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?

To collect feedback on their learning environment from families, students and teachers. Aids in facilitating the understanding of families perceptions, students, and teachers regarding their school. School leaders use feedback from the survey to reflect and make improvements to schools and programs. Each year all parents, teachers and students in grades 6-12 take the NYC School Survey. The survey is aligned to the DOE's Framework for Great Schools. It is designed to collect important information about each school's ability to support student success.

The Postsecondary Education Participants System (PEPS) is the Office of Federal Student Aid (FSA) management information system of all organizations that have a role in administering student financial aid and other Higher Education Act programs. PEPS maintains eligibility, certification, demographic, financial, review, audit, and default rate data about schools, lenders, and guarantors participating in the Title IV programs.

This table contains data on the percent of population age 25 and up with a four-year college degree or higher for California, its regions, counties, county subdivisions, cities, towns, and census tracts. Greater educational attainment has been associated with health-promoting behaviors including consumption of fruits and vegetables and other aspects of healthy eating, engaging in regular physical activity, and refraining from excessive consumption of alcohol and from smoking. Completion of formal education (e.g., high school) is a key pathway to employment and access to healthier and higher paying jobs that can provide food, housing, transportation, health insurance, and other basic necessities for a healthy life. Education is linked with social and psychological factors, including sense of control, social standing and social support. These factors can improve health through reducing stress, influencing health-related behaviors and providing practical and emotional support. More information on the data table and a data dictionary can be found in the Data and Resources section. The educational attainment table is part of a series of indicators in the Healthy Communities Data and Indicators Project (HCI) of the Office of Health Equity. The goal of HCI is to enhance public health by providing data, a standardized set of statistical measures, and tools that a broad array of sectors can use for planning healthy communities and evaluating the impact of plans, projects, policy, and environmental changes on community health. The creation of healthy social, economic, and physical environments that promote healthy behaviors and healthy outcomes requires coordination and collaboration across multiple sectors, including transportation, housing, education, agriculture and others. Statistical metrics, or indicators, are needed to help local, regional, and state public health and partner agencies assess community environments and plan for healthy communities that optimize public health. More information on HCI can be found here: https://www.cdph.ca.gov/Programs/OHE/CDPH%20Document%20Library/Accessible%202%20CDPH_Healthy_Community_Indicators1pager5-16-12.pdf The format of the educational attainment table is based on the standardized data format for all HCI indicators. As a result, this data table contains certain variables used in the HCI project (e.g., indicator ID, and indicator definition). Some of these variables may contain the same value for all observations.

CR: Lower Secondary Completion Rate: Total: % of Relevant Age Group data was reported at 66.808 % in 2022. This records a decrease from the previous number of 70.750 % for 2021. CR: Lower Secondary Completion Rate: Total: % of Relevant Age Group data is updated yearly, averaging 40.888 % from Dec 1970 (Median) to 2022, with 43 observations. The data reached an all-time high of 71.644 % in 2019 and a record low of 19.465 % in 1970. CR: Lower Secondary Completion Rate: Total: % of Relevant Age Group data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Costa Rica – Table CR.World Bank.WDI: Social: Education Statistics. Lower secondary education completion rate is measured as the gross intake ratio to the last grade of lower secondary education (general and pre-vocational). It is calculated as the number of new entrants in the last grade of lower secondary education, regardless of age, divided by the population at the entrance age for the last grade of lower secondary education.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;Weighted average;

In addition to respondents’ highest educational qualification, some surveys also collect data on their main field of education. Current measurement practice involves either a closed question with highly aggregated response categories, which are difficult to use for respondents, or an open question, requiring expensive post-coding. Therefore, a measurement tool for fields of education was developed in the SERISS-project in work package 8, Task 8.3. In deliverable D8.9 we provide a database of fields of education and training in 34 languages, including the definition of a search tree interface to facilitate navigation of categories for respondents. All 120 standard categories and classification codes are taken from UNESCO's International Standard Classification of Education for Fields of Education and Training (ISCED-F). For most languages, detailed 3-digit information is available. The database, including a live search feature, is available at the surveycodings website at https://surveycodings.org/articles/codings/fields-of-education. The search tree can be used for respondents’ self-identification of fields of education and training in computer-assisted surveys. The live search feature can also be used for post-coding open answers in already collected data.

