Code.org's Approach to Diversity and Equity in Computer Science
The fields of software, computing, and computer science are plagued by stark underrepresentation by gender, race, ethnicity, geography, and family income. While nearly 58% of U.S. high schools offer foundational computer science, disparities in access persist. Rural schools, urban schools, and schools with high percentages of economically disadvantaged students are less likely to offer computer science; and Black/African American students, Hispanic/Latino/Latina/Latinx students, and Native American/Alaskan students are less likely to attend a school that offers it.
This problem extends to university programs and to the software workplace, which suffer a similar lack of diversity. There are many issues to address to solve the entire problem of diversity in the tech workforce - from bias in hiring, retention, and promotion practices to capacity-building in university programs.
Our focus: computer science in grades K-12
More important than the tech workforce pipeline, computer science is now a foundational subject for all 21st-century careers, making access in K-12 to this knowledge an equity issue that must be addressed.
Past studies show that children who study computer science perform better in other subjects, excel at problem-solving, and are more likely to enroll in college. Among young women, those who try AP Computer Science in high school are more likely to major in computer science. Black and Hispanic/Latino students who try AP Computer Science in high school are 7-8 times more likely to major in computer science.
But access to computer science is unequal. A student’s opportunity should not be determined by the color of their skin, their family income, or the neighborhood they grow up in. But in the United States, the opposite is true when it comes to K-12 computer science. Data from the 2023 State of Computer Science report shows there are still big gaps in access and participation to computer science.
Our goal at Code.org is for every student in every school to have the opportunity to learn computer science, and to reach balanced representation in grades K-12. Working towards that goal, we use a holistic approach that spans marketing, curriculum, professional learning, and government policy to close gaps in participation and improve equity across gender, race, income, and geography. We measure our success not only by the total number of students learning computer science, but also by the participation of students from underrepresented groups.
Diversity in AP Computer Science
The charts below show participation in the AP Computer Science exam among young women and students from underrepresented racial and ethnic groups* since 2011. Not only has overall participation grown, but the overall proportion of students from these traditionally marginalized groups has been increasing.
The improvements aren't the result of Code.org's work alone. There is a whole community of organizations working on diversity in CS, but the real credit belongs to the thousands of teachers who have worked for years to improve diversity in their classrooms. While things are moving in the right direction, we have a long way to go to reach a balanced population in computer science.
Diversity of students in Code.org courses
Most Code.org classrooms are nearly evenly balanced. This shows that when educators and administrators offer a curriculum and program designed to support diversity and equity in computer science, participation by these underrepresented groups dramatically exceeds the nationwide numbers and the reality of the tech industry today. ## Code.org’s holistic approach spans curriculum, professional learning, policy, and marketing Below are examples of the many tactics of Code.org to address diversity and equity in K-12 computer science. ### Curriculum From elementary school all the way to high school, Code.org courses are designed specifically with a focus on diverse and equitable participation by traditionally underrepresented students. This is factored into the curriculum itself. As just one example, our high school course sequencing begins with a unit on problem solving, instead of jumping directly into computer programming. This allows students to learn together on an even playing field, even if some students have already had the opportunity to learn some coding elsewhere, like at a summer camp or after-school program.
As another example, across all the [video tutorials](/educate/videos) we produce, we showcase a wide cast of presenters, featuring not only celebrities like Yara Shahidi and Serena Williams, but also computing professionals from underrepresented groups such as Paola Minaya (Latina engineer at Microsoft), Tess Winlock (female engineer at Google), Makinde Adeagbo (Nigerian-American engineer at Facebook and Pinterest), and Kate Starbird (former WNBA basketball player, current computer scientist and associate professor at University of Washington). By including an array of lecturers, diverse role models from different industries are part of our curriculum materials. The outcomes speak for themselves: |Code.org program | Scale (students) | % Female students | % Black, Hispanic/Latino, Native American, Pacific Islander students | |------------------------------------------------- | ----------------- |-------------------|---------------------------------------------------------------------| |Hour of Code | Tens of millions | 61% | 49% (U.S.) | |CS Fundamentals for K-8 | Millions | 46% | 51% (U.S.) |CS Discoveries - middle & high school intro class | Hundreds of thousands | 41% (U.S.) | 49% (U.S.) | |CS Principles - high school AP class | Tens of thousands | 34% (U.S.) | 42% (U.S.) |
The Hour of Code has been offered in classrooms by teachers of all backgrounds and subjects, reaching students globally in over 180 countries.
The results speak for themselves: After over a billion “hours served” reaching almost a quarter of the students on the planet, and with nearly 50% of participants being female, the Hour of Code is the largest-scale effort to introduce computer science to girls.
In addition to the Hour of Code, Code.org regularly produces new materials and programs to improve diversity in computer science. For example, we distribute recruitment posters, and other marketing materials to CS teachers to help them engage more young women and students from underrepresented groups in their classrooms. We also produced the following videos — featuring Black, LGBTQIA+, and female and female-identifying voices — on the importance of learning computer science.
The sum of all these efforts — the curriculum design, the professional learning program, the Code.org Advocacy Coalition, the Hour of Code, and countless smaller efforts and initiatives — is how Code.org is holistically addressing the historical problems with diversity and equity in K-12 computer science.
Our own team’s diversity
Code.org team diversity | % female and nonbinary | % people of color** | % Black | % Hispanic/Latino *** | % Native American/Pacific Islander **** |
---|---|---|---|---|---|
Full time staff | 60% | 34% | 6% | 6% | 1% |
Our leadership team | 60% | 40% | 7% | 7% | 0% |
Our engineering team (software engineers only) | 32% | 27% | 0% | 5% | 3% |
Our technical staff (software engineers, product managers, CS educators) | 44% | 30% | 2% | 8% | 2% |
Teachers attending our professional development workshops | 64% | 21% | 12% | 8% | 2% |
*URG or underrepresented racial/ethnic groups refers to students from marginalized racial/ethnic groups underrepresented in computer science including students who are Black/African American, Hispanic/Latino/Latina/Latinx, Native American/Alaskan, and Native Hawaiian/Pacific Islander. See how Code.org extrapolates this number from external data.
**Two or more races include students from more than one racial/ethnic group. 79% of students who identified as multiracial are from more than one marginalized racial and ethnic groups underrepresented in computer science (Black/African American, Hispanic/Latino/Latina/Latinx, Native American/Alaskan, and Native Hawaiian/Pacific Islanders). See how Code.org extrapolates this number from external data.
***Anybody not identifying as white