100+ datasets found
  1. w

    Global Education Policy Dashboard 2019 - Jordan

    • microdata.worldbank.org
    • catalog.ihsn.org
    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
    Halsey Rogers
    Reema Nayar
    Brian Stacy
    Sergio Venegas Marin
    Marta Carnelli
    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.

  2. Global survey on free education by country 2018

    • statista.com
    Updated Jul 7, 2025
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    Statista (2025). Global survey on free education by country 2018 [Dataset]. https://www.statista.com/statistics/858072/share-of-people-worldwide-who-agree-education-should-be-free-of-charge/
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    Dataset updated
    Jul 7, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 23, 2018 - Apr 6, 2018
    Area covered
    Worldwide
    Description

    This statistic shows the results of a 2018 survey conducted by Ipsos in ** countries around the world on socialism. During the survey, the respondents were asked if they agree or disagree with the notion that education should be free of charge in their country. This statistic only shows those respondents who somewhat or strongly agreed with this statement. Some ** percent of respondents in Russia agreed somewhat or strongly with this statement.

  3. Educational disruptions caused by the COVID-19 pandemic worldwide 2020-2022

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Educational disruptions caused by the COVID-19 pandemic worldwide 2020-2022 [Dataset]. https://www.statista.com/statistics/1345508/global-educational-disruptions-covid-19-world/
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    The COVID-19 pandemic had severe impacts on almost every aspect of life, from health via economy to education. School closures around the world caused disruptions in learning development of children and youth. South Asia as well as Latin America and the Caribbean had the highest number of weeks where schools were either partially or fully closed. In the former, a total of 84 weeks of education were conducted either partially or completely remote. On the other hand, Europe and Central Asia saw just above 30 weeks of some form of remote learning. Infrastructure and remote learning It may not come as a surprise, then, that South Asia and Latin America and the Caribbean were the two regions with the highest levels of learning delays caused by the COVID-19 pandemic. Moreover, different countries in different regions have different infrastructures that make remote learning possible. For instance, Sub-Saharan Africa, where many countries have a poor internet infrastructure, was the region with the highest number of academic weeks held in person as remote learning was impossible in many areas. Economic impact
    The learning disruptions caused by the pandemic could also have severe economic impacts in the future if counter measures are not taken. Estimates show that globally, *** trillion U.S. dollars of GDP could be lost annually by 2040 due to the educational disruptions caused by COVID-19.

  4. World Bank: Education Data

    • kaggle.com
    zip
    Updated Mar 20, 2019
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    World Bank (2019). World Bank: Education Data [Dataset]. https://www.kaggle.com/datasets/theworldbank/world-bank-intl-education
    Explore at:
    zip(0 bytes)Available download formats
    Dataset updated
    Mar 20, 2019
    Dataset authored and provided by
    World Bankhttp://worldbank.org/
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    The World Bank is an international financial institution that provides loans to countries of the world for capital projects. The World Bank's stated goal is the reduction of poverty. Source: https://en.wikipedia.org/wiki/World_Bank

    Content

    This dataset combines key education statistics from a variety of sources to provide a look at global literacy, spending, and access.

    For more information, see the World Bank website.

    Fork this kernel to get started with this dataset.

    Acknowledgements

    https://bigquery.cloud.google.com/dataset/bigquery-public-data:world_bank_health_population

    http://data.worldbank.org/data-catalog/ed-stats

    https://cloud.google.com/bigquery/public-data/world-bank-education

    Citation: The World Bank: Education Statistics

    Dataset Source: World Bank. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

    Banner Photo by @till_indeman from Unplash.

    Inspiration

    Of total government spending, what percentage is spent on education?

