Blog Post

Diversity Tools for Assessing CS in Your High School

In previous blogs from my series on Assessing CS in Your High School, I wrote about how your classroom and school fit into the larger movement and dove into the first element of equity—access. This post provides tools for tracking and reporting on the second element—diversity.

Tracking Diversity Data

Equity in CS is not likely to improve if it is not measured, providing visibility and feedback to the effort. While this is best managed at the district level, it can start with one teacher and one school, and grow over time. A spreadsheet I’ve created serves as a first step, focused on an initial assessment at the school level.

A goal for CS diversity is for student participation in CS to be consistent with the overall student population, relative to gender, ethnicity/race, and social/economic status (SES). This comparison may seem straightforward, but the data may be challenging for a teacher to collect. Teachers do not always have access to official schoolwide or student-specific data. A teacher might feel uncomfortable asking students how they identify or simply guessing.

Ideally, this data would be collected at the district level using official school data. This would be required before major decisions could be made based on the data. But, as a first step, more informal data can be helpful to provide visibility and inform recruitment efforts for CS classes. This data can also be the start of conversations that lead to more formal data collection at the district level.

Data needed includes:

● Percentage breakdowns for gender, ethnicity/race, and SES for the school.

● Percentage breakdowns for gender, ethnicity/race, and SES for each CS course.

● Gender categories: female, male, and non-binary.

● Ethnicity/race categories: Asian, Black or African American, Hispanic/Latino, Native Hawaiian/Other Pacific Islander, White, and two or more races.

● SES categories: Free or Reduced Price Lunch (FRPL) or not.

The following categories are underrepresented in computer science:

● Female and non-binary

● Black or African American, Hispanic/Latino, Native Hawaiian/Other Pacific Islander, and two or more races.


How to Use the Spreadsheet

Make a copy of the spreadsheet and choose the Diversity tab. The box at the top provides the summary of the goals and if they are met or if improvement is needed.

image of spread sheet header showing measurement categories


The grey cells are cells that you edit. The purple text is sample text that you will replace with real data. The other cells are based on formulas and are locked. Enter the course names and percentage breakdowns for each category, by course and for the school as a whole. The summary at the top will update automatically.

image of spread sheet showing diversity percentages


Next Steps

You can use this data to start a conversation about computer science at your school with your team lead and your administration. You can proactively recruit for CS courses using toolkits such as NCWIT’s Computer Science Is for Everyone. You can meet with school counselors to share information about the importance of CS.

It would be ideal to connect with the person at the district who oversees computer science. This person may be able to track more accurate data. Ideally, the data would also be tracked across schools and school years. The district is also in a position to take powerful steps, such as requiring at least one CS course for graduation. CSforAll’s SCRIPT program is ideal for a district-level assessment of equitable CS.

Providing equitable computer science education is a daunting effort! Especially if your school currently has limited CS offerings, it might seem like there isn’t much you can do. But strong CS programs are most often started by a single, passionate teacher who begins the conversation. This could be you!

Be on the lookout for my final post in the series about inclusion!


Carol Ramsey has researched using narrative as pedagogy to increase interest and engagement in STEM for girls and managed programs developing equity-focused curriculum and teacher professional development. She holds a computer science degree and has 20 years of experience as a software developer and program manager. She strives to bring positive tech experiences to under-represented students, to support more student opportunities and a more diverse tech workforce.



Submitted by Brianna Blaser on Thu, 06/17/2021 - 4:23 pm EDT

This is a great resource.  If I could make one addition, it would be to also collect data on the participation of students with disabilities in your CS classes. At the K12 level, you can track students that have an IEP or a 504 plan.  If you're interested in learning more, we published a paper on collecting data on disabilities in CS at the RESPECT conference last year: Why is Data on Disability so Hard to Collect and Understand?.