Goal & Concept
Goal
This exercise explores gender participation in science, technology, engineering, and mathematics (STEM) education, from high school through college and into the workforce, and whether participation has changed over the past 20 years. Crosstabulations and frequencies will be used.
Concept
Although the historic discrimination against girls and women in education has been eliminated for the most part, and schools have made much progress in eliminating gender bias from their policies, programs, and practices, there is evidence that females still have not achieved full educational equity.
One area where this becomes apparent is in science, technology, engineering, and mathematics (STEM) education, where females continue to be under-represented even though girls and boys start out performing the same academically.
Examples of research questions about gender in education:
- How does gender affect educational experiences and opportunities?
- How are educational expectations and opportunities related to social views of gender?
- Are educational practices gendered, and if so, how do they affect student achievement?
- How do males and females differ in their attainment of degrees in STEM fields?
- What individual, family and school characteristics are related to students' attainment of a STEM major?
- How do young men and women differ in college trajectories toward or away from STEM?
Dataset
Data for this exercise come from the National Science Foundation (NSF) Surveys of Public Attitudes, which were administered every two or three years from 1979 to 2001. The goal of the surveys was to assess public attitudes toward, and interest in, science and technology, as well as the public's understanding of scientific concepts. The dataset has two subsets. Part 1 is used in this exercise, and includes a wide variety of topics including respondents' interest in medical inventions, space exploration, foreign policy, and government spending on scientific research. It also contains demographic information (gender, race, age, marital status, etc.), and data on levels of education with an emphasis on STEM (Science, Technology, Engineering and Mathematics).
This exercise will use the following variables:
- Gender (GENDER)
- Highest level of math in high school (HIHSMATH)
- Took high school physics course (HSPHYSIC)
- Took high school chemistry course (HSCHEMIS)
- Number of science courses in college in 3 categories (COLLSCI3)
- College major (COLMAJ)
- Job in science field (SCIENG)
- How would R feel if daughter wanted to be a scientist? (DAUGHSCI)
- How would R feel if son wanted to be a scientist? (SONSCI)
- Study year (YEAR)
Application
The NSF Survey of Public Attitudes toward Science and Technology is a multi-year study. Unless otherwise noted, analyses in this exercise focus on data from the last survey year (2001).
Gender and High School STEM Education
Historically women were discouraged from pursuing an education in STEM fields, which were considered inappropriate for women. At the beginning of the 21st Century, do males and females have similar exposure to high school STEM education? To find out, run crosstabs of gender and highest level of math in high school (HIHSMATH), took high school physics course (HSPHYSIC) , and took high school chemistry course (HSCHEMIS) , respectively.
Take a look at the results. Did more men or women take high levels of math? What percentage of women in the sample took calculus, compared to men?
What percentage of men and women took a high school physics course? A chemistry course?
Gender and College STEM Education
To see if these patterns hold for college education look at the variable COLLSCI3, which measures the number of college science courses respondents have taken.
Consider the results of the crosstab between number of science courses in college (COLLSCI3) and gender. Are there significant differences between men and women? Which gender was more likely to have taken 3 or more science courses?
The next crosstab shows the distribution of college majors for each gender in 1981 and 2001. The results are restricted to those respondents with a college degree. The first table shows the crosstab for 1981, the second shows the results for 2001, and the last table combines data for both years.
Looking at the results for 1981 first, then 2001, what percent of (degree-holding) males has a degree in the math/engineering fields? What is the percentage of females with a similar degree? What are the percentages for degrees in biology/physical science/health fields? What do you make of these patterns? Are there similar gender patterns for other majors, and if so, how have they changed between 1981 and 2001? What does this imply for males and females' educational opportunities?
Gendered Expectations, Job Realities
One possible explanation for these gender differences is that males and females face different expectations from parents and teachers. To explore this possibility, examine the variables DAUGHSCI and SONSCI, in which respondents report how they would feel if their daughter/son wanted to be a scientist. This question was only asked in the 1983 and 2001 surveys, so those are the years used in our analyses.
What percentage of 1983 respondents said they would be unhappy if their daughter wanted to be a scientist? What percentage of 2001 respondents reported feeling the same way? Were responses different when respondents were asked about their sons?
The variable SCIENG shows whether respondents have a job in science, engineering or technology fields (coded as "1") or in another field (coded as "0"). Examine the crosstab of SCIENG and GENDER.
What percent of males and females were employed in STEM fields in 2001? Have these percentages changed appreciably compared to 1981?
Interpretation & Summary
Think about your answers to the application questions before you click through to the interpretation guide for help in answering them.
Did more men or women take higher levels of math? What percentage of women in the sample took calculus, compared to men?
