Detailed tables showing the budget history of the U.S. Department of Education from FY 1980 to the FY 2018 President's Budget, by major program, and showing State allocations by State and by program from FY 1980-2017.

This table gives an overview of expenditure on regular education within the Netherlands.

The government finances schools, colleges and universities. It pays for research which is done by universities on its behalf. Furthermore it provides student grants and loans, allowances for school costs, provisions for students with a disability and child care allowances as well as subsidies to companies and non-profit organisations. The government reclaims unjustified payments for student grants and loans and allowances for school costs. It also receives interest and repayments on student loans as well as EU subsidies for education.

Parents and/or students have to pay tuition fees for schools, colleges and universities, parent contributions and contributions for school activities. They also have to purchase books and materials, pay for transport from home to school and back for students who are not eligible for subsidised transport, pay for private tutoring, pay interest and repayments on student loans, and repay wrongfully received student grants, loans and allowances for school costs. Parents and/or students receive child care allowances, provisions for students with a disability and an allowance for school costs as well as student grants and loans and scholarships of companies.

Companies and non-profit organisations incur costs for supervising trainees and apprentices who combine learning with work experience. They also contribute to the cost of work related education of their employees and spend money on research that is outsourced to colleges for higher professional education and universities. Furthermore they contribute to the childcare allowances given to households and provide scholarships to students. Companies receive subsidies and tax benefits for the creation of apprenticeship places and trainee placements and for providing transport for pupils.

Organisations abroad contract universities in the Netherlands to undertake research for them. The European Union provides funds and subsidies for education to schools, colleges and universities as well as to the Dutch government. Foreign governments contribute to international schools in the Netherlands that operate under their nationality.

The table also contains various indicators used nationally and internationally to compare expenditure on education and place it in a broader context. The indicators are compounded on the basis of definitions of Statistics Netherlands and/or the OECD (Organisation for Economic Cooperation and Development). All figures presented have been calculated according to the standardised definitions of the OECD.

In this table tertiary education includes research and development, except for the indicator Expenditure on education institutions per student, excluding R&D.

The statistic on Education spending is compiled on a cash basis. This means that the education expenditure and revenues are allocated to the year in which they are paid out or received. However, the activity or transaction associated with the payment or receipt can take place in a different year.

Statistics Netherlands published the revised National Accounts in June 2024. Among other things, GDP and total government expenditures have been adjusted upwards as a result of the revision.

Data available from: 1995

Status of the figures: The figures from 1995 to 2022 are final. The 2023 figures are provisional.

Changes as of 31 December 2024: The final figures of 2021 and 2022 and the provisional figures of 2023 have been added. As a result of the revision of the National Accounts, among other things, GDP and total government expenditures have been adjusted upwards. The indicators in this table that are expressed as a percentage of GDP and total government expenditure have been updated for the entire time series from 1995 on the basis of the revised figures.

When will new figures be published? The final figures for 2023 and the provisional figures for 2024 will be published in December 2025. More information on the revision policy of National Accounts can be found under 'relevant articles' under paragraph 3.

This dataset includes expenditure data reported by school districts, charter schools, and virtual schools starting with fiscal year 2009. It also includes student enrollment, demographic, and performance indicators as well as teacher salary and staffing data.

In addition to showing the overall cost per pupil, this dataset provides detail about how much districts spend in major functional areas such as administration, teaching, and maintenance. For more information about the data and how to interpret it, please visit the School Finance Dashboard.

Economically Disadvantaged was used 2015-2021. Low Income was used prior to 2015, and a different version of Low Income has been used since 2022. Please see the DESE Researcher's Guide for more information.

This dataset is one of three containing the same data that is also published in the School Finance Dashboard: District Expenditures by Spending Category District Expenditures by Function Code School Expenditures by Spending Category

List of Indicators by Category

Student Enrollment

• In-District FTE Pupils
• Out-of-District FTE Pupils
• Total FTE Pupils

Student Demographics

• Student Headcount
• Low-Income % Headcount
• English Learner % Headcount
• Students with Disabilities % Headcount

Teacher Salaries

• Teacher FTE
• Teachers per 100 FTE Students
• Average Teacher Salary

Other Staff

• Instructional Coach FTE
• Instructional Support FTE
• Special Education Instructional Support FTE
• Paraprofessional FTE

