Introduction

High school graduation rates are widely used as indicators of school performance, student readiness, and system effectiveness. But a single percentage, while convenient, compresses variation that exists across schools, districts, and student populations. To better understand graduation outcomes, we need geographic, structural, and demographic contexts.

This project begins with Travis County, Texas, a region with a large public school network and direct pathways into higher education through UT Austin, Austin Community College, St. Edward’s University, and beyond. Its scale and educational infrastructure make it a strong starting point for examining graduation outcomes across four major student groups: Asian, Black, Hispanic, and White. We focus on the year 2020, when learning environments, support systems, and academic structures were tested in ways that exposed differences in student experiences.

What drives this project is my own experience attending a boarding school in Travis County as an international student. I received a wonderful education and made meaningful connections with peers from diverse backgrounds, which also highlighted to me how educational environments shape student trajectories and motivated my interest in graduation patterns across demographic groups. This leads to the project’s central question:

“How do graduation outcomes for Asian, Black, Hispanic, and White students differ at the school, county, and state levels, and how do these racial gaps change as we move from local to national scales?”

From this starting point, the analysis expands outward: We first examine Travis County high schools, then across Texas counties, and finally the United States as a whole.

1. Graduation Outcomes Within Travis County Schools


The visualization above enables us to examine Travis County’s high school graduation outcomes over five years (2016-2020), school by school with each point representing a campus and provides overall rates alongside rates for Asian, Black, White, and Hispanic students. This approach allows us to compare schools, observe trends, and see how outcomes vary across student groups, revealing patterns that a single countywide average would obscure.

Across 2016 through 2020, racial gaps in graduation rates remain stable, shaped largely by each school’s environment. At high-performing campuses like Austin and Anderson High, graduation rates are consistently high for Asian, Black, White, and Hispanic students, suggesting these schools provide structures that support all students. In contrast, schools such as Garza Independence, Graduation Prep Academy, and The Excel Center show lower overall graduation rates and wider racial gaps, where Asian students often graduate at the highest rates, while Black and Hispanic students graduate at substantially lower rates despite attending the same schools. This repeated pattern over five years demonstrates that graduation depends not just on location but on how race interacts with the specific school environment. This observation proves to us that demographics could be an influencing factor for high school graduation outcomes.

These school-level results prompt the question of whether racial gaps are driven by individual campuses or whether they persist when viewed through district structures. Individual schools may vary in size, resources, student composition, etc, but school districts represent the broader forces that shape graduation outcomes. Therefore, aggregating five years of campus data into district-wide averages could help reveal race-based graduation gaps.

2. Travis County Five-year Average By Demographics & School District

Across all 7 school districts in Travis County, racial graduation gaps show variations: Certain districts lift all groups together, while others produce divides, similar to how schools behave in the previous section. Eanes, Lake Travis, and Pflugerville ISD rise to the top with graduation rates in the mid to upper-90s for all four racial groups, showing that strong performance and racial balance can exist together. Austin ISD sits slightly lower but remains consistently high, keeping every racial group near or above the ninety percent mark. In these districts, Asian, Black, Hispanic, and White students graduate at nearly parallel levels, and the absence of large racial gaps is as important as the high averages themselves. These districts give us a sense of what it looks like when race is not strongly tied to graduation chances.

In the lower half of the chart, the colors shift and the racial patterns become more uneven: Manor ISD shows a wide spread, with Asian, Black, and Hispanic students clustered in the mid eighties while White students fall far lower, creating the largest gap of any district in this set. Del Valle ISD reveals a different distribution entirely. Hispanic and Black students average above ninety percent, White students sit a few points below them, and Asian students fall under eighty percent, producing the lowest five year average of any race in the chart. Each district produces its own racial layout, and no racial group seems universally advantaged or disadvantaged across the county.

These district-level gaps show that racial gaps are not uniform but shaped by district contexts, just as they varied by school contexts earlier. In some districts disparities nearly disappear, while in others they widen. This raises the next question: If we zoom out to the county level and examine trends across time, can we isolate and observe racial differences alone once both school-level and district-level variation fade into the background?

4. Where does Travis County stand in Texas?


Stepping out from Travis County to view the statewide context offers us an important reality check: In the full distribution of Texas counties, Travis County falls below the statewide average. In 2020, Travis County’s overall graduation rate is 89.7 percent, while the Texas average across all counties is 91.6 percent. On the boxplot, most counties cluster on the higher end of the distribution, with Travis County positioned toward the lower half, ranking 51th out of 66 counties studied. This makes Travis County more of an outlier in the opposite direction we might expect. Even though we saw earlier that Travis County’s racial groups perform strongly and uniformly when examined alone, the county as a whole does not keep pace with many of its statewide peers. The boxplot makes this clear by situating Travis County among a wide spread of counties that, on average, graduate a larger share of students. What explains this difference?

To understand why Travis County finishes 2020 below the state average, we need to consider the characteristics of the counties it is compared with. Graduation outcomes vary across Texas, and these differences may reflect factors beyond school systems alone. Since this project examines racial patterns in relation to graduation outcomes, in the next section, we introduce the racial makeup of each county and explore whether that relates to the graduation rates those counties achieve.

