In 2022, about 37.7 percent of the U.S. population who were aged 25 and above had graduated from college or another higher education institution, a slight decline from 37.9 the previous year. However, this is a significant increase from 1960, when only 7.7 percent of the U.S. population had graduated from college. Demographics Educational attainment varies by gender, location, race, and age throughout the United States. Asian-American and Pacific Islanders had the highest level of education, on average, while Massachusetts and the District of Colombia are areas home to the highest rates of residents with a bachelor’s degree or higher. However, education levels are correlated with wealth. While public education is free up until the 12th grade, the cost of university is out of reach for many Americans, making social mobility increasingly difficult. Earnings White Americans with a professional degree earned the most money on average, compared to other educational levels and races. However, regardless of educational attainment, males typically earned far more on average compared to females. Despite the decreasing wage gap over the years in the country, it remains an issue to this day. Not only is there a large wage gap between males and females, but there is also a large income gap linked to race as well.

Overall educational attainment measures the highest level of education attained by a given individual: for example, an individual counted in the percentage of the measured population with a master’s or professional degree can be assumed to also have a bachelor’s degree and a high school diploma, but they are not counted in the population percentages for those two categories. Overall educational attainment is the broadest education indicator available, providing information about the measured county population as a whole.

Only members of the population aged 25 and older are included in these educational attainment estimates, sourced from the U.S. Census Bureau American Community Survey (ACS).

Champaign County has high educational attainment: over 48 percent of the county's population aged 25 or older has a bachelor's degree or graduate or professional degree as their highest level of education. In comparison, the percentage of the population aged 25 or older in the United States and Illinois with a bachelor's degree in 2023 was 21.8% (+/-0.1) and 22.8% (+/-0.2), respectively. The population aged 25 or older in the U.S. and Illinois with a graduate or professional degree in 2022, respectively, was 14.3% (+/-0.1) and 15.5% (+/-0.2).

Educational attainment data was sourced from the U.S. Census Bureau’s American Community Survey 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Educational Attainment for the Population 25 Years and Over.

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using data.census.gov; (16 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using data.census.gov; (29 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using data.census.gov; (6 October 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using data.census.gov; (4 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using data.census.gov; (4 June 2021).; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using American FactFinder; (13 September 2018). U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table S1501; generated by CCRPC staff; using American FactFinder; (16 March 2016).

In 2021, the District of Columbia had the most highly educated population in the United States, with **** percent of residents over the age of 25 having a Bachelor's degree or higher. Massachusetts followed closely behind, with **** percent of residents having completed a Bachelor's degree or higher. For the United States as a whole, this figure stood at **** percent of the population.

In 2023, there were *** institutions of higher education in the state of California. Of these *** institutions, *** were four-year institutions and *** were two-year institutions. California had the most higher education institutions of any state in that year.

This web map shows the predominant education level attained by the US population aged 25 or over. This is shown by Census Tract and County centroids. This data is from the 2012-2016 American Community Survey 5-year estimates in the S1501 Table for Educational Attainment by age and gender. The popup in the map provides a breakdown of the highest level of education attained by the population in an area.The color of the symbols represent the most common level of education. This predominance map style compares the count of people based on their highest level of education, and returns the value with the highest count. The census breaks down the 25+ population by the following education levels:Less than 9th grade9th to 12th grade [no diploma]High school graduate [includes equivalency]Some College [no degree]Associates degreeBachelor's degreeGraduate or professional degreeThe size of the symbols represents how many people are 25 years or older, which helps highlight the quantity of people that live within an area. The strength of the color represents HOW predominant an education level is within an area. If the symbol is a strong color, it makes up a larger portion of the population. This map helps to show the most common level of education at a local and regional level. The tract pattern shows how distinct neighborhoods are clustered by their level of education. The county pattern shows an rural/urban difference in education. This pattern is shown by census tracts at large scales, and counties at smaller scales.This data was downloaded from the United States Census Bureau American Fact Finder on January 10, 2018. It was then joined with 2016 vintage centroid points and hosted to ArcGIS Online and the Living Atlas as hosted feature layers. Census Tract Centroid Layer with educational attainment attributesCounties Layer with educational attainment attributesNationally, the breakdown of education for the population 25+ is as follows:

Total Estimate Margin of Error Percent Estimate Margin of Error

Population 25 years and over 213,649,147 +/-15,761 (X) (X)

Less than 9th grade 11,913,913 +/-60,796 5.60% +/-0.1

9th to 12th grade, no diploma 15,904,467 +/-70,156 7.40% +/-0.1

High school graduate (includes equivalency) 58,820,411 +/-182,369 27.50% +/-0.1

Some college, no degree 44,772,845 +/-41,794 21.00% +/-0.1

Associate's degree 17,469,724 +/-41,879 8.20% +/-0.1

Bachelor's degree 40,189,920 +/-142,140 18.80% +/-0.1

Graduate or professional degree 24,577,867 +/-151,189 11.50% +/-0.1

This statistic shows the top metropolitan areas with the highest percentage of college graduates in the United States in 2019. In 2019, Boulder in Colorado was ranked first with 64.8 percent of its population having a Bachelor's degree or higher.

The National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimate (EDGE) program develops annually updated school district boundary composite files that include public elementary, secondary, and unified school district boundaries clipped to the U.S. shoreline. School districts are special-purpose governments and administrative units designed by state and local officials to provide public education for local residents. District boundaries are collected for NCES by the U.S. Census Bureau to develop demographic estimates and to support educational research and program administration. The NCES Common Core of Data (CCD) program is an annual collection of basic administrative characteristics for all public schools, school districts, and state education agencies in the United States. These characteristics are reported by state education officials and include directory information, number of students, number of teachers, grade span, and other conditions. The administrative attributes in this layer were developed from the most current CCD collection available. For more information about NCES school district boundaries, see: https://nces.ed.gov/programs/edge/Geographic/DistrictBoundaries. For more information about CCD school district attributes, see: https://nces.ed.gov/ccd/files.asp.

Notes:

Collections are available for the following years:

• 2022-23
  
• 2021-22
  
• 2020-21
  
• 2019-20
  
• 2018-19
  
• 2017-18
  

All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show levels of educational attainment by Neighborhood Statistical Areas in the Atlanta region. The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website. Naming conventions: Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)Suffixes:NoneChange over two periods_eEstimate from most recent ACS_mMargin of Error from most recent ACS_00Decennial 2000 Attributes: SumLevelSummary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)GEOIDCensus tract Federal Information Processing Series (FIPS) code NAMEName of geographic unitPlanning_RegionPlanning region designation for ARC purposesAcresTotal area within the tract (in acres)SqMiTotal area within the tract (in square miles)CountyCounty identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)CountyNameCounty NamePop25P_e# Population 25 years and over, 2017Pop25P_m# Population 25 years and over, 2017 (MOE)NoHS_e# Population 25 years and over, less than 9th grade education, 2017NoHS_m# Population 25 years and over, less than 9th grade education, 2017 (MOE)pNoHS_e% Population 25 years and over, less than 9th grade education, 2017pNoHS_m% Population 25 years and over, less than 9th grade education, 2017 (MOE)SomeHS_e# Population 25 years and over, 9th-12th grade, no diploma, 2017SomeHS_m# Population 25 years and over, 9th-12th grade, no diploma, 2017 (MOE)pSomeHS_e% Population 25 years and over, 9th-12th grade, no diploma, 2017pSomeHS_m% Population 25 years and over, 9th-12th grade, no diploma, 2017 (MOE)HSGrad_e# Population 25 years and over, high school graduate (includes GED), 2017HSGrad_m# Population 25 years and over, high school graduate (includes GED), 2017 (MOE)pHSGrad_e% Population 25 years and over, high school graduate (includes GED), 2017pHSGrad_m% Population 25 years and over, high school graduate (includes GED), 2017 (MOE)SomeColl_e# Population 25 years and over, some college, no degree, 2017SomeColl_m# Population 25 years and over, some college, no degree, 2017 (MOE)pSomeColl_e% Population 25 years and over, some college, no degree, 2017pSomeColl_m% Population 25 years and over, some college, no degree, 2017 (MOE)Associates_e# Population 25 years and over, associate's degree, 2017Associates_m# Population 25 years and over, associate's degree, 2017 (MOE)pAssociates_e% Population 25 years and over, associate's degree, 2017pAssociates_m% Population 25 years and over, associate's degree, 2017 (MOE)BA_e# Population 25 years and over, bachelor's degree, 2017BA_m# Population 25 years and over, bachelor's degree, 2017 (MOE)pBA_e% Population 25 years and over, bachelor's degree, 2017pBA_m% Population 25 years and over, bachelor's degree, 2017 (MOE)GradProf_e# Population 25 years and over, graduate or professional degree, 2017GradProf_m# Population 25 years and over, graduate or professional degree, 2017 (MOE)pGradProf_e% Population 25 years and over, graduate or professional degree, 2017pGradProf_m% Population 25 years and over, graduate or professional degree, 2017 (MOE)LtHS_e# Population 25 years and over, Less than high school graduate, 2017LtHS_m# Population 25 years and over, Less than high school graduate, 2017 (MOE)pLtHS_e% Population 25 years and over, Less than high school graduate, 2017pLtHS_m% Population 25 years and over, Less than high school graduate, 2017 (MOE)HSPlus_e# Population 25 years and over, high school graduate or higher, 2017HSPlus_m# Population 25 years and over, high school graduate or higher, 2017 (MOE)pHSPlus_e% Population 25 years and over, high school graduate or higher, 2017pHSPlus_m% Population 25 years and over, high school graduate or higher, 2017 (MOE)BAPlus_e# Population 25 years and over, bachelor's degree or higher, 2017BAPlus_m# Population 25 years and over, bachelor's degree or higher, 2017 (MOE)pBAPlus_e% Population 25 years and over, bachelor's degree or higher, 2017pBAPlus_m% Population 25 years and over, bachelor's degree or higher, 2017 (MOE)last_edited_dateLast date the feature was edited by ARC Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2013-2017 For additional information, please visit the Census ACS website.

This data explores 8th grade writing scores as measured by the Nation's Report Card. This report presents the results of the 2007 National Assessment of Educational Progress (NAEP) writing assessment. It was administered to a nationally representative sample of more than 165,000 eighth- and twelfth-graders from public and private schools. In addition to national results, the report includes state and urban district results for grade 8 public school students. Forty-five states, the Department of Defense schools, and 10 urban districts voluntarily participated. To measure their writing skills, the assessment engaged students in narrative, informative, and persuasive writing tasks. NAEP presents the writing results as scale scores and achievement-level percentages. Results are also reported for student performance by various demographic characteristics such as race/ethnicity, gender, and eligibility for the National School Lunch Program. The 2007 national results are compared with results from the 2002 and 1998 assessments. At grades 8 and 12, average writing scores and the percentages of students performing at or above Basic were higher than in both previous assessments. The White -- Black score gap narrowed at grade 8 compared to 1998 and 2002 but showed no significant change at grade 12. The gender score gap showed no significant change at grade 8 compared with previous assessments but narrowed at grade 12 since 2002. Eighth-graders eligible for free or reduced-price school lunch scored lower on average than students who were not eligible. Compared with 2002, average writing scores for eighth-graders increased in 19 states and the Department of Defense schools, and scores decreased in one state. Compared with 1998, scores increased in 28 states and the Department of Defense Schools, and no states showed a decrease. Scores for most urban districts at grade 8 were comparable to or higher than scores for large central cities but were below the national average.