MCAS Performance

• ELA Grades 3-8 % Meets Exceeds
• Math Grades 3-8 % Meets Exceeds
• ELA Grade 10 % Meets Exceeds
• Math Grade 10 % Meets Exceeds

Expenditures

• Administration
• Instructional Leadership
• Teachers
• Other Teaching Services
• Professional Development
• Instructional Materials, Equipment and Technology
• Guidance, Counseling and Testing
• Pupil Services
• Operations and Maintenance
• Insurance, Retirement Programs and Other
• Total In-District Expenditures
• Total Expenditures

This dataset contains school-level expenditures reported by major functional spending category starting with fiscal year 2019. It also includes school-level enrollment, demographic, and performance indicators as well as teacher salary and staffing data.

The dataset shows school-level per pupil expenditures by major functional expenditure categories and funding sources, including state and local funds (general fund and state grants) and federal funds.

School districts only report instructional expenditures by school. This report attributes other costs to each school on a per pupil basis to show a full resource picture. The three cost centers are:

1. Non-instructional per pupil spending reported at the school district level;
2. Instructional per pupil spending reported at the district level; and
3. Instructional per pupil spending reported at the school level

Economically Disadvantaged was used 2015-2021. Low Income was used prior to 2015, and a different version of Low Income has been used since 2022. Please see the DESE Researcher's Guide for more information.

This dataset is one of three containing the same data that is also published in the School Finance Dashboard: District Expenditures by Spending Category District Expenditures by Function Code School Expenditures by Spending Category

List of Indicators by Category

Student Enrollment

• In-District FTE Pupils
• Out-of-District FTE Pupils
• Total FTE Pupils

Student Demographics

• Student Headcount
• Low-Income % Headcount
• English Learner % Headcount
• Students with Disabilities % Headcount

Teacher Salaries

• Teacher FTE
• Teachers per 100 FTE Students
• Average Teacher Salary

Other Staff

• Instructional Coach FTE
• Instructional Support FTE
• Special Education Instructional Support FTE
• Paraprofessional FTE

MCAS Performance

• ELA Grades 3-8 % Meets Exceeds
• Math Grades 3-8 % Meets Exceeds
• ELA Grade 10 % Meets Exceeds
• Math Grade 10 % Meets Exceeds

District-Level FTE Pupils

District-Level State and Local Non-Instructional Expenditures Per Pupil

• Administration
• Benefits and Fixed Costs
• Operations and Maintenance
• Pupil Services

District-Level Federal Non-Instructional Expenditures Per Pupil

• Administration
• Benefits and Fixed Costs
• Operations and Maintenance
• Pupil Services

Sub-total A

District-Level State and Local Instructional Expenditures Per Pupil

• Guidance and Psychological Services
• Instructional Leaders
• Instructional Materials
• Other Teaching Services
• Professional Development
• Teachers

District-Level Federal Instructional Expenditures Per Pupil

• Guidance and Psychological Services
• Instructional Leaders
• Instructional Materials
• Other Teaching Services
• Professional Development
• Teachers

Sub-total B

School-Level State and Local Instructional Expenditures Per Pupil

• Guidance and Psychological Services
• Instructional Leaders
• Instructional Materials
• Other Teaching Services
• Professional Development
• Teachers

School-Level Federal Instructional Expenditures Per Pupil

• Guidance and Psychological Services
• Instructional Leaders
• Instructional Materials
• Other Teaching Services
• Professional Development
• Teachers

Sub-total C

Total A+B+C

Analysis of ‘County Board of Education - Spending Disclosures’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/4c133a0c-a713-49f1-859f-647d3704e458 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

PLEASE READ THIS DATASET DESCRIPTION IN FULL BEFORE EXPORTING ANY DATA.

The data compiled in this dataset was provided by each County Board of Education. The data provides records of vendors that receive payments of $25,000 or more during a fiscal year from the County Board of Education. Chapter 541 of the Acts of 2019 requires each county school board must annually report (1) the name of a payee receiving a payment; (2) the location of a payee by postal zip code; (3) the amount of a payment; (4) for the Baltimore County Board of Education, the purpose for the payment and whether the payee is a minority business enterprise; and (5) for the Prince George’s County Board of Education, the budget data prepared under § 5-101 of the Education Article.

