100+ datasets found
  1. School District Characteristics - Current

    • s.cnmilf.com
    • datasets.ai
    • +1more
    Updated Oct 21, 2024
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    National Center for Education Statistics (NCES) (2024). School District Characteristics - Current [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/school-district-characteristics-current-f96a2
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    Dataset updated
    Oct 21, 2024
    Dataset provided by
    National Center for Education Statisticshttps://nces.ed.gov/
    Description

    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:-1 or MIndicates that the data are missing.-2 or NIndicates that the data are not applicable.-9Indicates that the data do not meet NCES data quality standards.Collections are available for the following years:2022-232021-222020-212019-202018-192017-18All 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.

  2. Public School Characteristics 2022-23

    • s.cnmilf.com
    • catalog.data.gov
    Updated Oct 21, 2024
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    National Center for Education Statistics (NCES) (2024). Public School Characteristics 2022-23 [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/public-school-characteristics-2022-23-451db
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    Dataset updated
    Oct 21, 2024
    Dataset provided by
    National Center for Education Statisticshttps://nces.ed.gov/
    Description

    The National Center for Education Statistics' (NCES) Education Demographic and Geographic Estimates (EDGE) program develops annually updated point locations (latitude and longitude) for public elementary and secondary schools included in the NCES Common Core of Data (CCD). The CCD program annually collects administrative and fiscal data about all public schools, school districts, and state education agencies in the United States. The data are supplied by state education agency officials and include basic directory and contact information for schools and school districts, as well as characteristics about student demographics, number of teachers, school grade span, and various other administrative conditions. CCD school and agency point locations are derived from reported information about the physical _location of schools and agency administrative offices. The point locations and administrative attributes in this data layer were developed from the 2022-2023 CCD collection. For more information about NCES school point data, see: https://nces.ed.gov/programs/edge/Geographic/SchoolLocations. For more information about these CCD attributes, as well as additional attributes not included, 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.

  3. School District Characteristics 2020-21

    • catalog.data.gov
    • datasets.ai
    • +2more
    Updated Oct 21, 2024
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    National Center for Education Statistics (NCES) (2024). School District Characteristics 2020-21 [Dataset]. https://catalog.data.gov/dataset/school-district-characteristics-2020-21-99af4
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    Dataset updated
    Oct 21, 2024
    Dataset provided by
    National Center for Education Statisticshttps://nces.ed.gov/
    Description

    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 2020-2021 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.

  4. N

    School Attendance Statistics

    • data.cityofnewyork.us
    • cloud.csiss.gmu.edu
    • +2more
    application/rdfxml +5
    Updated Mar 22, 2013
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    Department of Education (DOE) (2013). School Attendance Statistics [Dataset]. https://data.cityofnewyork.us/Education/School-Attendance-Statistics/u6fv-5dqe
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    application/rdfxml, application/rssxml, csv, json, xml, tsvAvailable download formats
    Dataset updated
    Mar 22, 2013
    Dataset authored and provided by
    Department of Education (DOE)
    Description

    Daily Attendance figures are accurate as of 4:00pm, but are not final as schools continue to submit data after we generate this preliminary report.

  5. U

    United States US: Adjusted Net Enrollment Rate: Primary: Female: % of...

    • ceicdata.com
    Updated Jun 30, 2018
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    CEICdata.com (2018). United States US: Adjusted Net Enrollment Rate: Primary: Female: % of Primary School Age Children [Dataset]. https://www.ceicdata.com/en/united-states/education-statistics
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    Dataset updated
    Jun 30, 2018
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2004 - Dec 1, 2015
    Area covered
    United States
    Variables measured
    Education Statistics
    Description

    US: Adjusted Net Enrollment Rate: Primary: Female: % of Primary School Age Children data was reported at 94.162 % in 2015. This records an increase from the previous number of 93.723 % for 2014. US: Adjusted Net Enrollment Rate: Primary: Female: % of Primary School Age Children data is updated yearly, averaging 95.576 % from Dec 1986 (Median) to 2015, with 25 observations. The data reached an all-time high of 98.967 % in 1990 and a record low of 92.941 % in 2013. US: Adjusted Net Enrollment Rate: Primary: Female: % of Primary School Age Children data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Education Statistics. Adjusted net enrollment is the number of pupils of the school-age group for primary education, enrolled either in primary or secondary education, expressed as a percentage of the total population in that age group.; ; 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).

