42 datasets found
  1. Per student expenditure on educational institutions in OECD countries 2020

    • statista.com
    Updated May 30, 2025
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    Statista (2025). Per student expenditure on educational institutions in OECD countries 2020 [Dataset]. https://www.statista.com/statistics/238733/expenditure-on-education-by-country/
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    Dataset updated
    May 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2020
    Area covered
    OECD
    Description

    Out of the OECD countries, Luxembourg was the country that spent the most on educational institutions per full-time student in 2020. On average, 23,000 U.S dollars were spent on primary education, nearly 27,000 U.S dollars on secondary education, and around 53,000 U.S dollars on tertiary education. The United States followed behind, with Norway in third. Meanwhile, the lowest spending was in Mexico.

  2. Global Primary Education Expenditure by Country, 2023

    • reportlinker.com
    Updated Apr 9, 2024
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    ReportLinker (2024). Global Primary Education Expenditure by Country, 2023 [Dataset]. https://www.reportlinker.com/dataset/95ce94d94f2cf1697942311d8cbe04bb9df7dcce
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    Dataset updated
    Apr 9, 2024
    Dataset provided by
    Reportlinker
    Authors
    ReportLinker
    License

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

    Description

    Global Primary Education Expenditure by Country, 2023 Discover more data with ReportLinker!

  3. m

    Initial government funding per pre-primary student, constant PPP$ - France

    • macro-rankings.com
    csv, excel
    Updated Dec 31, 2017
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    macro-rankings (2017). Initial government funding per pre-primary student, constant PPP$ - France [Dataset]. https://www.macro-rankings.com/france/initial-government-funding-per-pre-primary-student-constant-ppp$
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    csv, excelAvailable download formats
    Dataset updated
    Dec 31, 2017
    Dataset authored and provided by
    macro-rankings
    License

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

    Area covered
    France
    Description

    Time series data for the statistic Initial government funding per pre-primary student, constant PPP$ and country France. Indicator Definition:Total general (local, regional and central, current and capital) initial government funding of education per student, which includes transfers paid (such as scholarships to students), but excludes transfers received, in this case international transfers to government for education (when foreign donors provide education sector budget support or other support integrated in the government budget). Calculation Method: Total general (local, regional and central) government expenditure (current and capital) on a given level of education (primary, secondary, etc) minus international transfers to government for education, divided by the number of student enrolled at that level of education. This is then expressed at constant purchasing power parity (constant PPP$). Limitations: In some instances data on total government expenditure on education refers only to the Ministry of Education, excluding other ministries which may also spend a part of their budget on educational activities. There are also cases where it may not be possible to separate international transfers to government from general government expenditure on education, in which cases they have not been subtracted in the formula. For more information, consult the UNESCO Institute of Statistics website: http://www.uis.unesco.org/Education/

  4. Data from: Indian Students Abroad

    • kaggle.com
    Updated Jan 5, 2023
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    The Devastator (2023). Indian Students Abroad [Dataset]. https://www.kaggle.com/datasets/thedevastator/number-of-indian-students-studying-abroad-in-201
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 5, 2023
    Dataset provided by
    Kaggle
    Authors
    The Devastator
    Description

    Indian Students Abroad

    Country-wise Statistics

    By Harish Kumar Garg [source]

    About this dataset

    This dataset is about the number of Indian students studying abroad in different countries and the detailed information about different nations where Indian students are present. The data has been complied from the Ministry Of External Affairs to answer a question from the Member of Parliament regarding how many students from India are studying in foreign countries and which country. This dataset includes two fields, Country Name and Number of Indians Studying Abroad as of Mar 2017, giving a unique opportunity to track student mobility across various nations around the world. With this valuable data about student mobility, we can gain insights into how educational opportunities for Indian students have increased over time as well as look at trends in international education throughout different regions. From comparison among countries with similar academic opportunities to tracking regional popularity among study destinations, this dataset provides important context for studying student migration patterns. We invite everyone to explore this data further and use it to draw meaningful conclusions!

    More Datasets

    For more datasets, click here.

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    How to use the dataset

    How to use this dataset?

    The data has two columns – Country Name and Number of Indians studying there as of March 2017. It also includes a third column, Percentage, which gives an indication about the proportion of Indian students enrolled in each country relative to total number enrolled abroad globally.

    To get started with your exploration, you can visualize the data against various parameters like geographical region or language speaking as it may provide more clarity about motives/reasons behind student’s choice. You can also group countries on basis of research opportunities available, cost consideration etc.,to understand deeper into all aspects that motivate Indians to explore further studies outside India.

    Additionally you can use this dataset for benchmarking purpose with other regional / international peer groups or aggregate regional / global reports with aim towards making better decisions or policies aiming greater outreach & support while targeting foreign universities/colleges for educational promotion activities that highlights engaging elements aimed at attracting more potential students from India aspiring higher international education experience abroad!

    Research Ideas

    • Using this dataset, educational institutions in India can set up international exchange programs with universities in other countries to facilitate and support Indian students studying abroad.
    • Higher Education Institutions can also understand the current trend of Indian students sourcing for opportunities to study abroad and use this data to build specialized short-term courses in collaboration with universities from different countries that cater to the needs of students who are interested in moving abroad permanently or even temporarily for higher studies.

    • Policy makers could use this data to assess the current trends and develop policies that aim at incentivizing international exposure among young professionals by commissioning fellowships or scholarships with an aim of exposing them to different problem sets around the world thereby making their profile more attractive while they look for better job opportunities globally

    Acknowledgements

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

    License

    Unknown License - Please check the dataset description for more information.

    Columns

    File: final_data.csv | Column name | Description | |:--------------------------|:-------------------------------------------------------------------------------------------------------------------------------| | Country | Name of the country where Indian students are studying. (String) | | No of Indian Students | Number of Indian students studying in the country. (Integer) | | Percentage | Percentage of Indian students studying in the country compared to the total number of Indian students studying abroad. (Float) |

    Acknowledgements

    If you use this dataset in your research, please credit ...

  5. g

    US Dept of Education, Expenditures Per Pupil in Public Elementary and...

