20 18.2
12.3 11.6
9.4
10
0
4-Year Completion 5-Year Completion 6-Year Completion
All students (N=56,499) White (N=39,160) Asian American (N=7,621)
Latino (N=3,863) Black (N=4,695) Native American (N=1,160)
Data Source: 2004 Freshman Survey, 2010-11 National Student Clearinghouse;
HERI, UCLA

9. Method
• Longitudinal Data on STEM Aspirants
• Individual level: 2004 Freshman Survey, CIRP
merged with completion data from the National
Student Clearinghouse
• Sample: 58, 292 students across 353 institutions
• Faculty Data: 2007 & 2010 HERI Faculty Survey from
659 institutions, with STEM Supplement for over
10,000 STEM faculty
• STEM Best Practices Survey – administered to STEM
deans and department chairs at our participating
campuses
• Institutional Data obtained from IPEDS, Aggregates of
Faculty, and Aggregates of Peer characteristics from
students entering the same institutions in 2004.

10. Method
 Dependent Variable:
 STEM completion compared to:
 Bachelor’s completion in non-STEM field
 No bachelor’s degree completion-includes students still
enrolled (major not known)
 Measured at four, five, and six years to reflect
differences in time to degree

11. Method
 Independent variables
 Background characteristics
 Pre-college preparation and experiences
 Aspirations and expectations
 Intended major
 Aggregate peer effects
 Institutional characteristics
 Faculty contextual measures
 Best practices in STEM

12. Method
 Analysis
 National weights
 Missing data with multiple imputation
 Multinomial HGLM
 Limitations
 Intended rather than declared major
 NSC data – no information on term-to-term major
 No college experience measures
 Few high school preparation variables
 BPS data reported by STEM Deans and Dept.
Chairs

13. Key Findings for Four Year Completers:
STEM vs. Non-STEM
 Denser concentrations of MD aspirants and larger
campuses negatively predict STEM completion
 Differences by race
 Latino (-), Black(ns)
 Asian/Pacific Islander (+)
 Other race (+)
 Women (-)
 HS grade (+), and effect enhanced by faculty use
of student-centered pedagogy
 SAT, years of HS math and biology (+)

14. Key Findings for Four-Year Completers:
STEM vs. Non-STEM
 MD aspirant (+) but effect mitigated by faculty
grading on a curve and selectivity (-) condition
 Ph.D./Ed.D. aspirant (+)
 Law degree aspirant (-)
 Engineering, physical sciences, health
tech/nursing, and computer science (+)
 Pre-med, pre-pharm, pre-dental, pre-vet (-)

15. Key Findings for Five-Year Completers:
STEM vs. Non-STEM
 Drop in predictive power of institutional size
 Non-sig difference between Latino/other groups
and White students
 Decrease in gender gap
 Decrease in salience of SAT
 Decrease in gap between BA/BS aspirants and
law/medical aspirants
 Changes regarding majors
 Engineering increased gap, more likely to complete
in 5 years
 Physical science, health tech/nursing, and computer
science gap decreased compared to biomedical
aspirants

16. Key Findings for Six-Year Completers:
STEM vs. Non-STEM
 Decreased salience of institutional size
 Closing of gender gap
 Women at selective institutions have lower STEM
completion rates than women at less selective
institutions
 Drop in gap between medical degree aspirants
and BA/BS aspirants

17. Key Findings for Four-Year STEM
Completion versus No Completion
 Control: private (+)
 Research-focused (-) vs. comp. masters
 Concentration of STEM undergraduates (-)
 Institutional size (+)
 Pct. of faculty involving undergraduates in research
(+)
 Selectivity (+)
 Racial differences: Native American and Latino (-);
Asian American (+)
 Black (-), mitigated by HBCU (+) and selectivity (-)
 Women (+)
 Low/Low-middle income (-); upper-middle (+)