  5. w

    Global Education Policy Dashboard 2020-2021 - Ethiopia

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Nov 13, 2024
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    Brian Stacy (2024). Global Education Policy Dashboard 2020-2021 - Ethiopia [Dataset]. https://microdata.worldbank.org/index.php/catalog/6408
    Explore at:
    Dataset updated
    Nov 13, 2024
    Dataset provided by
    Halsey Rogers
    Reema Nayar
    Brian Stacy
    Sergio Venegas Marin
    Marta Carnelli
    Time period covered
    2020 - 2021
    Area covered
    Ethiopia
    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

    Overall, we draw a sample of 300 public schools from each of the regions of Ethiopia. As a comparison to the total number of schools in Ethiopia, this consistutes an approximately 1% sample. Because of the large size of the country, and because there can be very large distances between Woredas within the same region, we chose a cluster sampling approach. In this approach, 100 Woredas were chosen with probability proportional to 4th grade size. Then within each Woreda two rural and one urban school were chosen with probability proportional to 4th grade size.

    Because of conflict in the Tigray region, an initial set of 12 schools that were selected had to be trimmed to 6 schools in Tigray. These six schools were then distributed to other regions in Ethiopia.

    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.

  6. w

    Learning Poverty Global Database

    • data360.worldbank.org
    Updated Apr 18, 2025
    + more versions
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    (2025). Learning Poverty Global Database [Dataset]. https://data360.worldbank.org/en/dataset/WB_LPGD
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    Dataset updated
    Apr 18, 2025
    License

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

    Time period covered
    2001 - 2023
    Description

    Will all children be able to read by 2030? The ability to read with comprehension is a foundational skill that every education system around the world strives to impart by late in primary school—generally by age 10. Moreover, attaining the ambitious Sustainable Development Goals (SDGs) in education requires first achieving this basic building block, and so does improving countries’ Human Capital Index scores. Yet past evidence from many low- and middle-income countries has shown that many children are not learning to read with comprehension in primary school. To understand the global picture better, we have worked with the UNESCO Institute for Statistics (UIS) to assemble a new dataset with the most comprehensive measures of this foundational skill yet developed, by linking together data from credible cross-national and national assessments of reading. This dataset covers 115 countries, accounting for 81% of children worldwide and 79% of children in low- and middle-income countries. The new data allow us to estimate the reading proficiency of late-primary-age children, and we also provide what are among the first estimates (and the most comprehensive, for low- and middle-income countries) of the historical rate of progress in improving reading proficiency globally (for the 2000-17 period). The results show that 53% of all children in low- and middle-income countries cannot read age-appropriate material by age 10, and that at current rates of improvement, this “learning poverty” rate will have fallen only to 43% by 2030. Indeed, we find that the goal of all children reading by 2030 will be attainable only with historically unprecedented progress. The high rate of “learning poverty” and slow progress in low- and middle-income countries is an early warning that all the ambitious SDG targets in education (and likely of social progress) are at risk. Based on this evidence, we suggest a new medium-term target to guide the World Bank’s work in low- and middle- income countries: cut learning poverty by at least half by 2030. This target, together with improved measurement of learning, can be as an evidence-based tool to accelerate progress to get all children reading by age 10.

    For further details, please refer to https://thedocs.worldbank.org/en/doc/e52f55322528903b27f1b7e61238e416-0200022022/original/Learning-poverty-report-2022-06-21-final-V7-0-conferenceEdition.pdf

  7. G

    Secondary school enrollment by country, around the world |...

    • theglobaleconomy.com
    csv, excel, xml
    Updated Apr 24, 2015
    + more versions
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    Globalen LLC (2015). Secondary school enrollment by country, around the world | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/rankings/Secondary_school_enrollment/
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    excel, csv, xmlAvailable download formats
    Dataset updated
    Apr 24, 2015
    Dataset authored and provided by
    Globalen LLC
    License

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

    Time period covered
    Dec 31, 1970 - Dec 31, 2023
    Area covered
    World, World
    Description

    The average for 2022 based on 126 countries was 94.03 percent. The highest value was in Finland: 144.85 percent and the lowest value was in Burkina Faso: 33.72 percent. The indicator is available from 1970 to 2023. Below is a chart for all countries where data are available.

