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Sex differences in mathematics and reading achievement

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Gender inequality is a fact around the globe. According to the U.S. Department of Commerce, women occupy nearly half of all U.S. jobs, yet represent less than 25% of those in science, technology, engineering and math (STEM). The White House has framed the need for women in STEM careers as critical to the continuing success of the U.S. economy. According to the Department of Education, 31% of the degrees and certificates in STEM fields were earned by women in 2008-2009. While this represents an increase of approximately 6% since 2000, this is still troubling given that women represent over 50% of enrollment in bachelor’s (57.4%) and master’s (62.6%) degree-granting institutions.

To better understand the factors that could contribute to such imbalances, Gijsbert Stoet of the University of Leeds and David C. Geary of the University of Missouri looked at sex differences in math and reading achievement levels and their relationship with gender equality indicators. The resulting study, “Sex Differences in Mathematics and Reading Achievement Are Inversely Related: Within- and Across-Nation Assessment of 10 Years of PISA Data,” was published in PloS One in 2013. The researchers used data collected by the Programme for International Student Assessment (PISA), which included math and reading achievement data for nearly 1.5 million 15-year-olds in 75 countries.

The study’s findings include:

  • Sex differences in math are inversely correlated with sex differences in reading, meaning that countries with smaller sex differences in math have larger sex differences in reading, and vice versa.
  • The sex difference in math was negligible among the students at the bottom of the math achievement continuum, but the difference increased as performance levels rose. This difference ranged from 1.9 points favoring girls to 2.4 points favoring boys among boys and girls at the bottom 5% of achievers. At the high end of performance scores, the performance difference ranged from 19.3 points to 21.7 points, both favoring boys. The authors note that this large difference between boys’ and girls’ achievement in math has implications for the under-representation of women in STEM fields.
  • Conversely, sex difference in reading is smaller at the high end of the performance continuum. The average sex difference in reading was three times larger than the sex difference in math. The average difference increased from 32 points in 2000 to 38.8 points in 2009. In 2009, the bottom 5% of boys scored 50 points lower than the bottom 5% of girls.
  • Countries with higher living standards showed larger differences in math.
  • Among all countries, as math and reading scores for both boys and girls go up, living standards and gender equality measures are more likely to be higher.

In considering possible approaches to closing the gender gap in STEM employment, the authors argue that increasing national prosperity is not enough. “The implication is that if policy makers decide that changes in these sex differences are desired, different approaches will be needed to achieve this for reading and mathematics,” they state. “Interventions that focus on high-achieving girls in mathematics and on low-achieving boys in reading are likely to yield the strongest educational benefits.”

Tags: youth, higher education, technology

    Writer: | Last updated: April 25, 2013

    Citation: Stoet, Gijsbert; Geary, David C. PLoS One, 2013. doi: 10.1371/journal.pone.0057988.

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    Analysis assignments

    Read the issue-related New York Times article titled "Bias Persists for Women of Science, a Study Finds."

    1. What key insights from the news article and the study in this lesson should reporters be aware of as they cover these issues?

    Read the full study titled “Sex Differences in Mathematics and Reading Achievement Are Inversely Related: Within- and Across-Nation Assessment of 10 Years of PISA Data.”

    1. What are the study's key technical terms? Which ones need to be put into language a lay audience can understand?
    2. Do the study’s authors put the research into context and show how they are advancing the state of knowledge about the subject? If so, what did the previous research indicate?
    3. What is the study’s research method? If there are statistical results, how did the scholars arrive at them?
    4. Evaluate the study's limitations. (For example, are there weaknesses in the study's data or research design?)
    5. How could the findings be misreported or misinterpreted by a reporter? In other words, what are the difficulties in conveying the data accurately? Give an example of a faulty headline or story lead.

    Newswriting and digital reporting assignments

    1. Write a lead, headline or nut graph based on the study.
    2. Spend 60 minutes exploring the issue by accessing sources of information other than the study. Write a lead (or headline or nut graph) based on the study but informed by the new information. Does the new information significantly change what one would write based on the study alone?
    3. Compose two Twitter messages of 140 characters or fewer accurately conveying the study’s findings to a general audience. Make sure to use appropriate hashtags.
    4. Choose several key quotations from the study and show how they would be set up and used in a brief blog post.
    5. Map out the structure for a 60-second video segment about the study. What combination of study findings and visual aids could be used?
    6. Find pictures and graphics that might run with a story about the study. If appropriate, also find two related videos to embed in an online posting. Be sure to evaluate the credibility and appropriateness of any materials you would aggregate and repurpose.

    Class discussion questions

    1. What is the study’s most important finding?
    2. Would members of the public intuitively understand the study’s findings? If not, what would be the most effective way to relate them?
    3. What kinds of knowledgeable sources you would interview to report the study in context?
    4. How could the study be “localized” and shown to have community implications?
    5. How might the study be explained through the stories of representative individuals? What kinds of people might a reporter feature to make such a story about the study come alive?
    6. What sorts of stories might be generated out of secondary information or ideas discussed in the study?