100+ datasets found
  1. d

    Media Advisories--Department of Education

    • catalog.data.gov
    • datasets.ai
    • +1more
    Updated Aug 13, 2023
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    Office of Communications and Outreach (OCO) (2023). Media Advisories--Department of Education [Dataset]. https://catalog.data.gov/dataset/media-advisories-department-of-education
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    Dataset updated
    Aug 13, 2023
    Dataset provided by
    Office of Communications and Outreach (OCO)
    Description

    Archived: This page provides the most recent media advisories from the US Department of Education.

  2. How higher education (HE) statistics are used

    • gov.uk
    Updated Jul 31, 2009
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    Department for Business, Innovation & Skills (2009). How higher education (HE) statistics are used [Dataset]. https://www.gov.uk/government/statistics/how-he-statistics-are-used
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    Dataset updated
    Jul 31, 2009
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Business, Innovation & Skills
    Description

    The Department for Business, Innovation and Skills (BIS)

    The key statistic in the “Participation Rates in Higher Education” Statistical First Release (SFR) is the Higher Education Initial Participation Rate (HEIPR).

    HEIPR was used by BIS (and former Departments) and Her Majesty’s Treasury to track progress on the former Skills PSA target to “Increase participation in Higher Education towards 50 per cent of those aged 18 to 30, with growth of at least a percentage point every two years to the academic year 2010-11”. For example, it was reported in the http://www.bis.gov.uk/assets/biscore/corporate/migratedD/publications/D/DIUS-Annual%20Report-2009">Departmental annual report.

    HEIPR has been quoted in http://www.parliament.the-stationery-office.co.uk/pa/cm200809/cmselect/cmpubacc/226/22605.htm">Public Accounts Committees around increasing and widening participation in higher education

    HEIPR has been quoted extensively by the http://news.bbc.co.uk/1/hi/education/8596504.stm">Press

    BIS receives enquiries (including Freedom of Information (FoI) requests) from the public about HEIPR, including from the following groups:

    • academic researchers
    • higher education sector
    • local authorities - students
    • Members of Parliament (via Parliamentary Questions).

    The Higher Education Statistics Agency (HESA)

    Figures in the HESA SFRs are high profile and are frequently used in the press and other external publications to illustrate: trends in university entry and graduation, often in the context of current higher education policies; graduate employment/unemployment rates, average salaries, and job quality. Members of the public also often request these figures. Some examples of media coverage are included below:

    Higher Education student enrolments and qualifications

    Destinations of leavers from Higher Education

    These statistical outputs are not used to measure progress on any government targets, but the data that underpin them are of importance to funding bodies, Higher Education Institutions, and potential students:

    Potential Students – sources such as the http://unistats.direct.gov.uk/">Unistats website use qualifier and graduate employment information to inform students when they are making their choice of what course to study and at which university.

    Figures from the HESA statistical outputs are often u

  3. US Department of Education ED Data Express Data Library ZIP Files and Index,...

    • datalumos.org
    delimited
    Updated Feb 14, 2025
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    United States Department of Education. Institute of Education Sciences (2025). US Department of Education ED Data Express Data Library ZIP Files and Index, School Years 2010-2011 to 2021-2022 [Dataset]. http://doi.org/10.3886/E219487V1
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    delimitedAvailable download formats
    Dataset updated
    Feb 14, 2025
    Dataset provided by
    United States Department of Educationhttps://ed.gov/
    Institute of Education Scienceshttp://ies.ed.gov/
    Authors
    United States Department of Education. Institute of Education Sciences
    License

    https://creativecommons.org/share-your-work/public-domain/pdmhttps://creativecommons.org/share-your-work/public-domain/pdm