The bill defines a “payee” as any party who receives an aggregate payment of $25,000 in a fiscal year from a school board. A “payee” does not include (1) a public school employee with respect to the employee’s compensation; (2) a public school retiree with respect to the retiree’s retirement allowance; or (3) in Baltimore County, a third-party payee that accepts specified employee payroll-related payments.

All questions in regards to this data should be directed to the Maryland Department of Budget and Management or the individual county board of education(s).

--- Original source retains full ownership of the source dataset ---

This dataset tracks annual average expenditure per student from 1995 to 2021 for Tehama County Department Of Education School District

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_fa81cdad2b8e8d0d5ac6d97b992ea8e1/view

This dataset contains Chapter 70 foundation budget and net school spending data from 2008 onward.

The Chapter 70 program is the major program of state aid to public elementary and secondary schools providing state aid to support school operations. It establishes minimum spending requirements for each school district and minimum requirements for each municipality's share of school costs.

Detailed numbers for the Chapter 70 formula are available on the School Finance area of the Massachusetts Department of Elementary and Secondary Education’s website. Key files on this site include:

• Chapter 70 District Profiles – data including key formula components including foundation enrollment, foundation budget, Chapter 70 aid and required net school spending from 2008 to the most recent year of data available
• Chapter 70 Trends in Aid and Local Contribution – graphs and data at the district level comparing key formula components including foundation enrollment, foundation budget, Chapter 70 aid, and required net school spending from 2007 to the most recent year of data available
• Compliance with Net School Spending Requirements – data on net school spending at the district level from 2017 to the most recent year of data available

This dataset contains the same data that is also published on our DESE Profiles site: Chapter 70 Foundation Budget and Net School Spending

This dataset contains data from the National Center for Education Statistics' Academic Library Survey, which was gathered every two years from 1996 - 2014, and annually in IPEDS starting in 2014 (this dataset has continued to only merge data every two years, following the original schedule). This data was merged, transformed, and used for research by Starr Hoffman and Samantha Godbey.This data was merged using R; R scripts for this merge can be made available upon request. Some variables changed names or definitions during this time; a view of these variables over time is provided in the related Figshare Project. Carnegie Classification changed several times during this period; all Carnegie classifications were crosswalked to the 2000 classification version; that information is also provided in the related Figshare Project. This data was used for research published in several articles, conference papers, and posters starting in 2018 (some of this research used an older version of the dataset which was deposited in the University of Nevada, Las Vegas's repository).SourcesAll data sources were downloaded from the National Center for Education Statistics website https://nces.ed.gov/. Individual datasets and years accessed are listed below.[dataset] U.S. Department of Education, National Center for Education Statistics, Academic Libraries component, Integrated Postsecondary Education Data System (IPEDS), (2020, 2018, 2016, 2014), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7[dataset] U.S. Department of Education, National Center for Education Statistics, Academic Libraries Survey (ALS) Public Use Data File, Library Statistics Program, (2012, 2010, 2008, 2006, 2004, 2002, 2000, 1998, 1996), https://nces.ed.gov/surveys/libraries/aca_data.asp[dataset] U.S. Department of Education, National Center for Education Statistics, Institutional Characteristics component, Integrated Postsecondary Education Data System (IPEDS), (2020, 2018, 2016, 2014), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7[dataset] U.S. Department of Education, National Center for Education Statistics, Fall Enrollment component, Integrated Postsecondary Education Data System (IPEDS), (2020, 2018, 2016, 2014, 2012, 2010, 2008, 2006, 2004, 2002, 2000, 1998, 1996), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7[dataset] U.S. Department of Education, National Center for Education Statistics, Human Resources component, Integrated Postsecondary Education Data System (IPEDS), (2020, 2018, 2016, 2014, 2012, 2010, 2008, 2006), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7[dataset] U.S. Department of Education, National Center for Education Statistics, Employees Assigned by Position component, Integrated Postsecondary Education Data System (IPEDS), (2004, 2002), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7[dataset] U.S. Department of Education, National Center for Education Statistics, Fall Staff component, Integrated Postsecondary Education Data System (IPEDS), (1999, 1997, 1995), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7