The United States higher education market size was valued at USD 6.0 Billion in 2024. Looking forward, IMARC Group estimates the market to reach USD 16.8 Billion by 2033, exhibiting a CAGR of 12.20% from 2025-2033. The market is driven by the growing adoption of e-learning platforms that enable institutions to offer various courses without physical infrastructure restraints, along with the rising establishments of community colleges that make higher education more affordable.

IMARC Group provides an analysis of the key trends in each segment of the United States higher education market, along with forecasts at the country and regional levels from 2025-2033. The market has been categorized based on component, deployment mode, course type, learning type, and end user.

A broad and generalized selection of 2011-2015 US Census Bureau 2015 5-year American Community Survey education data estimates, obtained via Census API and joined to the appropriate geometry (in this case, New Mexico Census tracts). The selection is not comprehensive, but allows a first-level characterization of educational attaiment by grade level and sex (for all persons 25 years and older), plus enrollment estimates at key educational levels (for the universe of all persons 3+ years old). The determination of which estimates to include was based upon level of interest and providing a manageable dataset for users.The U.S. Census Bureau's American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. The ACS collects long-form-type information throughout the decade rather than only once every 10 years. The ACS combines population or housing data from multiple years to produce reliable numbers for small counties, neighborhoods, and other local areas. To provide information for communities each year, the ACS provides 1-, 3-, and 5-year estimates. ACS 5-year estimates (multiyear estimates) are “period” estimates that represent data collected over a 60-month period of time (as opposed to “point-in-time” estimates, such as the decennial census, that approximate the characteristics of an area on a specific date). ACS data are released in the year immediately following the year in which they are collected. ACS estimates based on data collected from 2009–2014 should not be called “2009” or “2014” estimates. Multiyear estimates should be labeled to indicate clearly the full period of time. While the ACS contains margin of error (MOE) information, this dataset does not. Those individuals requiring more complete data are directed to download the more detailed datasets from the ACS American FactFinder website. This dataset is organized by Census tract boundaries in New Mexico. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

This data explores Access to early childhood programs, by state: 2002 * In 2001, all preschool efforts in Florida were consolidated into a block grant administered by the Agency for Workforce Innovation. Funding is distributed to county-level early-childhood coalitions that make decisions on distribution. It is unclear yet how the new configuration will affect pre-K programs in the state. All data presented here are from before the consolidation. * In Alabama, pilot program is targeted based on need. However, any 4-year-old in pilot communities is eligible. In Minnesota, all 4-year-olds are eligible, but priority for services is given to children from low-income families that exceed Head Start income guidelines. * Risk factors are locally determined. In Nevada and West Virginia, all eligibility requirements for pre-K are locally determined. * Enrollment count for New Jersey is for Abbott districts only. In New Jersey, full-day kindergarten is mandated for 132 high-poverty districts. * Ohio serves an additional 18,705 children in its state-financed Head Start program. * Because pre-K funding is in the form of block grants and subject to district discretion, enrollment figures cannot be determined. NOTE: ES: Elementary School; MS: Middle School; HS: High School. SOURCE: Education Week, Quality Counts 2002, table Access to Early Childhood Programs. Data Source.

Utah Unified School Boundary - School districts are geographic entities within which state, county, or local officials provide public educational services for the area's residents. The U.S. Census Bureau obtains the boundaries and names for school districts from state officials. The U.S. Census Bureau first provided data for school districts in the 1970 census. For Census 2000, the U.S. Census Bureau tabulated data for three types of school districts: elementary, secondary, and unified. Each school district is assigned a five-digit code that is unique within state. School district codes are assigned by the Department of Education and are not necessarily in alphabetical order by school district name.

