Search for specific education indicators by country, theme or level of education and compare the results using interactive charts and tables.
Base Theme
| PISA 2022 Results (Volume I): The State of Learning and Equity in Education |
| PISA 2022 Results (Volume II): Learning During - and From - Disruption |
| PISA 2018 Results (Volume IV): Are Students Smart About Money? |
| PISA 2018 Results (Volume VI): Are Students Ready to Thrive in an Interconnected World? |
| PISA 2018: Are Students Ready To Take On Environmental Challenges? |
| Education at a Glance 2023 (EAG 2023): Highlights |
| EAG 2023, Chapter A: The output of educational institutions and the impact of learning |
| EAG 2023, Chapter B: Access to education, participation and progression |
| EAG 2023, Chapter C: Financial resources invested in education |
| EAG 2023, Chapter D: Teachers, learning environment and organisation of schools |
| TALIS 2018: Highlight indicators |
| TALIS 2018 (Volume I): Teachers and School Leaders as Lifelong Learners |
| TALIS 2018 (Volume II): Teachers and School Leaders as Valued Professionals |
| TALIS 2018 (results for primary and upper secondary) |
| TALIS 2018: Starting Strong Survey |
| Survey of Adult Skills (PIAAC) |
| Skills |
| Low performers |
| Computers, education & skills |
| Access & participation |
| Student mobility |
| Education attainment |
| Education system & governance |
| Financing education |
| Learning environment |
| Students' well-being |
| Equity |
| Gender |
| Digital divide |
| Special needs |
| Socio-economic status |
| Migrant background |
| Economic & social outcomes |
| Teachers & educators |
| Education leadership |
| Evaluation & quality assurance |
| Future of education and skills |
| Research & innovation |
| Early childhood education & care |
| Vocational education & training (VET) |
| Tertiary education |
| Impact of COVID-19 in education |
Filters
Level
| Not in education |
| Early childhood education and care |
| Non-educational programmes (early childhood) |
| Pre-primary |
| Pre-primary and primary |
| Early childhood and primary |
| Pre-primary to tertiary education |
| Primary |
| Primary and lower secondary |
| Primary and secondary |
| Primary to tertiary |
| Primary, secondary and post-secondary non-tertiary education |
| Lower secondary |
| Lower secondary, general |
| Lower secondary, vocational |
| Below upper secondary |
| Lower secondary to post-secondary non-tertiary, general programmes |
| Lower secondary to post-secondary non-tertiary, vocational programmes |
| Upper secondary |
| Upper secondary, general |
| Upper secondary general education, sufficient for partial level completion, without direct access to tertiary education |
| Upper secondary general education, sufficient for level completion, without direct access to tertiary education |
| Upper secondary general education, sufficient for level completion, with direct access to tertiary education |
| Upper secondary, vocational |
| Upper secondary vocational education, sufficient for partial level completion, without direct access to tertiary education |
| Upper secondary vocational education, sufficient for level completion, without direct access to tertiary education |
| Upper secondary vocational education, sufficient for level completion, with direct access to tertiary education |
| Upper secondary and post-secondary non-tertiary |
| Upper secondary and post-secondary non-tertiary, general |
| Upper secondary and post-secondary non-tertiary, vocational |
| Upper secondary and post-secondary non-tertiary, orientation not specified |
| Upper secondary vocational education, school and work-based programmes |
| At least upper secondary |
| Secondary |
| Secondary, general |
| Secondary, vocational |
| Post-secondary non-tertiary |
| Post-secondary non-tertiary, general |
| Post-secondary non-tertiary, vocational |
| Post-secondary non-tertiary vocational education, sufficient for level completion, without direct access to tertiary education |
| Post-secondary non-tertiary vocational education, sufficient for level completion, with direct access to tertiary education |
| Short-cycle tertiary education |
| Short-cycle tertiary education, general |
| Short-cycle tertiary education, vocational |
| Bachelor's or equivalent level |
| Bachelor's or equivalent level, academic |
| Bachelor's or equivalent level, professional |
| Short-cycle tertiary and Bachelor's |
| Bachelor's and Master's or equivalent levels |
| Total tertiary excluding doctoral level |
| Bachelor's to doctorate |
| Master's or equivalent level |
| Master’s or equivalent academic level, long first degree |
| Master's or equivalent level, academic |
| Master's or equivalent level, professional |
| Master's to doctorate |
| Doctoral or equivalent level |
| Total tertiary |
| Lower secondary to tertiary, general programmes |
| Lower secondary to tertiary, vocational programmes |
| Total tertiary education, academic programmes |
| Total tertiary education, professional programmes |
| All levels of education |
| All levels of education + not allocated by level |
| Not allocated by level of education |
| Master's long first degree (LFD) degree |
Age Group
| Early childhood |
| Basic school ages |
| Compulsory school ages |
| 15 year-olds |
| 15-19 year-olds |
| Youths |
| Young adults |
| Adults |
| All ages and age unknown |
Refine the indicator selection after selecting a base theme.