    • geocommons.com
    Updated May 27, 2008
    + more versions
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    data (2008). US Dept of Education, Expenditures Per Pupil in Public Elementary and Secondary Education, USA, 2003-2004 [Dataset]. http://geocommons.com/search.html
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    Dataset updated
    May 27, 2008
    Dataset provided by
    data
    Description

    This dataset explores Total and current expenditures per pupil in fall enrollment in public elementary and secondary education, by function and state 2003 - 2004. NOTE: Excludes expenditures for state education agencies. "0" indicates none or less than $0.50. Some data have been revised from previously published figures. Detail may not sum to totals because of rounding. SOURCE: U.S. Department of Education, National Center for Education Statistics, Common Core of Data (CCD), "National Public Education Financial Survey," 200304. (This table was prepared August 2006.) http://nces.ed.gov/programs/digest/d06/tables/dt06_168.asp Accessed on 12 November 2007

  6. w

    Global Education Policy Dashboard 2019 - Jordan

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Nov 13, 2024
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    Sergio Venegas Marin (2024). Global Education Policy Dashboard 2019 - Jordan [Dataset]. https://microdata.worldbank.org/index.php/catalog/6407
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    Dataset updated
    Nov 13, 2024
    Dataset provided by
    Sergio Venegas Marin
    Reema Nayar
    Marta Carnelli
    Halsey Rogers
    Brian Stacy
    Time period covered
    2019 - 2020
    Area covered
    Jordan
    Description

    Abstract

    The dashboard project collects new data in each country using three new instruments: a School Survey, a Policy Survey, and a Survey of Public Officials. Data collection involves school visits, classroom observations, legislative reviews, teacher and student assessments, and interviews with teachers, principals, and public officials. In addition, the project draws on some existing data sources to complement the new data it collects. A major objective of the GEPD project was to develop focused, cost-effective instruments and data-collection procedures, so that the dashboard can be inexpensive enough to be applied (and re-applied) in many countries. The team achieved this by streamlining and simplifying existing instruments, and thereby reducing the time required for data collection and training of enumerators.

    Geographic coverage

    National

    Analysis unit

    Schools, teachers, students, public officials

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The aim of the Global Education Policy Dashboard school survey is to produce nationally representative estimates, which will be able to detect changes in the indicators over time at a minimum power of 80% and with a 0.05 significance level. We also wish to detect differences by urban/rural location.

    For our school survey, we will employ a two-stage random sample design, where in the first stage a sample of typically around 200 schools, based on local conditions, is drawn, chosen in advance by the Bank staff. In the second stage, a sample of teachers and students will be drawn to answer questions from our survey modules, chosen in the field. A total of 10 teachers will be sampled for absenteeism. Five teachers will be interviewed and given a content knowledge exam. Three 1st grade students will be assessed at random, and a classroom of 4th grade students will be assessed at random. Stratification will be based on the school’s urban/rural classification and based on region. When stratifying by region, we will work with our partners within the country to make sure we include all relevant geographical divisions.

    For our Survey of Public Officials, we will sample a total of 200 public officials. Roughly 60 officials are typically surveyed at the federal level, while 140 officials will be surveyed at the regional/district level. For selection of officials at the regional and district level, we will employ a cluster sampling strategy, where roughly 10 regional offices (or whatever the secondary administrative unit is called) are chosen at random from among the regions in which schools were sampled. Then among these 10 regions, we also typically select around 10 districts (tertiary administrative level units) from among the districts in which schools werer sampled. The result of this sampling approach is that for 10 clusters we will have links from the school to the district office to the regional office to the central office. Within the regions/districts, five or six officials will be sampled, including the head of organization, HR director, two division directors from finance and planning, and one or two randomly selected professional employees among the finance, planning, and one other service related department chosen at random. At the federal level, we will interview the HR director, finance director, planning director, and three randomly selected service focused departments. In addition to the directors of each of these departments, a sample of 9 professional employees will be chosen in each department at random on the day of the interview.

    Sampling deviation

    For our school survey, we select only schools that are supervised by the Minsitry or Education or are Private schools. No schools supervised by the Ministry of Defense, Ministry of Endowments, Ministry of Higher Education , or Ministry of Social Development are included. This left us with a sampling frame containing 3,330 schools, with 1297 private schools and 2003 schools managed by the Minsitry of Education. The schools must also have at least 3 grade 1 students, 3 grade 4 students, and 3 teachers. We oversampled Southern schools to reach a total of 50 Southern schools for regional comparisons. Additionally, we oversampled Evening schools, for a total of 40 evening schools.

    A total of 250 schools were surveyed.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    The dashboard project collects new data in each country using three new instruments: a School Survey, a Policy Survey, and a Survey of Public Officials. Data collection involves school visits, classroom observations, legislative reviews, teacher and student assessments, and interviews with teachers, principals, and public officials. In addition, the project draws on some existing data sources to complement the new data it collects. A major objective of the GEPD project was to develop focused, cost-effective instruments and data-collection procedures, so that the dashboard can be inexpensive enough to be applied (and re-applied) in many countries. The team achieved this by streamlining and simplifying existing instruments, and thereby reducing the time required for data collection and training of enumerators.

    More information pertaining to each of the three instruments can be found below:

    • School Survey: The School Survey collects data primarily on practices (the quality of service delivery in schools), but also on some de facto policy indicators. It consists of streamlined versions of existing instruments—including Service Delivery Surveys on teachers and inputs/infrastructure, Teach on pedagogical practice, Global Early Child Development Database (GECDD) on school readiness of young children, and the Development World Management Survey (DWMS) on management quality—together with new questions to fill gaps in those instruments. Though the number of modules is similar to the full version of the Service Delivery Indicators (SDI) Survey, the number of items and the complexity of the questions within each module is significantly lower. The School Survey includes 8 short modules: School Information, Teacher Presence, Teacher Survey, Classroom Observation, Teacher Assessment, Early Learner Direct Assessment, School Management Survey, and 4th-grade Student Assessment. For a team of two enumerators, it takes on average about 4 hours to collect all information in a given school. For more information, refer to the Frequently Asked Questions.