5. County Makeup and Graduation Outcomes in Texas


Once we move from Travis County to individual Texas counties, we see that while Travis County ends 2020 with all racial groups clustered between 95 and 97 percent, many Texas counties do not show such alignment on the County Overview tab. Across Texas counties, the graduation outcomes of the four racial groups separate more sharply than they did within Travis County. In counties such as Chambers or San Patricio, all four groups graduate at or near 100 percent, showing that high performance is possible, but not typical. In other counties, outcomes separate noticeably: in Comal County, the highest graduation rates are recorded by White students (above 95 percent), while in Cameron County Hispanic students graduate at 88.3 percent, which pulls the countywide rate into the high 80s. Black students are often the lowest-performing group when we compare counties statewide, and their rates decline most sharply across counties relative to Asian, White, and Hispanic students. By contrast, Asian students tend to cluster at the higher end of the distribution, frequently exceeding 95 percent. Taken together, these examples demonstrate a consistent statewide ordering of outcomes: Asian students perform highest, White students generally follow, Hispanic students fall below those levels, and Black students face the most persistent disadvantage across counties.

Moreover, at the statewide county level, racial composition becomes a clearer and consistent predictor of graduation outcomes. The scatterplots show that Asian and White students generally follow upward trajectories: counties with larger proportions of these groups tend to have higher graduation outcomes for them. Hispanic students show flatter, slightly downward trends, indicating weaker or modestly negative changes as their representation increases. Black students display the most visible downward pattern, with outcomes decreasing more sharply in counties where they constitute a larger share of the student population. These results indicate that the relative presence of each group in a county can either reinforce or weaken graduation outcomes in systematic ways. The What-If tab makes this relationship even clearer. As demographic shares increase, the fitted lines for Asian and White students slope upward, while the fitted line for Hispanic students remains relatively flat and the fitted line for Black students slopes downward. This shift in slopes highlights how demographic composition shapes graduation trajectories in distinct and consistent ways across racial groups.

When we previously examined Travis County alone, school and district conditions introduce layers that have could have softened or obscured racial differences, which potentially led to four student groups aligning by 2020. However, once we shift to counties across Texas, those local influences fall away, and clearer racial gaps emerge after county demographic composition is introduced to predict graduation outcomes. This prompts us to examine how graduation outcomes for these four student racial groups across states in the next section.

6. Graduation Outcomes Across the United States by State


When we zoom out to the national landscape, the 2020 graduation map reveals a country that performs comparatively well overall, but with clear regional patterns that shape where students are most likely to graduate. Nationally, the average stands at 86.5%, and most states cluster in the mid- to high-80s. Still, several regions stand out: The Upper Midwest including Iowa, Wisconsin, Nebraska, Missouri, and Minnesota, posts graduation rates near or above 90 percent, which hints at well-established statewide systems that support broad student attainment. Much of the Northeast parallels this strength, with states such as New Jersey, Pennsylvania, Massachusetts, and Maine hovering near the top of the distribution. Other regions tell a different story: The Southwest and portions of the Mountain West, such as Arizona and New Mexico, fall well below the national average, dipping into the low- to mid-70s. The variation becomes even more pronounced in the Deep South: Mississippi and Alabama perform competitively, while Georgia and South Carolina trail noticeably behind their neighbors. Western states like Colorado, Nevada, and California sit near or slightly below the national mean, forming a mixed mid-range cluster.

Texas stands at 91.6 percent, outperforming the national average by more than five percentage points and aligning more closely with the higher-performing Midwest and Northeast than with its neighboring Southwestern states. What this map emphasizes is not simply the broad distribution of graduation outcomes, but that performance clusters systematically by region rather than scattering randomly. High outcomes tend to concentrate across parts of the Midwest and Northeast, while states across the Southwest and Mountain West more often fall below the national average, with much of the South occupying an intermediate band. These clear regional differences reflect structural conditions operating at the state level and suggest that the drivers of variation extend beyond the influence of local school systems observed earlier in Travis County and across Texas counties.

This statewide variation also indicates that averages may conceal differences among the demographic groups within each state. Whereas localized influences moderated patterns in Travis County, the broader state-level environment may allow racial disparities to surface more clearly. To assess this, we next break down the national data by our original four student racial groups.

7. State-Level Graduation Outcomes by Student Demographics



The violin plot demonstrates that when graduation outcomes are compared at the national level, the racial gaps become wider and more patterned than what we observed in Travis County or across Texas counties. Asian and White students form the upper tiers: their state-level graduation distributions are tightly concentrated, with most states reporting outcomes above 90% and very few states falling below 85%. Hispanic and Black students occupy distinctly lower ranges. Hispanic state averages center around the low 80s, and the spread extends from the mid-70s up through the high 80s. Black students show the broadest and lowest distribution, with many states in the low-to-mid 70s and only a few approaching or exceeding 85%. The magnitude of separation is substantial: the gap between the average Asian outcomes and the average Black outcomes is often 15-20 percentage points, far exceeding what we saw when examining Texas alone. This difference in spread illustrates that demographic disparities do not simply persist when the scale widens; they expand, stabilize, and become predictable features of the national outcome structure.