The National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimate (EDGE) program develops annually updated school district boundary composite files that include public elementary, secondary, and unified school district boundaries clipped to the U.S. shoreline. School districts are special-purpose administrative units designed by state and local officials to provide public education for local residents. District boundaries are collected for NCES by the U.S. Census Bureau to develop demographic estimates and to support educational research and program administration. The NCES Common Core of Data (CCD) program is an annual collection of basic administrative characteristics for all public schools, school districts, and state education agencies in the United States. These characteristics are reported by state education officials and include directory information, number of students, number of teachers, grade span, and other conditions. The administrative attributes in this layer were developed from the 2017-2018 CCD collection. For more information about NCES school district boundaries, see: https://nces.ed.gov/programs/edge/Geographic/DistrictBoundaries. For more information about CCD school district attributes, see: https://nces.ed.gov/ccd/files.asp.Notes:

-1 or M

Indicates that the data are missing.

-2 or N

Indicates that the data are not applicable.

-9

Indicates that the data do not meet NCES data quality standards.

All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

The COVID-19 pandemic brought with it not only sanitary challenges, but also social and economic difficulties on a global scale. The provision of means for students to keep on with their education despite the multiple social distancing restrictions is one of them. In this context, online learning has become a very useful alternative. Among 29 Latin American and Caribbean countries analyzed in 2020, the most commonly used distance learning tool was online learning, implemented by 26 countries in the region. In comparison, less than 10 countries evaluated delivered devices or provided students with live online classes. Alternatives to online education Although online education has been the most chosen learning delivery system in Latin America and the Caribbean during the pandemic, a considerable part of the population in the region has little to no access to the internet or to digital learning tools. As a result, other creative ways of providing learning resources have been adopted. A good example of this has been the broadcasting of educational programs via television and radio. In Mexico, for instance, the program “Aprende en Casa” was launched at the beginning of the 2020/2021 scholar year to air educational content for each school level throughout the day. Digitalization in schools pre COVID-19 pandemic One of the characteristics of digitalization in Latin American schools, even before the COVID-19 pandemic, has been the evident inequalities among institutions and students. These disparities are present in multiple areas and vary not only between countries, but also within them. Uruguay, for instance, having one of the largest shares of pupils with an effective online learning support platform in the region, was also among the Latin American countries with the lowest share of students whose teachers were prepared to integrate digital devices to education.

This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, but they rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The 2020 NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line 2020. The NCES Education Demographic and Geographic Estimate (EDGE) program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to annually update the locale boundaries. For more information about the NCES locale framework, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include: City - Large (11): Territory inside an Urbanized Area and inside a Principal City with population of 250,000 or more. City - Midsize (12): Territory inside an Urbanized Area and inside a Principal City with population less than 250,000 and greater than or equal to 100,000. City - Small (13): Territory inside an Urbanized Area and inside a Principal City with population less than 100,000. Suburb – Large (21): Territory outside a Principal City and inside an Urbanized Area with population of 250,000 or more. Suburb - Midsize (22): Territory outside a Principal City and inside an Urbanized Area with population less than 250,000 and greater than or equal to 100,000. Suburb - Small (23): Territory outside a Principal City and inside an Urbanized Area with population less than 100,000. Town - Fringe (31): Territory inside an Urban Cluster that is less than or equal to 10 miles from an Urbanized Area. Town - Distant (32): Territory inside an Urban Cluster that is more than 10 miles and less than or equal to 35 miles from an Urbanized Area. Town - Remote (33): Territory inside an Urban Cluster that is more than 35 miles of an Urbanized Area. Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urbanized Area, as well as rural territory that is less than or equal to 2.5 miles from an Urban Cluster. Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urbanized Area, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Cluster. Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urbanized Area and is also more than 10 miles from an Urban Cluster.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

The Times Higher Education World University Rankings 2023 include 1,799 universities across 104 countries and regions, making them the largest and most diverse university rankings to date. The table is based on 13 carefully calibrated performance indicators that measure an institution’s performance across four areas: teaching, research, knowledge transfer and international outlook.