    • Policy Survey: The Policy Survey collects information to feed into the policy de jure indicators. This survey is filled out by key informants in each country, drawing on their knowledge to identify key elements of the policy framework (as in the SABER approach to policy-data collection that the Bank has used over the past 7 years). The survey includes questions on policies related to teachers, school management, inputs and infrastructure, and learners. In total, there are 52 questions in the survey as of June 2020. The key informant is expected to spend 2-3 days gathering and analyzing the relavant information to answer the survey questions.

    • Survey of Public Officials: The Survey of Public Officials collects information about the capacity and orientation of the bureaucracy, as well as political factors affecting education outcomes. This survey is a streamlined and education-focused version of the civil-servant surveys that the Bureaucracy Lab (a joint initiative of the Governance Global Practice and the Development Impact Evaluation unit of the World Bank) has implemented in several countries. The survey includes questions about technical and leadership skills, work environment, stakeholder engagement, impartial decision-making, and attitudes and behaviors. The survey takes 30-45 minutes per public official and is used to interview Ministry of Education officials working at the central, regional, and district levels in each country.

    Sampling error estimates

    The aim of the Global Education Policy Dashboard school survey is to produce nationally representative estimates, which will be able to detect changes in the indicators over time at a minimum power of 80% and with a 0.05 significance level.

  7. g

    NCES, Expenditure per Pupil in Public Secondary and Elementary Schools by...

    • geocommons.com
    Updated May 27, 2008
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    National Center for Educational Statistics (NCES) (2008). NCES, Expenditure per Pupil in Public Secondary and Elementary Schools by State, USA, 1959-60 through 2003-04 [Dataset]. http://geocommons.com/search.html
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    Dataset updated
    May 27, 2008
    Dataset provided by
    National Center for Educational Statistics (NCES)
    data
    Description

    This dataset explores Current expenditure per pupil in average daily attendance in public elementary and secondary schools, by state -- Selected years, 1959-60 through 2003-04 * Note - data is in unadjusted dollars http://nces.ed.gov/programs/digest/d06/tables/dt06_171.asp Accessed on 12 November 2007

  8. g

    US Census Bureau, Public School Expenditure, USA, 2004

    • geocommons.com
    Updated May 27, 2008
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    data (2008). US Census Bureau, Public School Expenditure, USA, 2004 [Dataset]. http://geocommons.com/search.html
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    Dataset updated
    May 27, 2008
    Dataset provided by
    data
    US Census Bureau
    Description

    This dataset shows school district expenditures. It is derived from US Census bureau's Public Elementary-Secondary Education Finance data for year 2004. It breaks down spending per student by expenditure on staff salaries and benefits, monies spent on general administration and other support services. Source: http://www.census.gov/www/school04.html Note: Value of zero indicates no data

  9. p

    Lake Country School District

    • publicschoolreview.com
    json, xml
    Updated Sep 21, 2025
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    Public School Review (2025). Lake Country School District [Dataset]. https://www.publicschoolreview.com/wisconsin/lake-country-school-district/5500013-school-district
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    json, xmlAvailable download formats
    Dataset updated
    Sep 21, 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

    Time period covered
    Jan 1, 1991 - Dec 31, 2025
    Area covered
    Lake Country School District
    Description

    Historical Dataset of Lake Country School District is provided by PublicSchoolReview and contain statistics on metrics:Comparison of Diversity Score Trends,Total Revenues Trends,Total Expenditure Trends,Average Revenue Per Student Trends,Average Expenditure Per Student Trends,Reading and Language Arts Proficiency Trends,Math Proficiency Trends,Science Proficiency Trends,Overall School District Rank Trends,American Indian Student Percentage Comparison Over Years (2013-2014),Asian Student Percentage Comparison Over Years (1992-2023),Hispanic Student Percentage Comparison Over Years (1996-2023),Black Student Percentage Comparison Over Years (2002-2023),White Student Percentage Comparison Over Years (1991-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Comparison of Students By Grade Trends

  10. p

    Copper Country Independent School District

    • publicschoolreview.com
    json, xml
    Updated Sep 21, 2025
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    Public School Review (2025). Copper Country Independent School District [Dataset]. https://www.publicschoolreview.com/michigan/copper-country-independent-school-district/2680505-school-district
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    json, xmlAvailable download formats
    Dataset updated
    Sep 21, 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

    Time period covered
    Jan 1, 1992 - Dec 31, 2025
    Description

    Historical Dataset of Copper Country Independent School District is provided by PublicSchoolReview and contain statistics on metrics:Comparison of Diversity Score Trends,Total Revenues Trends,Total Expenditure Trends,Average Revenue Per Student Trends,Average Expenditure Per Student Trends,Reading and Language Arts Proficiency Trends,Math Proficiency Trends,Science Proficiency Trends,Graduation Rate Trends,Overall School District Rank Trends,American Indian Student Percentage Comparison Over Years (1999-2023),Asian Student Percentage Comparison Over Years (1998-2023),Hispanic Student Percentage Comparison Over Years (1999-2023),Black Student Percentage Comparison Over Years (1992-2023),White Student Percentage Comparison Over Years (1992-2023),Two or More Races Student Percentage Comparison Over Years (2021-2023),Comparison of Students By Grade Trends

  11. p

    North Country Union Junior High School District

    • publicschoolreview.com
    json, xml
    Updated Feb 14, 2023
    + more versions
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    Public School Review (2023). North Country Union Junior High School District [Dataset]. https://www.publicschoolreview.com/vermont/north-country-union-junior-high-school-district/5009570-school-district
    Explore at:
    json, xmlAvailable download formats
    Dataset updated
    Feb 14, 2023
    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

    Time period covered
    Jan 1, 1993 - Dec 31, 2025
    Description

    Historical Dataset of North Country Union Junior High School District is provided by PublicSchoolReview and contain statistics on metrics:Comparison of Diversity Score Trends,Total Revenues Trends,Total Expenditure Trends,Average Revenue Per Student Trends,Average Expenditure Per Student Trends,Reading and Language Arts Proficiency Trends,Math Proficiency Trends,Science Proficiency Trends,Overall School District Rank Trends,American Indian Student Percentage Comparison Over Years (1993-2003),Asian Student Percentage Comparison Over Years (1995-2020),Hispanic Student Percentage Comparison Over Years (2000-2023),Black Student Percentage Comparison Over Years (1995-2023),White Student Percentage Comparison Over Years (1993-2023),Two or More Races Student Percentage Comparison Over Years (2009-2020),Comparison of Students By Grade Trends

