The document provides data on access to education globally and by region. Key points include:
- Global primary enrollment reached 90.7% in 2010 but has stagnated since 2008. Sub-Saharan Africa lags other regions at 76.2%.
- 60.7 million primary-age children remained out of school in 2010, over half in sub-Saharan Africa and over 1/5 in South Asia.
- Pre-primary enrollment increased globally to 48.3% but sub-Saharan Africa and Middle East/North Africa lag at under 25%.
- Gender parity has been achieved in primary education globally but secondary enrollment shows a small male bias while tertiary favors females.
Eradicate extreme poverty and hunger Large gender gaps in employment persist and may have been exacerbated by the global financial crisis in some regions Employment-to-population ratio, women and men, 2000-2012 (Percentage) Employment-to-population ratio, women and men, 2000-2012.
Sub-Saharan Africa the Caribbean Caucasus and Central Asia South-eastern Asia Northern Africa Southern Asia Oceania Developed regions Developing regions Gender gap Men Women 74.7 46.6 The lack of data on women’s experiences of poverty and hunger limits the analysis of MDG 1 to women’s employment outcomes. Between 2000 and 2012, women’s employment-to-population ratio declined globally from 48.5 per cent to 47.1 per cent compared to 73.9 and 72.2 per cent for men. In 2012, female employment ratio was still 25.1 percentage points lower than male’s.
North Africa, Southern Asia and Western Asia stand out as regions where women are particularly disadvantaged with gender gaps in employment of 50.0, 48.9 and 48.3 percentage points, respectively. The global financial crisis has contributed significantly to the decline in employment ratio in some regions and has had a significant impact on women. Globally, whereas before the crisis (2000-2007) female employment ratio declined only modestly by 0.1 percentage points (compared to a 0.8 decline for men), between 2007 and 2012, they declined by 1.3 percent-age points compared to 0.9 percentage points decline for men. Proportion of own-account and contributing family workers in total employment, women and men, 2000-2012 (Percentage)
While the share of people in vulnerable employment is decreasing, large gender gaps persist in most regions Proportion of own-account and contributing family workers in total employment, women and men, 2000-2012. Globally the proportion of women in vulnerable employment declined from 55.3 per cent in 2000 to 49.3 in 2012, compared to 50.5 and 47.1 per cent for men. Both the scale of vulnerable employment and the gap be-tween women and men differ widely across regions.
Sub-Saharan Africa, Southern Asia and Oceania have the highest shares of people in vulnerable employment with values of over 80 per cent for women and around 70 per cent for men. The widest gender gaps can be found in Northern Africa and sub-Saharan Africa with 20.6 and 15.6 percentage points, respectively. Due to pervasive occupational segregation, women are overrepresented in low paid jobs, have less access to social protection, and are paid on average less than men for work of equal value. Women’s employment opportunities are further limited by the disproportionate amounts of unpaid care work that they perform.
Contextualising demographic transition in subSaharan AfricaSeamus Grimes
It explores different perspectives on demographic change in the context of sub-Saharan Africa, paying particular attention to the case of Kenya. It will seek to understand the relatively high levels of fertility, mortality and population growth in sub-Saharan Africa, despite the many decades of population programmes focusing on raising levels of contraceptive prevalence. Having explored the different philosophical perspectives, attention will be focused on empirical trends in relation to the dynamics of population change in the region.
24%: that is the proportion of women holding the most senior roles in businesses across the globe. We have been tracking this figure over the past decade and are sorry to report there has been no significant movement. In fact, this figure is exactly the same as 2007, 2009 and 2013, suggesting that women’s ascent up the corporate ladder has returned to its ‘natural level’ following the financial crisis, during which women were disproportionately hit.
Demographic Dividend in Africa: Does it Apply to Malawi?IFPRIMaSSP
Special Seminar by Prof. David Canning: Demographic dividend in Africa: Does it apply to Malawi?
On Friday 5 August 2016, IFPRI-Malawi held a special seminar by Professor David Canning (Professor of Population Science and Professor of Economics & Public Health at Harvard University’s Chan School of Public Health) entitled “Demographic dividend in Africa: Does it apply to Malawi?”. Professor Canning presented on the components of population growth, the Asian economic miracle, the new view on importance of population, health and wealth of nations, the demographic dividend and Africa’s demographic transition.
Plan 2040 Goals: Fostering a Well-Trained and Prosperous PopulationARCResearch
This looks at ARC's Plan 2040 goal of fostering a health, educated and prosperous population. The presentation displays several different indicators that reflect this goal, including educational attainment, the "education gap," as well as health and quality of life of older adults.
How the world views migration - by IOM Global Migration Data Analysis CentreICMPD
"How the World Views Migration" is also about the potential role of diasporas in shaping public opinion on migration. There is a strong influence of public opinion on migration policymaking. Public attitudes towards migration affect migrants (in origin/destination countries) - Migration management includes managing perceptions of migration.
Survey research is difficult in Afghanistan. Violence, illiteracy in both urban and rural areas, cultural constraints, and access to family and women in particular have all been faced by D3 Systems in the process of building a self-sustaining national survey operation in Afghanistan. Grown from an organization capable of simple urban polls of Kabul in 2003 to multistage, nationally representative random survey samples today, D3’s partially-owned subsidiary called the Afghan Center for Socio-Economic Research is a vibrant, busy company conducting research every day throughout Afghanistan. This paper focuses on the various challenges faced by ACSOR operating in Afghanistan. Findings from the 2006 and 2007 nationwide probability samples completed by ACSOR for the Asia Foundation’s Annual Reports on Afghanistan and D3’s research on women’s issues will be included. Particular emphasis will be placed on issues of education, armed violence, lack of familiarity with research, cultural restrictions on women, ethno-linguistic fragmentation, and outdated population data. General results of the D3 Women in Muslim Countries and Asia Foundation surveys are discussed with emphasis on trends across time related to international development issues as they relate to survey research. Among these are human security as Afghans perceive it, the status of women in Afghan society, and education and awareness of democratic practices like public opinion polling among Afghans nationwide. Trends are demonstrated empirically with the Asia Foundation tracking data and supplemented with findings from recent reporting by D3 and the Center for Strategic and International Studies.
Current state of migration in the Mediterranean - Nov 2016 by OECDICMPD
The OECD presents seven migration challenges and opportunities:
1. Continuing emigration from MENA to OECD countries
2. Existence of large diasporas in the OECD
3. Return migration to MENA countries
4. International students
5. Remittances
6. Transit migration in MENA countries
7. Emerging permanent immigration to MENA countries
Eradicate extreme poverty and hunger Large gender gaps in employment persist and may have been exacerbated by the global financial crisis in some regions Employment-to-population ratio, women and men, 2000-2012 (Percentage) Employment-to-population ratio, women and men, 2000-2012.
Sub-Saharan Africa the Caribbean Caucasus and Central Asia South-eastern Asia Northern Africa Southern Asia Oceania Developed regions Developing regions Gender gap Men Women 74.7 46.6 The lack of data on women’s experiences of poverty and hunger limits the analysis of MDG 1 to women’s employment outcomes. Between 2000 and 2012, women’s employment-to-population ratio declined globally from 48.5 per cent to 47.1 per cent compared to 73.9 and 72.2 per cent for men. In 2012, female employment ratio was still 25.1 percentage points lower than male’s.