What percent of men and women took a high school physics course? A chemistry course?
Were there significant differences between men and women in terms of the number of science courses they've had? Were males or females more likely to have taken 3 or more science courses?
Looking at the results for 1981 first, then 2001, what percent of (degree-holding) males has a degree in the math-engineering fields? What is the percentage of females with a similar degree? What are the percentages for degrees in biology-physical science-health fields? What do you make of these patterns? Are there similar gender patterns for other majors, and if so, how have they changed between 1981 and 2001? What does this imply for males and females' educational opportunities?
What percentage of 1983 respondents said they would be unhappy if their daughter wanted to be a scientist? What percentage of 2001 respondents reported feeling the same way? Were responses different when respondents were asked about their sons?
What percent of men and women were employed in STEM fields in 2001? Have these percentages changed appreciably compared to 1981?
Interpretation
Reading the Results:
- The numbers in each cell of the crosstabulation tables show the percent of the people who fall into the overlapping categories, followed by the actual number of people it represents in this sample. The coloring in the tables demonstrates how the observed numbers in each cell compares to the expected number if there were no association between the two variables. The accompanying bar charts display the patterns visually as well.
- Weights (mathematical formulas) are often used to adjust the sample proportions, usually by race, sex, or age, to more closely match those of the general population. The weight "WT5" was used throughout this guide.
- The results show the following:
- Males and females appear equally as likely to have been exposed to lower levels of math education, with females having a slight edge over males. However, this pattern reverses when looking at the higher levels of math. For example, 13.8% of males but only 8.1% of females had taken calculus.
- 25.8% of women, compared to 39.2% of men in the sample have taken a high school physics course. 47.5% of women and 53% of men have taken a high school chemistry course.
- About two thirds of both men and women had no science course in college. Males were slightly more likely than females to take 3 or more science courses (23.6%, compared to 19.6% for females).
- Among degree holders, men were about 3 times more likely than women to major in math/engineering (23.9% vs. 8.7%) in 1981. These numbers were virtually unchanged in 2001, with 24.1% of males and 8.7% of females majoring in these fields. However females were more likely to major in biology/physical science/health (19.7% vs. 13.1%) in 1981. In 2001 these percentages had increased for both genders, and the difference between men and women had narrowed slightly. One possible explanation for these patterns is that math and engineering are traditionally male subjects. On the other hand, the biology/physical science/health fields, which lead to careers like nursing for example, are typically considered better-suited to women. In 1981 women were more likely than men to major in arts/humanities and education, while men were more likely than women to major in business. By 2001, these differences had all but disappeared, with the exception of education. It appears that math/engineering and education remain highly gendered, unlike other educational fields where these patterns have disappeared or been attenuated.
- Only 6.3% of 1983 respondents reported that they would feel unhappy if their daughter wanted to be a scientist. This percentage dropped to 1.9% in 2001. Even fewer (4.8%) said that they would be unhappy if their son wanted to be a scientist (1983). The number dropped to 1.8% in 2001.
- In 2001 as in 1981, men were about twice as likely as women to be employed in STEM fields (7.6% vs. 4.5% in 1981; 9.9% vs. 5% in 2001). There appears to be very little change between 1981 and 2001.
Summary
The goal of this exercise was to explore gender participation in STEM education, from high school through college and into the workforce, and to see whether participation has changed over the past 20 years. Taken together, the results show that although men are still slightly more likely than women to take physics, chemistry and higher-level math, women are closing the gap both in high school and college. However, it appears that gender still influences students' choice of major, especially when it comes to math and engineering. This carries over to employment, where men are twice as likely to work in STEM fields. This situation has remained virtually unchanged since 1981, despite women's gains in STEM participation and achievement, and the fact that compared to 20 years ago, parents appear more supportive of their daughters' embracing a STEM career.
Further research might explore the role of such factors as peer expectations; societal pressures; classroom climate and student-teacher interaction; dearth of role models; poor preparation and lack of encouragement; lack of a critical mass of women in STEM departments; bias and discrimination in hiring and advancement of women; salary differences and low status; and work/life balance.
Gender in STEM Education: A Data-Driven Learning Guide
Bibliography
We have compiled a list of references (http://www.icpsr.umich.edu/cgi/CITATIONS/search?study={id}&method=study&path=OLC) that might be useful to instructors and students wishing to further explore this topic. All were chosen because they relate to the topic of study, whether or not they use the specific dataset that was used in this exercise. Some relate directly to the concepts as defined by the exercise, others explore the topic more broadly either conceptually or empirically. For even more resources, try a key word search in the ICPSR Bibliography (http://www.icpsr.umich.edu/ICPSR/citations/)!