  12. p

    Chico Country Day School District

    • publicschoolreview.com
    json, xml
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    Public School Review, Chico Country Day School District [Dataset]. https://www.publicschoolreview.com/california/chico-country-day-school-district/601665-school-district
    Explore at:
    xml, jsonAvailable download formats
    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

    Time period covered
    Jan 1, 2019 - Dec 31, 2025
    Area covered
    Chico
    Description

    Historical Dataset of Chico Country Day School District is provided by PublicSchoolReview and contain statistics on metrics:Comparison of Diversity Score Trends,Total Revenues Trends,Total Expenditure Trends,Average Revenue Per Student Trends,Average Expenditure Per Student Trends,Reading and Language Arts Proficiency Trends,Math Proficiency Trends,Science Proficiency Trends,Overall School District Rank Trends,American Indian Student Percentage Comparison Over Years (2019-2023),Asian Student Percentage Comparison Over Years (2019-2023),Hispanic Student Percentage Comparison Over Years (2019-2023),Black Student Percentage Comparison Over Years (2019-2023),White Student Percentage Comparison Over Years (2019-2023),Two or More Races Student Percentage Comparison Over Years (2019-2023),Comparison of Students By Grade Trends

  13. p

    Nord Country School District

    • publicschoolreview.com
    json, xml
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    Public School Review, Nord Country School District [Dataset]. https://www.publicschoolreview.com/california/nord-country-school-district/602014-school-district
    Explore at:
    json, xmlAvailable download formats
    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

    Time period covered
    Jan 1, 2019 - Dec 31, 2025
    Description

    Historical Dataset of Nord Country School District is provided by PublicSchoolReview and contain statistics on metrics:Comparison of Diversity Score Trends,Total Revenues Trends,Total Expenditure Trends,Average Revenue Per Student Trends,Average Expenditure Per Student Trends,Reading and Language Arts Proficiency Trends,Math Proficiency Trends,Science Proficiency Trends,Overall School District Rank Trends,American Indian Student Percentage Comparison Over Years (2019-2023),Asian Student Percentage Comparison Over Years (2021-2022),Hispanic Student Percentage Comparison Over Years (2019-2023),Black Student Percentage Comparison Over Years (2019-2022),White Student Percentage Comparison Over Years (2019-2023),Two or More Races Student Percentage Comparison Over Years (2019-2023),Comparison of Students By Grade Trends

  14. g

    NACCRRA, Head Start Allocation and State-Funded Prekindergarten...

    • geocommons.com
    Updated May 6, 2008
    + more versions
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    data (2008). NACCRRA, Head Start Allocation and State-Funded Prekindergarten Participation, USA, 2004 [Dataset]. http://geocommons.com/search.html
    Explore at:
    Dataset updated
    May 6, 2008
    Dataset provided by
    National Association of Child Care Resources and Referral Agencies
    data
    Description

    This dataset explores Early Care and Education Funding: Head Start Allocation and State-Funded Prekindergarten Participation. This data is state level and expresses the participation per state. Head Start and Early Head Start are comprehensive child development programs that serve children from birth to age 5, their families, and pregnant women. The overall goal of these programs is to increase the school readiness of young children in families earning low incomes. The Head Start program delivers comprehensive services including: education, health, nutrition, screening for developmental delays, and a variety of social services, if the family needs them. The program is designed to meet the social, emotional, physical and cognitive development of children. This data is from Latest Data: Fiscal Year 2004 (Head Start) and School Year 2002-2003 (State Funded Prekindergarten). This data is from National Child Care Information Center. Refer to NCCIC Child Care Database for detailed state information (http://nccic.org/IMS/Results.asp). Compiled by: National Association of Child Care Resources and Referral Agencies (http://www.naccrra.org/randd/head_start/expenditure.php)

  15. e

    Flash Eurobarometer 260 (Students and Higher Education Reform) - Dataset -...

    • b2find.eudat.eu
    Updated Aug 6, 2018
    + more versions
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    (2018). Flash Eurobarometer 260 (Students and Higher Education Reform) - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/40bce8f5-06b5-57f0-afef-c16cbdb57aaa
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    Dataset updated
    Aug 6, 2018
    Description

