Disability in Science, Technology, Engineering and Mathematics (STEM)

Karl S. BookshMissy Postlewaite

Lea Vest

Outline

• A bit about myself• Provocative (hopefully) interpretation of

statistics regarding students with disabilities in STEM

• Introduce panelists– There background and views

• Open discussion

Short CV

• Professor of Chemistry and Biochemistry, University Delaware (2005)– Prof. Arizona State University (1998)

• National Science Foundation (NSF), Committee on Equal Opportunity in Science and Engineering

• Chair, American Chemical Society, Committee on Chemists with Disabilities

• P.I., Summer Research Experience for Undergraduates (REU) aimed at chemists with disabilities

Short Bio – Disability Perspective

• Brother – AVM at age 9• Self – broken neck at age 19• Wife – cerebral palsy• Twin boys– One with ADHD– Both being tested for LD

• Been active with students since undergrad– Parents, Inc. and Easter Seals in Alaska– DO-IT at Univ. Washington

Personal Perspective

Failure to Adequately Serve Persons with Disabilities in STEM

History of Disability in Academic Science

• Ireland, they say, has the honour of being the only country which never persecuted the jews. Do you know that? No. And do you know why? He frowned sternly on the bright air.

• Why, sir? Stephen asked, beginning to smile.• Because she never let them in, Mr. Deasy said

solemnlyJames Joyce in Ulysses

8

Academic Distribution of Disabilities in STEM

7% Population 16 – 20 (1)

13% Population 18- 44 (2)

13% Population 20 – 65 (1)

1% of STEM doctorates (2008) (1)

Biological Sciences 76 Chemistry 23 Agricultural Sciences 23 Phys. and Astronomy 13 Environmental Sciences 8 Math and Stats. 14 Computer Science 22 Psychology 74 Sociology 83 Engineering 50

Postdoctoral Associates suppressed by NSF (1)

Increasing representation with age

1. National Science Foundation, Division of Science Resources Statistics, Women, Minorities and Persons with Disabilities in Science and Engineering, 2009. NSF 09-305.

Session 5

Baseline Data on Students with Disabilities

• 8.6% total school population under IDEA– 13.8% public school attendees

• 7% population between 16 and 21• 13% population between 21 and 65• Interested in STEM fields at same rate as

students without disabilities– In college: 21.7% v. 23.1% – In graduate school: 20.3% v. 21.3%

National Science Foundation, Division of Science Resources Statistics, Women, Minorities and Persons with Disabilities in Science and Engineering, 2009. NSF 09-305.The Condition of Education 2007 (NCES 2007064), National Center for Education Statistics, 2007.

No change in relative STEM Doctoral Attainment since ADA

1985 1990 1995 2000 2005 20100

1.0

2.0

3.0

4.0

5.0

6.0

Year

Perc

ent C

itize

n or

Per

man

ent R

esid

ent

of U

.S. D

octo

rate

s

Black = +0.16 % per year

Hispanic = +0.17 % per year

Disabilities = +0.009 % per year

Native American = +0.011 % per year

National Science Foundation, Division of Science Resources Statistics, Women, Minorities and Persons with Disabilities in Science and Engineering, various years with data from NSF on US Citizens w/ disabilities.

Our (Poorly) Hidden Biases Cause Problems for Others

Faculty prefer to hire themselvesGender

RaceEthnicity

Thought processWork habits

Shared beliefs

Schema

Career trajectory

Solo status / Tokenism Stereotype Threat

Pogo Possum

Session 5 11

Education Path Discrepancies

2-Year v. 4-Year Collegew/ disability 47% v. 42%w/o disability 42% v. 47%

Full-time v. Part-timew/ disability 58.2% v. 41.8%w/o disability 63.4% v. 38.6%

Graduate Students < 24-years oldw/ disability 7.5%

w/o disability 17.6%

Returning students Retraining post disability

Leave of absence for illness

Military Commitments

National Science Foundation, Division of Science Resources Statistics, Women, Minorities and Persons with Disabilities in Science and Engineering, 2009. NSF 09-305.