The California School Campus Database (CSCD) is now available for all public schools and colleges/universities in California.CSCD is a GIS data set that contains detailed outlines of the lands used by public schools for educational purposes. It includes campus boundaries of schools with kindergarten through 12th grade instruction, as well as colleges, universities, and public community colleges. Each is accurately mapped at the assessor parcel level. CSCD is the first statewide database of this information and is available for use without restriction.PURPOSEWhile data is available from the California Department of Education (CDE) at a point level, the data is simplified and often inaccurate.CSCD defines the entire school campus of all public schools to allow spatial analysis, including the full extent of lands used for public education in California. CSCD is suitable for a wide range of planning, assessment, analysis, and display purposes.The lands in CSCD are defined by the parcels owned, rented, leased, or used by a public California school district for the primary purpose of educating youth. CSCD provides vetted polygons representing each public school in the state.Data is also provided for community colleges and university lands as of the 2018 release.CSCD is suitable for a wide range of planning, assessment, analysis, and display purposes. It should not be used as the basis for official regulatory, legal, or other such governmental actions unless reviewed by the user and deemed appropriate for their use. See the user manual for more information.Link to California School Campus Database.

This dataset includes school district expenditures by function code starting with fiscal year 2009.

Function codes describe discrete expenditures within major functional areas such as administration, teaching, and maintenance. The report also distinguishes between in-district and out-of-district programs and spending is categorized by funding source, including general fund and grants and revolving funds. For more information about the data and how to interpret it, please visit the School Finance Dashboard.

This dataset only includes school district expenditures. Due to differences how data is reported by school districts and charter schools and virtual schools, charter school and virtual school data is not available at the function code level. Visit the charter school financial report page for more information.

This dataset is one of three containing the same data that is also published in the School Finance Dashboard: District Expenditures by Spending Category District Expenditures by Function Code School Expenditures by Spending Category

List of Functional Spending Codes by Category

*Function code discontinued starting in fiscal year 2018

ADMN Administration

• 1110 School Committee
• 1210 Superintendent
• 1220 Assistant Superintendents
• 1230 Other District-Wide Administration
• 1410 Business and Finance
• 1420 Human Resources and Benefits
• 1430 Legal Service for School Committee
• 1435 Legal Settlements
• 1450 Administrative Technology-Districtwide

LDRS Instructional Leadership

• 2110 Curriculum Directors and Dept. Heads (Supervisory)
• 2120 Curriculum Directors and Dept. Heads (Non-Supervisory)
• 2130 Instructional Technology Leadership and Training
• 2210 School Leadership
• 2220 Curriculum/Dept Leaders (School Level)*
• 2250 Administrative Technology and Support (Schools)*
• 2315 Instructional Coordinators (Non-Supervisory)*

TCHR Teachers

• 2305 Teachers, Classroom
• 2310 Teachers, Specialists*

TSER Other Teaching Services

• 2320 Medical/ Therapeutic Services
• 2324 Substitutes, Long-Term
• 2325 Substitutes, Short-Term
• 2330 Paraprofessionals
• 2340 Librarians/Media Center Directors
• 2345 Distance Learning and Online Coursework

PDEV Professional Development

• 2351 Professional Development Leadership
• 2352 Instructional Coaches
• 2353 Instructional Staff-Professional Days*
• 2354 Stipends for Teachers Providing Instructional Coaching
• 2355 Substitutes for Prof. Development*
• 2356 Costs for Instructional Staff to Attend Professional Development
• 2357 Prof. Dev. Stipends, Providers, Expenses*
• 2358 Outside Professional Development Providers for Instructional Staff

MATL Instructional Materials, Equipment and Technology

• 2410 Textbooks
• 2415 Other Instructional Matls (Libraries)
• 2420 Instructional Equipment
• 2430 General Classroom Supplies
• 2440 Other Instructional Services
• 2451 Instructional Hardware - Student and Staff Devices (computers)
• 2453 Instructional Hardware - All Other
• 2455 Instructional Software and Other Instructional Materials

GUID Guidance, Counseling and Testing

• 2710 Guidance incl Adjustment Counselors
• 2720 Testing and Assessment
• 2800 Psychological Services

SERV Pupil Services

• 3100 Attendance and Parent Liaison Services
• 3200 Medical/Health Services
• 3300 Transportation Services
• 3400 Food Services
• 3510 Athletics
• 3520 Other Student Activities
• 3600 School Security

OPMN Operations and Maintenance

• 4110 Custodial Services
• 4120 Heating of Buildings
• 4130 Utility Services
• 4210 Maintenance of Grounds
• 4220 Maintenance of Buildings
• 4225 Building Security System
• 4230 Maintenance of Equipment
• 4300 Extraordinary Maintenance
• 4400 Technology Infrastructure, Maintenance, and Support - Salaries
• 4450 Technology Infrastructure, Maintenance, and Support - All Other

