About the Data

Profiles of Education Performance Around the Nation

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Unlocking the Power of Education Data

Education data represents a powerful lever for initiating policy that leads to meaningful school and district improvement. With the focus of education policymaking increasingly on local control, mayors and state policymakers play a significant role in improving our Nation’s schools. Too often, though, education data are not available in accessible and meaningful formats that allow for productive analysis and action.

In recognition of the transformative power of education data, as well as the need for educators, policymakers, families, and city leaders alike to access reliable and comparable data, the George W. Bush Institute released the first Mayors’ Report Card on Education, for 33 cities, in January of 2015.

Building on the vision to make comparable city-level data more widely available, The State of Our Cities online tool features data for over 100 cities across the United States. It offers a user-friendly single source for a comprehensive range of education data, enabling users to both holistically assess education in a given city as well as make valid comparisons among multiple cities.

While for many cities, the district data is inclusive of most of the students within that city’s limits, we know that is not universally true for the 114 cities featured in State of Our Cities. We discussed this limitation extensively, including with mayors who were requesting this report card, and we determined together that using the data from the largest or most centrally located district and offering charter school enrollment data by subgroup within those district’s boundaries was the most feasible option for this tool. We all agree that it would be ideal to be able to include private schools, charter schools and other school data, but it is currently difficult, if not impossible, to gather these data in a manner that is comprehensive, credible and comparable. We hope that improves over time in order to deepen our understanding and improve student outcomes.

Download list of cities

We want to acknowledge Dallas Mayor Mike Rawlings for his interest in this project and for bringing usable data to his fellow mayors. Collaborative Communications Group and Graphicacy have continued to provide excellent support of this work since its inception. We would like to thank the staff at National Alliance for Public Charter Schools, who willingly shared data on charter school enrollment. Dr. Gregory Matthews provided invaluable support on the tool.

Finally, this tool would not be possible without the generous support from the Charles Stewart Mott Foundation, Sammons Enterprises Foundation, and the Walton Family Foundation.

State of Our Cities Methodology and Sources

Each city’s data includes data from schools belonging to the Local Education Agency (LEA) of the most centrally located or largest school district in that city. Charts displaying three racial groups highlight the three racial groups in each LEA with the largest enrollment totals in the Common Core of Data (CCD) School Universe Survey for 2013-14.

All data was collected from public sources by either downloading publicly available files or directly contacting public institutions. Office of Civil Rights (OCR) Civil Right Data Collection (CRDC) data for the 2011-12 school year was provided by the Office of Civil Rights in files received November 18, 2015. Data for the 2013-14 school year was downloaded from the CRDC website on June 8, 2016. CCD School Universe Survey data uses version 1b for 2007-08, 1b for 2008-09, 2a for 2009-10, 2a for 2010-11, 1a for 2011-12, 2a for 2012-13, and 2a for 2013-14.

OCR data is limited by district reporting and rates should be interpreted with caution. Large differences between 2011-12 and 2013-14 data may be due to changes in district reporting procedures and may not reflect real year-to-year changes.

For indicators where both OCR CRDC and CCD numbers are used to calculate rates, racial subgroups of fewer than 25 students have been removed to reduce the risk of inaccuracies resulting from schools or LEAs reporting to different datasets inconsistently.

The Memphis City Schools school district was disbanded and merged with Shelby County School District in 2013. Memphis, TN displays data from Shelby County School District for the 2013-14 school year and on, and Memphis City Schools for prior school years.

District Information and Demographics

Number of Schools and Students

Data is from the 2013-14 CCD School Universe Survey.

Median Family Income

Data is from the U.S. Census American Community Survey (ACS) 2014, 2013, and 2012 1-year estimates. Data is in 2014 dollars, adjusted for inflation using the Bureau of Labor Statistics CPI inflation calculator. Burlington, VT; Charleston, WV; and Cheyenne, WY do not have 1-year estimates and display 5-year estimates instead.

Children in Poverty

Data is from the U.S. Census Small Area Income and Poverty Estimates: School District Estimates for 2014, 2013 and 2012.

Population

Data is district-level data from the U.S. Census American Community Survey (ACS) from the National Center for Education Statistics (NCES) Education Demographic and Geographic Estimates (EDGE) tool, 2009-2013 estimate. This data is used for the “% Hispanic”, “% Black”, “% White”, and “% Asian” options in the Explore page and in the similar cities calculation described below.

Similar Cities

Similar cities are suggested based on which five cities are closest to the selected city on each of the six criteria listed (region, population, racial makeup, child poverty, median family income, and percent charter enrollment). Similarity by region is calculated using longitude and latitude. Similarity by racial makeup calculates the five cities with the lowest total differences in Hispanic, Black, White, and Asian subpopulation percentages using a euclidean distance calculation, or the difference between two points using a straight line. Similar cities for each of the other criteria (population, child poverty, median family income, and percent charter enrollment) are the five cities with values closest to the selected city’s value.

Academic Outcomes

Trial Urban District Assessment

National Assessment of Educational Progress (NAEP) average scale scores and proficiency rates are retrieved from http://www.nationsreportcard.gov/. Washington, DC data uses the Trial Urban District Assessment (TUDA) district, District of Columbia Public Schools, for comparability.