  8. International student share of higher-ed population worldwide in 2022, by...

    • statista.com
    • ai-chatbox.pro
    Updated Jun 26, 2025
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    Statista (2025). International student share of higher-ed population worldwide in 2022, by country [Dataset]. https://www.statista.com/statistics/788155/international-student-share-of-higher-education-worldwide/
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    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Worldwide
    Description

    In 2022, Canada had the greatest number of international students compared to their entire higher education population, with nearly ** percent of students being international. Australia followed with a share of ** percent of the students being international, while the United Kingdom ranked third.

  9. G

    Primary school enrollment by country, around the world |...

    • theglobaleconomy.com
    csv, excel, xml
    Updated Jan 16, 2015
    + more versions
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    Globalen LLC (2015). Primary school enrollment by country, around the world | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/rankings/Primary_school_enrollment/
    Explore at:
    excel, xml, csvAvailable download formats
    Dataset updated
    Jan 16, 2015
    Dataset authored and provided by
    Globalen LLC
    License

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

    Time period covered
    Dec 31, 1970 - Dec 31, 2023
    Area covered
    World, World
    Description

    The average for 2022 based on 149 countries was 100.44 percent. The highest value was in Sierra Leone: 156.8 percent and the lowest value was in Liberia: 67.23 percent. The indicator is available from 1970 to 2023. Below is a chart for all countries where data are available.

  10. G

    Tertiary school enrollment by country, around the world |...

    • theglobaleconomy.com
    csv, excel, xml
    Updated Jan 18, 2015
    + more versions
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    Globalen LLC (2015). Tertiary school enrollment by country, around the world | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/rankings/Tertiary_school_enrollment/
    Explore at:
    xml, csv, excelAvailable download formats
    Dataset updated
    Jan 18, 2015
    Dataset authored and provided by
    Globalen LLC
    License

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

    Time period covered
    Dec 31, 1970 - Dec 31, 2023
    Area covered
    World
    Description

    The average for 2022 based on 119 countries was 55.47 percent. The highest value was in Greece: 166.67 percent and the lowest value was in Tanzania: 5.43 percent. The indicator is available from 1970 to 2023. Below is a chart for all countries where data are available.

  11. C

    Chile CL: Educational Attainment: At Least Master's or Equivalent:...

    • ceicdata.com
    Updated Feb 27, 2018
    + more versions
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    CEICdata.com (2018). Chile CL: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Female: % Cumulative [Dataset]. https://www.ceicdata.com/en/chile/social-education-statistics
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    Dataset updated
    Feb 27, 2018
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2012 - Dec 1, 2023
    Area covered
    Chile
    Variables measured
    Education Statistics
    Description

    CL: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Female: % Cumulative data was reported at 2.926 % in 2023. This records an increase from the previous number of 2.822 % for 2022. CL: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Female: % Cumulative data is updated yearly, averaging 1.246 % from Dec 2010 (Median) to 2023, with 14 observations. The data reached an all-time high of 2.926 % in 2023 and a record low of 0.370 % in 2011. CL: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Female: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chile – Table CL.World Bank.WDI: Social: Education Statistics. The percentage of population ages 25 and over that attained or completed Master's or equivalent.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;;

  12. o

    Global Data Set on Education Quality - Dataset - Data Catalog Armenia

    • data.opendata.am
    Updated Jul 7, 2023
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    (2023). Global Data Set on Education Quality - Dataset - Data Catalog Armenia [Dataset]. https://data.opendata.am/dataset/dcwb0040288
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    Dataset updated
    Jul 7, 2023
    Description