North Africa, Southern Asia and Western Asia stand out as regions where women are particularly disadvantaged with gender gaps in employment of 50.0, 48.9 and 48.3 percentage points, respectively. The global financial crisis has contributed significantly to the decline in employment ratio in some regions and has had a significant impact on women. Globally, whereas before the crisis (2000-2007) female employment ratio declined only modestly by 0.1 percentage points (compared to a 0.8 decline for men), between 2007 and 2012, they declined by 1.3 percent-age points compared to 0.9 percentage points decline for men. Proportion of own-account and contributing family workers in total employment, women and men, 2000-2012 (Percentage)
While the share of people in vulnerable employment is decreasing, large gender gaps persist in most regions Proportion of own-account and contributing family workers in total employment, women and men, 2000-2012. Globally the proportion of women in vulnerable employment declined from 55.3 per cent in 2000 to 49.3 in 2012, compared to 50.5 and 47.1 per cent for men. Both the scale of vulnerable employment and the gap be-tween women and men differ widely across regions.
Sub-Saharan Africa, Southern Asia and Oceania have the highest shares of people in vulnerable employment with values of over 80 per cent for women and around 70 per cent for men. The widest gender gaps can be found in Northern Africa and sub-Saharan Africa with 20.6 and 15.6 percentage points, respectively. Due to pervasive occupational segregation, women are overrepresented in low paid jobs, have less access to social protection, and are paid on average less than men for work of equal value. Women’s employment opportunities are further limited by the disproportionate amounts of unpaid care work that they perform.
Contextualising demographic transition in subSaharan AfricaSeamus Grimes
It explores different perspectives on demographic change in the context of sub-Saharan Africa, paying particular attention to the case of Kenya. It will seek to understand the relatively high levels of fertility, mortality and population growth in sub-Saharan Africa, despite the many decades of population programmes focusing on raising levels of contraceptive prevalence. Having explored the different philosophical perspectives, attention will be focused on empirical trends in relation to the dynamics of population change in the region.
24%: that is the proportion of women holding the most senior roles in businesses across the globe. We have been tracking this figure over the past decade and are sorry to report there has been no significant movement. In fact, this figure is exactly the same as 2007, 2009 and 2013, suggesting that women’s ascent up the corporate ladder has returned to its ‘natural level’ following the financial crisis, during which women were disproportionately hit.
Demographic Dividend in Africa: Does it Apply to Malawi?IFPRIMaSSP
Special Seminar by Prof. David Canning: Demographic dividend in Africa: Does it apply to Malawi?
On Friday 5 August 2016, IFPRI-Malawi held a special seminar by Professor David Canning (Professor of Population Science and Professor of Economics & Public Health at Harvard University’s Chan School of Public Health) entitled “Demographic dividend in Africa: Does it apply to Malawi?”. Professor Canning presented on the components of population growth, the Asian economic miracle, the new view on importance of population, health and wealth of nations, the demographic dividend and Africa’s demographic transition.
Plan 2040 Goals: Fostering a Well-Trained and Prosperous PopulationARCResearch
This looks at ARC's Plan 2040 goal of fostering a health, educated and prosperous population. The presentation displays several different indicators that reflect this goal, including educational attainment, the "education gap," as well as health and quality of life of older adults.
How the world views migration - by IOM Global Migration Data Analysis CentreICMPD
"How the World Views Migration" is also about the potential role of diasporas in shaping public opinion on migration. There is a strong influence of public opinion on migration policymaking. Public attitudes towards migration affect migrants (in origin/destination countries) - Migration management includes managing perceptions of migration.
Survey research is difficult in Afghanistan. Violence, illiteracy in both urban and rural areas, cultural constraints, and access to family and women in particular have all been faced by D3 Systems in the process of building a self-sustaining national survey operation in Afghanistan. Grown from an organization capable of simple urban polls of Kabul in 2003 to multistage, nationally representative random survey samples today, D3’s partially-owned subsidiary called the Afghan Center for Socio-Economic Research is a vibrant, busy company conducting research every day throughout Afghanistan. This paper focuses on the various challenges faced by ACSOR operating in Afghanistan. Findings from the 2006 and 2007 nationwide probability samples completed by ACSOR for the Asia Foundation’s Annual Reports on Afghanistan and D3’s research on women’s issues will be included. Particular emphasis will be placed on issues of education, armed violence, lack of familiarity with research, cultural restrictions on women, ethno-linguistic fragmentation, and outdated population data. General results of the D3 Women in Muslim Countries and Asia Foundation surveys are discussed with emphasis on trends across time related to international development issues as they relate to survey research. Among these are human security as Afghans perceive it, the status of women in Afghan society, and education and awareness of democratic practices like public opinion polling among Afghans nationwide. Trends are demonstrated empirically with the Asia Foundation tracking data and supplemented with findings from recent reporting by D3 and the Center for Strategic and International Studies.
Current state of migration in the Mediterranean - Nov 2016 by OECDICMPD
The OECD presents seven migration challenges and opportunities:
1. Continuing emigration from MENA to OECD countries
2. Existence of large diasporas in the OECD
3. Return migration to MENA countries
4. International students
5. Remittances
6. Transit migration in MENA countries
7. Emerging permanent immigration to MENA countries
Education at a Glance is the authoritative source for information on the state of education around the world. It provides key information on the output of educational institutions; the impact of learning across countries; the financial and human resources invested in education; access, participation and progression in education; and the learning environment and organisation of schools.
The 2016 edition introduces a new indicator on the completion rate of tertiary students and another one on school leaders. It provides more trend data and analysis on diverse topics, such as: teachers’ salaries; graduation rates; expenditure on education; enrolment rates; young adults who are neither employed nor in education or training; class size; and teaching hours. The publication examines gender imbalance in education and the profile of students who attend, and graduate from, vocational education.
The report covers all 35 OECD countries and a number of partner countries (Argentina, Brazil, China, Colombia, Costa Rica, India, Indonesia, Lithuania, the Russian Federation, Saudi Arabia and South Africa).
This edition includes more than 125 figures and 145 tables. The Excel™ spreadsheets used to create them are available via the StatLinks provided throughout the publication. More data is available in the OECD Education Statistics database.
Education at a Glance is the authoritative source for information on the state of education around the world. It provides key information on the output of educational institutions; the impact of learning across countries; the financial and human resources invested in education; access, participation and progression in education; and the learning environment and organisation of schools.
The 2016 edition introduces a new indicator on the completion rate of tertiary students and another one on school leaders. It provides more trend data and analysis on diverse topics, such as: teachers’ salaries; graduation rates; expenditure on education; enrolment rates; young adults who are neither employed nor in education or training; class size; and teaching hours. The publication examines gender imbalance in education and the profile of students who attend, and graduate from, vocational education.
The report covers all 35 OECD countries and a number of partner countries (Argentina, Brazil, China, Colombia, Costa Rica, India, Indonesia, Lithuania, the Russian Federation, Saudi Arabia and South Africa).
