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.

In 2021, about ** percent of the United States population aged 25 to 34 years had attained a bachelor's degree or higher. In comparison, only ** percent of the U.S. population aged 65 years or older had a bachelor's degree.

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).

US: School Enrollment: Preprimary: Female: % Gross data was reported at 68.891 % in 2015. This records a decrease from the previous number of 70.205 % for 2014. US: School Enrollment: Preprimary: Female: % Gross data is updated yearly, averaging 63.943 % from Dec 1981 (Median) to 2015, with 17 observations. The data reached an all-time high of 70.447 % in 1996 and a record low of 51.131 % in 1981. US: School Enrollment: Preprimary: Female: % Gross data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Education Statistics. Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Preprimary education refers to programs at the initial stage of organized instruction, designed primarily to introduce very young children to a school-type environment and to provide a bridge between home and school.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

In 2023, about four percent of the people with a Bachelor's degree or higher were living below the poverty line in the United States. This is far below the poverty rate of those without a high school diploma, which was 25.1 percent in 2023.

As of 2022, there were approximately 4.86 million people in the United States who had completed their doctorate degree. Furthermore, there were 74.53 million people in the U.S. whose highest educational attainment was a high school degree.

This map shows the predominant highest level of education for the population age 25+ in the United States. This is shown by state, county, and census tracts throughout the US. Click on a feature to learn more about the breakdown of population by their highest level of education.The categories are grouped as:Less than High SchoolHigh SchoolAssociate's DegreeSome CollegeBachelor's Degree or HigherThe data shown is current-year American Community Survey (ACS) data from the US Census. The data is updated each year when the ACS releases its new 5-year estimates. For more information about the data layer used in this map, visit this page.To learn more about when the ACS releases data updates, click here.

Graph and download economic data for High School Graduate or Higher for California (GCT1501CA) from 2006 to 2023 about secondary schooling, secondary, 25 years +, educational attainment, education, CA, and USA.

Graph and download economic data for Labor Force Participation Rate - High School Graduates, No College, 25 Yrs. & over (LNU01327660) from Jan 1992 to Jun 2025 about secondary schooling, secondary, 25 years +, participation, tertiary schooling, civilian, education, labor force, labor, household survey, rate, and USA.

Graph and download economic data for Unemployment Level - Some College or Associate Degree, 25 Yrs. & over (LNU03027689) from Jan 1992 to Jun 2025 about associate degree, 25 years +, tertiary schooling, education, household survey, unemployment, and USA.

Graph and download economic data for Unemployment Level - Bachelor's Degree and Higher, 20 to 24 years (CGRAU2024) from Jan 2000 to May 2025 about 20 to 24 years, tertiary schooling, education, household survey, unemployment, and USA.

This layer shows education level for adults (25+) by race by sex. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percent of adults age 25+ who have a bachelor's degree or higher as their highest education level. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B15002, C15002B, C15002C, C15002D, C15002E, C15002F, C15002G, C15002H, C15002I (Not all lines of these ACS tables are available in this layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

United States US: School Enrollment: Secondary: Female: % Net data was reported at 92.215 % in 2015. This records an increase from the previous number of 90.026 % for 2014. United States US: School Enrollment: Secondary: Female: % Net data is updated yearly, averaging 89.309 % from Dec 1987 (Median) to 2015, with 21 observations. The data reached an all-time high of 92.215 % in 2015 and a record low of 85.694 % in 2002. United States US: School Enrollment: Secondary: Female: % Net data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Education Statistics. Net enrollment rate is the ratio of children of official school age who are enrolled in school to the population of the corresponding official school age. Secondary education completes the provision of basic education that began at the primary level, and aims at laying the foundations for lifelong learning and human development, by offering more subject- or skill-oriented instruction using more specialized teachers.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Graph and download economic data for Employment Level - Less Than a High School Diploma, 25 Yrs. & over (LNU02027659) from Jan 1992 to Jun 2025 about secondary schooling, secondary, 25 years +, education, household survey, employment, and USA.

