– Regardless of how prior achievement is measured, very little of the strong and persistent gender gap in physical science and engineering majors over time is explained.
– The results indicate that whether focusing on the high end of the test distribution or focusing more broadly on average differences across several indicators including course-taking, conditioning on achievement does extremely little to diminish the gender gap in PS/E majors across time.
– While models that include measures of comparative advantage in math/science (vs. English/reading) appear to account for more of the gender gap in field of study than the other models considered, overall the evidence we present strongly undermines the assertion that women’s underrepresentation in PS/E fields is due to deficits in prior achievement.
– Students whose race and social class background are typically associated with educational disadvantages (including Black and lower socioeconomic status youth) were not underrepresented in PS/E majors at any time point. This offers some evidence consistent with the assertion that STEM fields are universalistic, such that social background characteristics per se are irrelevant for entry.
– The authors have offered powerful evidence that long-standing underachievement arguments fail to provide the answer to the question of gender inequality in representation in STEM postsecondary fields.
2012 - The More Things Change, the More They Stay the Same? Prior Achievement Fails to Explain Gender Inequality in Entry Into STEM College Majors Over Time
The authors utilize data from three longitudinal studies conducted by the National Center for Educational Statistics: The High School and Beyond: Sophomore Cohort, the National Educational Longitudinal Study of 1988, and the Educational Longitudinal Study of 2002. They use data from student and parent surveys conducted during the students’ sophomore year of high school, which was in 1980, 1990, and 2002, respectively, and from follow-up student surveys conducted during their senior year, as well as 2 years after on-time high school graduation. They also utilize information from students’ high school transcripts collected by all three studies to construct measures of course-taking and grades. They restrict their analyses to all students who enrolled in a 4-year degree-granting institution and reported having declared a major field of study on the student survey administered 2 years post high school.
The IVs include self-reported measures for students’ gender and race/ethnicity. Family background indicators include a series of dummy variables to capture the highest level of education obtained by either parent. They also used a measure for family income. They included a dichotomous measure of whether the student enrolled in college the fall subsequent to high school graduation or was delayed in enrollment.
For high school achievement, the authors use relatively standard measures of high school academic preparation (math and science course-taking, math and science grades, and math achievement tests) and then they use measures of high-end achievement as well as their comparative advantage indicator. To measure comparative advantage for GPA, they simply subtract students’ cumulative GPA in English classes taken during high school from their GPA in their math and science courses
Their outcome of interest is student’s declared major. Because different fields within the broad category of STEM are known to have different histories of gender segregation, they distinguish among students who declared a major in PS/E fields (which includes physical sciences, engineering, math, and computer science), those who declared a major in the biological sciences, and those who declared a major in a non-STEM field.