This edition includes more than 125 figures and 145 tables. The Excel™ spreadsheets used to create them are available via the StatLinks provided throughout the publication. More data is available in the OECD Education Statistics database.
Publication de référence sur l’état de l’éducation dans le monde, Regards sur l’éducation fournit des données clés sur : les résultats des établissements d’enseignement ; l’impact de l’apprentissage dans les différents pays ; les ressources financières et humaines investies dans l’éducation ; l’accès, la participation et la progression au sein des systèmes d’éducation ; l’environnement d’apprentissage ; et l’organisation scolaire.
Cette édition 2016 présente de nouveaux indicateurs, notamment sur les taux de réussite des étudiants dans l’enseignement tertiaire et les chefs d’établissement. Elle offre également de nouvelles données tendancielles et analyses sur différents thèmes, dont : le salaire des enseignants ; les taux d’obtention d’un diplôme ; les dépenses d’éducation ; les taux de scolarisation ; les jeunes adultes sans emploi ne suivant ni études ni formation ; la taille des classes ; et le nombre d’heures d’enseignement. La publication analyse en outre les déséquilibres entre les sexes dans le domaine de l’éducation, ainsi que le profil des élèves/étudiants des filières professionnelles et de leurs diplômés.
Ce rapport couvre l’ensemble des 35 pays de l’OCDE ainsi qu’un certain nombre de pays partenaires (Afrique du Sud, Arabie saoudite, Argentine, Brésil, Chine, Colombie, Costa Rica, Fédération de Russie, Inde, Indonésie et Lituanie).
Cette édition inclut plus de 125 graphiques et 145 tableaux. Les fichiers Excel™ qui ont servi à leur création sont disponibles via les liens StatLinks fournis tout au long de la publication, corpus que vient compléter la Base de données statistique de l’OCDE sur l’éducation.
Presentación-Conferencia de prensa de Gabriela Ramos,
Consejera Especial del Secretario General,
Directora de Gabinete y Sherpa de la OCDE
14 de septiembre de 2016
Priorities for Equity and Inclusion? Quality in Early Childhood Care and Educ...Young Lives Oxford
Keynote speech by Renu Singh at the British Association of Comparative and International Education conference, 10 Sept 2014.
The importance of early development in shaping children's education outcomes is widely acknowledged. The Dakar Framework for Action reinforced the call for 'expanding and improving comprehensive early childhood care and education, especially for the most vulnerable and disadvantaged children'. Building an enabling policy environment which focuses on equity and equality in allocations and interventions is essential if the rights of every young child are to be promoted.
What is TransMonEE - A database capturing a vast range of in-formation on social and economic issues relevant to the situation and wellbeing of children, adolescents and women in 28 countries of Central and Eastern Europe, Commonwealth of Independent States and the European Union.
The database represents a useful tool for governments, civil soci-ety organizations, donors and academia to better orient their decisions, policies, programmes and agendas. The database is up-dated every year thanks to the collaboration of national statistical offices (NSOs). The published data are only a selection of the larger amount of indicators annually collected.
Proximate Determinants of Fertility in Eastern Africa: The case of Kenya, Rw...Scientific Review SR
This study presents some determinants of fertility for three countries in east Africa. It examines the
role of the proximate determinants of fertility to total births during last five years before the surveys in Kenya,
Rwanda and Tanzania. The study is based on the analysis of secondary data obtained from Demographic and
Health Surveys in the three countries. The surveys were conducted between 2014 and 2016. The response
variable used in this study is the number of births in the last five years before the survey. The study employed
Quasi-Poisson regression model as the main method of data analysis. The results show that place of residence,
working status, number of union, age at first birth, age at first cohabitation, age at first sex, contraceptive use
and intention, unmet need and educational level mothers are significant determinants of fertility. Moreover, the
findings of this study indicate that educational level of mothers has negative impact on fertility. For current
contraceptive users, the mean birth for the last five years is highest for Kenya followed by Tanzania. For those
who never use contraception, the mean births for the last five years for Rwanda is lower as compared to
Tanzania and Kenya. The mean births for working mothers is also lower than that of non-working mothers for
all three countries. The study suggests that improving the educational level of mothers, increasing the use of
contraception, and involving more women to work force can reduce fertility in the three countries.
We welcomed Dr Jeanette Botha (University of South Africa) to the Centre to conduct a presentation and a discussion on issues around the ‘digital divide’ within South Africa (something likely to be an issue in other countries around the world). The main thrust of the talk was: “Who are we teaching?” Dr Botha alluded to the issue of technology driving education vs education driving technology and highlighted numerous concerns of developing world ODL practitioners and students, contextualizing ODEL in South Africa in the current socio-economic framework, with reference to Unisa. The argument was made for the pragmatic consideration of the acquisition and use of appropriate technologies in line with these “real world” considerations.
Education Series Volume IV: Early Childhood Development in South Africa, 2016Statistics South Africa
“If we are to break the cycle of poverty, we need to educate the children of the poor.” – President Cyril Ramaphosa, SoNA 2018
The first one thousand days in a child’s life could hold the key to unlocking his/her life-long potential. By the age of 5, almost 90% of a child’s brain will be developed. These are the formative years where factors such as adequate healthcare, good nutrition, good quality childcare and nurturing, a clean and safe environment, early learning and stimulation will, to a large extent, influence his/her future as an adult.
Read more here:
http://www.statssa.gov.za/?p=10950
IIEP-UNESCO Strategic Debate: the impact of inequalities on learning achievementIIEP-UNESCO
Towards progressive universalism: the impact of inequalities on learning achievement.
IIEP Strategic Debate - May 2017
Speaker: Pauline Rose, Director, Research for Equitable Access and Learning (REAL) Centre, University of Cambridge
Moderator: Suzanne Grant Lewis (Director IIEP)
Drawing on analysis of available large-scale datasets, this session will show how inequalities in learning between the rich and poor and, amongst the poor by gender, widen substantially over the primary school cycle. It will also identify that children with disabilities are most likely to be left behind. The evidence further demonstrates that access to higher education for children from poor households is strongly dependent on their learning in the early years. Analysis will be presented showing that, where children from poor backgrounds have the same opportunities as those from rich backgrounds, learning gaps narrow significantly. It will further identify the importance of changing the way in which public resources are allocated, to achieve ‘progressive universalism’. The Debate will conclude by identifying ways in which data collection could be improved in resource-poor environments to enable better monitoring of education SDGs related to learning, with a focus on tracking progress for the most disadvantaged groups.
