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?

This feature layer provides the educational attainment levels in the City of Tempe by census tract. The feature layer was created by clipping the ACS Educational Attainment Variables - Boundaries 2014-18, downloaded from Esri's Living Atlas, to the City of Tempe boundary layer.https://tempegov.maps.arcgis.com/home/item.html?id=84e3022a376e41feb4dd8addf25835a3

In 2021, about 37.7 percent of the U.S. population who were aged 25 and above had graduated from college or another higher education institution, a slight decline from 37.9 the previous year. However, this is a significant increase from 1960, when only 7.7 percent of the U.S. population had graduated from college.

Demographics

Educational attainment varies by gender, location, race, and age throughout the United States. Asian-American and Pacific Islanders had the highest level of education, on average, while Massachusetts and the District of Colombia are areas home to the highest rates of residents with a bachelor’s degree or higher. However, education levels are correlated with wealth. While public education is free up until the 12th grade, the cost of university is out of reach for many Americans, making social mobility increasingly difficult.

Earnings

White Americans with a professional degree earned the most money on average, compared to other educational levels and races. However, regardless of educational attainment, males typically earned far more on average compared to females. Despite the decreasing wage gap over the years in the country, it remains an issue to this day. Not only is there a large wage gap between males and females, but there is also a large income gap linked to race as well.

The National Education Longitudinal Study of 1988 (NELS:88) is a study that is part of the Longitudinal Studies Branch (LSB) program; program data is available since 1988 at . NELS:88 (https://nces.ed.gov/surveys/nels88/) is a longitudinal study that is designed to provide trend data about critical transitions experienced by students as they leave middle or junior high school, and progress through high school and into postsecondary institutions or the work force. A nationally representative sample of eighth-graders were first surveyed in the spring of 1988. A sample of these respondents were then resurveyed through four follow-ups in 1990, 1992, 1994, and 2000. Overall weighted response rate was unavailable as of December 2014. Key statistics produced from NELS:88 data can be used for policy-relevant research about educational processes and outcomes, for example: student learning; early and late predictors of dropping out; and school effects on students' access to programs and equal opportunity to learn.

Abstract copyright UK Data Service and data collection copyright owner.

This database contains an up-to-date array of comparative education statistics and indicators from Organisation for Economic Co-operation and Development (OECD) and non-OECD countries from 1985 onwards. It provides information on the human and financial resources invested in education, on access to, progression and completion of education, on how education and learning systems operate, and on the returns to educational investments.

These data were first provided by the UK Data Service in January 2007.

Main Topics:

Within UKDS.Stat, the OECD Education Statistics are presented in the following datasets (some will include missing data):

• Education and skills.
• Education at a Glance.


Data series include (but is not limited to):

• Educational Personnel
• Expenditure by funding source and transaction type
• Expenditure by nature and resource category
• Foreign / international students enrolled
• Graduates by age
• Graduates by field of education
• New entrants by sex and age
• Students aligned to finance and personnel data
• Students enrolled by age
• Students enrolled by type of institution
• Total population by sex and age

Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all : Access to education has improved, shown through increased attendance levels in early childhood, primary and secondary school in the Pacific region. Goal 4 highlights the need to focus on improving the quality and relevance of education and cognitive learning outcomes, since literacy and numeracy improvements have not made the expected gains for all. There is also a renewed focus on lifelong learning with early childhood care education and post-secondary education and training needing priority attention; The quality of educational facilities in some countries in the region, especially for girls and students with disabilities, is below standard.

Find more Pacific data on PDH.stat.

In the fall of 2021, about 95,715 students who were enrolled exclusively in distance education courses in postsecondary institutions were located outside of the United States. This is compared to 3.85 million students who were located in the same state as the institution, but enrolled in exclusively distance education courses. This high level of enrollment in distance learning courses is due to the impact of the COVID-19 pandemic.

The National Indian Education Study, 2007 (NIES 2007), is a study that is part of the National Indian Education Study (NIES), which is a part of National Assessment of Educational Progress (NAEP) program; program data is available since 2005 at https://nces.ed.gov/nationsreportcard/nies/. NIES 2007 (https://nces.ed.gov/nationsreportcard/nies/) is a cross-sectional survey that is designed to describe the condition of education for American Indian and Alaska Native (AI/AN) students in the United States. Students in public, private, Department of Defense, and Bureau of Indian Education-funded schools were sampled using paper-and-pencil assessment. Overall weighted response rate for 4th grade was 75 percent. Overall weighted response rate for 8th grade was 74 percent. Key statistics produced from NIES 2007 provides educators, policymakers, and the public with information about the academic performance in reading and mathematics of AI/AN fourth- and eighth-graders as well as their exposure to Native American culture.