Session 5 12

13

The Matthew EffectMatthew 13:12 For whoever has, to him more shall be given, and he will have an abundance; but whoever does not have, even what he has shall be taken away from him.

R.K. Merton

“The Matthew Effect in Science”, Science 159: 56-63 (1968)

The more accomplished scientist gets credit, even if lesser contribution

Top universities recruit people with recognized successes (awards)

Receiving small awards impacts receiving bigger awards

Awards tend to go to people from top universities

Same Schema in deciding nominations!

RA supported graduate students w/ disability 16.4% w/o disability 24.4%

National Science Foundation, Division of Science Resources Statistics, Women, Minorities and Persons with Disabilities in Science and Engineering, 2009. NSF 09-305.

Session 5

Civil Rights and/or Jobs Issue• Vicious cycle

– Not attaining educational goals – Under- or unemployment – Lack of role-models and avatars

• March 2013 Dept. of Labor statistics– Labor force participation: 20.7% v. 68.7%– Unemployment: 13.0% v. 7.4%

• Salary gap in S&E– 4% younger than 29 years old– 13% for 40 to 49 years old

• Dept. of Commerce– Predicts 17% increase in STEM jobs 2008 – 2018– 2/3 require college degree– Verses 9% and 1/3 for non-STEMDaughtry, D., J. Gibson, and A. Abels, Mentoring Students and Professionals With Disabilities. Professional Psychology-Research and Practice,

2009. 40(2): p. 201-205National Science Foundation, Division of Science Resources Statistics, Women, Minorities and Persons with Disabilities in Science and Engineering, 2009. NSF 09-305Langdon, D., G. McKittrick, D. Beede, B. Khan, and M. Doms, STEM: Good Jobs Now and for the Future, E.a.S.A. US Depatment of Commere, 2011.

Lack of Programs to Support Students with Disabilities in Postsecondary Education

• 2010 Federal STEM Education Inventory Data Set on broadening participation– All federal agencies with outreach– $397.8M to ‘Institutional Capacity’ or

‘Postsecondary STEM’ • $378.3M to underrepresented minorities• $19.6M to students with disabilities• 19:1 ratio

Sampling of Biggest Programs• NSF LSAMP (~$45M 2010 budget)• NIH RISE (~$24M 2010 budget)• NIH MARC U-STAR (~$21M 2010 budget), • NOAA Educational Partnership with Minority Serving

Institutions (~$15M 2010 budget), • NASA University Research Centers for minority serving

institutions (~$14M 2010 budget),• DOE HBCU STEM Research Workforce Development Program

(~$9M 2010 budget)• NSF Research on Disability Education program (~$ 7 M 2010

budget)– ~35% of available federal funds

‘Focus’ Program Funding (in $M)Program Focus FY 05 FY 06 FY 07 FY 08 FY 09 FY 10 Fy 11 FY 12 (est)

ADVANCE Women 19.9 19.5 16.6 20.1 21.7 21.0 19.8 18.0

AGEP UM 15.0 14.6 15.3 15.9 17.2 16.7 16.7 9.8

BPC UM n/a 14.2 13.5 14.0 14.0 14.0 8.0 8.0

CREST UM 15.6 17.8 18.8 25.0 30.4 30.3 30.4 24.2

HBCU-UP UM 25.3 25.7 27.9 29.7 31.1 32.1 31.9 31.9

LSAMP UM 35.6 36.1 38.1 40.5 42.5 44.6 45.6 45.6

RDE Dis 5.0 5.3 5.4 5.9 6.9 6.9 6.5 6.5

GSE Women 9.9 9.7 9.9 10.1 11.4 11.6 10.4 10.5

TCUP UM 9.2 10.8 10.4 12.8 13.4 13.4 13.3 13.3

TOTAL 135.5 153.7 155.9 174.0 188.6 190.6 182.6 167.8

‘Vicious Cycle’

• How are the academic role models faring?