Datos de la población mundial 2015. (Population Reference Bureau) 2015 worl...Juan Martín Martín
Datos de la Población Mundial en 2015. Datos de todos los países del Mundo. gráficos, pirámides de población, natalidad, mortalidad, fecundidad, esperanza de vida, maternidad, envejecimiento, previsiones mundiales, etc.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
2. Access to Education: Indicators
This presentation includes data on:
Total enrollments by region
Out of School Children (OOS) of primary
school age
Net Enrollment Rates (NER)/Gross
Enrollment Rates (GER)
Correlations between GDP per capita and
enrollment rates for each educational level
Education equality: Income/gender/location
disparities in education access
3. Acronym Guide
Acronym Name
EAP East Asia and Pacific
ECA Europe and Central Asia
LAC Latin American and the Caribbean
MNA Middle East and North Africa
SAS South Asia
SSA Sub-Saharan Africa
WLD World (Global Aggregate)
GER Gross Enrollment Rate
NER Net Enrollment Rate
OOS Out of School
GNI p.c. Gross National Income per capita
NAR Net Attendance Rate
GAR Gross Attendance Ratio
GPI
Gender Parity Index (female value/male
value)
4. Summary
Less than half of the world’s pre-primary age
students were enrolled in pre-primary education in
2010 (48.3%), but enrolment rates have been rising
over time. SSA and MNA’s enrolment rates lag far
behind other regions with less than ¼ of pre-primary
age children enrolled.
In 2010, 90.7% of primary age students worldwide
were enrolled in school. The rate has improved
since 2000 (84.5%), but little progress has been
made since 2008.
60.7 million primary school age children were out of
school (OOS) in 2010. Over half of the world's out
of school children live in SSA and over 1/5 live in
South Asia.
Since 2008, the global rate of children out of school
has remained the same at 9.3%.
5. Summary
(continued)
62.5% of secondary school age students were
enrolled in 2010, which was an 9.4 percentage point
improvement over 2000. SSA lags far behind other
regions in secondary enrollments with just over ¼ of
students enrolled in 2010.
The global tertiary gross enrollment rate (GER) has
gradually improved from 19% in 2000 to 29.2% in
2010 but GERs vary greatly across regions. More
than half of youth are enrolled in ECA (55.6%)
compared to 6.8% of youth in SSA.
On the global level, gender parity in pre-primary
and primary enrolment rates has been achieved.
There is a small male bias in secondary enrolment
rates (GPI = 0.96) and a female bias in tertiary
enrolments (GPI = 1.08).
7. How many children are enrolled in
pre-primary education?
Around 164 million
children were enrolled in
pre-primary education in
2010. This is up from
134 million in 2005 and
112 million in 1999.
Over half of enrolled
students were in either
SAS or EAP (48 and 40
million respectively).
25% of total pre-primary
enrollments were in India
and 16% were in China.
79 million (48.2%) were
girls.
EAP
24.3%
ECA
6.4%
HIC
18.1%
LAC
12.5%MNA
2.0%
SAS
29.1%
SSA
7.6%
Share of Total Pre-Primary
Enrollments by Region (%)
2010
Source: UNESCO Institute for Statistics in EdStats, November 2012;
Notes: Regional aggregates are World Bank regions;
HIC = high income countries in all geographic regions.
8. How many children are enrolled?
Pre-Primary – Gross Enrolment Rates (GER)
Globally, less than half of
pre-primary age students
were enrolled in pre-
primary education in
2010, but all regions
increased pre-primary
enrolments between
2000 and 2010.
SAS almost doubled its
pre-primary GER
between 2000 (25.4%)
and 2010 (48.3%).
LAC’s GERs are
consistently the highest
among regions ranging
from 56.8% to 70.1%.
SSA and MNA lag
behind other regions with
17.7% and 23.8% GERs
respectively in 2010.
Pre-Primary Gross Enrolment Rates have
increased in all regions since 2000
34.1 34.7
37.1
40.9
45.6
48.3
0
10
20
30
40
50
60
70
80
2000 2002 2004 2006 2008 2010
GrossEnrolmentRate.Pre-Primary.Total(%)
Source: UNESCO Institute for Statistics in EdStats, November 2012
EAP ECA LAC MNA SAS SSA WLD
9. Which countries have the lowest
pre-primary enrollment rates?
8 of the 10 countries
with the lowest pre-
primary net enrolment
rates (NER) are in SSA.
Of the 130 countries
with data, 18 countries
had less than 10% of
their children enrolled in
pre-primary education.
36 countries had less
than 25% of their
children enrolled in pre-
primary.
19 countries had pre-
primary enrollments
higher than 90%.
10 Countries with the Lowest Pre-
Primary Net Enrollment Rates
(2009-2011)
1 Yemen, Rep. 0.35
2 Chad 1.77
3 Burkina Faso 2.75
4 Mali 3.37
5 Djibouti 3.41
6 Cote d'Ivoire 3.54
7 Ethiopia 3.92
8 Guinea-Bissau 4.68
9 Niger 4.76
10 Central African Republic 5.64
Source: UNESCO Institute for Statistics in EdStats, Nov 2012
Notes: Purple data is for 2011; Black is 2010; Blue is 2009;
Data were not available for 84 of 214 countries.
10. Which countries have increased pre-
primary enrollment rates the most?
These countries
have increased their
pre-primary GERs
by 25 to 66
percentage points
between 1999-2001
and 2009-2011.
Half of the countries
at least doubled
their NER over time.
Algeria improved
from 3.4% to 66% –
a 1928%
improvement.
Only two of these
countries have a
current NER over
90% – Barbados
and Maldives.
10 Countries with the Most
Improvement in Pre-Primary
Net Enrollment Rates
Percentage
Points
Improved
1999-
2001
NER
2009-
2011
NER
%
Improved
1 Algeria 66.1 3.4 69.5 1927.9
2 Korea, Rep. 41.0 44.0 85.0 93.0
3 Moldova 37.3 36.8 74.0 101.4
4 Barbados 33.6 62.1 95.7 54.0
5 Sao Tome & Principe 32.4 24.2 56.5 133.8
6 Maldives 30.8 61.4 92.2 50.1
7 Mongolia 29.1 28.4 57.5 102.5
8 Nicaragua 26.7 28.6 55.4 93.5
9 Ghana 26.0 21.5 47.5 120.7
10 Uruguay 25.4 52.9 78.3 48.0
Source: UNESCO Institute for Statistics in EdStats, November 2012;
Note: Data were not available for 118 of 213 countries.
11. Net Enrollment Rate. Pre-Primary (%)
The maps displayed were produced by EdStats. The boundaries, colors, denominations and any
other information shown on this map do not imply, on the part of the World Bank Group, any
judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries.
The maps are for reference only.
Source: UNESCO Institute for Statistics in EdStats, 2012
Note: Data displayed is for the latest available year (2008-2011)
12. Are lower pre-primary enrollment rates
related to lower national income per
capita?
All the low income
countries ($1025 or less)
have less than 16% of
children enrolled in pre-
primary education except
Gambia (27%), Kenya
(29%), and Tanzania
(33%).
24 countries had NERs
less than 15%. Only 4 of
those had GNI per capita
higher than $1100. All
the countries were lower
than $4780 (Bosnia).
All of the countries with
NERs higher than 90%
had GNI greater than
$12,000 except Thailand,
Grenada, and Maldives.
All low income countries had less than one-third of
children enrolled in pre-primary education.
R² = 0.229
0
20
40
60
80
100
0 20 40 60 80
NetEnrollmentRate.Pre-Primary.Total
GNI per capita, Atlas method (current US$)
Source: UNESCO Institute for Statistics in EdStats, Nov. 2012
Note: Data is for the most recent year between 2009 and 2011.