Graph and download economic data for Government current expenditures: Education (G160291A027NBEA) from 1959 to 2023 about expenditures, education, government, GDP, and USA.

Success.ai’s Education Industry Data provides access to comprehensive profiles of global professionals in the education sector. Sourced from over 700 million verified LinkedIn profiles, this dataset includes actionable insights and verified contact details for teachers, school administrators, university leaders, and other decision-makers. Whether your goal is to collaborate with educational institutions, market innovative solutions, or recruit top talent, Success.ai ensures your efforts are supported by accurate, enriched, and continuously updated data.

Why Choose Success.ai’s Education Industry Data? 1. Comprehensive Professional Profiles Access verified LinkedIn profiles of teachers, school principals, university administrators, curriculum developers, and education consultants. AI-validated profiles ensure 99% accuracy, reducing bounce rates and enabling effective communication. 2. Global Coverage Across Education Sectors Includes professionals from public schools, private institutions, higher education, and educational NGOs. Covers markets across North America, Europe, APAC, South America, and Africa for a truly global reach. 3. Continuously Updated Dataset Real-time updates reflect changes in roles, organizations, and industry trends, ensuring your outreach remains relevant and effective. 4. Tailored for Educational Insights Enriched profiles include work histories, academic expertise, subject specializations, and leadership roles for a deeper understanding of the education sector.

Data Highlights: 700M+ Verified LinkedIn Profiles: Access a global network of education professionals. 100M+ Work Emails: Direct communication with teachers, administrators, and decision-makers. Enriched Professional Histories: Gain insights into career trajectories, institutional affiliations, and areas of expertise. Industry-Specific Segmentation: Target professionals in K-12 education, higher education, vocational training, and educational technology.

Key Features of the Dataset: 1. Education Sector Profiles Identify and connect with teachers, professors, academic deans, school counselors, and education technologists. Engage with individuals shaping curricula, institutional policies, and student success initiatives. 2. Detailed Institutional Insights Leverage data on school sizes, student demographics, geographic locations, and areas of focus. Tailor outreach to align with institutional goals and challenges. 3. Advanced Filters for Precision Targeting Refine searches by region, subject specialty, institution type, or leadership role. Customize campaigns to address specific needs, such as professional development or technology adoption. 4. AI-Driven Enrichment Enhanced datasets include actionable details for personalized messaging and targeted engagement. Highlight educational milestones, professional certifications, and key achievements.

Strategic Use Cases: 1. Product Marketing and Outreach Promote educational technology, learning platforms, or training resources to teachers and administrators. Engage with decision-makers driving procurement and curriculum development. 2. Collaboration and Partnerships Identify institutions for collaborations on research, workshops, or pilot programs. Build relationships with educators and administrators passionate about innovative teaching methods. 3. Talent Acquisition and Recruitment Target HR professionals and academic leaders seeking faculty, administrative staff, or educational consultants. Support hiring efforts for institutions looking to attract top talent in the education sector. 4. Market Research and Strategy Analyze trends in education systems, curriculum development, and technology integration to inform business decisions. Use insights to adapt products and services to evolving educational needs.

Why Choose Success.ai? 1. Best Price Guarantee Access industry-leading Education Industry Data at unmatched pricing for cost-effective campaigns and strategies. 2. Seamless Integration Easily integrate verified data into CRMs, recruitment platforms, or marketing systems using downloadable formats or APIs. 3. AI-Validated Accuracy Depend on 99% accurate data to reduce wasted outreach and maximize engagement rates. 4. Customizable Solutions Tailor datasets to specific educational fields, geographic regions, or institutional types to meet your objectives.

