Help & FAQ

Learn about the data, and how to use our interactive visualizations.

Glossary

The average test score indicates how well the average student in a school, district, or county performs on standardized tests. Importantly, many factors—both early in life and when children are in school—affect test performance. As a result, the average test scores in a school, district, or county reflect the total set of educational opportunities children have had from birth through middle school, including opportunities at home, in child-care and preschool programs, and among peers. Average test scores therefore reflect a mix of school quality and out-of-school educational opportunities.

The learning rate indicates approximately how much students learn in each grade in a school, district, or county. Because most educational opportunities in grades 3–8 are provided by schools, the average learning rate largely reflects school quality.

The trend in scores indicates how rapidly average test scores within a school, district, or county have changed over time. It reflects changes over time in the total set of educational opportunities (in and out of schools) available to children. For example, average scores might improve over time because the schools are improving and/or because more high-income families have moved into the community.

A child’s educational opportunities include all experiences that contribute to learning the skills assessed on standardized tests. These include opportunities both in early childhood and during the schooling years, and experiences in homes, in neighborhoods, in child-care and preschool programs, with peers, and in schools.

Socioeconomic status. The below FAQ item, How is socioeconomic status measured?, describes the variables used to measure the average socioeconomic composition of families in each community, both overall and for different groups within a community.

As described in the Methods section, the test-score data in SEDA are adjusted so that a “4” represents the average test scores of 4th graders nationally, a “5” represents the average test scores of 5th graders nationally, and so on. One “grade level” thus corresponds to the average per-grade increase in test scores for students nationally.

Each traditional public-school district in the U.S. is defined by a geographic catchment area; the schools that fall within this boundary make up the geographic school district.

The gap in school poverty is a measure of school segregation. We use the proportion of students defined as “economically disadvantaged” in a school as a measure of school poverty. The black-white gap in school poverty, for example, measures the difference between the poverty rate of the average black student’s school and the poverty rate of the average white students’ school. When there is no segregation—when white and black students attend the same schools, or when white and black students’ schools have equal poverty rates—the black-white school poverty gap is zero. A positive black-white school poverty gap means that black students’ schools have higher poverty rates than white students’ schools, on average. A negative black-white school poverty gap means that white students’ schools have higher poverty rates than black students’ schools, on average.

A group of students beginning school together in the same year. For example, the 2006 cohort refers to students who were first enrolled in kindergarten in the fall of 2005 (and finished in the spring of 2006). While some of these students may repeat or skip a grade during school, the majority will progress through school together in the same grades each year.

The average, or “mean,” is used to represent the typical or central value in a set of numbers.

The standard deviation indicates how spread out a set of numbers is relative to the average. The standard deviation represents the typical amount by which any single number differs from the average.

When numbers in a set have been “standardized,” they have been transformed so that the average value is exactly 0 and the standard deviation is exactly 1. After being standardized, positive numbers represent values that are above the average and negative numbers represent values that are below the average.

A standardized test used to measure the knowledge and skills a student has attained in a particular subject, after instruction.

The numeric score earned on an achievement test.

A description of what test-takers earning scores in a particular range are expected to know and/or are able to do. Each achievement test usually has three to five achievement levels defined. Achievement levels often have labels describing performance relative to grade-level expectations, such as “basic,” “proficient,” or “advanced.”

The test scores, or boundaries, that separate a set of achievement levels.

A data set containing information about how many students in each group (where groups could be schools, districts, states, etc.) earned scores in each achievement level.

The percentage of students whose test scores were at or above the “proficient” achievement level in a given grade.

A set of statistical methods used to facilitate comparisons across different tests.

The National Assessment of Educational Progress.

The heteroskedastic ordered probit model is a statistical technique that can be used to analyze proficiency data.

Economically disadvantaged students.

Free or reduced-price-lunch-eligible students.

Understanding the Data

The data are based on the standardized accountability tests in math and English Language Arts (ELA) administered annually by each state to all public-school students in grades 3–8 from 2008–09 through 2015–16. In these years, 3rd through 8th graders in U.S. public schools took roughly 350 million standardized math and ELA tests. Their scores—provided to us in aggregated form by the U.S. Department of Education—are the basis of the data reported here.

We combine information on the test scores in each school, school district, or county with information from the National Assessment of Educational Progress (NAEP; see https://nces.ed.gov/nationsreportcard/about/) to compare scores from state tests on a common national scale (see see the Methods page).

We never see nor use individual test scores in this process. The raw data we receive includes only counts of students scoring at different test-score levels, not individual test scores. There is no individual or individually-identifiable information included in the raw or public data.