Source: UNESCO Institute for Statistics in EdStats, Nov. 2012
Note: Data is for the most recent year between 2009 and 2011.
Ireland
Switzerland
Qatar
Australia
Norway
13. Do gender disparities exist in pre-
primary enrollment rates?
Gender parity indices
(GPIs) are calculated by
dividing the female value
for an indicator by the
male value, so perfect
gender parity equals 1.
A value below 1
indicates a bias toward
males. A value above 1
indicates a bias toward
females.
Globally, the GPI has
been increasing from .98
in 2000 to perfect
gender parity (1.0) in
2010.
Most regions are very
close to gender parity
(+/- 0.02) in 2010. Only
MNA lags behind.
4 of 6 regions have a
slight female bias.
Gender parity in pre-primary enrolments (1.0) has
been achieved globally and in most regions.
0.98
0.99
0.99
0.99
0.99
1.00
0.75
0.80
0.85
0.90
0.95
1.00
1.05
2000 2002 2004 2006 2008 2010
GenderParityIndex(GPI)forGrossEnrolmentRatio.Pre-Primary
Source: UNESCO Institute for Statistics in EdStats, November 2012
WLD EAP ECA LAC MNA SAS SSA
Female Bias
Male Bias
14. Do rural/urban disparities exist in pre-
primary attendance rates in ECA?
Source: Demographic and Health Surveys and Multiple Indicator Cluster Surveys In World Inequality Database on Education (WIDE), Nov. 2012
% of 3 to 4 year olds attending any type of pre–primary education program
15. Do income disparities exist in pre-
primary attendance rates in SSA?
Source: Demographic and Health Surveys and Multiple Indicator Cluster Surveys In World Inequality Database on Education (WIDE), Nov. 2012
% of 3 to 4 year olds attending any type of pre–primary education program
17. How many children are enrolled in
primary schools?
Around 691 million
children were enrolled in
primary school in 2010.
This is up from 685
million in 2005 and 655
million in 2000.
Over half of enrolled
students were in either
SAS or EAP (182 and
172 million respectively).
21% of total primary
enrollments were in India
and 15% were in China.
330 million (47.7%) were
girls.
EAP
24.9%
ECA
3.0%
LAC
9.6%
MNA
5.5%
SSA
20.0%
SAS
26.4%
HIC
10.6%
Share of Total Primary Enrollments
by Region (%)
2010
Source: UNESCO Institute for Statistics in EdStats, November 2012
Notes: Regional aggregates are World Bank regions;
HIC = high income countries in all geographic regions.
18. In 2010, 90.7% of
primary school age
children around the
world were enrolled in
primary or secondary
education.
This figure rose each
year between 1999
(83.7%) and 2008, but
the figure remained
unchanged between
2008 and 2010.
All regions have
increased ANERs since
2000, but SSA and
SAS improved the most
– 16 percentage points
in SSA and 14
percentage points in
SAS.
Continued…
Have primary enrolments improved?
Primary – Adjusted Net Enrollment Rates (ANER)
Primary Enrolment Rates have increased since
2000, but little progress has been made since 2008.
84.5
85.5
88.7 89.1
90.7 90.7
60
65
70
75
80
85
90
95
100
2000 2002 2004 2006 2008 2010
AdjustedNetEnrolmentRate.Primary.Total(%)
Source: UNESCO Institute for Statistics in EdStats, November 2012
EAP ECA LAC MNA SAS SSA WLD
19. Since 2008, SSA has
only improved by 0.1%
and SAS by 0.4%.
SAS's improvement
moved it closer to other
regions by 2010
(92.3%), but SSA still
lags far behind with a
ANER of 76.2% in
2010.
ECA’s ANER peaked in
2002 at 96.6% and has
been lower since.
EAP and LAC are the
only 2 regions with
ANERs higher than
95% in 2010.
Have primary enrolments improved?
Primary – Adjusted Net Enrollment Rates (ANER)
84.5
85.5
88.7 89.1
90.7 90.7
60
65
70
75
80
85
90
95
100
2000 2002 2004 2006 2008 2010
AdjustedNetEnrolmentRate.Primary.Total(%)
Source: UNESCO Institute for Statistics in EdStats, November 2012
EAP ECA LAC MNA SAS SSA WLD
Primary Enrolment Rates have increased since
2000, but little progress has been made since 2008.
20. Which countries have the lowest
primary enrollment rates?
In the top 2 countries
(Eritrea and
Djibouti), less than half
of primary school age
children are enrolled in
primary school.
All of the countries with
the lowest adjusted net
enrollment rates (ANER)
are in SSA except
Djibouti.
Of the 20 countries with
the lowest primary
ANERs,15 are in SSA.
There is a large range
among the listed
countries: #10 Gambia’s
ANER almost doubles
#1 Eritrea’s.
10 Countries with the Lowest
Primary Enrollment Rates
(2009-2011)
1 Eritrea 34.9
2 Djibouti 44.6
3 Equatorial Guinea 56.3
4 Nigeria 57.6
5 Cote d'Ivoire 61.5
6 Niger 62.5
7 Burkina Faso 63.2
8 Mali 67.2
9 Central African Republic 68.9
10 Gambia, The 69.3
Source: UNESCO Institute for Statistics in EdStats, Nov 2012
Notes: Data is Adjusted Net Enrolment Rate. Primary (ANER);
Purple figures are for 2011; Black = 2010; Blue = 2009.
Data were not available for 67 of 214 countries.
21. Which countries have increased
primary enrollment rates the most?
These countries have
increased their
primary ANERs by 22
to 42 percentage
points between
1999/2000 and
2010/2011.
Ethiopia and Niger
more than doubled
their ANERs, but more
than 1/3 of children
are still not enrolled in
Niger.
Only Zambia has
increased its ANER to
over 90%. All the
countries need to
continue improving to
reach universal
primary enrolment.
10 Countries with the Most
Improvement in Primary
Enrollment Rates
Percentage
Points
Improved
1999/
2000
ANER
2010/
2011
ANER
%
Improved
1 Ethiopia 41.8 40.4 82.2 103.4
2 Niger 35.4 27.1 62.5 130.5
3 Mozambique 33.9 56.0 89.8 60.5
4 Bhutan 30.8 58.5 89.3 52.7
5 Guinea 30.1 46.9 77.0 64.1
6 Burkina Faso 28.7 34.5 63.2 83.0
7 Mali 25.0 42.2 67.2 59.1
8 Guinea-Bissau 23.8 51.2 75.0 46.5
9 Zambia 21.7 71.0 92.7 30.6
10 Yemen, Rep. 21.5 56.7 78.2 37.8
Source: UNESCO Institute for Statistics in EdStats, Nov. 2012;
Notes: Purple is 2011/1999 data; Black is 2010/2000;
Data were not available for 104 of 214 countries.
22. Adjusted Net Enrollment Rate. Primary (%)
The maps displayed were produced by EdStats. The boundaries, colors, denominations and any
other information shown on this map do not imply, on the part of the World Bank Group, any
judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries.
The maps are for reference only.