18. Key Findings for Four-Year STEM
Completion versus No Completion
 HS GPA, SAT scores, years of math and bio (+)
 Expect to transfer (-)
 MD aspirant (+), mitigated by faculty grading on a
curve (-) and selectivity (+)
 Masters degree aspirant (+)
 Law degree aspirant (-)
 Engineering and pre-med/pharm/dental/vet (-)
 Health tech/nursing (+)

19. Key Findings for Five-Year STEM
Completion vs. No Completion
 Loss of significance: institutional
control, concentration of STEM
undergraduates, size, percentage of faculty
involving UGs in research
 Expanded gender gap (women +)
 Expanded gap between low-income and middle
income
 Reduced salience for SAT composite
 MD aspirations become less salient
 Increased predictive power of planning to live on
campus
 Only academic major difference: pre-

20. Key Findings for Six-Year STEM
Completion vs. No Completion
 Size and faculty’s involvement of undergraduates
in research significant (like in 4-year model)
 Racial gaps persist, African American and Native
Am (- incr.)
 Gender gap declines and is moderated by
selectivity (+) condition
 Predictive power of MD aspiration drops
further, as does law degree aspiration

21. URM Six Year Completers in STEM
Compared With Non-STEM Completers:
 Concentration of premedical undergraduates (-)
 MD aspirants (+), but MD aspirants at more selective
institutions less likely to stay in science than MD aspiring
peers at less selective institutions
 Law degree asp. (-) vs. BA/BS aspirants
 Engineering aspirants (+) vs. biological sciences,
 HS GPA (+), and higher achieving students complete at even
higher rates on campuses where STEM faculty used student-
centered pedagogy more often
 SAT Composite and years of HS math (+)
 Females (-)
 Academic self-concept (+)
 No significant differences between URM groups among
completers in STEM vs. Non-STEM

22. URM Six Year Completers in STEM Compared
with non-Completers
 STEM faculty that involve undergrads in research
(+)
 Selectivity (+)
 HS STEM outreach programs at institutions (-)
 Native Americans (-) vs. Latina/os
 Women (+)
 English Native speakers (-)
 Health technology/nursing majors (-) vs. life
sciences majors
 HSGPA, years of HS math, and academic self-
concept (+)
 Intend to live on campus freshman year (+)

23. Conclusion
Contexts Matter
Selective institutions can improve productivity. They
promote degree completion, but students are not more
likely to complete in a STEM degrees.
Premed Phenomenon
Students who begin premed at institutions are more
likely to complete in STEM, are less likely to complete
in STEM at selective institutions, high % of premeds
causes students to switch from STEM among four year
completers—presumably a talented group.

24. Conclusion
Supportive Environments Work!
 Minority engineers are more likely to be retained
in STEM if they complete college compared to
bioscience aspirants.
 Having an undergraduate research program has
an effect on retaining minority students in STEM
(and quicker degree completion).
 Faculty student centered pedagogy was
important to staying in STEM for high-achieving
minority students.
 Grading on curve particularly hurt premed
aspirants, they were more likely to leave STEM at

25. Conclusion
In order to produce 1 million more STEM
degrees, we have to address diversity and
equity in attainments and improve access to
STEM careers.
Call for evidence-based teaching practices in
STEM.
New initiatives by AAU and APLU indicate
great interest in ―demonstration campuses‖ that
can make transformations to increase
productivity of STEM degrees.

26. Contact Information
Faculty/Co-PIs: Postdoctoral Scholars: Administrative
Sylvia Hurtado Kevin Eagan Staff:
Mitchell Chang Josephine Gasiewski Dominique
Harrison
Graduate Research Assistants:
Tanya Figueroa Felisha Herrera
Gina Garcia Bryce Hughes
Juan Garibay Cindy Mosqueda
Papers and reports are available for download from project website:
http://heri.ucla.edu/nih
Project e-mail: herinih@ucla.edu
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, the National Science Foundation, NSF Grant Number 0757076, and the American Recovery
and Reinvestment Act of 2009 through the National Institute of General Medical Sciences, NIH Grant 1RC1GM090776-01. This
independent research and the views expressed here do not indicate endorsement by the sponsors.