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

The dataset is related to student data, from an educational research study focusing on student demographics, academic performance, and related factors. Here’s a general description of what each column likely represents:

Sex: The gender of the student (e.g., Male, Female). Age: The age of the student. Name: The name of the student. State: The state where the student resides or where the educational institution is located. Address: Indicates whether the student lives in an urban or rural area. Famsize: Family size category (e.g., LE3 for families with less than or equal to 3 members, GT3 for more than 3). Pstatus: Parental cohabitation status (e.g., 'T' for living together, 'A' for living apart). Medu: Mother's education level (e.g., Graduate, College). Fedu: Father's education level (similar categories to Medu). Mjob: Mother's job type. Fjob: Father's job type. Guardian: The primary guardian of the student. Math_Score: Score obtained by the student in Mathematics. Reading_Score: Score obtained by the student in Reading. Writing_Score: Score obtained by the student in Writing. Attendance_Rate: The percentage rate of the student’s attendance. Suspensions: Number of times the student has been suspended. Expulsions: Number of times the student has been expelled. Teacher_Support: Level of support the student receives from teachers (e.g., Low, Medium, High). Counseling: Indicates whether the student receives counseling services (Yes or No). Social_Worker_Visits: Number of times a social worker has visited the student. Parental_Involvement: The level of parental involvement in the student's academic life (e.g., Low, Medium, High). GPA: The student’s Grade Point Average, a standard measure of academic achievement in schools.

This dataset provides a comprehensive look at various factors that might influence a student's educational outcomes, including demographic factors, academic performance metrics, and support structures both at home and within the educational system. It can be used for statistical analysis to understand and improve student success rates, or for targeted interventions based on specific identified needs.

United States US: School Enrollment: Secondary: Male: % Net data was reported at 89.513 % in 2015. This records an increase from the previous number of 87.832 % for 2014. United States US: School Enrollment: Secondary: Male: % Net data is updated yearly, averaging 87.442 % from Dec 1987 (Median) to 2015, with 21 observations. The data reached an all-time high of 89.513 % in 2015 and a record low of 85.450 % in 2002. United States US: School Enrollment: Secondary: Male: % Net data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Education Statistics. Net enrollment rate is the ratio of children of official school age who are enrolled in school to the population of the corresponding official school age. Secondary education completes the provision of basic education that began at the primary level, and aims at laying the foundations for lifelong learning and human development, by offering more subject- or skill-oriented instruction using more specialized teachers.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

This layer highlights the education status of women 25 or older, living below the poverty line. Compare this map to the Education Level of Men in Poverty for additional perspective, or use the Education Level of Women and Men in Poverty in the United States app to do a side by side comparison. The poverty line varies due to family size, state of residence, and other factors. The US Census normalizes the data by placing each respondent into an income category related to the poverty line. The Census then reports education levels for men and women above and below the poverty line. The US Census American Community Survey is an ongoing survey. These estimates were created from data collected from 2010 to 2014 and shown at the tract level. The tract borders are not shown to emphasize patterns.

The Educational Services sector comprises 13 subsectors of the US economy, ranging from public schools to testing and educational support services. Primary, secondary and postsecondary schools alone generate 92.0% of the sector's revenue. Most of these institutions rely entirely on government funding, and nearly three-quarters of the educational services revenue comes from public schools and public universities. Accordingly, strong federal, state and local support for all levels of education has driven revenue upward over the past five years. Expanding discretionary budgets made private schools and higher education more affordable for students and parents, but the Trump administration's changing policies have brought new complications. Still, substantial funding and skyrocketing investment returns for private nonprofit universities have elevated revenue. Revenue has climbed at a CAGR of 4.6% to an estimated $2.7 trillion through the end of 2025, when revenue will rise by 1.1%. Solid state and local government funding for education has helped support the sector's success despite fluctuating enrollment. Faltering birth rates are leading to lower headcounts in K-12 schools, and ballooning student debt has made many would-be college students skeptical of the return on investment of an expensive degree. While student loan forgiveness efforts slowed a decline in the number of college students, the new presidential administration's end to these efforts has begun to exacerbate price-based and quality-based competition among higher education institutions. President Trump's scrutiny of course curricula has made public funds harder to acquire for schools, and the administration's efforts to close the Department of Education have begun to deter would-be students from attending college. Trends in the domestic economy are set to move in the Educational Services sector's favor over the next five years as prospective students become better able to pay for rising tuition rates and premium education options. Government funding for primary, secondary and postsecondary institutions will continue to escalate through the next period, though lackluster enrollment will temper revenue growth. Public schools, which account for over half the sector's revenue, will continue to post losses and drag down the average profit for educational services. New school choice initiatives, including Texas's new, largest-ever voucher program, will make private schools more affordable for parents. However, heightened oversight and continued efforts to close the Department of Education will remain a significant pain point for many educational services. Overall, revenue is set to climb at a CAGR of 0.8% to $2.8 trillion through the end of 2030.

This layer shows education level for adults 25+. Counts broken down by sex. This is shown by tract, county, and state centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized by the count of total adults (25+) and the percentage of adults (25+) who were not high school graduates. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B15002Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.