    Attitudes of students towards higher education. Topics: preference of selected statements: right of all qualified students to study vs. right only for very best students, admittance of all students to universities vs. right of universities to select, higher education free of charge vs. acceptability of student fees in combination with grants and loans; attitude towards the following statements on higher education institutions (HEIs): should provide more programmes for part time students, should promote activities to increase variety of social and cultural backgrounds of students, study programmes should focus on teaching specialized knowledge, study programmes should include generic competences; importance of each of the following purposes of higher education: provide students with skills to be successful on the labour market, enhance personal development, education for active citizenship; attitude towards selected statements regarding the choice of the institution where to study: choice on the basis of reputation of the institution and study programmes, choice on the basis of other factors (e.g. location, friends, cost, …), sufficient availability of information materials, need for quality reports on universities, need for performance rankings, involvement of students in quality reports and rankings; considerations to study abroad; importance of each of the following obstacles with regard to studying abroad: lack of information on study opportunities, lack of funds, difficulty to obtain recognition for periods spent abroad, different quality of education abroad, language barriers, lack of encouragement by home university; attitude towards the following statements: short study periods abroad are mostly recognised by home university, all study programmes should include short study periods abroad, most non-mobile students obtain ECTS credit points for studies completed at their institutions, most mobile students obtain ECTS credit points for studies abroad, possibility of work placements in private enterprises as part of study programme, importance for HEIs to foster innovation and entrepreneurial mindset among students and staff, provision of tailor-made study programmes for enterprises by HEIs, more involvement of enterprises in higher education; future plans after graduation. Demography: study institute; sex; age; country where upper secondary diploma was obtained; number of years in higher education; field of study; full time student; study status; obtainable degrees at institution. Additionally coded was: respondent ID; country; interviewer ID; language of the interview; date of interview; time of the beginning of the interview; duration of the interview; type of phone line; region. Einstellung von Studierenden zum Hochschulwesen. Ziele der Hochschulbildung. Kriterien der Studienortwahl. Auslandsstudium. Zusammenarbeit der Hochschule mit Unternehmen. Bachelor und Master. Themen: Einstellung zu einem Recht aller Abiturienten auf ein Studium oder nur der Allerbesten; Universitäten sollten ein Selektionsrecht haben; Akzeptanz von Studiengebühren; Zustimmung zu folgenden Aussagen (Skala): Hochschulen sollten mehr Programme für Teilzeitstudenten anbieten, Hochschulen sollten Studenten mit vielfältigem sozialen und kulturellen Hintergrund aufnehmen, Studienpläne sollten sich auf spezifisches Fachwissen oder auf die Vermittlung allgemeiner Kompetenzen konzentrieren; wichtigste Ziele der Hochschulbildung (Skala): Ausbildung für den Arbeitsmarkt, persönliche Entwicklung, Ausbildung zum aktiven Bürger; wichtigste Aspekte der Studienortwahl: erfolgt nach Ruf der Hochschule, nach Lage, in Hinblick auf Freunde und Kosten, unabhängige Berichte über die Qualität sowie Rankings über die Leistung von Universitäten dienen als Entscheidungshilfe, Mitarbeit von Studierenden bei der Erstellung von Qualitätsberichten und Rankings; beabsichtigtes Auslandsstudium; Hindernisse für ein Auslandsstudium (fehlende Informationen, Geldmangel, fehlende Möglichkeit der Leistungsanerkennung der bisherigen Studienzeit im Ausland, unterschiedliche Qualität der Bildung, Sprachbarrieren, keine Förderung durch Dozenten); Einstellung zum Auslandsstudium (Skala): Anerkennung kurzer Studienaufenthalte im Ausland durch die Heimatuniversität, Auslandstudium sollte Bestandteil eines jeden Studienplans sein, ECTS Credit Points für Kurse an eigener Hochschule und für Auslandsaufenthalte, Wunsch nach Praktika in Privatunternehmen als Teil des Studienplans, Wichtigkeit der universitären Förderung von Innovation und unternehmerischem Denken bei Studenten und Angestellten, Wunsch nach einem Angebot maßgeschneiderter Studienpläne für Unternehmen zur Förderung der Weiterleitung von Arbeitskräften; Unternehmen sollten stärker an Hochschulorganisation beteiligt sein; Zukunftspläne nach dem Abschluss des Studiums. Demographie: Einrichtung, an der der Befragte studiert; Geschlecht; Alter; Land, in dem Hochschulreife erlangt wurde; Studiendauer; Studienrichtung; Vollzeitstudent; Studienstatus; an der Universität vergebene Abschlüsse. Zusätzlich verkodet wurde: Befragten-ID; Land; Interviewer-ID; Interviewsprache; Interviewdatum; Interviewdauer (Interviewbeginn und Interviewende); Interviewmodus (Mobiltelefon oder Festnetz); Region. ProbabilityProbability WahrscheinlichkeitsauswahlProbability Face-to-face interview: Paper-and-pencil (PAPI)Interview.FaceToFace.PAPI Persönliches Interview : Papier-und-Bleistift (PAPI)Interview.FaceToFace.PAPI

  16. w

    Vietnam - Young Lives: School Survey 2011-2012 - Dataset - waterdata

    • wbwaterdata.org
    Updated Mar 16, 2020
    + more versions
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    (2020). Vietnam - Young Lives: School Survey 2011-2012 - Dataset - waterdata [Dataset]. https://wbwaterdata.org/dataset/vietnam-young-lives-school-survey-2011-2012
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    Dataset updated
    Mar 16, 2020
    License

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

    Area covered
    Vietnam
    Description

    The Young Lives survey is an innovative long-term project investigating the changing nature of childhood poverty in four developing countries. The purpose of the project is to improve understanding of the causes and consequences of childhood poverty and examine how policies affect children's well-being, in order to inform the development of future policy and to target child welfare interventions more effectively. The study is being conducted in Ethiopia, India (in Andhra Pradesh), Peru and Vietnam. These countries were selected because they reflect a range of cultural, geographical and social contexts and experience differing issues facing the developing world; high debt burden, emergence from conflict, and vulnerability to environmental conditions such as drought and flood. The Young Lives study aims to track the lives of 12,000 children over a 15-year period, surveyed once every 3-4 years. Round 1 of Young Lives surveyed two groups of children in each country, at 1 year old and 5 years old. Round 2 returned to the same children who were then aged 5 and 12 years old. Round 3 surveyed the same children again at aged 7-8 years and 14-15 years, and Round 4 surveyed them at 12 and 19 years old. Thus the younger children are being tracked from infancy to their mid-teens and the older children through into adulthood, when some will become parents themselves. The survey consists of three main elements: a child questionnaire, a household questionnaire and a community questionnaire. The household data gathered is similar to other cross-sectional datasets (such as the World Bank's Living Standards Measurement Study). It covers a range of topics such as household composition, livelihood and assets, household expenditure, child health and access to basic services, and education. This is supplemented with additional questions that cover caregiver perceptions, attitudes, and aspirations for their child and the family. Young Lives also collects detailed time-use data for all family members, information about the child's weight and height (and that of caregivers), and tests the children for school outcomes (language comprehension and mathematics). An important element of the survey asks the children about their daily activities, their experiences and attitudes to work and school, their likes and dislikes, how they feel they are treated by other people, and their hopes and aspirations for the future. The community questionnaire provides background information about the social, economic and environmental context of each community. It covers topics such as ethnicity, religion, economic activity and employment, infrastructure and services, political representation and community networks, crime and environmental changes. The Young Lives survey is carried out by teams of local researchers, supported by the Principal Investigator and Data Manager in each country. Further information about the survey, including publications, can be downloaded from the Young Lives website. School surveys were introduced into Young Lives in 2010 in order to capture detailed information about children's experiences of schooling, and to improve our understanding of: the relationships between learning outcomes, and children's home backgrounds, gender, work, schools, teachers and class and school peer-groups. school effectiveness, by analysing factors explaining the development of cognitive and non-cognitive skills in school, including value-added analysis of schooling and comparative analysis of school-systems. equity issues (including gender) in relation to learning outcomes and the evolution of inequalities within education The survey allows us to link longitudinal information on household and child characteristics from the household survey with data on the schools attended by the Young Lives children and children's achievements inside and outside the school. It provides policy-relevant information on the relationship between child development (and its determinants) and children's experience of school, including access, quality and progression. This combination of household, child and school-level data over time constitutes the comparative advantage of Young Lives. Findings are all available on our Education theme pages and our publications page. Further information is available from the Young Lives School Survey webpages.