    Area covered
    United States of America
    Description

    This collection comprises unaltered data files downloaded from https://eddataexpress.ed.gov/download/data-library on February 6, 2025. The original access page consisted of a table with category filters, which provided links to data ZIP files containing the specified data fields. This table has been saved into tabular data formats here in the Index folder, with the original web links replaced with the matching ZIP filename only, which essentially replicates the functionality of the original web page in a downloadable format.In the website's underlying file structure, the original ZIP files were nested within folders named according to the format EID_####, apparently to avoid conflicts between files with the same name. These seeming duplications might have been due to updates or revisions that had to be made to a data file. To preserve this original order, the ZIP files were renamed by appending the EID number to their original file name. The files were not otherwise unzipped or altered in any way from their original state.At the time of download, the page at https://eddataexpress.ed.gov/download/data-library displayed the following two notices in red:"The COVID-19 pandemic disrupted the collection and reporting of data on EDE, beginning in SY 2019-20. The Department urges abundant caution when using the data and recommends reviewing the relevant data notes prior to use or interpretation. This includes data on state assessments, graduation rates, and chronic absenteeism.""WARNING: The data library functionality has stopped working temporarily for many SY2122 school files. Please go to the download tool page to download your data of interest. We apologize for the inconvenience."--------------------The "About Us" page from the ED Data Express website had this to say about its resources:Purpose of ED Data ExpressED Data Express is a website designed to improve the public's ability to access and explore high-value state- and district-level education data collected by the U.S. Department of Education. The site is designed to be interactive and to present the data in a clear, easy-to-use manner, with options to download information into Excel or to explore the data within the site's grant program dashboards. The site currently includes data from EDFacts, Consolidated State Performance Reports (CSPR), and the Department's Budget Service office. For more information about these topics, please visit the following web pages:https://www2.ed.gov/about/inits/ed/edfacts/index.html [see below for the text of the linked page]https://www2.ed.gov/about/offices/list/om/fs_po/ofo/budget-service.html [this URL was dead at the time of download]Using the SiteED Data Express includes two sections that allow users to access and view the data: (1) grant program data dashboards and (2) download functionality. The grant program data dashboards provide a snapshot of information on the funding, participation and performance of some of the grant programs administered by the U.S. Department of Education's Office of Elementary and Secondary Education. The dashboards are interactive and update depending on the program, state and school year selected. Additional information is provided through data notes as well as through the small "i" icon. The download functionality allows users to build customized tables of data and contain more data than what is available via the dashboards. The download functionality also allows users to download data notes which provide important caveats and contextual information to consider when using the data. Data Included and Frequency of UpdatesThe site currently includes funding, participation and performance data from school years 2010-11 to 2016-17 on formula grant programs administered in the Office of Elementary and Secondary Education. Additional data and data notes will be added to the site over time. Quality Control and Personally Identifiable InformationAll CSPR and EDFacts data are self-reported by each state. The U.S. Department of Education conducts a review of the data and provides feedback to states, but it is ultimately states’ responsibility to verify and certify that their data are correct. Please note that during the reporting years represented on this site, the Office of Elementary and Secondary Education in collaboration with EDFacts and SEAs have wor

  4. p

    Trends in White Student Percentage (2009-2023): Office Of Education...

    • publicschoolreview.com
    Updated Oct 26, 2025
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    Public School Review (2025). Trends in White Student Percentage (2009-2023): Office Of Education Department Of Children And Families School District vs. New Jersey [Dataset]. https://www.publicschoolreview.com/new-jersey/office-of-education-department-of-children-and-families-school-district/3400085-school-district
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    Dataset updated
    Oct 26, 2025
    Dataset authored and provided by
    Public School Review
    License

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

    Area covered
    New Jersey
    Description

    This dataset tracks annual white student percentage from 2009 to 2023 for Office Of Education Department Of Children And Families School District vs. New Jersey

  5. d

    U.S. Department of Education Budget History

    • catalog.data.gov
    • s.cnmilf.com
    Updated Aug 13, 2023
    + more versions
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    Office of Finance and Operations (OFO) (2023). U.S. Department of Education Budget History [Dataset]. https://catalog.data.gov/dataset/u-s-department-of-education-budget-history
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    Dataset updated
    Aug 13, 2023
    Dataset provided by
    Office of Finance and Operations (OFO)
    Area covered
    United States
    Description

    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.

  6. p

    Trends in Overall School Rank (2010-2021): Office Of Education Department Of...