Source: UNESCO Institute for Statistics in EdStats, 2012
Note: Data displayed is for the latest available year (2008-2011)
23. Do countries with low national income
per capita have low primary enrollments?
Low income does not
necessarily indicate
lower primary enrolment
rates: Countries with the
lowest gross national
income (GNI) per capita
(<$500) have ANERs
ranging from 35%
(Eritrea) to 97.5%
(Malawi).
Countries with the
lowest primary ANERs
(less than 75%) have
GNI p.c. less than
$1270. Equatorial
Guinea is the only
exception with 56.3%
primary ANER and
$14,540 GNI pc.
There is no clear association between low national
income p.c. and low primary enrollment rates.
R² = 0.098
30
40
50
60
70
80
90
100
0 5 10 15 20 25 30 35 40 45 50 55
AdjustedNetEnrollmentRate.Primary.Total
GNI per capita, Atlas method (current US$)
Source: UNESCO Institute for Statistics in EdStats, Nov. 2012
Note: ANER data are for the most recent year between 2009 and 2011.
Equitorial Guinea
Eritrea
Macao, China SAR
Djibouti
Nigeria
24. Which regions have reached gender
parity in primary enrollments?
Gender parity indices
(GPIs) are calculated by
dividing the female value
for an indicator by the
male value, so perfect
gender parity equals 1.
A value below 1
indicates a bias toward
males. A value above 1
indicates a bias toward
females.
Globally, the GPI has
been increasing from .93
in 1999 to .98 in 2010.
Most regions are very
close to gender parity
(+/- 0.03). Only MNA
and SSA lag behind.
EAP, ECA, and LAC
have achieved gender
parity in primary (+/-
0.02).
All regions except MNA and SSA are within 0.03 of
gender parity in primary enrollments.
0.93
0.93
0.94 0.94
0.96
0.97
0.97
0.97 0.97
0.98
0.98
0.80
0.82
0.84
0.86
0.88
0.90
0.92
0.94
0.96
0.98
1.00
1.02
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
GenderParityIndex(GPI)forAdjustedNetEnrolmentRate.Primary
Source: UNESCO Institute for Statistics in EdStats, November 2012
WLD EAP ECA LAC MNA SAS SSA
Female Bias
Male Bias
25. 0.65
0.70
0.75
0.80
0.85
0.90
0.95
1.00
1.05
1.10
1.15
GenderParityIndex(GPI)forGrossEnrolmentRatio.Primary
Source: UNESCO Institute for Statistics in EdStats, September, 2012
Note: Data points are the most recent year with data available (2008-
2011)
Have most countries reached gender
parity in primary enrollments?
Half of countries with
data have already
achieved gender parity
(+/- .02).
78% of countries with
data are within 0.05 of
gender parity.
Many more countries
have a bias toward
males in primary
enrolments (GPI<1).
Afghanistan has the
largest male bias at .69
followed by Central
African Rep. and Chad
at .73.
San Marino has the
highest female bias at
1.134.
78% of countries are within 0.05 of gender parity in
primary enrollments.
Female
Bias
Male Bias
26. Which countries have the largest gender
disparities in primary enrolment rates?
The male primary
gross enrolment rate
in these countries is
much higher than the
female gross
enrolment rate.
7 of 10 countries are
in SSA. 2 are in
South Asia and 1 is
in MNA.
Of the 20 countries
with the lowest GPIs
(GPI<0.9),14 are in
SSA, 2 are in SAS, 2
are in EAP (Togo and
PNG), and 1 is in
LAC (Dominican
Republic).
10 Countries with the Largest Gender
Disparities in Primary Enrollment Rates
(2008-2011)
1 Afghanistan 0.694
2 Central African Republic 0.725
3 Chad 0.729
4 Angola 0.813
5 Yemen, Rep. 0.817
6 Pakistan 0.818
7 Cote d'Ivoire 0.833
8 Niger 0.837
9 Guinea 0.838
10 Eritrea 0.838
Source: UNESCO Institute for Statistics in EdStats, September 2012;
Notes: Data is GPI for Primary Gross Enrolment Rate; Black figures are 2011
data; Blue=2010; Data were not available for 71 of 214 countries.
27. Which countries have decreased
gender disparity in primary the most?
These countries have
moved from 0.14 to
0.25 percentage
points closer to
gender parity (1)
between 2000/2001
and the most recent
data year.
6 of the 10 countries
are in SSA; 2 are in
MNA and 2 in South
Asia.
Senegal now has
higher female
enrollment rates than
male enrollment rates
(1.06).
Burundi and India
have reached gender
parity.
10 Countries with the Most Improvement
Toward Gender Parity in Primary
Enrollments
Percentage
Points
Improved
2000 or
2001
GPI
Most
current
GPI
%
Improved
1 Sierra Leone 0.25 0.67 0.93 37.53
2 Ethiopia 0.22 0.69 0.91 32.73
3 Burkina Faso 0.20 0.73 0.93 27.50
4 Benin 0.20 0.67 0.87 29.66
5 Yemen, Rep. 0.19 0.63 0.82 30.55
6 Burundi 0.19 0.80 0.99 23.64
7 Senegal 0.17 0.89 1.06 19.31
8 India 0.15 0.85 1.00 17.61
9 Pakistan 0.15 0.67 0.82 21.79
10 Djibouti 0.14 0.76 0.90 18.84
Source: UNESCO Institute for Statistics in EdStats, Sept. 2012;
Notes: Most current GPI is the most recent data point for 2008-2011;
Data were not available for 54 of 213 countries.
28. Do gender, income, or location disparities
exist in primary attendance rates?
EAP, ECA, LAC, and
MNA do not have large
disparities in primary net
attendance rates (NAR)
between
genders, rural/urban
locations, or top/bottom
income quintiles.
The largest disparities in
most regions are
associated with income.
In SSA and SAS, there
is a 20 percentage point
difference between the
top/bottom income
quintiles.
Rural students in SSA
also have NARs that are
12 percentage points
lower than urban
students.2
Gender, income and location disparities are small
in all regions except except SAS and SSA.
-2
0
2
4
6
8
10
12
14
16
18
20
EAP ECA LAC MNA SAS SSA
PercentagePointDifferenceinNetAttendanceRate.Primary
(Male-Female,Urban-Rural,andQuintile1-Quintile5)
Gender disparity
Location disparity
Income disparity
Source: Estimated by Porta (2011) using data from Demographic and Health
Surveys, Multiple Indicator Cluster Surveys, and Living Standards
Measurement Studies for 1985-2007
29. In 1999, 16% of
primary school age
children were OOS.
42% of children in SSA
and almost a quarter of
children in SAS were
OOS.
By 2010, 9.3% of
children were OOS
globally, but SSA’s rate
was still much higher at
23.8%.
Most of the progress in
reducing the rate of
children OOS occurred
between 1999 and
2008. Since
2008, global and
regional rates have
basically remained the
same.
Which regions have the highest
percentage of children out-of-school?
Rates of Children Out-of-School have decreased
since 1999, but progress has slowed since 2008.