  17. H

    Data from: Global School-based Student Health Survey (GSHS)

    • dataverse.harvard.edu
    • data.niaid.nih.gov
    • +1more
    Updated Feb 8, 2011
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    Harvard Dataverse (2011). Global School-based Student Health Survey (GSHS) [Dataset]. http://doi.org/10.7910/DVN/9J69TX
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 8, 2011
    Dataset provided by
    Harvard Dataverse
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Users can view and download data regarding youth health behaviors and risk factors from a variety of countries (including the United States). Background The Global School-based Student Health Survey is developed by the World Health Organization (WHO), the Centers for Disease Control and Prevention (CDC), UNICEF, UNAIDS and UNESCO. The survey is conducted in schools around the world and looks at the health behaviors of students. The information is used by countries to establish priorities and develop programs and by international agencies to make comparisons across countries to gain better understanding of the prevalence and trends of health behaviors.The core questionnaires are designed to gain understanding of the leading causes of mortality and morbidity world wide. The students are asked questions about alcohol and drug use, dietary behaviors, hygiene, mental health, physical activity, protective factors, sexual behaviors, tobacco use and violent behaviors. User Functionality From the website, users can view results by country. Many, but not all, countries have released copies of their questionnaire, fact sheets, full reports and their data. The data is available to download to SAS, Access, SPSS or ASCII. Data Notes The survey participants are between 13 and 15 years old. For some countries, the most recent report is from 2010 and the most recent data set available for download is from 2008. The site does not specify when the data sets will be updated.

  18. w

    Global Education Policy Dashboard 2022 - Sierra Leone

    • microdata.worldbank.org
    • datacatalog.ihsn.org
    • +1more
    Updated Nov 1, 2024
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    Adrien Ciret (2024). Global Education Policy Dashboard 2022 - Sierra Leone [Dataset]. https://microdata.worldbank.org/index.php/catalog/6401
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    Dataset updated
    Nov 1, 2024
    Dataset provided by
    Marie Helene Cloutier
    Adrien Ciret
    Sergio Venegas Marin
    Halsey Rogers
    Brian Stacy
    Time period covered
    2022
    Area covered
    Sierra Leone
    Description

    Abstract

    The dashboard project collects new data in each country using three new instruments: a School Survey, a Policy Survey, and a Survey of Public Officials. Data collection involves school visits, classroom observations, legislative reviews, teacher and student assessments, and interviews with teachers, principals, and public officials. In addition, the project draws on some existing data sources to complement the new data it collects. A major objective of the GEPD project was to develop focused, cost-effective instruments and data-collection procedures, so that the dashboard can be inexpensive enough to be applied (and re-applied) in many countries. The team achieved this by streamlining and simplifying existing instruments, and thereby reducing the time required for data collection and training of enumerators.

    Geographic coverage

    National

    Analysis unit

    Schools, teachers, students, public officials

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The aim of the Global Education Policy Dashboard school survey is to produce nationally representative estimates, which will be able to detect changes in the indicators over time at a minimum power of 80% and with a 0.05 significance level. We also wish to detect differences by urban/rural location. For our school survey, we will employ a two-stage random sample design, where in the first stage a sample of typically around 200 schools, based on local conditions, is drawn, chosen in advance by the Bank staff. In the second stage, a sample of teachers and students will be drawn to answer questions from our survey modules, chosen in the field. A total of 10 teachers will be sampled for absenteeism. Five teachers will be interviewed and given a content knowledge exam. Three 1st grade students will be assessed at random, and a classroom of 4th grade students will be assessed at random. Stratification will be based on the school’s urban/rural classification and based on region. When stratifying by region, we will work with our partners within the country to make sure we include all relevant geographical divisions. For our Survey of Public Officials, we will sample a total of 200 public officials. Roughly 60 officials are typically surveyed at the federal level, while 140 officials will be surveyed at the regional/district level. For selection of officials at the regional and district level, we will employ a cluster sampling strategy, where roughly 10 regional offices (or whatever the secondary administrative unit is called) are chosen at random from among the regions in which schools were sampled. Then among these 10 regions, we also typically select around 10 districts (tertiary administrative level units) from among the districts in which schools werer sampled. The result of this sampling approach is that for 10 clusters we will have links from the school to the district office to the regional office to the central office. Within the regions/districts, five or six officials will be sampled, including the head of organization, HR director, two division directors from finance and planning, and one or two randomly selected professional employees among the finance, planning, and one other service related department chosen at random. At the federal level, we will interview the HR director, finance director, planning director, and three randomly selected service focused departments. In addition to the directors of each of these departments, a sample of 9 professional employees will be chosen in each department at random on the day of the interview.

    Sampling deviation

    The sample for the Global Education Policy Dashboard in SLE was based in part on a previous sample of 260 schools which were part of an early EGRA study. Details from the sampling for that study are quoted below. An additional booster sample of 40 schools was chosen to be representative of smaller schools of less than 30 learners.

    EGRA Details:

    "The sampling frame began with the 2019 Annual School Census (ASC) list of primary schools as provided by UNICEF/MBSSE where the sample of 260 schools for this study were obtained from an initial list of 7,154 primary schools. Only schools that meet a pre-defined selection criteria were eligible for sampling.