    • publicschoolreview.com
    Updated Oct 26, 2025
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    Public School Review (2025). Trends in Overall School Rank (2010-2021): Office Of Education Department Of Children And Families School District [Dataset]. https://www.publicschoolreview.com/new-jersey/office-of-education-department-of-children-and-families-school-district/3400085-school-district
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    Dataset updated
    Oct 26, 2025
    Dataset authored and provided by
    Public School Review
    License

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

    Description

    This dataset tracks annual overall district rank from 2010 to 2021 for Office Of Education Department Of Children And Families School District

  7. p

    Trends in Reading and Language Arts Proficiency (2010-2021): Office Of...

    • publicschoolreview.com
    Updated Oct 26, 2025
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    Public School Review (2025). Trends in Reading and Language Arts Proficiency (2010-2021): Office Of Education Department Of Children And Families School District vs. New Jersey [Dataset]. https://www.publicschoolreview.com/new-jersey/office-of-education-department-of-children-and-families-school-district/3400085-school-district
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    Dataset updated
    Oct 26, 2025
    Dataset authored and provided by
    Public School Review
    License

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

    Area covered
    New Jersey
    Description

    This dataset tracks annual reading and language arts proficiency from 2010 to 2021 for Office Of Education Department Of Children And Families School District vs. New Jersey

  8. School Learning Modalities, 2021-2022

    • datahub.hhs.gov
    • data.virginia.gov
    • +5more
    csv, xlsx, xml
    Updated Jan 6, 2023
    + more versions
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    Centers for Disease Control and Prevention (2023). School Learning Modalities, 2021-2022 [Dataset]. https://datahub.hhs.gov/National/School-Learning-Modalities-2021-2022/aitj-yx37
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    xlsx, csv, xmlAvailable download formats
    Dataset updated
    Jan 6, 2023
    Dataset authored and provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description

    The 2021-2022 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 2021-2022 school year and the Fall 2022 semester, from August 2021 – December 2022.

    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 August 1, 2021 to June 24, 2022 correspond to the 2021-2022 school year. During this time frame, data from the AEI/Return to Learn Tracker and most state dashboards were not available. Inferred modalities with a probability below 0.6 were deemed inconclusive and were omitted. During the Fall 2022 semester, modalities for districts with a school closure reported by Burbio were updated to either “Remote”, if the closure spanned the entire week, or “Hybrid”, if the closure spanned 1-4 days of the week.
      • Data from August 1, 2022 to December 31, 2022 correspond to the 2022-2023 school year and were processed in a similar manner to data from the 2021-2022 school year.
      • 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

  9. M

    School Program Locations, Minnesota, SY2025-26

    • gisdata.mn.gov
    ags_mapserver, csv +5
    Updated Nov 19, 2025
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    Education Department (2025). School Program Locations, Minnesota, SY2025-26 [Dataset]. https://gisdata.mn.gov/dataset/struc-school-program-locs
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    csv, shp, fgdb, html, gpkg, jpeg, ags_mapserverAvailable download formats
    Dataset updated
    Nov 19, 2025
    Dataset provided by
    Education Department
    Area covered
    Minnesota
    Description

    This dataset attempts to represent the point locations of every educational program in the state of Minnesota that is currently operational and reporting to the Minnesota Department of Education. It can be used to identify schools, various individual school programs, school districts (by office location), colleges, and libraries, among other programs. Please note that not all school programs are statutorily required to report, and many types of programs can be reported at any time of the year, so this dataset is by nature an incomplete snapshot in time.

    Maintenance of these locations is a result of an ongoing project to identify current school program locations where Food and Nutrition Services Office (FNS) programs are utilized. The FNS Office is in the Minnesota Department of Education (MDE). GIS staff at MDE maintain the dataset using school program and physical addresses provided by local education authorities (LEAs) for an MDE database called "MDE ORG". MDE GIS staff track weekly changes to program locations, along with comprehensive reviews each summer. All records have been reviewed for accuracy or edited at least once since January 1, 2020.

    Note that there may remain errors due to the number of program locations and inconsistency in reporting from LEAs and other organizations. Some organization types (such as colleges and treatment programs) are not subject to annual reporting requirements, so various records included in this file may in fact be inactive or inaccurately located.

    Note that multiple programs may occur at the same location and are represented as separate records. For example, an elementary and secondary school may be in the same building, but each has a separate record in the data layer. Users may leverage the "CLASS" and "ORGTYPE" attributes to filter and sort records according to their needs. In general, records at the same physical address will be located at the same coordinates.