Strategic APIs for Enhanced Campaigns: 1. Data Enrichment API Enrich existing records with verified education professional profiles to enhance engagement and targeting. 2. Lead Generation API Automate lead generation for a consistent pipeline of qualified professionals in the education sector. Success.ai’s Education Industry Data enables you to connect with educators, administrators, and decision-makers transforming global...

Background, Methodology:

Local Law 102 enacted in 2015 requires the Department of Education of the New York City School District to submit to the Council an annual report concerning physical education for the prior school year.

This report provides information about average frequency and average total minutes per week of physical education as defined in Local Law 102 as reported through the 2015-2016 STARS database. It is important to note that schools self-report their scheduling information in STARS. The report also includes information regarding the number and ratio of certified physical education instructors and designated physical education instructional space.

This report consists of six tabs:

1. PE Instruction Borough-Level
2. PE Instruction District-Level
3. PE Instruction School-Level
4. Certified PE Teachers
5. PE Space

6. Supplemental Programs

7. PE Instruction Borough-Level

This tab includes the average frequency and average total minutes per week of physical education by borough, disaggregated by grade, race and ethnicity, gender, special education status and English language learner status. This report only includes students who were enrolled in the same school across all academic terms in the 2015-16 school year. Data on students with disabilities and English language learners are as of the end of the 2015-16 school year. Data on adaptive PE is based on individualized education programs (IEP) finalized on or before 05/31/2016.

1. PE Instruction District-Level

This tab includes the average frequency and average total minutes per week of physical education by district, disaggregated by grade, race and ethnicity, gender, special education status and English language learner status. This report only includes students who were enrolled in the same school across all academic terms in the 2015-16 school year. Data on students with disabilities and English language learners are as of the end of the 2015-16 school year. Data on adaptive PE is based on individualized education programs (IEP) finalized on or before 05/31/2016.

1. PE Instruction School-Level

This tab includes the average frequency and average total minutes per week of physical education by school, disaggregated by grade, race and ethnicity, gender, special education status and English language learner status. This report only includes students who were enrolled in the same school across all academic terms in the 2015-16 school year. Data on students with disabilities and English language learners are as of the end of the 2015-16 school year. Data on adaptive PE is based on individualized education programs (IEP) finalized on or before 05/31/2016.

1. Certified PE Teachers

This tab provides the number of designated full-time and part-time physical education certified instructors. Does not include elementary, early childhood and K-8 physical education teachers that provide physical education instruction under a common branches license. Also includes ratio of full time instructors teaching in a physical education license to students by school. Data reported is for the 2015-2016 school year as of 10/31/2015.

1. PE Space

This tab provides information on all designated indoor, outdoor and off-site spaces used by the school for physical education as reported through the Principal Annual Space Survey and the Outdoor Yard Report. It is important to note that information on each room category is self-reported by principals, and principals determine how each room is classified. Data captures if the PE space is co-located, used by another school or used for another purpose. Includes gyms, athletic fields, auxiliary exercise spaces, dance rooms, field houses, multipurpose spaces, outdoor yards, off-site locations, playrooms, swimming pools and weight rooms as designated PE Space.

1. Supplemental Programs

This tab provides information on the department's supplemental physical education program and a list of schools that use it.I. Includes all Move-to-Improve (MTI) supplemental programs for the 2015-2016 school year.

Link to NY State PE Regulations: http://www.p12.nysed.gov/ciai/pe/documents/title8part135.pdf

Any questions regarding this report should be directed to: Nnennaya Okezie, Executive Director NYC Department of Education, Office of Intergovernmental Affairs Phone: 212-374-4947"

Idiosyncrasies or limitations of the data to be aware of:

EdSight is an education data portal that integrates information from over 30 different sources – some reported by districts and others from external sources. The portal can be accessed here: http://edsight.ct.gov/.

Information is available on key performance measures that make up the Next Generation Accountability System, as well as dozens of other topics, including school finance, special education, staffing levels and school enrollment.