Educational opportunities include all experiences that help a child learn the skills assessed on standardized tests. These include opportunities both in early childhood and during the schooling years, and experiences in homes, in neighborhoods, in child-care and preschool programs, with peers, and in schools.

For more information see our interactive feature article, “Affluent Schools Are Not Always the Best Schools.”

To understand the role of educational opportunities in shaping average test-score patterns, it is necessary to distinguish between individual scores and average scores in a given school, district, or county.

Differences in two students’ individual test scores at a given age reflect both differences in their individual characteristics and abilities and differences in the educational opportunities they have had. However, because the average innate abilities of students born in one community do not differ from those born in another place, any difference in average test scores must reflect differences in the educational opportunities available in the two communities.

The three scores tell different stories.

  • Average test score: The average test score indicates how well the average student in a school, district, or county performs on standardized tests. Importantly, many factors—both early in life and when children are in school—affect test performance. As a result, the average test scores in a school, district, or county reflect the total set of educational opportunities children have had from birth through middle school, including opportunities at home, in child-care and preschool programs, and among peers. Average test scores therefore reflect a mix of school quality and out-of-school educational opportunities.

  • Learning rate: The learning rate indicates approximately how much students learn in each grade in a school, district, or county. Because most educational opportunities in grades 3–8 are provided by schools, the average learning rate largely reflects school quality.

  • Trend in test scores: The trend in scores indicates how rapidly average test scores within a school, district, or county have changed over time. It reflects changes over time in the total set of educational opportunities (in and out of schools) available to children. For example, average scores might improve over time because the schools are improving and/or because more high-income families have moved into the community.

For more information on how the average, learning rate, and trend in test scores are computed, see the Methods overview.

Once the test scores are placed on a common scale across states, grades, and years, we have measures of the average test scores in up to 96 grade-year-subject cells for each school, district, or county. The scores are adjusted so that a value of 3 corresponds to the average achievement of 3rd graders nationally, a value of 4 corresponds to the average achievement of 4th graders nationally, and so on.

  • Average test score: To compute the average test score, we compare students in each grade, year, and subject with the national average and then combine them.

  • Learning rate: To compute the average learning rate, we compare students’ average scores in one grade and year to those in the next grade and year. For example, we compare the average math score in grade 3 in 2009 to the average math score in grade 4 in 2010. The difference is an estimate of the learning rate in a specific grade and subject for a specific cohort of students. We then compute the same change for each cohort, grade, and subject for which we have data. The average of these grade-to-grade changes (across cohorts, grades, and subjects) is the learning rate. A learning rate of 1.0 indicates that average student’s scores improve by one grade level each grade.

  • Trend in test scores: To compute trends in test scores, we compare students’ average scores in one grade and year to those in the same grade in the next year. For example, we compare the average math score in grade 3 in 2009 to the average math score in grade 3 in 2010. The difference between these two values indicates how much math scores improved in one year in grade 3. We then compute the same change for each year, grade, and subject. The average of these annual changes (across years, grades, and subjects) is the trend in test scores.

All public schools—both traditional and charter schools—that serve students in any grade from 3 through 8 are included in the data.

The data include public schools that enroll students in grades 3–8. Schools that enroll both high school students and students in some of grades 3–8 are included, but the reported test-score measures are based only on the scores of students in grades 3–8. For example, schools serving grades 7–12 are included in the data, but the test scores we use are only those from students in grades 7–8.

In the district data, charter schools are considered part of the traditional public-school district chartering them. Charter schools not chartered by a district are considered to be part of the district in which they are physically located. A data file indicating which schools are charter schools and what districts they are associated with in the data is available from the Get the Data page.

We do not use or report test scores from virtual schools.

In most states, students in private schools do not take the annual state accountability tests that we use to build SEDA. Therefore, no test scores from private schools are included in the raw or public data.

We have taken a number of steps to ensure the accuracy of the data reported here. The statistical and psychometric methods underlying the data we report are published in peer-reviewed journals and described on the Methods page and in the technical documentation. Nonetheless, there may still be errors in the data files that we have not yet identified. If you believe you have found an error in the data, we would appreciate knowing about it. Please contact our SEDA support team at sedasupport@stanford.edu.

Yes. These data are available for researchers to use under the terms of our data use agreement. You can download the data files and full technical documentation on our Get the Data page.

No. The measures of average test scores, average learning rates, and average test-score trends are based solely on test-score data.

On the website, we note schools that serve exceptional student populations (large proportions of students with disabilities, students enrolled in gifted/talented programs, or students with limited English proficiency). These students’ characteristics should be taken into consideration when interpreting the test-score data and comparing performance to that of public schools serving more general populations.

