The following chart shows the “relative strength” between Hispanic-Latinx and White students of the “conditional probability” between each layer of the HS CS pathway in the 2021 State of Computer Science Education Report:
(Observant readers will note that the explanation in the two paragraphs below is the same as that in my previous two posts on Women in HS CS and Blacks in HS CS)
The metrics in the above chart correspond to the CAPE (Capacity-Access-Participation-Experience) framework developed by Carol Fletcher and Joyce Warner at The University of Texas at Austin. The following diagram shows how the CAPE framework maps to the metrics provided by the 2021 State of Computer Science Education Report:
This post also uses data on AP CS Exam pass rates available from Barbara Ericson’s blog to add another layer to the top of the pyramid.
The following table interprets the above chart of the relative strengths between Hispanic-Latinx and Whites of the conditional probabilities between each layer of the high school CS pathway:
| Metric | Value | Interpretation |
|---|---|---|
| Relative Strength Hispanic-Latinx/White FCS School Attendance Ratio | 96.0% | Hispanic-Latinx students are 4.0% less likely than White students to attend a school that offers a foundational computer science course |
| Relative Strength Hispanic-Latinx/White FCS Uptake Ratio | 79.2% | If they attend a school that offers FCS, Hispanic-Latinx students are 20.8% less likely to enroll in an FCS course than White Students |
| Relative Strength Hispanic-Latinx/White AP/FCS Uptake Ratio | 88.2% | Of students enrolled in an FCS course, Hispanic-Latinx students are 11.8% less likely to take an AP CS Exam than White Students. |
| Relative Strength Hispanic-Latinx/White AP Pass Rate | 77.3% | Of students taking an AP CS exam, Hispanic-Latinx students are 22.7% less likely to pass than White Students (AP CS P: 80.2%, AP CS A 67.5%) |
These results seem to be a combination of the issues facing the expansion of high school computer science explored in previous posts in this series:
- High schools that are smaller, rural, and less affluent are much less likely to have a computer science course: The “last mile” problem
- Too many elective alternatives to computer science
- Too few non-AP computer science courses to create a pathway for all students
Looking at Hispanic-Latinx/White relative strength data compared to Women/Men data and Black/White data from previous posts demonstrates the value of using the CAPE (Capacity – Access – Participation – Experience) framework to analyze HS CS statistical data. In general, reports on inequities in high school computer science education focus on the percentage of students taking the AP CS exam out of all students. Until the State of Computer Science Education reports started reporting additional metrics, data from the College Board was the only data that had been available on CS education. The CAPE framework helps break down the various factors behind this complex statistic into components:
The above chart shows that the relative strength of the percentage of women/men taking an AP CS exam out of all students (46.1%) is relatively close to the relative strength of the percentage of Black/White students taking an AP CS exam out of all students (43.4%). However, how the two groups reach these similar results are very different. The low percentage of women taking the AP exam comes from the Participation layer – a relatively small number of women are taking any computer science course. The low percentage of Black students taking the AP exam comes from the Experience layer. While Black students with access to a computer science course are just as likely as White students to take a high school CS class, they are far less likely to take an AP CS exam.
Meanwhile, Hispanic-Latinx students show small but significant gaps at all layers of the CAPE pyramid. But the cumulative effect is not as severe compared to the other two groups looking at the overall AP CS test-taking rates. Interestingly, the gap experienced by Hispanic-Latinx students always falls between the gap seen by women students and by Black students with their respective reference groups.
Please visit the CSEd Analytics page for the underlying data and reports behind this blog post for more nuanced information. The attached reports will also show how your state compares to others in critical CSEd metrics. The next post in the #CSEdAnalytics series will explore the percentage of high students enrolled in a foundational computer science metric from the 2021 report.