The Colleges and Universities feature class/shapefile is composed of all Post Secondary Education facilities as defined by the Integrated Post Secondary Education System (IPEDS, http://nces.ed.gov/ipeds/), National Center for Education Statistics (NCES, https://nces.ed.gov/), US Department of Education for the 2018-2019 school year. Included are Doctoral/Research Universities, Masters Colleges and Universities, Baccalaureate Colleges, Associates Colleges, Theological seminaries, Medical Schools and other health care professions, Schools of engineering and technology, business and management, art, music, design, Law schools, Teachers colleges, Tribal colleges, and other specialized institutions. Overall, this data layer covers all 50 states, as well as Puerto Rico and other assorted U.S. territories. This feature class contains all MEDS/MEDS+ as approved by the National Geospatial-Intelligence Agency (NGA) Homeland Security Infrastructure Program (HSIP) Team. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the "Place Keyword" section of the metadata. This feature class does not have a relationship class but is related to Supplemental Colleges. Colleges and Universities that are not included in the NCES IPEDS data are added to the Supplemental Colleges feature class when found. This release includes the addition of 175 new records, the removal of 468 no longer reported by NCES, and modifications to the spatial location and/or attribution of 6682 records.

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

This dataset provides transparency about the names and amounts of payments from county school boards to payees. More information about the statute for this dataset is under Maryland Education Article §5-115.

https://mgaleg.maryland.gov/mgawebsite/Laws/StatuteText?article=ged&section=5-115&enactments=false

Each county annually reports payment information about any payee who received an aggregate payment of $25,000 in a fiscal year from a school board.

This started with Fiscal Year 2019 payments. We now have payments data through Fiscal Year 2024 (6/30/24).

Baltimore County is also required to provide the purpose of the payment and whether the payee is a minority business enterprise.

Montgomery County and Howard County data goes back to 2010. Baltimore County and Prince George’s County goes back to 2012. 2019 is the first year where are all counties were required to submit the data with payee names and amounts.

Baltimore City data is missing for 2021 and 2023. Baltimore County data for 2023 needs further review. DBM will work on making these updates.

Separately, Prince George’s County is required to provide additional detail from Education Article §5-101. That info is not part of this dataset.

https://mgaleg.maryland.gov/mgawebsite/Laws/StatuteText?article=ged&section=5-101&enactments=False&archived=False

Data includes: board and school information, grade 3 and 6 EQAO student achievements for reading, writing and mathematics, and grade 9 mathematics EQAO and OSSLT. Data excludes private schools, Education and Community Partnership Programs (ECPP), summer, night and continuing education schools.

How Are We Protecting Privacy?

Results for OnSIS and Statistics Canada variables are suppressed based on school population size to better protect student privacy. In order to achieve this additional level of protection, the Ministry has used a methodology that randomly rounds a percentage either up or down depending on school enrolment. In order to protect privacy, the ministry does not publicly report on data when there are fewer than 10 individuals represented.

* Percentages depicted as 0 may not always be 0 values as in certain situations the values have been randomly rounded down or there are no reported results at a school for the respective indicator. * Percentages depicted as 100 are not always 100, in certain situations the values have been randomly rounded up.

The information in the School Information Finder is the most current available to the Ministry of Education at this time, as reported by schools, school boards, EQAO and Statistics Canada. The information is updated as frequently as possible.

This information is also available on the Ministry of Education's School Information Finder website by individual school.

Descriptions for some of the data types can be found in our glossary.

School/school board and school authority contact information are updated and maintained by school boards and may not be the most current version. For the most recent information please visit: https://data.ontario.ca/dataset/ontario-public-school-contact-information.

CR: Persistence to Grade 5: Female: % of Cohort data was reported at 97.867 % in 2020. This records an increase from the previous number of 97.260 % for 2015. CR: Persistence to Grade 5: Female: % of Cohort data is updated yearly, averaging 87.963 % from Dec 1970 (Median) to 2020, with 38 observations. The data reached an all-time high of 97.867 % in 2020 and a record low of 75.589 % in 1973. CR: Persistence to Grade 5: Female: % of Cohort data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Costa Rica – Table CR.World Bank.WDI: Social: Education Statistics. Persistence to grade 5 (percentage of cohort reaching grade 5) is the share of children enrolled in the first grade of primary school who eventually reach grade 5. The estimate is based on the reconstructed cohort method.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;Weighted average;