BENE Insurance, Retirement Programs and Other

• 5100 Employer Retirement Contributions
• 5150 Employee Separation Costs
• 5200 Insurance for Active Employees
• 5250 Insurance for Retired School Employees
• 5260 Other Non-Employee Insurance
• 5300 Rental Lease of Equipment
• 5350 Rental Lease of Buildings
• 5400 Short Term Interest RANs
• 5500 Other Fixed Charges
• 5550 School Crossing Guards

TUIT Tuition

• 9100 Tuition to Mass. Schools
• 9110 Tuition for School Choice
• 9120 Tuition to Commonwealth Charter Schools
• 9125 Tuition to Horace Mann Charter Schools
• 9200 Tuition to Out-of-State Schools
• 9300 Tuition to Non-Public Schools
• 9400 Tuition to Collaboratives

ODTR Out-of-district Transportation

• 9130 Charter Transportation Tuition

IIII In-district Expenditure

OODD Out-of-district Expenditure

TTPP Expenditure (Admin, Instruction, Operations)

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).

This web map provides and in-depth look at school districts within the United States. Clicking on a school district in the map will reveal different statistics about each district in the pop-up. The statistics presented in this map are approximations based on summarizing American Community Survey(ACS) data using tract centroids. They may differ from published statistics by school districts found on data.census.gov. A few things you will learn from this map:How many public and private schools fall within a district?Socioeconomic factors about the Census Tracts which fall within the district:School enrollment for grades Kindergarten through 12thDisconnected children in the districtChildren living below the poverty level Children with no internet at home Children without a working parentRace/ethnicity breakdown of population under the age of 19 in the districtFor more information about the data sources:This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases estimates, so values in the map always reflect the newest data available.Current School Districts Layer: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 single-purpose administrative units designed by state and local officials to organize and provide public education for local residents. District boundaries are collected for NCES by the U.S. Census Bureau to support educational research and program administration, and the boundaries are essential for constructing district-level estimates of the number of children in poverty.The Census Bureau’s School District Boundary Review program (SDRP) (https://www.census.gov/programs-surveys/sdrp.html) obtains the boundaries, names, and grade ranges from state officials, and integrates these updates into Census TIGER. Census TIGER boundaries include legal maritime buffers for coastal areas by default, but the NCES composite file removes these buffers to facilitate broader use and cleaner cartographic representation. The NCES EDGE program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to develop the composite school district files. The inputs for this data layer were developed from Census TIGER/Line and represent the most current boundaries available. For more information about NCES school district boundary data, see https://nces.ed.gov/programs/edge/Geographic/DistrictBoundaries.Public Schools Layer:This Public Schools feature dataset is composed of all Public elementary and secondary education facilities in the United States as defined by the Common Core of Data (CCD, https://nces.ed.gov/ccd/ ), National Center for Education Statistics (NCES, https://nces.ed.gov ), US Department of Education for the 2017-2018 school year. This includes all Kindergarten through 12th grade schools as tracked by the Common Core of Data. Included in this dataset are military schools in US territories and referenced in the city field with an APO or FPO address. DOD schools represented in the NCES data that are outside of the United States or US territories have been omitted. This feature class contains all MEDS/MEDS+ as approved by NGA. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the Place Keyword section of the metadata. This release includes the addition of 3065 new records, modifications to the spatial location and/or attribution of 99,287 records, and removal of 2996 records not present in the NCES CCD data.Private Schools Layer:This Private Schools feature dataset is composed of private elementary and secondary education facilities in the United States as defined by the Private School Survey (PSS, https://nces.ed.gov/surveys/pss/), National Center for Education Statistics (NCES, https://nces.ed.gov), US Department of Education for the 2017-2018 school year. This includes all prekindergarten through 12th grade schools as tracked by the PSS. This feature class contains all MEDS/MEDS+ as approved by NGA. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the Place Keyword section of the metadata. This release includes the addition of 2675 new records, modifications to the spatial location and/or attribution of 19836 records, the removal of 254 records no longer applicable. Additionally, 10,870 records were removed that previously had a STATUS value of 2 (Unknown; not represented in the most recent PSS data) and duplicate records identified by ORNL.Web Map originally owned by Summers Cleary