  • Special education schools or schools with a high percentage of students with disabilities: We flag schools that are explicitly identified as special education schools by the Common Core of Data (CCD) or the Civil Rights Data Collection (CRDC). We also flag schools where more than 40% of students are identified as having a disability in the CRDC data. Students with disabilities are identified per the Individuals with Disabilities Education Act (IDEA).

  • Schools with a high percentage of students in gifted/talented programs or with selective admissions: We flag schools where more than 40% of the students are enrolled in a gifted/talented program according to the CRDC data. We also flag some schools with selective-admission policies (schools where students must pass a test to be admitted), but we do not have a comprehensive list of such schools, so not all selective-admissions schools are yet identified in our data.

  • Schools with a high percentage of limited English-proficient students: We flag schools where more than 50% of the students are identified as limited English proficient (LEP) in the CRDC data. LEP students are classified by state definitions based on Title IX of the Elementary and Secondary Education Act (ESEA).

The downloadable SEDA data files include student, community, school, and district characteristics that researchers and others can use.

For each school district or county, we use data from the Census Bureau’s American Community Survey (ACS) to create estimates of the average socioeconomic status (SES) of families. Every year, the ACS surveys families in each community in the U.S. We use six community characteristics reported in the surveys from 2007 through 2016 to construct a composite measure of SES in each community:

  • Median income
  • Percentage of adults age 25 and older with a bachelor’s degree or higher
  • Poverty rate among households with children age 5–17
  • Percentage of households receiving benefits from the Supplemental Nutrition Assistance Program (SNAP)
  • Percentage of households headed by single mothers
  • Employment rate for adults age 25–64.

The composite SES measure is standardized so that a value of 0 represents the SES of the average school district in the U.S. Approximately two-thirds of districts have SES values between -1 and +1, and approximately 95% have SES values between -2 and +2. In some places we cannot calculate a reliable measure of socioeconomic status, because the ACS samples are too small; in these cases, no value for SES is reported. For more detailed information, please see the technical documentation.

The gap in school poverty (shown in the secondary gap charts) is a measure of school segregation. We use the proportion of students defined as “economically disadvantaged” in a school as a measure of school poverty. The black-white gap in school poverty, for example, measures the difference between the poverty rate of the average black student’s school and the poverty rate of the average white student’s school. When there is no segregation—when white and black students attend the same schools, or when white and black students’ schools have equal poverty rates—the black-white school-poverty gap is 0. A positive black-white school-poverty gap means that black students’ schools have higher poverty rates than white students’ schools, on average. A negative black-white school-poverty gap means that white students’ schools have higher poverty rates than black students’ schools, on average.

SEDA results may differ from publicly reported state test scores.

States typically report test scores in terms of percentages of proficient students. They may also report data only for a single year and grade, or average the percentages of proficient students across grades. Measures based on the percentage of proficiency are generally not comparable across states, grades, or test subjects, and are often not comparable across years because of differences in the tests administered and differences in definitions of “proficiency.”

States often provide school grades or other school scores as an index. These may take a number of factors into account, not just test scores. This makes them very difficult to compare across states and grades and over time.

In contrast, the test-score measures we report here are based on more detailed information about students’ test scores. They are also adjusted to account for differences in tests and proficiency standards across states, years, and grades.

The measures we report here also differ slightly from other publicly available measures of school and district performance due to differences in statistical methods. We provide a comparison of SEDA and other types of measures in our research papers.

There are several reasons that SEDA may not contain data for a school, district, or county:

  • The school or district is too small and/or has too few grades to allow for an accurate estimate.
  • Fewer than 95% of students in the school or district participated in testing in the subject, grade, and year.
  • More than 40% of students in the school, district, or county took alternative assessments rather than the regular tests.
  • Data were not reported to the National Center for Education Statistics.
  • Students took different, incomparable tests within the same subject, grade, and year. This is something our methodology cannot adjust for.
  • We identified data errors that would result in inaccurate estimates.

For more details, please see our technical documentation.

The Discoveries pages provide guidance on interpreting the data, the Glossary section and Methods page provide an overview of the process used to construct these data, and the technical documentation provides full methodological details along with reference for further reading.

Using the Opportunity Explorer

The Educational Opportunity Explorer offers a FAQ within the Explorer itself. Press the HELP button to get answers to your questions on using the Explorer and interpreting its map and charts.

If your questions are not answered there, please reach out to help@edopportunity.org for questions on how to use the Educational Opportunity Explorer and website.