    This paper presents the largest globally comparable panel database of education quality. The database includes 163 countries and regions over 1965-2015. The globally comparable achievement outcomes were constructed by linking standardized, psychometrically-robust international and regional achievement tests. The paper contributes to the literature in the following ways: (1) it is the largest and most current globally comparable data set, covering more than 90 percent of the global population; (2) the data set includes 100 developing areas and the most developing countries included in such a data set to date -- the countries that have the most to gain from the potential benefits of a high-quality education; (3) the data set contains credible measures of globally comparable achievement distributions as well as mean scores; (4) the data set uses multiple methods to link assessments, including mean and percentile linking methods, thus enhancing the robustness of the data set; (5) the data set includes the standard errors for the estimates, enabling explicit quantification of the degree of reliability of each estimate; and (6) the data set can be disaggregated across gender, socioeconomic status, rural/urban, language, and immigration status, thus enabling greater precision and equity analysis. A first analysis of the data set reveals a few important trends: learning outcomes in developing countries are often clustered at the bottom of the global scale; although variation in performance is high in developing countries, the top performers still often perform worse than the bottom performers in developed countries; gender gaps are relatively small, with high variation in the direction of the gap; and distributions reveal meaningfully different trends than mean scores, with less than 50 percent of students reaching the global minimum threshold of proficiency in developing countries relative to 86 percent in developed countries. The paper also finds a positive and significant association between educational achievement and economic growth. The data set can be used to benchmark global progress on education quality, as well as to uncover potential drivers of education quality, growth, and development.

  13. g

    World Bank - Education Statistics

    • gimi9.com
    Updated Mar 20, 2014
    + more versions
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    (2014). World Bank - Education Statistics [Dataset]. https://gimi9.com/dataset/worldbank_wb_edstats/
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    Dataset updated
    Mar 20, 2014
    License

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

    Description

    The World Bank EdStats All Indicator Query holds over 4,000 internationally comparable indicators that describe education access, progression, completion, literacy, teachers, population, and expenditures. The indicators cover the education cycle from pre-primary to vocational and tertiary education. The query also holds learning outcome data from international and regional learning assessments (e.g. PISA, TIMSS, PIRLS), equity data from household surveys, and projection/attainment data to 2050. For further information, please visit the EdStats website. For further details, please refer to https://datatopics.worldbank.org/education/wRsc/about

  14. A

    4th Global Report on Adult Learning and Education (GRALE)

    • data.amerigeoss.org
    pdf, xlsx
    Updated Nov 22, 2022
    + more versions
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    UN Humanitarian Data Exchange (2022). 4th Global Report on Adult Learning and Education (GRALE) [Dataset]. https://data.amerigeoss.org/it/dataset/4th-global-report-on-adult-learning-and-education-grale
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    xlsx(326737), pdf(166291), xlsx(137571)Available download formats
    Dataset updated
    Nov 22, 2022
    Dataset provided by
    UN Humanitarian Data Exchange
    License

    Open Data Commons Attribution License (ODC-By) v1.0https://www.opendatacommons.org/licenses/by/1.0/
    License information was derived automatically

    Description

    The Global Report on Adult Learning and Education (GRALE) by the UNESCO Institute for Lifelong Learning (UIL) provides a clear and comprehensive picture of the state of adult learning and education around the world. Five reports have been published since 2009. GRALE 4 monitors the extent to which UNESCO Member States put their international commitments on adult education into practice and reflects data submitted by 159 countries.

  15. Number of school aged children globally, by age group 1950-2100

    • statista.com
    Updated Jan 23, 2025
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    Statista (2025). Number of school aged children globally, by age group 1950-2100 [Dataset]. https://www.statista.com/statistics/914490/school-aged-children-worldwide-age-group/
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    Dataset updated
    Jan 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    This statistic shows the population of school aged children aged five to 19 worldwide from 1950 to 2100. In 2100, the population of school aged children ages five to nine globally is expected to reach about 632.44 million.

