One way to increase diversity in your school’s computer science classes?
New data points to impact of teacher diversity
Note: As of September 2020, this post contains outdated language or graphics referencing “underrepresented minorities.” To see our current language policy around race, ethnicity, and gender, see this support article.
We just ran the numbers for our high school classes and found that the diversity of students is directly correlated to the teachers in the classrooms. Though the difference is small, when multiplied by 10’s of thousands of students, the impact is real.
It’s not surprising to learn that you’d find more girls in classes with female teachers. And, having Black, Hispanic, or Latino teachers would be an inspiration to Black, Hispanic, or Latino students. But, we also see promising data that teachers from underrepresented minorities may also be correlated with more women in their classes.
Unfortunately, just as certain minorities are underrepresented in the tech industry, they are also underrepresented in teaching. Black, Hispanic, and Latino teachers are underrepresented across teaching in general — especially relative to our student populations. While 44% of students come from an underrepresented minority, only 18% of American teachers and only 15% of STEM teachers come from one of these groups.
To support our goal of increasing access to computer science, we’ve reached out to a diverse cohort of teachers through our professional learning program, and help all teachers understand the importance of including equitable teaching practices in their computer science classrooms. We want to buck the trend and support more women and underrepresented minorities teaching computer science. At this point, we’re encouraged to see that teachers in our programs mirror the general population of teachers — and show growth among STEM teachers — at 60% female and 19% underrepresented minorities. But, we clearly still have a long way to go.
We can’t wait to see the impact these teachers — and future teachers — will have after teaching Computer Science Principles over many years. We hope that this research inspires even more women and underrepresented minorities to begin teaching computer science at their schools.
Alice Steinglass — President, Code.org
Code.org collects self-reported gender data from all students and self-reported race data from students in the United States who are at least 13 years old. Since all data is self-reported and voluntary, our analyses assume that students of all races and genders report their demographic information at the same rate.
Students and teachers are considered underrepresented minorities (URM) in computer science if they listed their race as including one or more of the following: “American Indian/Alaska Native”, “Black or African American”, “Hispanic or Latino”, or “Native Hawaiian or other Pacific Islander.” Students are considered non-URM if they listed their race as “White,” “Asian,” or both “White” and “Asian.”