    This data is also available in CSV format. For that format only, OBJECTID and Shape columns are removed, and the Shape column is replaced by Latitude and Longitude columns.

  10. School Learning Modalities, 2020-2021

    • healthdata.gov
    • data.virginia.gov
    • +3more
    csv, xlsx, xml
    Updated Feb 27, 2023
    + more versions
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    Centers for Disease Control and Prevention (2023). School Learning Modalities, 2020-2021 [Dataset]. https://healthdata.gov/National/School-Learning-Modalities-2020-2021/a8v3-a3m3
    Explore at:
    csv, xml, xlsxAvailable download formats
    Dataset updated
    Feb 27, 2023
    Dataset authored and provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description

    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

  11. California School District Offices 2024-25

    • catalog.data.gov
    • hub.arcgis.com
    Updated Nov 23, 2025
    + more versions
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    California Department of Education (2025). California School District Offices 2024-25 [Dataset]. https://catalog.data.gov/dataset/california-school-district-offices-2024-25
    Explore at:
    Dataset updated
    Nov 23, 2025
    Dataset provided by
    California Department of Educationhttps://www.cde.ca.gov/
    Area covered
    California
    Description

    This layer serves as the authoritative geographic data source for all school district office locations in California. District office location and attribute information are derived from the California Department of Education"s (CDE) public schools and districts directory and district enrollment file.Since the school districts in this layer are represented as point locations instead of service areas, this layer includes additional district types that do not use geographically defined service areas to determine enrollment such as county offices of education, state special schools and State Board of Education (SBE) charter schools. In order to view districts represented as service area polygons, please see the "California School District Areas" layer.The school district enrollment and demographic information are based on the 2023-24 academic year student enrollment counts collected on Fall Census Day in 2023 (first Wednesday in October). These data elements are collected by the CDE through the California Longitudinal Achievement System (CALPADS) and can be accessed as a downloadable file from the Census Day Enrollment File page on the CDE website.District records are assigned X, Y coordinates using a quality controlled geocoding and validation process to optimize positional accuracy. Most district offices are mapped to the office structure or centroid of the district office property parcel and are individually verified using aerial imagery or assessor"s parcels databases. Districts are assigned various geographic area values based on their mapped locations including state and federal legislative district identifiers and National Center for Education Statistics (NCES) locale codes.

  12. School District Office Locations - Current

    • catalog.data.gov
    • s.cnmilf.com
    Updated Oct 21, 2024
    + more versions
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    National Center for Education Statistics (NCES) (2024). School District Office Locations - Current [Dataset]. https://catalog.data.gov/dataset/school-district-office-locations-current-c8f9d
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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 point locations (latitude and longitude) for public elementary, secondary, unified, and supervisory school district administrative offices included in the NCES Common Core of Data (CCD). The CCD is an annual collection of basic administrative characteristics that includes the physical address for all public schools, school districts, and state education agencies in the United States. For more information about NCES school point data, see: https://nces.ed.gov/programs/edge/Geographic/SchoolLocations. Collections are available for the following years: 2022-232021-22 2020-21 2019-20 2018-19 2017-18 2016-17 2015-16 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.

  13. p

    Trends in Diversity Score (2009-2023): Office Of Education Department Of...

    • publicschoolreview.com
    Updated Oct 26, 2025
    + more versions
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    Public School Review (2025). Trends in Diversity Score (2009-2023): Office Of Education Department Of Children And Families School District vs. New Jersey [Dataset]. https://www.publicschoolreview.com/new-jersey/office-of-education-department-of-children-and-families-school-district/3400085-school-district
    Explore at:
    Dataset updated
    Oct 26, 2025
    Dataset authored and provided by
    Public School Review
    License

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

    Area covered
    New Jersey
    Description

    This dataset tracks annual diversity score from 2009 to 2023 for Office Of Education Department Of Children And Families School District vs. New Jersey