The dot plot confirms this disparity through within-state comparisons. Rather than random deviations, the visualization shows a repeated hierarchy in which Asian and White students occupy the top positions and Hispanic and Black students occupy the lower positions in most states. The gaps are notable and, in some cases, extreme. In Maryland, Asian students graduate near 95% while Hispanic students fall near 75%, a spread of almost 20 percentage points. In Nevada, Asian rates are roughly 93% while Black and Hispanic rates sit near 80%. In the District of Columbia, the gap becomes even more severe: White students graduate above 93% while Black students graduate closer to 64%, a 20-30 percentage point separation. Even in states where all students do relatively well-such as New Jersey or Wisconsin-the hierarchy remains visible, with Asian and White students consistently outperforming Hispanic and Black students. Conversely, states such as New Mexico show lower outcomes for all groups, yet the spread between the highest- and lowest-performing racial groups still mirrors this national ordering. Together, the violin and dot plots demonstrate that racial gaps are not a collection of isolated cases but instead a structural pattern: two groups (Asian and White) consistently achieve higher outcomes across states, while two groups (Hispanic and Black) consistently experience lower outcomes and wider variability. The national-scale evidence shows that graduation outcomes are not merely influenced by local or county conditions; they reflect broad demographic stratifications that operate across the country.

Up to this point, our project has treated demographic patterns primarily by categorizing students as Asian, Black, Hispanic, or White. This approach revealed meaningful structure, especially as disparities became clearer when we moved from campuses to counties and eventually to states. However, race represents only one dimension of student identity, and examining graduation outcomes by racial categories offers a limited perspective. Education outcomes emerge from the combination of socioeconomic background, language needs, disability status, housing conditions, and other lived circumstances, making intersectionality central to understanding education. Therefore, the final section broadens our demographic lens to include some additional nationally reported student subgroups to reveal graduation outcomes across various identities that could shape student trajectories.

8. Graduation Outcomes Across States (Beyond Race)


The National Patterns tab in this Shiny app demonstrates how graduation outcomes become more uneven with bigger gaps when we expand beyond the four racial groups (race) to include economically disadvantaged students, English learners, students with disabilities, homeless enrolled students, and students in foster care. Every state is plotted as a point, centered around the national average. Asian and White students typically fall above that reference line and often exceed 90 percent. Economically disadvantaged students cluster lower, generally in the low 80s. English learners and students with disabilities fall further, averaging in the low 70s with many states below that level. Homeless enrolled students occupy a similar range but with more spread, and foster care students appear lowest and most unstable. The interactive filters and highlighting features allow users to examine where states cluster and which groups are consistently left further behind, reinforcing that graduation outcomes vary systematically with demographic identity rather than randomly.

The State Gaps and Stories tabs provide the within state interpretation that complements these national clusters. The State Gaps view shows that even in high performing states such as Alabama or New York, the ordering of groups does not match the aggregate outcome. Asian and White students usually sit at the top, while economically disadvantaged students, English learners, students with disabilities, homeless enrolled students, and foster care students fall well below them, often by 20 to 30 percentage points. Users can view either raw levels or differences from a chosen baseline, which makes the scale of these gaps straightforward to interpret. The Stories tab then links the graphics to concise narrative summaries, showing how different demographic identities are situated within states and how those positions shift across states. Together, these tabs make clear that when additional demographic dimensions are incorporated, the gaps widen rather than narrow. Graduation outcomes are shaped not only by race but also by poverty, language barriers, disability, and housing conditions. The app demonstrates that these disparities persist within states, and the lowest performing groups face both the greatest disadvantage and the least consistency across states.

Conclusion

Returning to the core question of this project, “How do graduation outcomes for Asian, Black, Hispanic, and White students differ at the school, county, and state levels, and how do these racial gaps change as we move from local to national scales?”, the results show us strong evidence that racial gaps widen as our scope expands. Within Travis County, the four groups converge at very high levels by 2020, which indicates that strong school and district systems can moderate disparities. Nevertheless, across Texas counties, this alignment disappears. Asian and White students tend to graduate at higher levels, Hispanic students fall below them, and Black students consistently show the weakest outcomes. At this level, the ordering of outcomes is no longer primarily driven by isolated school factors and reflects racial structure embedded in county-level environments.

At the national scale, these racial gaps become even larger and more systematic. Asian and White students occupy the upper ranges across most states, Hispanic students fall into lower and more variable ranges, and Black students appear lowest and least stable. Incorporating additional demographic dimensions such as economic disadvantage, English learner status, disability, homelessness, and foster-care involvement widens the separation even further. The project therefore demonstrates that graduation outcomes are not simply educational results, but reflections of social and demographic inequality. As the scale broadens, racial and other demographic-related gaps widen, geographic context becomes more decisive, and the lowest-performing groups fall further behind. Any meaningful effort to improve graduation outcomes must recognize that demographics are not incidental. They shape opportunity, outcomes, and inequity at every level of the system.

Data Sources

  1. Texas Education Agency (TEA)
  1. U.S. Census Bureau (2020)
  1. Institute of Education Sciences (IES)