  16. C

    Chile CL: Children Out of School: Primary: Male

    • ceicdata.com
    Updated Feb 27, 2018
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    CEICdata.com (2018). Chile CL: Children Out of School: Primary: Male [Dataset]. https://www.ceicdata.com/en/chile/social-education-statistics
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    Dataset updated
    Feb 27, 2018
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2011 - Dec 1, 2022
    Area covered
    Chile
    Variables measured
    Education Statistics
    Description

    CL: Children Out of School: Primary: Male data was reported at 4,869.000 Person in 2022. This records a decrease from the previous number of 12,692.000 Person for 2021. CL: Children Out of School: Primary: Male data is updated yearly, averaging 18,915.000 Person from Dec 2007 (Median) to 2022, with 16 observations. The data reached an all-time high of 34,893.000 Person in 2009 and a record low of 4,869.000 Person in 2022. CL: Children Out of School: Primary: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chile – Table CL.World Bank.WDI: Social: Education Statistics. Children out of school are the number of primary-school-age children not enrolled in primary or secondary school.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;Sum;

  17. o

    Education Attainment and Enrollment Around the World 1989-2008 - Dataset -...

    • data.opendata.am
    Updated Jul 7, 2023
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    (2023). Education Attainment and Enrollment Around the World 1989-2008 - Dataset - Data Catalog Armenia [Dataset]. https://data.opendata.am/dataset/dcwb0043697
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    Dataset updated
    Jul 7, 2023
    Description

    Data collected from World Bank data catalog https://datacatalog.worldbank.org

  18. G

    Education prices by country, around the world | TheGlobalEconomy.com

    • theglobaleconomy.com
    csv, excel, xml
    Updated May 17, 2021
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    Globalen LLC (2021). Education prices by country, around the world | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/rankings/education_prices_wb/
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    xml, excel, csvAvailable download formats
    Dataset updated
    May 17, 2021
    Dataset authored and provided by
    Globalen LLC
    License

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

    Time period covered
    Dec 31, 2017 - Dec 31, 2021
    Area covered
    World, World
    Description

    The average for 2021 based on 165 countries was 72.61 index points. The highest value was in Luxembourg: 422.59 index points and the lowest value was in Turkey: 10.85 index points. The indicator is available from 2017 to 2021. Below is a chart for all countries where data are available.

  19. Number of universities worldwide in 2023, by country

    • statista.com
    • ai-chatbox.pro
    Updated Jun 6, 2025
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    Statista (2025). Number of universities worldwide in 2023, by country [Dataset]. https://www.statista.com/statistics/918403/number-of-universities-worldwide-by-country/
    Explore at:
    Dataset updated
    Jun 6, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jul 2023
    Area covered
    World
    Description

    India has the most universities worldwide. According to data from July 2023, there were an estimated ***** universities in India. Indonesia had the second most universities, counting *****, followed by the United States with ***** universities.

  20. Kenya - Education

    • data.humdata.org
    csv
    Updated Jun 27, 2025
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    World Bank Group (2025). Kenya - Education [Dataset]. https://data.humdata.org/dataset/world-bank-education-indicators-for-kenya
    Explore at:
    csv(1339390), csv(1016)Available download formats
    Dataset updated
    Jun 27, 2025
    Dataset provided by
    World Bankhttp://worldbank.org/
    License

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

    Area covered
    Kenya
    Description

    Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

    Education is one of the most powerful instruments for reducing poverty and inequality and lays a foundation for sustained economic growth. The World Bank compiles data on education inputs, participation, efficiency, and outcomes. Data on education are compiled by the United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics from official responses to surveys and from reports provided by education authorities in each country.

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Sergio Venegas Marin (2024). Global Education Policy Dashboard 2019 - Jordan [Dataset]. https://microdata.worldbank.org/index.php/catalog/6407

Global Education Policy Dashboard 2019 - Jordan

Explore at:
Dataset updated
Nov 13, 2024
Dataset provided by
Halsey Rogers
Reema Nayar
Brian Stacy
Sergio Venegas Marin
Marta Carnelli
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.

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