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.

This dataset is designed to support research and development in improving digital literacy education in rural areas, with a focus on rural revitalization. It includes comprehensive learner interaction data, demographic attributes, and post-training outcomes, making it suitable for building adaptive and personalized learning systems.

Key features of this dataset include:

Demographics: Information on age, gender, education level, employment status, household income, and location type. Pre-Training Scores: Baseline scores for basic computer knowledge, internet usage, and mobile literacy. Post-Training Progress: Scores achieved after training to track the impact of education modules. Engagement Metrics: Data on session counts, modules completed, average time spent per module, and quiz performance. Behavioral Insights: Engagement levels, adaptability scores, and learner feedback ratings. Outcome Measures: Overall digital literacy scores, skill application data, and employment impact information. This dataset is ideal for:

Training and testing machine learning models for adaptive learning systems. Analyzing the effectiveness of digital literacy programs. Gaining insights into learner behavior and progress.

Graph and download economic data for Expenditures: Education by Education: Less Than High School Graduate (CXUEDUCATNLB1303M) from 1995 to 2012 about no college, secondary schooling, secondary, expenditures, education, and USA.

BR: Lower Secondary School Starting Age data was reported at 11.000 Year in 2023. This stayed constant from the previous number of 11.000 Year for 2022. BR: Lower Secondary School Starting Age data is updated yearly, averaging 11.000 Year from Dec 1970 (Median) to 2023, with 54 observations. The data reached an all-time high of 11.000 Year in 2023 and a record low of 11.000 Year in 2023. BR: Lower Secondary School Starting Age data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Social: Education Statistics. Lower secondary school starting age is the age at which students would enter lower secondary education, assuming they had started at the official entrance age for the lowest level of education, had studied full-time throughout and had progressed through the system without repeating or skipping a grade.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 24, 2024. https://apiportal.uis.unesco.org/bdds.;;

The average annual fee for tuition and required services at public higher education institutions in the United States was 7,998 U.S. dollars in 2023. This figure was significantly higher at private higher education institutions, which stood at 34,923 U.S. dollars.

While enrolment in tertiary education has increased dramatically over the past decades, many university-aged students do not enrol, nor do they expect to earn a university degree. While it is important to promote high expectations for further education, it is equally important to ensure that students’ expectations are well-aligned with their actual abilities. Grade Expectations: How Marks and Education Policies Shape Students' Ambitions reveals some of the factors that influence students’ thinking about further education. The report also suggests what teachers and education policy makers can do to ensure that more students have the skills, as well as the motivation, to succeed in higher education. In 2009, students in 21 PISA-participating countries and economies were asked about their expected educational attainment. An analysis of PISA data finds that students who expect to earn a university degree show significantly better performance in math and reading when compared to students who do not expect to earn such a university degree. However, performance is only one of the factors that determine expectations. On average across most countries and economies, girls and socio-economically advantaged students tend to hold more ambitious expectations than boys and disadvantaged students who perform just as well; and students with higher school marks are more likely to expect to earn a university degree – regardless of what those marks really measure.

BI: School Enrollment: Primary: % Net data was reported at 92.805 % in 2018. This records a decrease from the previous number of 94.876 % for 2017. BI: School Enrollment: Primary: % Net data is updated yearly, averaging 49.163 % from Dec 1973 (Median) to 2018, with 25 observations. The data reached an all-time high of 95.374 % in 2010 and a record low of 17.146 % in 1978. BI: School Enrollment: Primary: % Net data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Burundi – Table BI.World Bank.WDI: Social: Education Statistics. Net enrollment rate is the ratio of children of official school age who are enrolled in school to the population of the corresponding official school age. Primary education provides children with basic reading, writing, and mathematics skills along with an elementary understanding of such subjects as history, geography, natural science, social science, art, and music.;UNESCO Institute for Statistics (http://uis.unesco.org/). Data as of February 2020.;Weighted average;

K-12 Education Technology Market Outlook

The global K-12 education technology market size was valued at approximately USD 40 billion in 2023 and is projected to reach nearly USD 120 billion by 2032, growing at a CAGR of 12.5% during the forecast period. This remarkable growth can be attributed to the increasing integration of digital tools in classrooms, driven by advancements in technology and the rising demand for personalized learning experiences.

