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PREP workshop on Emerging Scholars Programs. Washington, DC 18 July 2008 Angela Johnson. You can download this presentation at: http://faculty.smcm.edu/acjohnson/PREP/. Making the case for a program Evaluating the first year Longer-term evaluation Expanding your program. Who I am. MASP

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Prep workshop on emerging scholars programs

PREP workshop on Emerging Scholars Programs

Washington, DC

18 July 2008

Angela Johnson




Who i am
Who I am

  • MASP

  • SMESP


Making the case
Making the case

  • Your ideas?

  • Think also of the particular people you must convince and how to tailor your arguments to them


Making the case1
Making the case

  • Your institution’s track record

  • National statistics

  • Diversity benefits math and science

  • Equity arguments

  • “It’s worked before”/“everybody else is doing it


Your institution s record
Your institution’s record

  • The argument: Our group of interest hasn’t performed as well in calculus (or in SEM majors) as the norm

  • And we can do something about this

  • Possible variables: calc completion rates, calc GPA, % receiving A or B in calc, majoring in math, completing math major, etc.


Your institution s record1
Your institution’s record

  • Our findings at SMCM: descriptive statistics

  • “Between 2000 and 2004, 47% of Black, Latino and American Indian students who enrolled in Calculus I did not complete the class; only 27% of White and Asian students did not.”

  • “Of students who completed the class, 47% of Black, Latino and American Indian students received a B- or above. In contrast, 78% of White and Asian students received a B- or above.”


Your institution s record2
Your institution’s record

  • At CU Boulder: statistical modeling. After controlling for preparation and financial need, Black, Latino & American Indian students were less likely to graduate in science than White & Asian students (Johnson, 2007a).

  • See what data your office of institutional research can give you


National statistics
National statistics

  • The argument: Our group of interest is under-represented among practicing scientists & mathematicians

  • So let’s encourage more of them

  • This approach worked at CU Boulder.


National statistics1
National statistics

  • The National Science Foundation has volumes of data

  • The NSF data can be disaggregated by major, gender, race and US citizenship

  • Examples: all natural science majors (careful: “Science” includes the social sciences; I had to back them out of the science rates)


2004 college grads
2004 college grads

Data retrieved from www.nsf.gov/statistics/nsf07308/content.cfm?pub_id=3633&id=2, 1 March 2007, tables 4, 5 & 6


2004 college grads1
2004 college grads

Data retrieved from www.nsf.gov/statistics/nsf07308/content.cfm?pub_id=3633&id=2, 1 March 2007, tables 4, 5 & 6


2004 phd completers
2004 PhD completers

Data retrieved from www.nsf.gov/statistics/nsf07308/content.cfm?pub_id=3633&id=2, 1 March 2007, tables 10, 11, & 12


2004 phd completers1
2004 PhD completers

Data retrieved from www.nsf.gov/statistics/nsf07308/content.cfm?pub_id=3633&id=2, 1 March 2007, tables 10, 11, & 12


2003 phd scientists
2003 PhD scientists

Data retrieved from www.nsf.gov/statistics/wmpd/employ.htm, 1 March 2007, table H-7


The good news
The good news

Data from www.nsf.gov/statistics/wmpd/sex.htm, Tables D-2 & D-3, retrieved 20 Feb 2007


The bad news
The bad news

  • African American, Latino and American Indian students are less likely to graduate in science than similarly prepared White and Asian students (Huang, Taddese & Walter, 2000, http://www.nsf.gov/statistics/seind04/c2/c2s2.htm#c2s2l2bp3)

  • At CU Boulder: This pattern persists among declared science majors after controlling for financial need and preparation (Johnson, 2007a)


Good for math science
Good for math & science

  • The argument: A more diverse scientific workforce is more creative and energetic; more ideas to draw from

  • Corporate evidence: More diverse companies have greater profits and market share


Equity arguments
Equity arguments

  • The argument: Certain groups have been historically excluded from math and science

  • Further: Those groups continue to have less access to high-quality education


Equity arguments1
Equity arguments

  • Note: This argument is not about the good of any and all diversity; it’s about the exclusion of particular groups.


Equity arguments2
Equity arguments

  • LBJ, 1965, Howard University: “You do not take a person who for years has been hobbled by chains and liberate him, bring him up to the starting line of a race and then say, ‘you're free to compete with all the others,’ and still justly believe that you have been completely fair. Thus it is not enough just to open the gates or opportunity. All our citizens must have the ability to walk through those gates .... We seek not...just equality as a right and a theory but equality as a fact and equality as a result.”


Ongoing inequities
Ongoing inequities

  • Schools are as segregated now as they were in 1967. (Kozol, 2005)

    • 70% of Black & Latino students attend schools that are essentially segregated

    • 80% of White students attend schools that are at least 85% white

  • African American students start kindergarten 1 year behind. By 12th grade they are 4 years behind. (Farkas, 2003)


Equity arguments3
Equity arguments

  • Subconscious bias

  • Implicit Association test: 71% associate science with men, 9% associate it with women.

  • To take the test: implicit.harvard.edu/implicit/demo/

  • For more info: www.projectimplicit.net/research.php

    Nosek, B. A., Smyth, F. L., Hansen, J. J., Devos, T., Lindner, N. M., Ranganath, K. A., Smith, C. T., Olson, K. R., Chugh, D., Greenwald, A. G., & Banaji, M. R. (2006). Pervasiveness and Correlates of Implicit Attitudes and Stereotypes.. Unpublished manuscript: University of Virginia.


Equity arguments4
Equity arguments

  • 2006 report, National Academies

  • Even after controlling for productivity and the significance of their work, women faculty members are paid less, promoted more slowly, given fewer leadership positions, and awarded fewer honors than their male colleagues.

Executive summary, Beyond Bias and Barriers, available at http://www.nap.edu/catalog/11741.html, under “download free”)


National academies report
National Academies report

Executive summary, Beyond Bias and Barriers, available at http://www.nap.edu/catalog/11741.html, under “download free”


National academies report1
National Academies report

Executive summary, Beyond Bias and Barriers, available at http://www.nap.edu/catalog/11741.html, under “download free”


Equity arguments5
Equity arguments

  • Résumés with Black-sounding names and excellent credentials received fewer responses than those with White-sounding names and adequate credentials

  • Bertrand & Mullainathan, 2004 (http://www.povertyactionlab.org/research/papers/bertrand_mullainathan.pdf)


Equity arguments6
Equity arguments

  • My own work documents the ways in which women of color face bigger obstacles than other science students (Johnson, 2007b; Carlone & Johnson, 2007)


It s worked before
“It’s worked before”

  • Refer to the great evaluations on the bibliography

  • Make the case for how an ESP program will set your institution apart from its competitors


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