  14. Education Marketing Data | Verified Contact Data for Educational...

    • datarade.ai
    Updated Oct 27, 2021
    + more versions
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    Success.ai (2021). Education Marketing Data | Verified Contact Data for Educational Institutions | Best Price Guaranteed [Dataset]. https://datarade.ai/data-providers/success-ai/data-products/education-marketing-data-verified-contact-data-for-educatio-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Oct 27, 2021
    Dataset provided by
    Area covered
    Tonga, United Arab Emirates, Turks and Caicos Islands, Costa Rica, Mexico, Svalbard and Jan Mayen, France, Guinea-Bissau, Dominica, Saint Vincent and the Grenadines
    Description

    Success.ai’s Education Marketing Data offers businesses and organizations direct access to verified contact details for educators, administrators, and marketing professionals in the education sector. Sourced from over 170 million verified professional profiles, this dataset includes work emails, direct phone numbers, and LinkedIn profiles, ensuring precise and meaningful connections with decision-makers at schools, universities, training centers, and educational service providers. By using continuously updated and AI-validated data, Success.ai empowers you to engage with the right contacts and drive targeted marketing campaigns, recruitment efforts, and partnership opportunities within the education landscape.

    Why Choose Success.ai’s Education Marketing Data?

    1. Comprehensive Contact Information

      • Access verified work emails, direct phone numbers, and social profiles of school administrators, university professors, department heads, and education marketers.
      • AI-driven validation ensures 99% accuracy, enabling confident outreach and reducing wasted efforts.
    2. Global Reach Across Education Segments

      • Includes contacts from K-12 schools, higher education institutions, vocational training centers, e-learning platforms, and professional certification organizations.
      • Covers regions including North America, Europe, Asia-Pacific, South America, and the Middle East, ensuring a broad spectrum of educational institutions and markets.
    3. Continuously Updated Datasets

      • Real-time updates guarantee that your contact data remains current, reflecting changes in roles, institutional structures, and academic priorities.
    4. Ethical and Compliant

      • Adheres to GDPR, CCPA, and other global privacy regulations, ensuring your outreach is both ethical and legally compliant.

    Data Highlights:

    • 170M+ Verified Professional Profiles: Includes education sector leaders, influencers, and key decision-makers.
    • 50M Work Emails: AI-validated for seamless communication and reduced bounce rates.
    • 30M Company (Institution) Profiles: Gain insights into school types, program offerings, and organizational structures.
    • 700M Global Professional Profiles: Enriched datasets to support market analysis, competitive benchmarking, and strategic planning.

    Key Features of the Dataset:

    1. Education Decision-Maker Profiles

      • Identify and connect with principals, superintendents, deans, admissions directors, marketing managers, and department heads shaping curriculum, enrollment, and academic initiatives.
    2. Advanced Filters for Precision Targeting

      • Filter by institution type, geographic region, academic level, specialty programs, or job function to refine your outreach and campaigns.
      • Tailor messaging to align with unique educational needs, cultural contexts, and policy frameworks.
    3. AI-Driven Enrichment

      • Profiles are enriched with actionable data, offering insights into institutional priorities, enrollment trends, and academic focal points, enabling more personalized and effective engagement.

    Strategic Use Cases:

    1. Marketing and Enrollment Campaigns

      • Target admissions and marketing professionals at universities, colleges, and language schools to promote your educational products, tutoring services, or learning management systems.
      • Craft campaigns that resonate with educators’ challenges, such as student retention, curriculum innovation, or digital learning adoption.
    2. EdTech and Resource Partnerships

      • Connect with decision-makers evaluating new technologies, software platforms, and resource providers to enhance teaching and learning experiences.
      • Position your EdTech solutions to solve institutional pain points like remote learning effectiveness or data-driven student success strategies.
    3. Academic Collaboration and Research

      • Identify contacts in academic research, curriculum development, or accreditation bodies to foster partnerships, co-develop programs, or share research findings.
      • Engage with administrators overseeing funding, grants, and educational policy to influence institutional decision-making.
    4. Recruitment and Talent Acquisition

      • Find HR professionals and department heads seeking qualified instructors, administrative staff, or specialized educators.
      • Offer recruitment and professional development services to institutions aiming to attract top-tier academic talent.

    Why Choose Success.ai?