Digital divide
According to PISA 2022, there is 0.81 computer per student in school on average across OECD countries. In Australia, Austria, Canada, New Zealand, the United Kingdom, the United States, El Salvador and Singapore, there is at least one computer per student. By contrast, in Albania, Baku (Azerbaijan), Brazil, Cambodia and Morocco, there is less than one computer per every five students. Students in OECD countries spend on average 25 minutes per day on line at school. In Australia, Denmark, Greece and Sweden, they spend 39 or more minutes per day. By contrast, in Germany, Italy, Japan, Jordan, Korea, Macao, Poland, Shanghai, Singapore, Turkey and Uruguay, at least 50% of students reported never being on line at school. Students in Australia, Brazil, Korea, Singapore, Sweden and the United States perform better in digital reading than in print reading. On average, 38% of adults without computer experience and below upper secondary education are employed. The likelihood of being employed increases with each additional level of education and skills proficiency. The greatest returns associated with increased education and ICT and problem-solving skills are observed in Norway and Poland. In these countries, the odds ratio increases as skills improve, which is not the case in Estonia and the Slovak Republic. Estonia, Hungary, Norway, Poland, Slovenia, Sweden and the United Arab Emirates have the widest gender gaps in digital reading. The more frequently students play one-player video games and collaborative online games, the worse their relative performance on print reading. However, these negative effects may be counterbalanced by positive effects on their ability to navigate through digital texts. In Australia, Chile, Denmark, Mexico, Norway and Abu Dhabi, more than one in two teachers reported that students use ICT "frequently" or "in all or nearly all lessons", while fewer than one in four teachers in Croatia, Finland, France, Israel, Japan, Malaysia and Serbia reported so. Teachers ranked their professional development needs and cited teaching students with special needs first, followed by using ICT for teaching and using new technologies in the workplace. Larger proportions of teachers in Brazil, Italy and Malaysia reported so.
| Education policies: Digital Divide | PISA 2022 Results (Volume II): Learning During - and From - Disruption | PISA 2015 Results (volume II): Policies and Practices for Successful Schools | PISA 2012 Results: Students, Computers and Learning | The ABC of Gender Equality in Education: Aptitude, Behaviour, Confidence | Education at a Glance 2015 (EAG 2015): OECD Indicators | TALIS 2013 Results: An International Perspective on Teaching and Learning |
Select first some countries to compare, choose the chart you wish to display and customise them.