This dataset tracks annual average expenditure per student from 1990 to 2015 for Hawaii Department Of Education School District

Educational Youth Indicators

School Enrollment, Attendance, Achievement, and Engagement

By City of Baltimore [source]

About this dataset

This dataset from the Baltimore Neighborhood Indicators Alliance-Jacob France Institute (BNIA-JFI) gathers information about education and youth across Baltimore. Through tracking 27 indicators grouped into seven categories - student enrollment and demographics, dropout rate and high school completion, student attendance, suspensions and expulsions, elementary and middle school student achievement, high school performance, youth labor force participation, and youth civic engagement - BNIA-JFI paints a comprehensive picture of education trends within the city limits. Data sourced from the Baltimore City Public School System (BCPSS), American Community Survey (ACS), as well as Maryland Department of Education allows for cross program comparison to better map connections between educational outcomes affected by neighborhood context. The 2009-2010 school year was used based on readily available data with an approximated 3.4% of address unable to be matched or geocoded and therefore not included in these calculations. Leveraging this data provides perspective to help guide decisions made at local government level that could impact thousands of lives in years ahead

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How to use the dataset

This dataset contains valuable information about the educational performance and youth engagement in Baltimore City. It provides data on 27 indicators, grouped into seven categories: student enrollment and demographics; dropout rate and high school completion; student attendance, suspensions and expulsions; elementary and middle school student achievement; high school performance; youth labor force participation; and youth civic engagement. This dataset can be used to answer important questions about education in Baltimore, such as examining the relationship between community conditions and educational outcomes.

Before using this dataset, it’s important to understand the source of data for each indicator (e.g., Baltimore City Public School System, American Community Survey) so you can understand potential limitations inherent in each data set. Additionally, keep in mind that this dataset does not include students whose home address cannot be geocoded or matched between datasets due to inconsistency of information or other issues - this means that comparisons between some of these indicators may not be as accurate as is achievable with other datasets available from sources such as the Maryland Department of Education or the Baltimore City Public Schools System.

Once you are familiar with where the data comes from you can use it to answer these questions by exploring different trends within Baltimore city over time:

• How have student enrollment numbers changed over time?
• What has been the overall trend in dropout rates across elementary schools?
• Are there any differences in student attendance based on school type?
• What correlations exist between neighborhood community characteristics (such as crime rates or poverty levels), and academic achievement scores?
• How have rates of labor force participation among adolescents shifted year-over-year?

And more! By looking at trends by geography within this diverse city we can gain valuable insight into what factors may play a role influencing educational outcomes for children growing up in different areas around Baltimore City - an essential step for developing methodologies for successful policy interventions targeting our most vulnerable populations!

Research Ideas

• Analyzing the correlation between student achievement and socio-economic status of the neighborhoods in which students live.
• Creating targeted policies that are tailored to address specific educational issues showcased in each Baltimore neighborhood demographic.
• Using data visualizations to demonstrate to residents and community leaders how their area is performing compared to other communities in terms of education, dropout rates, suspension rates, and more

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. [See Other Information](https://creativecommons.org/public...

As part of the transparency agenda commitment relating to public expenditure, intended to help achieve better value for money, the Department for Education (DfE) and our Arm’s Length Bodies (ALBs) are publishing spending over £25,000. QCDA operates a wholly owned company QCDA Enterprises, which predominately makes available optional tests to schools. Information for this is shown as a separate dataset. There was no expenditure for QCDAe in August 2010.

Analysis of ‘International Educational Attainment by Year & Age’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/international-comp-attainmente on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

The National Center for Education Statistics (NCES) is the primary federal entity for collecting and analyzing data related to education in the U.S. and other nations. NCES is located within the U.S. Department of Education and the Institute of Education Sciences. NCES fulfills a Congressional mandate to collect, collate, analyze, and report complete statistics on the condition of American education; conduct and publish reports; and review and report on education activities internationally.