16.3
15.5
15.1
14.5
13.1
11.3
11.1 10.9
10.1
9.3 9.3
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
45.0
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Out-of-schoolrateforchildrenofprimaryschoolage(%).Total
Source: UNESCO Institute for Statistics in Edstats, November 2012
WLD EAP ECA LAC MNA SAS SSA
30. Which countries have highest rates of
children out-of-school?
More than half of primary-
school age children are
out of school in Eritrea
and Djibouti.
More than a quarter of
primary school aged
children are out-of-school
in 14 countries.
47 countries have more
than 10% of children out-
of-school.
Nine of ten countries are
in SSA.
10 Countries with the Highest
Rates of Children Out-of School
(2009-2011)
1 Eritrea 65.1
2 Djibouti 55.4
3 Equatorial Guinea 43.7
4 Nigeria 42.4
5 Cote d'Ivoire 38.5
6 Niger 37.5
7 Burkina Faso 36.8
8 Mali 32.8
9 Central African Republic 31.1
10 Gambia, The 30.7
Source: UNESCO Institute for Statistics in EdStats, Nov 2012
Notes: Data displayed is the most current year available; Purple is
2011; Black is 2010; Blue is 2009; Green is 2008; Data was not
available for 61 of 214 countries.
31. Out-of-school rate for children of
primary school age (%)
The maps displayed were produced by EdStats. The boundaries, colors, denominations and any
other information shown on this map do not imply, on the part of the World Bank Group, any
judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries.
The maps are for reference only.
Source: UNESCO Institute for Statistics in EdStats, Nov. 2012
Note: Data displayed is for the latest available year (2008-2011)
32. Which region has the most out of
school (OOS) children?
In 2010, ¾ of the world’s
out-of-school (OOS)
children lived in two
regions: SSA and SAS.
Over half (55%) of the
world's out of school
children lived in SSA.
ECA had the smallest
percentage of the
world’s OOS children at
1.8% followed by MNA
(3.9%) and LAC (4.4%).
Out-of-School Children of Primary
School Age by Region (2010)
EAP
10.6%
6 Million
ECA
1.8%
LAC
4.4%
MNA
3.9%
SAS
21.8%
13 Million
SSA
54.4%
33 Million
HIC
3.1%
Source: UNESCO Institute for Statistics in EdStats, November 2012
Notes: Regional aggregates are World Bank regions;
33. How many primary school age
children are out of school (OOS)?
In 1999, 107.7 million
children were out of
primary school.
The total decreased
to 72.6 million in
2005 and 60.7
million in 2010.
There were 47 million
fewer children OOS
in 2010 than in 1999.
Since 2008, the
global number of
out-of-school
children has grown
from 60.66 million to
60.69 million (2009)
and 60.73 million in
2010.
The total number of out-of-school children has
decreased by 47 million since 1999.
0
10
20
30
40
50
60
70
80
90
100
110
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Out-of-SchoolChildren.Primary.Total(inmillions)
Source: UNESCO Institute for Statistics in EdStats, November 2012
Note: HIC = High Income Countries in all regions
HIC ECA LAC MNA EAP SAS SSA
34. How much have regions decreased
the total number of OOS children?
SAS and MNA more
than halved the total
number of OOS
children between 1999
and 2010. In SAS, the
total number of OOS
children decreased by
25.6 million or 66%.
SSA decreased the
total number by 12.3
million, which was a
27% decrease between
1999 and 2010, but the
total number increased
by 1.5 million between
2008 and 2010.
All regions have decreased their total number of
out-of-school children since 1999.
0
5
10
15
20
25
30
35
40
45
50
SSA SAS EAP MNA LAC ECA
Out-of-SchoolChildren.Total(inmillions)
Source: UNESCO Institute for Statistics in EdStats, Nov 2012
1999 2008 2010
35. Which countries have the most out-
of-school children?
45.8% of the world’s out-
of-school children live in
the 10 countries listed
here.
Five of the countries are
in SSA and 3 are in SAS.
Nigeria almost has as
many OOS children as
the regional totals for
LAC, ECA, and MNA
combined (10.9 million).
The US is #8 in the
ranking because of the
large size of the school
age population and also
possibly because of a
lack of consistent data
collection on home-
schooled children.
10 Countries with the Most Out-of
School Children
(2008-2011)
1 Nigeria 10,542,105
2 Pakistan 5,125,373
3 Ethiopia 2,389,945
4 India 2,278,322
5 Bangladesh 1,835,269
6 Philippines 1,460,431
7 Cote d'Ivoire 1,160,732
8 United States 1,023,231
9 Burkina Faso 1,022,362
10 Niger 1,012,228
Source: UNESCO Institute for Statistics in EdStats, Nov 2012
Notes: Data displayed is the most current year available; Purple is
2011; Black is 2010; Blue is 2009; Green is 2008; Data was not
available for 61 of 214 countries.
36. Are more females out-of-
school than males?
In 1999, there were
almost 62 million
females out-of-school
compared to 45.5
million males. 58% of
the world’s out-of-
school children were
female.
In 2010, around 32
million girls were out of
school compared to
28.6 million boys.
52.5% of out-of-school
children were female.
The gap between male
and female totals
decreased from 16.5
million to 3.6 million
between 1999 and
2010.
More Females are Out of Primary School than Males
0
20
40
60
80
100
120
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Out-of-SchoolChildren.Primary(inmillions)
Source: UNESCO Institute for Statistics in EdStats, September 2012
Males Out-of-School Females Out-of-School
37. Where are more females out-of-
school?
Over half of the
world’s out of school
girls are in SSA, and
just under 1/4 are in
South Asia.
South Asia has
decreased its total
number of females
out-of-school by 17.7
million since 1999.
The region’s total
dropped from 25
million to 7 million.
SSA has also
decreased its total
from 24.3 million in
1999 to 17.5 million in
2010.
3 out of every 4 Out-of-School Girls are
in either Sub-Saharan Africa or South Asia
0
5
10
15
20
25
30
35
40
45
50
55
60
65
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Out-of-SchoolChildren.Primary.Female(inmillions)
Source: UNESCO Institute for Statistics in EdStats, October 2012
LAC ECA MNA EAP SAS SSA
38. Which countries have the most
females OOS?
Around half of the world’s
out-of-school females live
in these 10 countries.
36% of the world’s out-of-
school females live in the
Top 4 countries.
Nigeria, Pakistan, and
India all have more our-
of-school females that the
sum of all females out-of-
school in LAC and ECA.
Half of the countries are
in SSA and three are in
South Asia.
10 Countries with the Most
Female Out-of School Children
(2008-2011)
1 Nigeria 5,487,901
2 Pakistan 3,241,203
3 India 1,407,495
4 Ethiopia 1,367,141
5 Cote d'Ivoire 663,809
6 Philippines 661,551
7 Bangladesh 591,325
8 Niger 568,884
9 Yemen, Rep. 567,702
10 Burkina Faso 530,731
Source: UNESCO Institute for Statistics in EdStats, October, 2012;
Notes: Data displayed is the most current year available; Orange is
2008;Blue is 2009; Blue is 2010; Black is 2011; Data were not
available for 61 of 213 countries.
39. Are there gender, income, or location
disparities in the % of children OOS?