The Nigeria MDG (Millennium Development Goals) Information System – NMIS education facility data is collected by the Office of the Senior Special Assistant to the President on the Millennium Development Goals (OSSAP-MDGs) in partner with the Sustainable Engineering Lab at Columbia University. A rigorous, geo-referenced baseline facility inventory across Nigeria is created spanning from 2009 to 2011 with an additional survey effort to increase coverage in 2014, to build Nigeria’s first nation-wide inventory of education facility. The database includes 98,667 education facilities info in Nigeria. The goal of this database is to make the data collected available to planners, government officials, and the public, to be used to make strategic decisions for planning relevant interventions. For data inquiry, please contact Ms. Funlola Osinupebi, Performance Monitoring & Communications, Advisory Power Team, Office of the Vice President at funlola.osinupebi@aptovp.org To learn more, please visit http://csd.columbia.edu/2014/03/10/the-nigeria-mdg-information-system-nmis-takes-open-data-further/

CR: Persistence to Grade 5: % of Cohort data was reported at 97.482 % in 2020. This records an increase from the previous number of 94.893 % for 2016. CR: Persistence to Grade 5: % of Cohort data is updated yearly, averaging 85.385 % from Dec 1970 (Median) to 2020, with 43 observations. The data reached an all-time high of 97.482 % in 2020 and a record low of 65.666 % in 1974. CR: Persistence to Grade 5: % of Cohort data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Costa Rica – Table CR.World Bank.WDI: Social: Education Statistics. Persistence to grade 5 (percentage of cohort reaching grade 5) is the share of children enrolled in the first grade of primary school who eventually reach grade 5. The estimate is based on the reconstructed cohort method.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;Weighted average;

Database for statistics on higher education (DBH) collects information about the activity at Norwegian universities, university colleges and vocational schools. The database contains information about education, research, employees, finances, areas etc. and is managed by the Directorate for Higher Education and Competence (HK-dir). The information constitutes a statistical bank where data can be retrieved programmatically via API or reports via screenshots, as well as as a special order upon request. There is a client that is linked to API and can be used for testing or ad hoc queries: https://dbh.hkdir.no/dbhapiklient/ The StatBank is divided by subject and table. Within each table, the user can create their own query. The query is designed in JSON format and can be tested in the client. Data is provided as CSV or JSON. Transfer is done via HTTPS or via the client. Data can be retrieved as a sample via the query, or as a whole data set (bulk data). Table 1 in the client provides an overview of the content of the API. Documentation: https://dbh.hkdir.no/static/files/dokumenter/api/api_dokumentasjon.pdf

US: School Enrollment: Preprimary: % Gross data was reported at 69.492 % in 2015. This records a decrease from the previous number of 69.917 % for 2014. US: School Enrollment: Preprimary: % Gross data is updated yearly, averaging 60.389 % from Dec 1971 (Median) to 2015, with 27 observations. The data reached an all-time high of 70.965 % in 1996 and a record low of 37.734 % in 1972. US: School Enrollment: Preprimary: % Gross data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Education Statistics. Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Preprimary education refers to programs at the initial stage of organized instruction, designed primarily to introduce very young children to a school-type environment and to provide a bridge between home and school.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Data Set Information: The experiments have been carried out with a group of 115 students of first-year, undergraduate Engineering major of the University of Genoa. We carried out this study over a simulation environment named Deeds (Digital Electronics Education and Design Suite) which is used for e-learning in digital electronics. The environment provides learning materials through specialized browsers for the students, and asks them to solve various problems with different levels of difficulty. For more information about the Deeds simulator used for this course look at: [Web Link] and to know more about the exercises contents of each session see exercises_info.txt . Our data set contains the students time series of activities during six sessions of laboratory sessions of the course of digital electronics. There are 6 folders containing the students’ data per session. Each Session folder contains up to 99 CSV files each dedicated to a specific student log during that ses