• Table 603.10. Percentage of the population 25 to 64 years old who completed high school, by age group and country: Selected years, 2001 through 2012
• Table 603.20. Percentage of the population 25 to 64 years old who attained selected levels of postsecondary education, by age group and country: 2001 and 2012
• Table 603.30. Percentage of the population 25 to 64 years old who attained a bachelor's or higher degree, by age group and country: Selected years, 1999 through 2012
• Table 603.40 Percentage of the population 25 to 64 years old who attained a postsecondary vocational degree, by age group and country: Selected years, 1999 through 2012
• Table 603.50 Number of bachelor's degree recipients per 100 persons at the typical minimum age of graduation, by sex and country: Selected years, 2005 through 2012
• Table 603.60. Percentage of postsecondary degrees awarded to women, by field of study and country: 2013
• Table 603.70. Percentage of bachelor's or equivalent degrees awarded in mathematics, science, and engineering, by field of study and country: 2013
• Table 603.80. Percentage of master's or equivalent degrees and of doctoral or equivalent degrees awarded in mathematics, science, and engineering, by field of study and country: 2013
• Table 603.90. Employment to population ratios of -25 to 64-year-olds, by sex, highest level of educational attainment, and country: 2014

Source: https://nces.ed.gov/programs/digest/current_tables.asp

This dataset was created by National Center for Education Statistics and contains around 100 samples along with Unnamed: 20, Unnamed: 24, technical information and other features such as: - Unnamed: 11 - Unnamed: 16 - and more.

How to use this dataset

• Analyze Unnamed: 15 in relation to Unnamed: 6
• Study the influence of Unnamed: 1 on Unnamed: 10
• More datasets

Acknowledgements

If you use this dataset in your research, please credit National Center for Education Statistics

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--- Original source retains full ownership of the source dataset ---

The 2020-2021 School Learning Modalities dataset provides weekly estimates of school learning modality (including in-person, remote, or hybrid learning) for U.S. K-12 public and independent charter school districts for the 2020-2021 school year, from August 2020 – June 2021.

These data were modeled using multiple sources of input data (see below) to infer the most likely learning modality of a school district for a given week. These data should be considered district-level estimates and may not always reflect true learning modality, particularly for districts in which data are unavailable. If a district reports multiple modality types within the same week, the modality offered for the majority of those days is reflected in the weekly estimate. All school district metadata are sourced from the https://nces.ed.gov/ccd/files.asp#Fiscal:2,LevelId:5,SchoolYearId:35,Page:1">National Center for Educational Statistics (NCES) for 2020-2021.

School learning modality types are defined as follows:

• In-Person: All schools within the district offer face-to-face instruction 5 days per week to all students at all available grade levels.
• Remote: Schools within the district do not offer face-to-face instruction; all learning is conducted online/remotely to all students at all available grade levels.
• Hybrid: Schools within the district offer a combination of in-person and remote learning; face-to-face instruction is offered less than 5 days per week, or only to a subset of students.

Data Information

• School learning modality data provided here are model estimates using combined input data and are not guaranteed to be 100% accurate. This learning modality dataset was generated by combining data from four different sources: Burbio [1], MCH Strategic Data [2], the AEI/Return to Learn Tracker [3], and state dashboards [4-20]. These data were combined using a Hidden Markov model which infers the sequence of learning modalities (In-Person, Hybrid, or Remote) for each district that is most likely to produce the modalities reported by these sources. This model was trained using data from the 2020-2021 school year. Metadata describing the location, number of schools and number of students in each district comes from NCES [21].
• You can read more about the model in the CDC MMWR: https://www.cdc.gov/mmwr/volumes/70/wr/mm7039e2.htm" target="_blank">COVID-19–Related School Closures and Learning Modality Changes — United States, August 1–September 17, 2021.
• The metrics listed for each school learning modality reflect totals by district and the number of enrolled students per district for which data are available. School districts represented here exclude private schools and include the following NCES subtypes:
  • Public school district that is NOT a component of a supervisory union
  • Public school district that is a component of a supervisory union
  • Independent charter district
• “BI” in the state column refers to school districts funded by the Bureau of Indian Education.

Technical Notes

• Data from September 1, 2020 to June 25, 2021 correspond to the 2020-2021 school year. During this timeframe, all four sources of data were available. Inferred modalities with a probability below 0.75 were deemed inconclusive and were omitted.
• Data for the month of July may show “In Person” status although most school districts are effectively closed during this time for summer break. Users may wish to exclude July data from use for this reason where applicable.

