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Disability in Science, Technology, Engineering and Mathematics (STEM) Karl S. Booksh Missy Postlewaite Lea Vest.

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Presentation on theme: "Disability in Science, Technology, Engineering and Mathematics (STEM) Karl S. Booksh Missy Postlewaite Lea Vest."— Presentation transcript:

1 Disability in Science, Technology, Engineering and Mathematics (STEM) Karl S. Booksh Missy Postlewaite Lea Vest

2 Outline A bit about myself Provocative (hopefully) interpretation of statistics regarding students with disabilities in STEM Introduce panelists – There background and views Open discussion

3 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

4 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

5 Personal Perspective

6 Failure to Adequately Serve Persons with Disabilities in STEM

7 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 solemnly James 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 Sciences76 Chemistry23 Agricultural Sciences23 Phys. and Astronomy13 Environmental Sciences 8 Math and Stats.14 Computer Science22 Psychology74 Sociology83 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 8

9 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.

10 No change in relative STEM Doctoral Attainment since ADA 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.

11 Our (Poorly) Hidden Biases Cause Problems for Others Faculty prefer to hire themselves Gender Race Ethnicity Thought process Work habits Shared beliefs Schema Career trajectory Solo status / Tokenism Stereotype Threat Pogo Possum Session 5 11

12 Education Path Discrepancies 2-Year v. 4-Year College w/ disability 47% v. 42% w/o disability 42% v. 47% Full-time v. Part-time w/ disability 58.2% v. 41.8% w/o disability 63.4% v. 38.6% Graduate Students < 24-years old w/ 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 512

13 The Matthew Effect Matthew 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/ disability16.4% 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 13

14 Some Reasons Students with disabilities are – More likely to attend 2-year (47%) than 4-year (42%) institutions – More likely to go part-time (63.8%) than students w/o disabilities (58.2%) – Older in graduate school 17.6% v. 7.5% younger than 23 – Less likely to be on RA 16.4% v. 24.4% National Science Foundation, Division of Science Resources Statistics, Women, Minorities and Persons with Disabilities in Science and Engineering, 2009. NSF 09-305

15 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-STEM Daughtry, D., J. Gibson, and A. Abels, Mentoring Students and Professionals With Disabilities. Professional Psychology-Research and Practice, 2009. 40(2): p. 201-205 National Science Foundation, Division of Science Resources Statistics, Women, Minorities and Persons with Disabilities in Science and Engineering, 2009. NSF 09-305 Langdon, 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.

16 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

17 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

18 ‘Focus’ Program Funding (in $M) ProgramFocusFY 05FY 06FY 07FY 08FY 09FY 10Fy 11FY 12 (est) ADVANCEWomen19.919.516.620.121.721.019.818.0 AGEPUM15.014.615.315.917.216.7 9.8 BPCUMn/a14.213.514.0 8.0 CRESTUM15.617.818.825.030.430.330.424.2 HBCU-UPUM25.325.727.929.731.132.131.9 LSAMPUM35.636.138.140.542.544.645.6 RDEDis5.05.35.45.96.9 6.5 GSEWomen9.99.79.910.111.411.610.410.5 TCUPUM9.210.810.412.813.4 13.3 TOTAL 135.5153.7155.9174.0188.6190.6182.6167.8

19 ‘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

20 NSF Percent PI on Submitted Proposals

21 NSF Percent PI on Funded Proposals

22 NSF Relative Funding Rates GroupFY 04FY 05FY 06FY 07FY 08FY 09FY 10FY 11 All23.7%23.4%24.6%25.7%25.1%32.3%23.4%21.7% Female25.1%25.5%26.2%27.1% 33.9%25.1%22.6% Male23.8%23.2%24.7%25.9%24.9%32.5%23.5%22.0% Minority23.4%23.1%24.5%25.5%24.3%30.2%22.5%21.4% Disability23.0%20.9%24.7%23.2%24.3%31.7%19.8%19.7% FemaleAllMaleMinorityDisabiltcrit 901.415 Femalex11.6797.7797.4786.497tcrit 951.895 All>99.9x-1.0552.6203.301tcrit 992.998 Male>99.9equivx2.6943.401tcrit 99.94.785 Minority>99.9>95 x1.629d.f.7 Disabil>99.9>99 >90x

23 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

24

25 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

26 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’?

27 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 ??

28 Transitions and Disclosure 28% of IEP students disclose disability at postsecondary level Disconnect between disclosure protocol at K12 vs. postsecondary

29 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

30 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

31 Panelists

32 Questions and Discussion


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