January/February 2017 – Vol. 29 No. 4

Where Are the Women in STEM? What Can We Do to Support and Retain Them?

Posted: Wednesday, April 1st, 2015

by Laura Henriques

Women are far less likely than men to earn pSTEM (physical Science Technology Engineering and Mathematics) degrees or work in the field. This isn’t a new phenomenon, but it has gotten a bit of press lately. US News and World Reports had an article highlighting a Clinton Foundation Report showing women in developing countries have less access to cell phones (and therefore the internet) than men. This results in decreased access to health care, fewer job options, a lack of flexibility with work and childcare related issues, and a lowered sense of empowerment. That article linked to several other articles about the lack of diversity in STEM fields in the US, the leaky pipeline and more.

US data show that women attend and graduate from college at higher rates than men yet they earn pSTEM degrees at lower rates. A new report released by the American Association of University Women entitled Solving the Equation: The Variables for Women’s Success in Engineering and Computing provides insight into the problem and makes recommendations for helping narrow the gender gap in engineering and computer science fields.

Their report shares research findings that female engineers and computer scientists get hired at lower rates than their male counterparts and are less likely to remain in the field. The figure below (taken from the report) shows the percentage of women in selected STEM occupations. While women have made gains and are fairly well represented in biology and chemistry related fields, their participation is significantly below men in computing/math and engineering fields. (The gender gaps are even larger for women of color.)

Notes: Postsecondary teachers are not included. For biological scientists in the 1980 and 1990 censuses, data include life scientists as well as biological scientists. For chemical and material scientists in the 1960 and 1970 censuses, the category was titled “chemists”; in the 1980 and 1990 censuses, the category was titled “chemists except biochemists.” For computer and mathematical occupations in the 1960 census, no category for computer scientists

Notes: Postsecondary teachers are not included. For biological scientists in the 1980 and 1990 censuses, data include life scientists as well as biological scientists. For chemical and material scientists in the 1960 and 1970 censuses, the category was titled “chemists”; in the 1980 and 1990 censuses, the category was titled “chemists except biochemists.” For computer and mathematical occupations in the 1960 census, no category for computer scientists

One of the findings from the study suggests we have a gender bias. A study was done where university research scientists were given resumes that were identical in every way except for the gender of the applicant. They were asked to provide feedback on the applicant of potential student science-laboratory managers. Male applicants were deemed more competent, more hirable and the faculty member was more willing to mentor the male student. The gender of the scientist reviewing the resume did not factor into the decisions. The scientists were less likely to hire the woman because they viewed her as less competent even though she had an identical resume to the male student (Moss-Racusin et al, 2012 as cited in Corbett & Hill, 2015). The AAUW report shares findings from another study by Reuben and colleagues (2014) that show gender bias in hiring decisions. Based solely on appearance, men got selected at higher rates, based on predictions of future performance men got selected at higher rates. Only when objective past performances could be compared were women selected “correctly” based on performance. There are findings from other studies about stereotype threat, gender bias, and how gender-bias influences self-concept.

The report is not all doom and gloom. The authors showcase successes at Harvey Mudd College (where revisions to their computer science courses, early research experiences and bringing women students to a the Grace Hopper Celebration of Women in Computing conference) and elsewhere. They also make suggestions for us as we move forward. The list below is taken from the report (pages 104-105).

Educators at all levels influence how students perceive the fields of engineering and computing, as well as how students view themselves. The following recommendations come from the literature reviewed on bias (chapters 2, 3, and 4), stereotype threat (chapters 2 and 5), and values and career choice (chapters 6, 7, and 8).

Table2_STEM

While the recommendations from this report are specifically aimed at helping increase participation by girls and women, the recommendations are useful for promoting involvement for all students – male, female, under-represented students, etc.

Works Cited:

Corbett, C. & Hill, C. (2015). Solving the Equation: The Variables for Women’s Success in Engineering and Computing. Washington DC: AAUW. Available online at http://www.aauw.org/research/solving-the-equation/

Moss-Racusin, C. A., Dovidio, J. F., Brescoll, V. L., Graham, M. J., & Handelsman, J. (2012). Science faculty’s subtle gender biases favor male students. Proceedings of the National Academy of Sciences, 109(41), 16474–79. doi:10.1073/pnas.1211286109.

Written by Laura Henriques

Laura Henriques

Laura Henriques is a professor of science education at CSU Long Beach and past-president of CSTA. She serves as chair of CSTA’s Nominating Committee and is a co-chair of the NGSS Committee.

2 Responses

  1. Dear CSTA and Laura,

    Great Article!! I am sharing it with Assembly Woman Ling Ling Chang of the 55th District … she is highly involved in STEM and would be a great advocate for CSTA to reach out to and partner.

    She is coming to our school this week and we are very excited about her visit.

    Your article is enlightening and hopeful. Keep up the great work!

    Gratefully,
    Sue Pritchard … aka … Dr. P. of Washington Middle School in La Habra

  2. Sue — glad you found it useful. How did the meeting go? Laura

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