One of the primary growth factors for the K-12 education technology market is the widespread adoption of digital learning platforms. The COVID-19 pandemic accelerated the shift towards online education, making digital tools indispensable for both teachers and students. As a result, educational institutions are investing heavily in innovative technologies that facilitate remote learning, enhance student engagement, and improve educational outcomes. Furthermore, the availability of high-speed internet and affordable digital devices has made it easier for schools to implement these technologies on a large scale.

Another significant driver of market growth is the increasing emphasis on personalized learning. Educators are recognizing the importance of tailoring educational content to meet the individual needs of students. EdTech solutions, such as adaptive learning platforms and AI-driven analytics, enable teachers to create customized learning paths, track student progress in real-time, and provide targeted interventions. This personalized approach not only improves student performance but also fosters a more inclusive learning environment by addressing the diverse needs of learners.

The rise of K-12 Online Education has been a significant factor in the transformation of the educational landscape. With the advent of digital learning platforms, students now have the flexibility to access educational content from anywhere, at any time. This mode of learning has particularly benefited students in remote areas, providing them with opportunities that were previously inaccessible. Moreover, online education supports diverse learning styles, allowing students to learn at their own pace and revisit complex topics as needed. As technology continues to evolve, K-12 Online Education is expected to play an even more integral role in shaping the future of education, offering a more personalized and inclusive learning experience for all students.

Additionally, government initiatives and policies aimed at modernizing the education sector are playing a crucial role in driving the market. Many countries are prioritizing digital literacy and investing in infrastructure to support the integration of technology in schools. For instance, the U.S. governmentÂ’s E-rate program provides funding to help schools and libraries obtain affordable broadband. Similar initiatives are being rolled out globally, creating a favorable environment for the growth of the K-12 education technology market.

Regional outlook for the K-12 education technology market shows significant growth potential across various regions. North America currently leads the market, driven by high adoption rates of advanced technologies and substantial government funding. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, fueled by increasing investments in educational infrastructure, a large student population, and growing awareness about the benefits of EdTech solutions. Europe and Latin America are also experiencing steady growth, although challenges such as budget constraints and varying levels of digital literacy remain.

Component Analysis

The K-12 education technology market is segmented by component into hardware, software, and services. The hardware segment includes devices like laptops, tablets, interactive whiteboards, and other digital tools used in the classroom. The demand for hardware is driven by the need for reliable and user-friendly devices that facilitate the seamless integration of digital content into the curriculum. As schools continue to invest in one-to-one device programs, the hardware segment is expected to experience steady growth.

The software segment encompasses a wide range of applications designed to enhance the learning experience. This includes learning management systems (LMS), student information systems (SIS), classroom management software, and assessment tools. LMS and SIS are particularly crucial as they provide a centralized

Adults with the highest education level - particularly with a postgraduate degree - had the greatest level of familiarity with ChatGPT. The program, developed by startup OpenAI, was of far less concern to those with high school degrees or lower education. When looking at respondents with a little knowledge of ChatGPT, the numbers are far less drastically different. It is quite likely that the considerable coverage of the ChatGPT topic in media had an impact, giving most people some awareness of the topic.

BR: Secondary Education: Vocational Pupils: % Female data was reported at 54.556 % in 2017. This records a decrease from the previous number of 54.908 % for 2016. BR: Secondary Education: Vocational Pupils: % Female data is updated yearly, averaging 55.918 % from Dec 1970 (Median) to 2017, with 25 observations. The data reached an all-time high of 73.044 % in 2003 and a record low of 44.567 % in 1975. BR: Secondary Education: Vocational Pupils: % Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Social: Education Statistics. Secondary vocational pupils are the number of secondary students enrolled in technical and vocational education programs, including teacher training.;UNESCO Institute for Statistics (http://uis.unesco.org/). Data as of February 2020.;Weighted average;

Various data tables on student demographics, school enrollment trends, characteristics of traditional public school students and charter school students, student achievement, budget and school resources, principal and teacher information, building and school utilization and the availability of specialized facilities.