The percentage of each subgroup qualifying for free or reduced-price meals (FRL) is estimated using the CCD School Universe Survey. Subgroup membership in each school is multiplied by the overall rate of FRL eligibility at the school to obtain an estimated count of FRL-eligible students in the subgroup.

The 2014-15 display of the scatterplot uses enrollment and estimated FRL rates from the 2013-14 CCD School Universe Survey because the 2014-15 survey was not yet available.

The 2013-14 FRL rate for Washington, DC showed outlier values and so the 2012-13 FRL rate has been substituted.

Global Report Card

For a full explanation of the Global Report Card methodology, please visit http://www.bushcenter.org/StateOfOurCities/compare/.

Middle School Algebra Completion

Rates are calculated by dividing the number of students who passed Algebra I in grade seven or eight (from the 2011-12 and 2013-14 CRDC) by 8th grade enrollment (from the 2011-12 and 2013-14 CCD School Universe Survey). Philadelphia and Milwaukee (in 2011) and Cleveland, Indianapolis, and Salt Lake City (in 2013) have been removed due to missing data.

State Assessments

Data for school years 2011-12 through 2013-14 is from EDFacts. Data for the 2014-15 school year was gathered from states’ department of education websites. The full list of URLs used is provided in the downloadable data files. For states not reporting proficiency rates aggregated across grades, a weighted average was calculated using the available grade-level data, using the number of students taking the test in each grade as the weights. EDFacts data combines Asian and Hawaiian/Pacific Islander into one racial subgroup. Scores and proficiency rates from different states may not be comparable due to differences in state assessments and proficiency rate cutoffs. In addition, states’ assessments and proficiency rate cutoffs may change from year to year and so may not be comparable between years.

District Trends

Enrollment

Data is from the 2008-09 to 2013-14 CCD School Universe Survey.

Charter Schools

Data was provided in March 2016 by the National Alliance for Public Charter Schools in a file including enrollment counts from the CCD. Charter school enrollment displays enrollment totals for charter schools within the geographic boundaries of the traditional public school district. Non-charter school enrollment displays enrollment totals for non-charter schools in the traditional public school district, using version 1a of the 2012-13 and 2013-14 CCD School Universe Survey for consistency.

School Finance

Revenue & Spending

Data is from the 2007-08 to 2012-13 NCES CCD LEA Finance Survey. Spending per student is calculated by dividing total expenditures by total enrollment as provided in the CCD School Universe Survey for each year. Data is in 2012 dollars, adjusted for inflation using the Bureau of Labor Statistics CPI inflation calculator.

Average Teacher Salary

Data is from the OCR CRDC for the 2011-12 and 2013-14 school years. The Minneapolis Public Schools district data was missing for 2011-12 and has been replaced with data from the 2011-12 CCD LEA Finance Survey. Salaries are adjusted for cost of living to the national average using the comparable wage index published by the Bush School of Government & Public Service here.

Pay for performance data was gathered from publicly available documents from sources including district websites and teacher unions.

College & Career Pathways

AP Course/Test Participation

Course participation rates are calculated by dividing number of students taking an AP course (from the 2011-12 and 2013-14 OCR CRDC) by grade 9-12 enrollment (from the 2011-12 and 2013-14 CCD School Universe Survey). Test passing rates are calculated by dividing number of students passing some or all of their AP courses (from the 2011-12 and 2013-14 OCR CRDC) by grade 9-12 enrollment (from the 2011-12 and 2013-14 CCD School Universe Survey). Percentages may be over 100% due to students taking an AP course before the 9th grade.

SAT/ACT Performance

SAT and ACT performance data was collected from state department of education or school district websites or provided by the state department of education or school district. Where data was only available at the school level, district rates were calculated using a weighted average, using the number of students taking the test in each school as the weights. States do not always report the grades taking the test, and scores may be for the 11th grade, 12th grade, or both.

High School Graduation Rate

Data is from EDFacts. Rates are Adjusted Cohort Graduation Rates (ACGR) for the 2010-11 to 2013-14 school years. These rates are calculated by state education agencies (SEAs) in accordance with guidance published by the US Department of Education (ED). EDFacts data combines Asian and Hawaiian/Pacific Islander into one racial subgroup.

FAFSA Completion

Data is from Federal Student Aid from the 2015-16 application cycle. District rates are estimated by Federal Student Aid and reported as percentage ranges. District rates for public high schools include only first-time filing applicants no older than 18.

School Characteristics & Environment

Effective Teachers & Principals

Data for teacher absenteeism and new teachers is from the 2011-12 and 2013-14 OCR CRDC. Indianapolis Public Schools showed outlier rates of new teachers so it has been removed.

Suspensions

Suspension rates are calculated by dividing the number of students suspended one or more times (including students with and without disabilities) by total enrollment, using data from the 2013-14 OCR CRDC.

Chronic Absenteeism

Chronic absenteeism rates are calculated by dividing the number of students absent for 15 or more days in the school year by total enrollment, using data from the 2013-14 OCR CRDC.

Early Childhood

Early Childhood Enrollment

Data is from the 2008-09 to 2013-14 CCD School Universe Survey.

Early Childhood Programs

Data for the availability, type, and eligibility requirements of district pre-K services is from the OCR CRDC for the 2011-12 and 2013-14 school years.

Data for access to free pre-K was gathered from research into the individual district pre-K programs. The full list of URLs used is provided in the downloadable data files.