  6. School Proficiency Index

    • hudgis-hud.opendata.arcgis.com
    • data.lojic.org
    • +1more
    Updated Jul 5, 2023
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    Department of Housing and Urban Development (2023). School Proficiency Index [Dataset]. https://hudgis-hud.opendata.arcgis.com/datasets/school-proficiency-index
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    Dataset updated
    Jul 5, 2023
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Authors
    Department of Housing and Urban Development
    Area covered
    Description

    SCHOOL PROFICIENCY INDEXSummaryThe school proficiency index uses school-level data on the performance of 4th grade students on state exams to describe which neighborhoods have high-performing elementary schools nearby and which are near lower performing elementary schools. The school proficiency index is a function of the percent of 4th grade students proficient in reading (r) and math (m) on state test scores for up to three schools (i=1,2,3) within 1.5 miles of the block-group centroid. S denotes 4th grade school enrollment:Elementary schools are linked with block-groups based on a geographic mapping of attendance area zones from School Attendance Boundary Information System (SABINS), where available, or within-district proximity matches of up to the three-closest schools within 1.5 miles. In cases with multiple school matches, an enrollment-weighted score is calculated following the equation above. Please note that in this version of the data (AFFHT0004), there is no school proficiency data for jurisdictions in Kansas, West Virginia, and Puerto Rico because no data was reported for jurisdictions in these states in the Great Schools 2013-14 dataset. InterpretationValues are percentile ranked and range from 0 to 100. The higher the score, the higher the school system quality is in a neighborhood. Data Source: Great Schools (proficiency data, 2015-16); Common Core of Data (4th grade school addresses and enrollment, 2015-16); Maponics (attendance boundaries, 2016).Related AFFH-T Local Government, PHA and State Tables/Maps: Table 12; Map 7.

    To learn more about the School Proficiency Index visit: https://www.hud.gov/program_offices/fair_housing_equal_opp/affh ; https://www.hud.gov/sites/dfiles/FHEO/documents/AFFH-T-Data-Documentation-AFFHT0006-July-2020.pdf, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Date of Coverage: 07/2020

  7. France FR: School Enrollment: Primary: Private: % of Total Primary

    • ceicdata.com
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    CEICdata.com, France FR: School Enrollment: Primary: Private: % of Total Primary [Dataset]. https://www.ceicdata.com/en/france/education-statistics
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    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2004 - Dec 1, 2015
    Area covered
    France
    Variables measured
    Education Statistics
    Description

    FR: School Enrollment: Primary: Private: % of Total Primary data was reported at 14.644 % in 2015. This records a decrease from the previous number of 14.652 % for 2014. FR: School Enrollment: Primary: Private: % of Total Primary data is updated yearly, averaging 14.657 % from Dec 1971 (Median) to 2015, with 40 observations. The data reached an all-time high of 15.079 % in 1985 and a record low of 13.890 % in 1971. FR: School Enrollment: Primary: Private: % of Total Primary data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s France – Table FR.World Bank.WDI: Education Statistics. Private enrollment refers to pupils or students enrolled in institutions that are not operated by a public authority but controlled and managed, whether for profit or not, by a private body such as a nongovernmental organization, religious body, special interest group, foundation or business enterprise.; ; 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).

  8. c

    School size by type of education and ideological basis

    • cbs.nl
    • ckan.mobidatalab.eu
    • +5more
    xml
    Updated Apr 14, 2025
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    Centraal Bureau voor de Statistiek (2025). School size by type of education and ideological basis [Dataset]. https://www.cbs.nl/en-gb/figures/detail/03753eng
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    xmlAvailable download formats
    Dataset updated
    Apr 14, 2025
    Dataset authored and provided by
    Centraal Bureau voor de Statistiek
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    The Netherlands
    Description

    This table contains figures on schools and educational institutions by type of education, ideological basis and school size. It concerns schools and educational institutions financed by the government. Figures for the adult education are left out of this table, because the number of institutions is not available.

    Data available from: School-/academic year 1990/91

    Status of the figures: The figures up to and including school-/academic year 2023/24 are final and the figures of school-/academic year 2024/25 are provisional.

    Changes on 14 April 2025: The final figures of school-/academic year 2023/24 and the provisional figures of school-/academic year 2024/25 have been added.

    When will new figures be published? In the second quarter of 2026 the provisional figures of school-/academic year 2024/25 will be replaced by final figures and the provisional figures of school-/academic year 2025/26 will be added in this publication.