The National Assessment of Educational Progress (NAEP) is the largest nationally representative and continuing assessment of what students in the United States know and can do in various subject areas. Assessments are conducted periodically in mathematics, reading, science, writing, the arts, civics, economics, geography, United States history, and beginning in 2014, in Technology and Engineering Literacy (TEL). Since NAEP assessments are administered uniformly using the same sets of test booklets across the United States, NAEP results serve as a common metric for all states and selected urban districts. The assessment stays essentially the same from year to year, with only carefully documented changes. This permits NAEP to provide a clear picture of student academic progress over time and for teachers, principals, parents, policymakers, and researchers to use NAEP results to assess progress and develop ways to improve education in the United States. There are two types of assessments: main NAEP and long-term trend NAEP. Main NAEP is administered to fourth-, eighth-, and twelfth-graders across the United States in a variety of subjects. The Main NAEP is conducted between the last week of January and the first week in March every year. National results are available for all assessments and subjects. Results for states and select urban districts are available in some subjects for grades 4 and 8. The Trial Urban District Assessment (TUDA) is a special project developed to determine the feasibility of reporting district-level NAEP results for large urban districts. In 2009 a trial state assessment was administered at grade 12. Long-term trend NAEP is administered nationally every four years. During the same academic year, 13-year olds are assessed in the fall, 9-year olds in the winter, and 17-year olds in the spring. Long-term trend assessments measure student performance in mathematics and reading, and allow the performance of students from recent time periods to be compared with students since the early 1970s. The 1997 and 2008 NAEP arts assessments were part of the Main NAEP Assessments. The NAEP 1997 Arts Assessment was conducted nationally at grade 8. For music and visual arts, representative samples of public and nonpublic school students were assessed. A special "targeted" sample of students took the theatre assessment. Schools offering at least 44 classroom hours of a theatre course per semester, and offering courses including more than the history or literature of theatre, were identified. Students attending those schools who had accumulated 30 hours of theatre classes by the end of the 1996-97 school year were selected to take the theatre assessment. The NAEP 2008 Arts Assessment was administered to a nationally representative sample of 7,900 eighth-grade public and private school students. Approximately one-half of these students were assessed in music, and the other half were assessed in visual arts. The music portion of the assessment measured students' ability to respond to music in various ways. Students were asked to analyze and describe aspects of music they heard, critique instrumental and vocal performances, and demonstrate their knowledge of standard musical notation and music's role in society. The visual arts portion of the assessment included questions that measured students' ability to respond to art as well as questions that measured their ability to create art. Responding questions asked students to analyze and describe works of art and design. For example, students were asked to describe specific differences in how certain parts of an artist's self-portrait were drawn. Creating questions required students to create works of art and design of their own. For example, students were asked to create a self-portrait that was scored for identifying detail, compositional elements, and use of materials. In addition, NAEP has a number of special studies that are conducted periodically. These include research and development efforts such as the High School Transcript Study and the National Indian Education Study. More information on these special studies is available on the NAEP Web site.

The American Community Survey (ACS) is designed to estimate the characteristic distribution of populations and estimated counts should only be used to calculate percentages. They do not represent the actual population counts or totals. Beginning in 2019, the Washington Student Achievement Council (WSAC) has measured educational attainment for the Roadmap Progress Report using one-year American Community Survey (ACS) data from the United States Census Bureau. These public microdata represents the most current data, but it is limited to areas with larger populations leading to some multi-county regions*. *The American Community Survey is not the official source of population counts. It is designed to show the characteristics of the nation's population and should not be used as actual population counts or housing totals for the nation, states or counties. The official population count — including population by age, sex, race and Hispanic origin — comes from the once-a-decade census, supplemented by annual population estimates (which do not typically contain educational attainment variables) from the following groups and surveys: -- Washington State Office of Financial Management (OFM): https://www.ofm.wa.gov/washington-data-research/population-demographics -- US Census Decennial Census: https://www.census.gov/programs-surveys/decennial-census.html and Population Estimates Program: https://www.census.gov/programs-surveys/popest.html **In prior years, WSAC used both the five-year and three-year (now discontinued) data. While the 5-year estimates provide a larger sample, they are not recommended for year to year trends and also are released later than the one-year files. Detailed information about the ACS at https://www.census.gov/programs-surveys/acs/guidance.html