Browser View
Select OECD Countries
| Australia |
| Austria |
| Belgium |
| Belgium (Flanders) |
| Belgium (French) |
| Belgium (excl. Flemish) |
| Canada |
| Alberta (Canada) |
| Canadian provinces |
| Chile |
| Colombia |
| Costa Rica |
| Czechia |
| Denmark |
| Estonia |
| Finland |
| France |
| Germany |
| Greece |
| Hungary |
| Iceland |
| Ireland |
| Israel |
| Italy |
| Japan |
| Korea |
| Latvia |
| Lithuania |
| Luxembourg |
| Mexico |
| Netherlands |
| New Zealand |
| Norway |
| Poland |
| Portugal |
| Slovak Republic |
| Slovenia |
| Spain |
| Sweden |
| Switzerland |
| Türkiye |
| United Kingdom |
| England (UK) |
| Northern Ireland (UK) |
| United States |
| OECD average |
Non-OECD Countries
| G20 average |
| TALIS average |
| TALIS avg. primary education |
| TALIS avg. upper secondary education |
| Albania |
| Algeria |
| Argentina |
| Buenos Aires (Argentina) |
| Azerbaijan |
| Baku (Azerbaijan) |
| Bosnia and Herzegovina |
| Brazil |
| Brunei Darussalam |
| Bulgaria |
| Cambodia |
| China |
| B-S-J-Z (China) |
| Hong Kong (China) |
| Macao (China) |
| Shanghai (China) |
| Chinese Taipei |
| Croatia |
| Dominican Republic |
| Ecuador |
| Egypt |
| El Salvador |
| Georgia |
| Guatemala |
| India |
| Indonesia |
| Jamaica |
| Jordan |
| Kazakhstan |
| Kyrgyz Republic |
| Kosovo |
| Lebanon |
| North Macedonia |
| Malaysia |
| Malta |
| Moldova |
| Mongolia |
| Montenegro |
| Morocco |
| Palestinian Authority |
| Panama |
| Paraguay |
| Peru |
| Philippines |
| Qatar |
| Romania |
| Saudi Arabia |
| Serbia |
| Singapore |
| South Africa |
| Tajikistan |
| Thailand |
| Trinidad and Tobago |
| Tunisia |
| United Arab Emirates |
| Abu Dhabi (UAE) |
| Ukraine |
| Uruguay |
| Uzbekistan |
| Viet Nam |
The data table will display up to four selected countries (unselect the OECD average to have one more).
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for more indicators:Country Profile quick links
Note: These values should be interpreted with care since they are influenced
by countries' specific contexts and trade-offs. In education, there is often no simple
most- or least-efficient model. For instance, the share of private expenditure in
education must be read against other measures designed to mitigate inequities,
such as loans and grants; longer learning time is an opportunity to convey
more and better content to students, but may hinder investments in other important
areas. If you want further information on the nature of different variables, please
take the time to read the analysis and contextual information, available at the website
for each publication.
The OECD average includes only OECD countries which are listed here: http://www.oecd.org/about/membersandpartners/
Reference years displayed in the Education GPS correspond to the most common year of reference among countries for which data is available on each variable. Data for the latest available year is preferred and some countries may have provided data refering to a more recent or late year. To know more about possible exceptions on data please click on the "Download Indicator" link on each variable. When a year of reference corresponds to a school year encompassing two years, the reference reads as follows: 2018 for school year 2017/2018.
*TALIS averages are based on all countries participating in the TALIS survey, including partner countries and economies. This explains the difference between the OECD average and the TALIS average. Data from the TALIS survey and Education at a Glance (EAG) may differ. See Annex E of the TALIS technical report and Annex 3 of EAG 2021 for more details about the data collections.
B-S-J-Z (China) refers to the four PISA-participating provinces/municipalities of the People's Republic of China: Beijing, Shanghai, Jiangsu and Zhejiang.
For additional notes, please refer to annexes in the list of links below the introductory text.
The OECD average includes only OECD countries which are listed here: http://www.oecd.org/about/membersandpartners/
Reference years displayed in the Education GPS correspond to the most common year of reference among countries for which data is available on each variable. Data for the latest available year is preferred and some countries may have provided data refering to a more recent or late year. To know more about possible exceptions on data please click on the "Download Indicator" link on each variable. When a year of reference corresponds to a school year encompassing two years, the reference reads as follows: 2018 for school year 2017/2018.
*TALIS averages are based on all countries participating in the TALIS survey, including partner countries and economies. This explains the difference between the OECD average and the TALIS average. Data from the TALIS survey and Education at a Glance (EAG) may differ. See Annex E of the TALIS technical report and Annex 3 of EAG 2021 for more details about the data collections.
B-S-J-Z (China) refers to the four PISA-participating provinces/municipalities of the People's Republic of China: Beijing, Shanghai, Jiangsu and Zhejiang.
For additional notes, please refer to annexes in the list of links below the introductory text.