    1. Best Price Guarantee

      • Access top-quality verified data at competitive prices, ensuring cost-effective growth and strategic advantage in education-focused outreach.
    2. Seamless Integration

      • Integrate verified contact data into your CRM or marketing automation tools using APIs or downloadable formats for efficient data management.
    3. Data Accuracy with AI Validation

      • Rely on 99% accuracy to inform decisions, refine targeting, and enhance campai...
  15. p

    Trends in Math Proficiency (2010-2021): Office Of Education Department Of...

    • publicschoolreview.com
    Updated Oct 26, 2025
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    Public School Review (2025). Trends in Math Proficiency (2010-2021): Office Of Education Department Of Children And Families School District vs. New Jersey [Dataset]. https://www.publicschoolreview.com/new-jersey/office-of-education-department-of-children-and-families-school-district/3400085-school-district
    Explore at:
    Dataset updated
    Oct 26, 2025
    Dataset authored and provided by
    Public School Review
    License

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

    Area covered
    New Jersey
    Description

    This dataset tracks annual math proficiency from 2010 to 2021 for Office Of Education Department Of Children And Families School District vs. New Jersey

  16. Education Directory

    • data.ct.gov
    • catalog.data.gov
    • +2more
    csv, xlsx, xml
    Updated Apr 1, 2024
    + more versions
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    Connecticut State Department of Education (CSDE) (2024). Education Directory [Dataset]. https://data.ct.gov/Education/Education-Directory/9k2y-kqxn
    Explore at:
    xlsx, xml, csvAvailable download formats
    Dataset updated
    Apr 1, 2024
    Dataset provided by
    Connecticut State Department of Educationhttps://portal.ct.gov/sde
    Authors
    Connecticut State Department of Education (CSDE)
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    This dataset contains the official listing of all public educational organizations in Connecticut. Data elements include district name, school name, organization type, organization code, address, open date, interdistrict magnet status and grades offered.

    Included data are collected by the CT State Department of Education (CSDE) through the Directory Manager (DM) portal in accordance with Connecticut General Statute (C.G.S.) 10-4. This critical information is used by other data collection systems and for state and federal reporting.

    For more information regarding DM, please visit http://www.csde.state.ct.us/public/directorymanager/default.asp

  17. Civil Service HQ occupancy data

    • gov.uk
    • s3.amazonaws.com
    Updated Dec 1, 2025
    + more versions
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    Cabinet Office (2025). Civil Service HQ occupancy data [Dataset]. https://www.gov.uk/government/publications/civil-service-hq-occupancy-data
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    Dataset updated
    Dec 1, 2025
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Cabinet Office
    Description

    Details

    The Civil Service published weekly data on HQ Office Occupancy from Whitehall departments’ as a proxy measure of ‘return to offices’ following the pandemic. This was suspended in line with pre-election guidance for the duration of the Election Period. Going forward this data will now be published quarterly, resuming October 2024.

    Contacts

    Press enquiries: pressoffice@cabinetoffice.gov.uk

    Methodology

    The data was originally gathered for internal purposes to indicate the progress being made by departments in returning to the workplace in greater numbers. Data was collected in respect of Departmental HQ buildings to gain a general understanding of each department’s position without requiring departments to introduce data collection methods across their whole estate which would be expensive and resource intensive.

    These figures are representative of employees whose home location is their departmental HQ building. These figures do not include contractors and visitors. Departments providing data are listed below.

    All data presented is sourced and collected by departments and provided to the Cabinet Office. The data presented are not Official Statistics.

    There are four main methods used to collect the Daily Average Number of Employees in the HQ building:

    • wifi and/or computer log-ins associated with location
    • swipe pass entry data
    • space or desk booking system
    • manual count

    It is for departments to determine the most appropriate method of collection. This data does not capture employees working in other locations such as other government buildings, other workplaces or working from home.

    Notes on measure of attendance in the workplace

    The data provided is for Departmental HQ buildings only and inferences about the wider workforce cannot be made.

    Comparisons between departments

    The data should not be used to make comparisons between departments. The factors determining the numbers of employees working in the workplace will differ across departments, this is due to, the variation in operating models and the broad range of public services they deliver. The different data collection methods used by departments will also make comparisons between departments invalid.