    To achieve the recommended sample size of 10 learners per grade, schools that had an enrolment of at least 30 learners in Grade 2 in 2019 were considered. To achieve a high level of confidence in the findings and generate enough data for analysis, the selection criteria only considered schools that: • had an enrolment of at least 30 learners in grade 1; and • had an active grade 4 in 2019 (enrolment not zero)

    The sample was taken from a population of 4,597 primary schools that met the eligibility criteria above, representing 64.3% of all the 7,154 primary schools in Sierra Leone (as per the 2019 school census). Schools with higher numbers of learners were purposefully selected to ensure the sample size could be met in each site.

    As a result, a sample of 260 schools were drawn using proportional to size allocation with simple random sampling without replacement in each stratum. In the population, there were 16 districts and five school ownership categories (community, government, mission/religious, private and others). A total of 63 strata were made by forming combinations of the 16 districts and school ownership categories. In each stratum, a sample size was computed proportional to the total population and samples were drawn randomly without replacement. Drawing from other EGRA/EGMA studies conducted by Montrose in the past, a backup sample of up to 78 schools (30% of the sample population) with which enumerator teams can replace sample schools was also be drawn.

    In the distribution of sampled schools by ownership, majority of the sampled schools are owned by mission/religious group (62.7%, n=163) followed by the government owned schools at 18.5% (n=48). Additionally, in school distribution by district, majority of the sampled schools (54%) were found in Bo, Kambia, Kenema, Kono, Port Loko and Kailahun districts. Refer to annex 9. for details on the population and sample distribution by district."

    Because of the restriction that at least 30 learners were available in Grade 2, we chose to add an additional 40 schools to the sample from among smaller schools, with between 3 and 30 grade 2 students. The objective of this supplement was to make the sample more nationally representative, as the restriction reduced the sampling frame for the EGRA/EGMA sample by over 1,500 schools from 7,154 to 4,597.

    The 40 schools were chosen in a manner consistent with the original set of EGRA/EGMA schools. The 16 districts formed the strata. In each stratum, the number of schools selected were proportional to the total population of the stratum, and within stratum schools were chosen with probability proportional to size.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    The dashboard project collects new data in each country using three new instruments: a School Survey, a Policy Survey, and a Survey of Public Officials. Data collection involves school visits, classroom observations, legislative reviews, teacher and student assessments, and interviews with teachers, principals, and public officials. In addition, the project draws on some existing data sources to complement the new data it collects. A major objective of the GEPD project was to develop focused, cost-effective instruments and data-collection procedures, so that the dashboard can be inexpensive enough to be applied (and re-applied) in many countries. The team achieved this by streamlining and simplifying existing instruments, and thereby reducing the time required for data collection and training of enumerators.

    More information pertaining to each of the three instruments can be found below: - School Survey: The School Survey collects data primarily on practices (the quality of service delivery in schools), but also on some de facto policy indicators. It consists of streamlined versions of existing instruments—including Service Delivery Surveys on teachers and inputs/infrastructure, Teach on pedagogical practice, Global Early Child Development Database (GECDD) on school readiness of young children, and the Development World Management Survey (DWMS) on management quality—together with new questions to fill gaps in those instruments. Though the number of modules is similar to the full version of the Service Delivery Indicators (SDI) Survey, the number of items and the complexity of the questions within each module is significantly lower. The School Survey includes 8 short modules: School Information, Teacher Presence, Teacher Survey, Classroom Observation, Teacher Assessment, Early Learner Direct Assessment, School Management Survey, and 4th-grade Student Assessment. For a team of two enumerators, it takes on average about 4 hours to collect all information in a given school. For more information, refer to the Frequently Asked Questions.

    • Policy Survey: The Policy Survey collects information to feed into the policy de jure indicators. This survey is filled out by key informants in each country, drawing on their knowledge to identify key elements of the policy framework (as in the SABER approach to policy-data collection that the Bank has used over the past 7 years). The survey includes questions on policies related to teachers, school management, inputs and infrastructure, and learners. In total, there are 52 questions in the survey as of June 2020. The key informant is expected to spend 2-3 days gathering and analyzing the relavant information to answer the survey
  19. g

    National Center for Education Statistics (NCES), 8th Grade Writing Scores by...

    • geocommons.com
    Updated May 6, 2008
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    Department of Education, National Center for Education Statistics, Nations Report Card (2008). National Center for Education Statistics (NCES), 8th Grade Writing Scores by Achievement Level and State, USA, 1998-2007 [Dataset]. http://geocommons.com/search.html
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    Dataset updated
    May 6, 2008
    Dataset provided by
    data
    Department of Education, National Center for Education Statistics, Nations Report Card
    Description

    This dataset explores Achievement-level results in NAEP writing for eighth-grade public school students, by state: 1998, 2002, and 2007 Not available. The state/jurisdiction did not participate or did not meet the minimum participation guidelines for reporting. # Rounds to zero. * Significantly different (p < .05) from 2007 when only one state/jurisdiction or the nation is being examined. 1 National results for assessments prior to 2002 are based on the national sample, not on aggregated state samples. SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center for Education Statistics, National Assessment of Educational Progress (NAEP), 1998, 2002, and 2007 Writing Assessments.

  20. i

    Global Education Policy Dashboard 2020 - Rwanda

    • catalog.ihsn.org
    • microdata.worldbank.org
    Updated Nov 7, 2024
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    Sergio Venegas Marin (2024). Global Education Policy Dashboard 2020 - Rwanda [Dataset]. https://catalog.ihsn.org/catalog/12616
    Explore at:
    Dataset updated
    Nov 7, 2024
    Dataset provided by
    Sergio Venegas Marin
    Reema Nayar
    Marta Carnelli
    Halsey Rogers
    Brian Stacy
    Time period covered
    2020
    Area covered
    Rwanda
    Description

    Abstract

    The dashboard project collects new data in each country using three new instruments: a School Survey, a Policy Survey, and a Survey of Public Officials. Data collection involves school visits, classroom observations, legislative reviews, teacher and student assessments, and interviews with teachers, principals, and public officials. In addition, the project draws on some existing data sources to complement the new data it collects. A major objective of the GEPD project was to develop focused, cost-effective instruments and data-collection procedures, so that the dashboard can be inexpensive enough to be applied (and re-applied) in many countries. The team achieved this by streamlining and simplifying existing instruments, and thereby reducing the time required for data collection and training of enumerators.