Sources

1. K-12 School Opening Tracker. Burbio 2021; https://cai.burbio.com/school-opening-tracker/. June 2021.
2. COVID-19 IMPACT: School District Operational Status. MCH Strategic Data: 2021; https://www.mchdata.com/covid19/schoolclosings. (30 June 2021, date last accessed).
3. Return to Learn Tracker. American Enterprise Institute 2021; https://www.returntolearntracker.net/. (30 June 2021, date last accessed).
4. Colorado School District Reopening Plans. Colorado Department of Education 2021; https://docs.google.com/spreadsheets/d/e/2PACX-1vQipdjO8QWhilhhJ4bX0FBebnHEzK1G3LEDQbE_S-xRvs2t0oHNm--acHwMRFmL9uKw4cXcOUqy1V66/pubhtml. (30 June 2021, date last accessed).
5. Connecticut Report Cards. Connecticut State Department of Education 2021; http://edsight.ct.gov/SASPortal/main.do. (30 June 2021, date last accessed).
6. COVID Planning Tool. Hawaii Department of Education 2021; https://public.tableau.com/views/COVIDPlanningTool-Embed700px/SimpleDashboard. (30 June 2021, date last accessed).
7. Idaho School District Status. Idaho State Department of Education 2021; https://ioem.maps.arcgis.com/apps/opsdashboard/index.html#/379299e56f234fa89cff3c8c6acf3ac8. (30 June 2021, date last accessed).
8. How Illinois Districts Are Providing Instruction: Virtual, In-Person, and Blended Learning. Illinois State Board of Education 2021; https://isp.maps.arcgis.com/apps/opsdashboard/index.html#/fceeacb37da04de4b237ed941dd7d5c4. (30 June 2021, date last accessed).
9. Digital Learning Model Schools. Louisiana Department of Education 2021; https://analytics.la.gov/t/DOE/views/DigitalLearningModel/SchoolLevelModeofLearning. (30 June 2021, date last accessed).
10. Safe Learning Model Dashboard. Minnesota Department of Education 2021; https://analytics.education.state.mn.us/t/MDEPublic/views/MN_Safe_Learning_Model/Dashboard. (30 June 2021, date last accessed).
11. Coronavirus (COVID-19) information. Missouri Department of Elementary & Secondary Education 2021; https://dese.mo.gov/communications/coronavirus-covid-19-information. (30 June 2021, date last accessed).
12. North Carolina School Dashboard. North Carolina Department of Public Instruction 2021. https://docs.google.com/spreadsheets/d/1We8gDpa4Do5NR83Nf8niGE_YxzLDf-KZh-tVWifStxE/edit#gid=0. (30 June 2021, date last accessed).
13. Ring the Bell: Return to In-Person Learning. New Mexico Public Education Department 2021; https://webnew.ped.state.nm.us/reentry-district-and-school-guidance/. (30 June 2021, date last accessed).
14. Reset and Restart Education. Ohio Department of Education 2021; http://education.ohio.gov/Topics/Reset-and-Restart. (30 June 2021, date last accessed).
15. 2020-21 School Status. Oregon Department of Education 2021; https://www.oregon.gov/ode/students-and-family/healthsafety/Pages/2020-21-School-Status.aspx. (30 June 2021, date last accessed).
16. Current Operational Status. South Carolina Department of Education 2021; https://ed.sc.gov/districts-schools/schools/district-and-school-closures/operational-status/#blk2102. (30 June 2021, date last accessed).
17. Tennessee Department of Education COVID-19 District Information. Tennessee Department of Education 2021; https://districtinformation.tnedu.gov/covid-information/search/-1. (30 June 2021, date last accessed).
18. State Snapshot: Virginia School Operational Status. Virginia Department of Education 2021; https://www.doe.virginia.gov/support/health_medical/office/reopen-status.shtml. (30 June 2021, date last accessed).
19. Current Reopening Status of Vermont's K-12 Public Schools. Vermont Department of Financial Regulation 2021; https://dfr.vermont.gov/about-us/covid-19/school-reopening#public-school. (30 June 2021, date last accessed).
20. School Reopening Data. Washington Office of Superintendent of Public Instruction 2021; https://www.k12.wa.us/about-ospi/press-releases/novel-coronavirus-covid-19-guidance-resources/school-reopening-data. (30 June 2021, date last accessed).
21. Public school districts. National Center for Education Statistics 2021; https://nces.ed.gov/ccd/districtsearch/. (30 June 2021, date last accessed).

This dataset tracks annual average expenditure per student from 2016 to 2021 for Suquamish Tribal Education Department School District

This dataset tracks annual average expenditure per student from 1995 to 2021 for Orange County Department Of Education School District