  9. Aruba AW: Gender Parity Index (GPI): Secondary School Enrollment: Gross

    • ceicdata.com
    Updated Feb 6, 2018
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    CEICdata.com (2018). Aruba AW: Gender Parity Index (GPI): Secondary School Enrollment: Gross [Dataset]. https://www.ceicdata.com/en/aruba/education-statistics
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    Dataset updated
    Feb 6, 2018
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2001 - Dec 1, 2012
    Area covered
    Aruba
    Variables measured
    Education Statistics
    Description

    AW: Gender Parity Index (GPI): Secondary School Enrollment: Gross data was reported at 1.018 Ratio in 2012. This records a decrease from the previous number of 1.056 Ratio for 2011. AW: Gender Parity Index (GPI): Secondary School Enrollment: Gross data is updated yearly, averaging 1.047 Ratio from Dec 1999 (Median) to 2012, with 14 observations. The data reached an all-time high of 1.071 Ratio in 2008 and a record low of 0.988 Ratio in 2006. AW: Gender Parity Index (GPI): Secondary School Enrollment: Gross data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Aruba – Table AW.World Bank.WDI: Social: Education Statistics. Gender parity index for gross enrollment ratio in secondary education is the ratio of girls to boys enrolled at secondary level in public and private schools.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed October 24, 2022. https://apiportal.uis.unesco.org/bdds.;Weighted average;

  10. Share of students enrolled in U.S. public K-12 schools 2022, by ethnicity...

    • statista.com
    • ai-chatbox.pro
    Updated Mar 24, 2025
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    Statista (2025). Share of students enrolled in U.S. public K-12 schools 2022, by ethnicity and state [Dataset]. https://www.statista.com/statistics/236244/enrollment-in-public-schools-by-ethnicity-and-us-state/
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    Dataset updated
    Mar 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In California in 2022, 20.5 percent of students enrolled in K-12 public schools were white, 11.9 percent were Asian, and 56.2 percent were Hispanic. In the United States overall, 44.7 percent of K-12 public school students were white, 5.5 percent were Asian, and 28.7 percent were Hispanic.

  11. Data from: University of Washington - Beyond High School (UW-BHS)

    • icpsr.umich.edu
    • search.datacite.org
    ascii, delimited, r +3
    Updated Feb 15, 2016
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    Hirschman, Charles; Almgren, Gunnar (2016). University of Washington - Beyond High School (UW-BHS) [Dataset]. http://doi.org/10.3886/ICPSR33321.v5
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    delimited, r, ascii, spss, stata, sasAvailable download formats
    Dataset updated
    Feb 15, 2016
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Hirschman, Charles; Almgren, Gunnar
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/33321/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/33321/terms

    Time period covered
    2000 - 2010
    Area covered
    Washington, United States
    Description

    The University of Washington - Beyond High School (UW-BHS) project surveyed students in Washington State to examine factors impacting educational attainment and the transition to adulthood among high school seniors. The project began in 1999 in an effort to assess the impact of I-200 (the referendum that ended Affirmative Action) on minority enrollment in higher education in Washington. The research objectives of the project were: (1) to describe and explain differences in the transition from high school to college by race and ethnicity, socioeconomic origins, and other characteristics, (2) to evaluate the impact of the Washington State Achievers Program, and (3) to explore the implications of multiple race and ethnic identities. Following a successful pilot survey in the spring of 2000, the project eventually included baseline and one-year follow-up surveys (conducted in 2002, 2003, 2004, and 2005) of almost 10,000 high school seniors in five cohorts across several Washington school districts. The high school senior surveys included questions that explored students' educational aspirations and future career plans, as well as questions on family background, home life, perceptions of school and home environments, self-esteem, and participation in school related and non-school related activities. To supplement the 2000, 2002, and 2003 student surveys, parents of high school seniors were also queried to determine their expectations and aspirations for their child's education, as well as their own educational backgrounds and fields of employment. Parents were also asked to report any financial measures undertaken to prepare for their child's continued education, and whether the household received any form of financial assistance. In 2010, a ten-year follow-up with the 2000 senior cohort was conducted to assess educational, career, and familial outcomes. The ten year follow-up surveys collected information on educational attainment, early employment experiences, family and partnership, civic engagement, and health status. The baseline, parent, and follow-up surveys also collected detailed demographic information, including age, sex, ethnicity, language, religion, education level, employment, income, marital status, and parental status.