    Geographic coverage

    National

    Analysis unit

    Schools, teachers, students, public officials

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The aim of the Global Education Policy Dashboard school survey is to produce nationally representative estimates, which will be able to detect changes in the indicators over time at a minimum power of 80% and with a 0.05 significance level. We also wish to detect differences by urban/rural location. For our school survey, we will employ a two-stage random sample design, where in the first stage a sample of typically around 200 schools, based on local conditions, is drawn, chosen in advance by the Bank staff. In the second stage, a sample of teachers and students will be drawn to answer questions from our survey modules, chosen in the field. A total of 10 teachers will be sampled for absenteeism. Five teachers will be interviewed and given a content knowledge exam. Three 1st grade students will be assessed at random, and a classroom of 4th grade students will be assessed at random. Stratification will be based on the school’s urban/rural classification and based on region. When stratifying by region, we will work with our partners within the country to make sure we include all relevant geographical divisions. For our Survey of Public Officials, we will sample a total of 200 public officials. Roughly 60 officials are typically surveyed at the federal level, while 140 officials will be surveyed at the regional/district level. For selection of officials at the regional and district level, we will employ a cluster sampling strategy, where roughly 10 regional offices (or whatever the secondary administrative unit is called) are chosen at random from among the regions in which schools were sampled. Then among these 10 regions, we also typically select around 10 districts (tertiary administrative level units) from among the districts in which schools were sampled. The result of this sampling approach is that for 10 clusters we will have links from the school to the district office to the regional office to the central office. Within the regions/districts, five or six officials will be sampled, including the head of organization, HR director, two division directors from finance and planning, and one or two randomly selected professional employees among the finance, planning, and one other service related department chosen at random. At the federal level, we will interview the HR director, finance director, planning director, and three randomly selected service focused departments. In addition to the directors of each of these departments, a sample of 9 professional employees will be chosen in each department at random on the day of the interview.

    Sampling deviation

    In order to visit two schools per day, we clustered at the sector level choosing two schools per cluster. With a sample of 200 schools, this means that we had to allocate 100 PSUs. We combined this clustering with stratification by district and by the urban rural status of the schools. The number of PSUs allocated to each stratum is proportionate to the number of schools in each stratum (i.e. the district X urban/rural status combination).

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    The dashboard project collects new data in each country using three new instruments: a School Survey, a Policy Survey, and a Survey of Public Officials. Data collection involves school visits, classroom observations, legislative reviews, teacher and student assessments, and interviews with teachers, principals, and public officials. In addition, the project draws on some existing data sources to complement the new data it collects. A major objective of the GEPD project was to develop focused, cost-effective instruments and data-collection procedures, so that the dashboard can be inexpensive enough to be applied (and re-applied) in many countries. The team achieved this by streamlining and simplifying existing instruments, and thereby reducing the time required for data collection and training of enumerators.

    More information pertaining to each of the three instruments can be found below: - School Survey: The School Survey collects data primarily on practices (the quality of service delivery in schools), but also on some de facto policy indicators. It consists of streamlined versions of existing instruments—including Service Delivery Surveys on teachers and inputs/infrastructure, Teach on pedagogical practice, Global Early Child Development Database (GECDD) on school readiness of young children, and the Development World Management Survey (DWMS) on management quality—together with new questions to fill gaps in those instruments. Though the number of modules is similar to the full version of the Service Delivery Indicators (SDI) Survey, the number of items and the complexity of the questions within each module is significantly lower. The School Survey includes 8 short modules: School Information, Teacher Presence, Teacher Survey, Classroom Observation, Teacher Assessment, Early Learner Direct Assessment, School Management Survey, and 4th-grade Student Assessment. For a team of two enumerators, it takes on average about 4 hours to collect all information in a given school. For more information, refer to the Frequently Asked Questions.

    • Policy Survey: The Policy Survey collects information to feed into the policy de jure indicators. This survey is filled out by key informants in each country, drawing on their knowledge to identify key elements of the policy framework (as in the SABER approach to policy-data collection that the Bank has used over the past 7 years). The survey includes questions on policies related to teachers, school management, inputs and infrastructure, and learners. In total, there are 52 questions in the survey as of June 2020. The key informant is expected to spend 2-3 days gathering and analyzing the relavant information to answer the survey questions.

    • Survey of Public Officials: The Survey of Public Officials collects information about the capacity and orientation of the bureaucracy, as well as political factors affecting education outcomes. This survey is a streamlined and education-focused version of the civil-servant surveys that the Bureaucracy Lab (a joint initiative of the Governance Global Practice and the Development Impact Evaluation unit of the World Bank) has implemented in several countries. The survey includes questions about technical and leadership skills, work environment, stakeholder engagement, impartial decision-making, and attitudes and behaviors. The survey takes 30-45 minutes per public official and is used to interview Ministry of Education officials working at the central, regional, and district levels in each country.

    Cleaning operations

    Data quality control was performed in R and Stata Code to calculate all indicators can be found on github here: https://github.com/worldbank/GEPD/blob/master/Countries/Rwanda/2019/School/01_data/03_school_data_cleaner.R

    Sampling error estimates

    The aim of the Global Education Policy Dashboard school survey is to produce nationally representative estimates, which will be able to detect changes in the indicators over time at a minimum power of 80% and with a 0.05 significance level.

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Statista (2025). Per student expenditure on educational institutions in OECD countries 2020 [Dataset]. https://www.statista.com/statistics/238733/expenditure-on-education-by-country/
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Per student expenditure on educational institutions in OECD countries 2020

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5 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
May 30, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2020
Area covered
OECD
Description

Out of the OECD countries, Luxembourg was the country that spent the most on educational institutions per full-time student in 2020. On average, 23,000 U.S dollars were spent on primary education, nearly 27,000 U.S dollars on secondary education, and around 53,000 U.S dollars on tertiary education. The United States followed behind, with Norway in third. Meanwhile, the lowest spending was in Mexico.

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