    Calculations

    Percentage of employees working in the HQ building compared to building capacity is calculated by: Monthly total number of employees in the HQ building divided by the monthly capacity of the HQ building.

    Definitions

    In the majority of cases the HQ building is defined as where the Secretary of State for that department is based.

    Current Daily Capacity is the total number of people that can be accommodated in the building.

    Departments providing data

    • Cabinet Office
    • Department for Business and Trade
    • Department for Culture, Media and Sport
    • Department for Education
    • Department for Energy Security and Net Zero
    • Department for Environment, Food and Rural Affairs
    • Department of Health and Social Care
    • Department for Science, Innovation and Technology
    • Department for Transport
    • Department for Work and Pensions
    • Foreign, Commonwealth & Development Office
    • HM Revenue and Customs
    • HM Treasury
    • Home Office
    • Ministry of Defence
    • Ministry of Housing, Communities and Local Government
    • Ministry of Justice
    • Northern Ireland Office
    • Office of the Secretary of State for Scotland
    • Office of the Secretary of State for Wales
  18. p

    Trends in Black Student Percentage (2009-2023): Office Of Education...

    • publicschoolreview.com
    Updated Oct 26, 2025
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    Public School Review (2025). Trends in Black Student Percentage (2009-2023): Office Of Education Department Of Children And Families School District vs. New Jersey [Dataset]. https://www.publicschoolreview.com/new-jersey/office-of-education-department-of-children-and-families-school-district/3400085-school-district
    Explore at:
    Dataset updated
    Oct 26, 2025
    Dataset authored and provided by
    Public School Review
    License

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

    Area covered
    New Jersey
    Description

    This dataset tracks annual black student percentage from 2009 to 2023 for Office Of Education Department Of Children And Families School District vs. New Jersey

  19. a

    County of Board of Education Trustee Areas

    • maps-nevcounty.opendata.arcgis.com
    • hub.arcgis.com
    Updated Aug 13, 2020
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    County of Nevada, California (2020). County of Board of Education Trustee Areas [Dataset]. https://maps-nevcounty.opendata.arcgis.com/datasets/county-of-board-of-education-trustee-areas
    Explore at:
    Dataset updated
    Aug 13, 2020
    Dataset authored and provided by
    County of Nevada, California
    Area covered
    Description

    The Nevada County Board of Education has three Trustee Areas.The Nevada County Board of Education is the elected governing body of the Nevada County Office of Education. It’s five members serve four-year terms; are elected by voters in Nevada County; and represent different regions of the county. The primary responsibilities of the Nevada County Board of Education are to work with the Nevada County Superintendent of Schools to establish the direction and priorities for the Nevada County Office of Education through its budgetary determinations and to provide leadership to support the success of school districts in the county. In addition, supervisory oversight is provided for any charter school whose petition was accepted by the county office of education.Source: https://nevco.org/nevada-county-board-of-education/Questions about the Board of Education can be emailed to Samie White (Assistant to the Superintendent/Board Secretary): swhite@nevco.org

  20. p

    Trends in Two or More Races Student Percentage (2019-2021): Office Of...

    • publicschoolreview.com
    Updated Oct 26, 2025
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    Public School Review (2025). Trends in Two or More Races Student Percentage (2019-2021): Office Of Education Department Of Children And Families School District vs. New Jersey [Dataset]. https://www.publicschoolreview.com/new-jersey/office-of-education-department-of-children-and-families-school-district/3400085-school-district
    Explore at:
    Dataset updated
    Oct 26, 2025
    Dataset authored and provided by
    Public School Review
    License

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

    Area covered
    New Jersey
    Description

    This dataset tracks annual two or more races student percentage from 2019 to 2021 for Office Of Education Department Of Children And Families School District vs. New Jersey

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
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Office of Communications and Outreach (OCO) (2023). Media Advisories--Department of Education [Dataset]. https://catalog.data.gov/dataset/media-advisories-department-of-education

Media Advisories--Department of Education

Explore at:
Dataset updated
Aug 13, 2023
Dataset provided by
Office of Communications and Outreach (OCO)
Description

Archived: This page provides the most recent media advisories from the US Department of Education.

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