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Why So Few? Women in Science, Technology, Engineering, and Mathematics

Why So Few? Women in Science, Technology, Engineering, and Mathematics. Why So Few?. High School Credits Earned in Mathematics and Science, by Gender, 1990–2005. Grade Point Average in High School Mathematics and Science (Combined), by Gender, 1990–2005.

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Why So Few? Women in Science, Technology, Engineering, and Mathematics

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  1. Why So Few? Women in Science, Technology, Engineering, and Mathematics

  2. Why So Few? High School Credits Earned in Mathematics and Science, by Gender, 1990–2005 Grade Point Average in High School Mathematics and Science (Combined), by Gender, 1990–2005

  3. Women are underrepresented in many science and engineering occupations. Percentage of Employed STEM Professionals Who Are Women, Selected Professions, 2008

  4. STEM achievement varies by income level and race/ethnicity

  5. 2009 SAT Math mean scores by family income Source: College Board

  6. 2009 SAT Reading, Math, and Writingmean scores by family income Source: College Board

  7. Why So Few? presents evidence that social and environmental factors contribute to the underrepresentation of women and girls in STEM.

  8. Finding 1 Beliefs about Intelligence Believing in the potential for intellectual growth, in and of itself, improves outcomes.

  9. In math and science, a growth mindset benefits girls. Teach children that intellectual skills can be acquired. Praise children for effort. Gifted and talented programs should send the message that they value growth and learning.

  10. Finding 2 Stereotypes Negative stereotypes about girls’ math abilities can adversely affect girls’ performance in math

  11. Expose girls to successful female role models in math and science. Teach students about stereotype threat. Performance on a Challenging Math Test, by Stereotype Threat Condition and Gender Source: Spencer, S. J., Steele, C. M., & Quinn, D. M., 1999, "Stereotype threat and women's math performance," Journal of Experimental Social Psychology, 35(1), p. 13.

  12. Finding 3 Self-Assessment Girls are “harder on themselves” when assessing their abilities in “male” fields like science and math.

  13. Does this rectangle have more black or more white?

  14. Gender differences in self-assessment

  15. Set clear performance standards • Help girls recognize their career-relevant skills

  16. Finding 4 Spatial Skills Spatial skills are not innate and can be improved with training.

  17. Spatial skills are not innate and can be improved with training. This is a sample question on mental rotation. Do you know the right answer? Encourage girls to play with building toys and to draw to develop their spatial skills.

  18. Finding 5 Implicit Bias In a test of implicit bias, most people associate science and math fields with “male” and humanities and arts fields with “female”.

  19. Our unconscious beliefs may be morepowerful than our explicitly held beliefs simply because we are not aware of them. • Take a test to learn about your unconscious bias at https://implicit.harvard.edu. • Take steps to address your biases.

  20. Finding 6 Bias against Women in Non-traditional Fields • Women in “male” jobs are viewed as less competent than their male peers. • When women are clearly competent, they are often considered less “likable.”

  21. Raise awareness about bias against women in STEM fields. • Create clear criteria for success.

  22. To download the reports: http://www.aauw.org/learn/research/current.cfm To contact me: corbettc@aauw.org

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