• Observational data– I don’t know another chemists at a R1 university

who went through undergrad w/ a disability

• Statistical data from NSF

NSF Percent PI on Submitted Proposals

200320042005200620072008200920102011201220130

0.5

1

1.5

2

2.5

3

3.5

4

4.5

f(x) = − 0.0433333333333333 x + 88.1911111111111

f(x) = 0.0716666666666666 x − 140.195555555556

f(x) = 0.0466666666666666 x − 91.5511111111111

Black

Linear (Black)

Year

Perc

ent P

I on

Subm

itted

Pro

posa

ls

NSF Percent PI on Funded Proposals

20022004

20062008

20102012

20140

0.51

1.52

2.53

3.54

4.5

f(x) = − 0.025 x + 51.3333333333333

f(x) = 0.05 x − 96.8333333333334

f(x) = 0.025 x − 48.1777777777778

BlackLinear (Black)Linear (Black)HispanicLinear (Hispanic)Linear (Hispanic)DisabilitiesLinear (Disabilities)Linear (Disabilities)

Year

Perc

ent P

I on

NSF

Aw

ards

NSF Relative Funding Rates

Group FY 04 FY 05 FY 06 FY 07 FY 08 FY 09 FY 10 FY 11

All 23.7% 23.4% 24.6% 25.7% 25.1% 32.3% 23.4% 21.7%

Female 25.1% 25.5% 26.2% 27.1% 27.1% 33.9% 25.1% 22.6%

Male 23.8% 23.2% 24.7% 25.9% 24.9% 32.5% 23.5% 22.0%

Minority 23.4% 23.1% 24.5% 25.5% 24.3% 30.2% 22.5% 21.4%

Disability 23.0% 20.9% 24.7% 23.2% 24.3% 31.7% 19.8% 19.7%

Female All Male Minority Disabil tcrit 90 1.415

Female x 11.679 7.779 7.478 6.497 tcrit 95 1.895

All >99.9 x -1.055 2.620 3.301 tcrit 99 2.998

Male >99.9 equiv x 2.694 3.401 tcrit 99.9 4.785

Minority >99.9 >95 >95 x 1.629 d.f. 7

Disabil >99.9 >99 >99 >90 x

PI Success

• Convolution with university size?• Convolution with career stage?• Lack of mentoring?– NIH study on AA PIs indicates 5% lower funding

rate due to lack of mentoring

Only 3 Active Professional Societies

• American Advancement for Science and Engineering– Project on Science, Technology and Disability

• American Chemical Society– Committee on Chemists with Disabilities

• American Psychological Society– Committee on Disability Issues in Psychology

Where are the Role Models?

• Postdocs with Disabilities in pipeline?– NIH will fund but few apply.

• Faculty at R1 Universities who have successfully navigated the system?– Willing to add outreach to research and teaching

(and home-life)?• Educators at all levels who can see past

‘disabilities’?

Why are We Failing?

• Lack of financial support– Committing funds sends a message of priorities

• Need effort to focus at start of academic career– Losing students after transitions

• Identity– People primarily identify by race/gender, not disability

status• Lack data – To track, understand, and make compelling arguments

• ??

Transitions and Disclosure

• 28% of IEP students disclose disability at postsecondary level

• Disconnect between disclosure protocol at K12 vs. postsecondary

Support Services

K-12• All support integrated under

IDEA

University• Must reapply as adult• Support services

fragmented at federal, state, and local levels

• Must anticipate and articulate needs

• Needs to occur before classes start

Association of University Centers on Disabilities (AUCD)

• Self-determination should be the foundation for transition planning

• Transition should be viewed through a cultural lens

• Interagency collaboration is essential to effective transition

• Transition planning should include all the perspectives, disciplines, and organizations that will impact the transitioning student

Panelists

Questions and Discussion