  12. Net enrollment rate in primary school worldwide 2000-2018

    • statista.com
    • ai-chatbox.pro
    Updated Feb 26, 2025
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    Statista (2025). Net enrollment rate in primary school worldwide 2000-2018 [Dataset]. https://www.statista.com/statistics/1226999/net-enrollment-rate-in-primary-school-worldwide/
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    Dataset updated
    Feb 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    89.4 percent of children in primary school age were enrolled in primary schools worldwide in 2018. That was an increase of about five percent when compared to the figures from 2000. The highest primary school net enrollment rate was measured in 2016 when 89.42 percent of children worldwide were enrolled in primary education. In 2018, the net enrollment rate in secondary school worldwide was 66.27 percent.

  13. High school enrollment in public and private institutions U.S. 1965-2031

    • statista.com
    • ai-chatbox.pro
    Updated Jul 5, 2024
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    Statista (2024). High school enrollment in public and private institutions U.S. 1965-2031 [Dataset]. https://www.statista.com/statistics/183996/us-high-school-enrollment-in-public-and-private-institutions/
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    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2021, about 1.5 million students were enrolled in private high schools or similar institutions in the United States. There were significantly more students enrolled in public high schools across the United States, at 15.4 million students.

  14. d

    School Quality Reports Data

    • catalog.data.gov
    • data.cityofnewyork.us
    Updated Mar 22, 2025
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    data.cityofnewyork.us (2025). School Quality Reports Data [Dataset]. https://catalog.data.gov/dataset/school-quality-reports-data
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    Dataset updated
    Mar 22, 2025
    Dataset provided by
    data.cityofnewyork.us
    Description

    This report shares information about school performance, sets expectations for schools, and promotes school improvement. School Quality Report Educator Guides can be found here.

  15. Thailand TH: School Enrollment: Primary: % Gross

    • ceicdata.com
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    CEICdata.com, Thailand TH: School Enrollment: Primary: % Gross [Dataset]. https://www.ceicdata.com/en/thailand/education-statistics
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    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2004 - Dec 1, 2015
    Area covered
    Thailand
    Variables measured
    Education Statistics
    Description

    TH: School Enrollment: Primary: % Gross data was reported at 100.586 % in 2015. This records a decrease from the previous number of 102.031 % for 2014. TH: School Enrollment: Primary: % Gross data is updated yearly, averaging 97.009 % from Dec 1971 (Median) to 2015, with 44 observations. The data reached an all-time high of 102.031 % in 2014 and a record low of 82.380 % in 1978. TH: School Enrollment: Primary: % Gross data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Thailand – Table TH.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. Primary education provides children with basic reading, writing, and mathematics skills along with an elementary understanding of such subjects as history, geography, natural science, social science, art, and music.; ; 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).

  16. Top EdTech tools used in K-12 schools U.S. SY 2023-24

    • statista.com
    Updated Dec 10, 2024
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    Statista (2024). Top EdTech tools used in K-12 schools U.S. SY 2023-24 [Dataset]. https://www.statista.com/statistics/1447234/top-edtech-tools-used-in-k-12-schools-us/
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    Dataset updated
    Dec 10, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Sep 1, 2023 - May 31, 2024
    Area covered
    United States
    Description

    In the 2023-24 school year, sites and resources were the most accessed educational technology (EdTech) solution for K-12 students and teachers in the United States, at 15 percent, followed by supplemental platforms. Supplemental platforms, generally used for individual learning, may be used to access online activities, creation, research, and games to aid learning.

  17. U.S. teens (16-19) who are enrolled in school and working 1985-2022

    • statista.com
    • ai-chatbox.pro
    Updated Oct 21, 2024
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    Statista (2024). U.S. teens (16-19) who are enrolled in school and working 1985-2022 [Dataset]. https://www.statista.com/statistics/477668/percentage-of-youth-who-are-enrolled-in-school-and-working-in-the-us/
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    Dataset updated
    Oct 21, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2022, around 20.3 percent of teenagers between ages 16 and 19 were employees while enrolled at school in the United States. This is an increase from the previous year, when 19.4 percent of teenagers were working while in school.

  18. Education Industry Data | Education Professionals Worldwide Contact Data |...

    • datarade.ai
    Updated Oct 27, 2021
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    Success.ai (2021). Education Industry Data | Education Professionals Worldwide Contact Data | Verified Work Emails for Educators & Administrators | Best Price Guaranteed [Dataset]. https://datarade.ai/data-products/education-industry-data-education-professionals-worldwide-c-success-ai
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    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Oct 27, 2021
    Dataset provided by
    Area covered
    Guam, Botswana, Christmas Island, Papua New Guinea, Honduras, Malta, Bermuda, Ethiopia, Antarctica, Slovakia
    Description

    Success.ai’s Education Industry Data with B2B Contact Data for Education Professionals Worldwide enables businesses to connect with educators, administrators, and decision-makers in educational institutions across the globe. With access to over 170 million verified professional profiles, this dataset includes crucial contact details for key education professionals, including school principals, department heads, and education directors.

    Whether you’re targeting K-12 educators, university faculty, or educational administrators, Success.ai ensures your outreach is effective and efficient, providing the accurate data needed to build meaningful connections.

    Why Choose Success.ai’s Education Professionals Data?

    1. Comprehensive Contact Information
    2. Access verified work emails, direct phone numbers, and LinkedIn profiles for educators, administrators, and education leaders worldwide.
    3. AI-driven validation guarantees 99% accuracy, ensuring the highest level of reliability for your outreach.

    4. Global Reach Across Educational Roles

    5. Includes profiles of K-12 teachers, university professors, education directors, and school administrators.

    6. Covers regions such as North America, Europe, Asia-Pacific, South America, and the Middle East.

    7. Continuously Updated Datasets

    8. Real-time updates ensure that you’re working with the most current contact information, keeping your outreach relevant and timely.

    9. Ethical and Compliant

    10. Success.ai’s data is fully GDPR, CCPA, and privacy regulation-compliant, ensuring ethical data usage in all your outreach efforts.

    Data Highlights:

    • 170M+ Verified Professional Profiles: Includes educators and administrators across various levels of education.
    • 50M Work Emails: Verified and AI-validated emails for seamless communication.
    • 30M Company Profiles: Rich insights into educational institutions, supporting detailed targeting.
    • 700M Global Professional Profiles: Enriched datasets for comprehensive outreach across the education sector.

    Key Features of the Dataset:

    1. Education Decision-Maker Profiles
    2. Identify and connect with decision-makers at educational institutions, including principals, department heads, and education directors.
    3. Reach K-12 educators, higher education faculty, and administrative professionals with relevant needs.

    4. Advanced Filters for Precision Targeting

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  19. Public schools in the U.S. - share reporting incidents of crime 2022

    • statista.com
    Updated Jul 5, 2024
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    Statista (2024). Public schools in the U.S. - share reporting incidents of crime 2022 [Dataset]. https://www.statista.com/statistics/183638/incidents-of-crime-at-public-schools-by-type-of-crime/
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    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021 - 2022
    Area covered
    United States
    Description

    In the 2021-2022 school year, 35.8 percent of surveyed public schools recorded an incident of vandalism in the United States. In comparison, 20.2 percent recorded a theft and 4.2 percent recorded a robbery, with or without a weapon.

  20. High School and Beyond

    • catalog.data.gov
    • gimi9.com
    • +1more
    Updated Aug 13, 2023
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    National Center for Education Statistics (NCES) (2023). High School and Beyond [Dataset]. https://catalog.data.gov/dataset/high-school-and-beyond-e9284
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    Dataset updated
    Aug 13, 2023
    Dataset provided by
    National Center for Education Statisticshttps://nces.ed.gov/
    Description

    High School and Beyond (HS&B) is a study that is part of the Longitudinal Studies Branch (LSB) program; program data is available since 1980 at https://nces.ed.gov/pubsearch/getpubcats.asp?sid=022. HS&B (https://nces.ed.gov/surveys/hsb/) is a longitudinal survey. HS&B survey included two cohorts: the 1980 senior class, and the 1980 sophomore class. Both cohorts were surveyed every two years through 1986, and the 1980 sophomore class was also surveyed again in 1992.

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National Center for Education Statistics (NCES) (2024). School District Characteristics - Current [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/school-district-characteristics-current-f96a2
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School District Characteristics - Current

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6 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Oct 21, 2024
Dataset provided by
National Center for Education Statisticshttps://nces.ed.gov/
Description

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:-1 or MIndicates that the data are missing.-2 or NIndicates that the data are not applicable.-9Indicates that the data do not meet NCES data quality standards.Collections are available for the following years:2022-232021-222020-212019-202018-192017-18All 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.

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