In all regions, more low
income students are
OOS than high income
students. SAS has the
largest income disparity
at 29 percentage points
difference between the
top and bottom quintiles.
SSA follows closely
behind with 24 points.
A higher % of boys are
OOS in EAP, ECA, and
LAC, but a higher % of
girls are OOS in SAS
and SSA.
In all regions except for
ECA, a higher % of rural
students are OOS. This
disparity is highest in
SSA at 15 percentage
points.2
Low income is the greatest source of disparity in
percentages of OOS children across regions.
-30
-28
-26
-24
-22
-20
-18
-16
-14
-12
-10
-8
-6
-4
-2
0
2
EAP ECA LAC MNA SAS SSA
PercentagePointDifferenceinthe%ofChildrenOut-of-School
(Male-Female,Urban-Rural,andQuintile1-Quintile5)
Gender disparity
Location disparity
Income disparity
Source: Estimated by Porta (2011) using data from Demographic and Health
Surveys, Multiple Indicator Cluster Surveys, and Living Standards
Measurement Studies for 1985-2007
40. Do rural/urban disparities in educational
access exist in SSA?
Source: Demographic and Health Surveys and Multiple Indicator Cluster Surveys In World Inequality Database on Education (WIDE), Nov. 2012
Percentage of the population in the official age range of
lower secondary education not in school
Percentage of 7 to16 year olds who has never been to school.
41. Do income disparities exist in educational
access in SAS and EAP?
South Asia (SAS)
East Asia and the Pacific (EAP)
Source: Demographic and Health Surveys and Multiple Indicator Cluster Surveys In World Inequality Database on Education (WIDE), Nov. 2012
Percentage of 7 to16 year olds who has never been to school.
43. How many children are enrolled in
secondary schools?
Over 543 million
students are enrolled
in secondary school
worldwide.
This total is up from
510 million in 2005 and
451 million in 2000.
Over half of the world’s
secondary school
students are in either
EAP or SAS.
38 percent of total
secondary enrolments
are in China (18%) and
India (20%)
258 million (47.5%) are
girls.
EAP
27.4%
ECA
6.4%
LAC
11.0%
MNA
5.8%
SSA
8.4%
SAS
24.9%
HIC
16.0%
Share of Total Secondary
Enrollments by Region (%)
2010
Source: UNESCO Institute for Statistics in EdStats, November 2012
Notes: Regional aggregates are World Bank regions;
HIC = high income countries in all geographic regions.
44. In 2000, just over half
(53%) of secondary
school age children
were enrolled. This
figure has risen by 9.4
percentage points to
62.5% in 2010.
ECA has consistently
had the highest net
enrolment rates (NERs)
over time at around
80%.
Unlike in
primary, secondary
NERs have consistently
improved over time
globally and in most
regions.
Continued…
How many children are enrolled?
Secondary – Net Enrollment Rates (NER)
Over one-third of secondary school age children are
not in school, but progress has been made over time.
53.1
54.8
57.1 58.7
61.1 62.5
0
10
20
30
40
50
60
70
80
90
2000 2002 2004 2006 2008 2010
NetEnrolmentRate.Secondary.Total(%)
Source: UNESCO Institute for Statistics in EdStats, Nov 2012; Notes:
SSA 2008 is 2007 data; 2010 Data not available for SSA & SAS
EAP ECA LAC MNA SAS SSA WLD
45. EAP has made the most
progress between 2000
(55%) and 2010 (72%)
followed by SAS, which
improved by 11
percentage points
between 2000 and 2008.
SSA improved by 6.7
percentage points
between 2000 and
2007, but still was more
than 20 percent behind
other regions with NERs
ranging from 20-26%.
Almost ¾ of secondary
school age students are
not enrolled in SSA, and
almost half are not
enrolled in SAS.
How many children are enrolled?
Secondary – NER (continued)
Over one-third of secondary school age children are
not in school, but progress has been made over time.
53.1
54.8
57.1 58.7
61.1 62.5
0
10
20
30
40
50
60
70
80
90
2000 2002 2004 2006 2008 2010
NetEnrolmentRate.Secondary.Total(%)
Source: UNESCO Institute for Statistics in EdStats, Nov 2012; Notes:
SSA 2008 is 2007 data; 2010 Data not available for SSA & SAS
EAP ECA LAC MNA SAS SSA WLD
46. Which countries have the lowest
secondary enrollment rates?
More than 2/3 of
secondary school age
students are out-of-school
in these countries. Almost
90% of students are not
enrolled in Niger and
Angola.
25 countries have less
than half of secondary
school age students
enrolled.
Djibouti is the only
country on the list that is
not in SSA.
#10 Eritrea’s NER is
almost 3 times higher
than #1 Niger’s NER.
#5 Mozambique improved
from 3.4% in 2001 to
17.3% in 2011.
10 Countries with the Lowest
Secondary Net Enrollment Rates
(2008-2011)
1 Niger 10.2
2 Angola 11.5
3 Central African Republic 14.1
4 Burundi 16.2
5 Mozambique 17.3
6 Burkina Faso 17.5
7 Madagascar 23.6
8 Djibouti 24.2
9 Malawi 27.5
10 Eritrea 28.6
Source: UNESCO Institute for Statistics in EdStats, November 2012
Notes: Figures are most recent year with available data between 2008-
2011. Green = 2008; Blue = 2009; Black = 2010; Purple = 2011. Data
were not available for 96 of 214 countries.
47. Which countries have improved
secondary enrolment rates the most?
These countries
have improved their
secondary net
enrolment rates
(NER) by 16 to 32
percentage points
between 1999-2001
and 2009-2011.
Bhutan has more
than doubled its
2001 NER, but still
has around half of
secondary school
age students OOS
in 2011.
Despite their
improvement, only
three of these
countries have
NERs higher than
75%.
10 Countries with the Most
Improvement in Secondary
Net Enrollment Rates
Percentage
Points
Improved
1999-
2001
NER
Most
current
NER
%
Improved
1 Bhutan 32.0 21.7 53.8 147.5
2 Syrian Arab Republic 25.2 41.7 67.0 60.5
3 St. Lucia 25.0 60.3 85.3 41.4
4 St. Vincent and the
Grenadines
22.4 67.9 90.4 33.0
5 Dominican Republic 22.1 40.2 62.3 55.0
6 Oman 21.5 68.2 89.7 31.6
7 Indonesia 20.6 46.7 67.3 44.1
8 Venezuela, RB 17.5 54.3 71.8 32.2
9 Kenya 16.0 34.0 50.0 47.0
10 Ghana 15.8 32.9 48.7 48.1
Source: UNESCO Institute for Statistics in EdStats, Nov. 2012;
Notes: Black data is for 2001 or 2010; Purple is 2000 or 2011; Blue is 2009;
Data were not available for 123 of 214 countries.
48. Net Enrollment Rate. Secondary (%)
The maps displayed were produced by EdStats. The boundaries, colors, denominations and any
other information shown on this map do not imply, on the part of the World Bank Group, any
judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries.
The maps are for reference only.
Source: UNESCO Institute for Statistics in EdStats, November 2012
Note: Data displayed is for the latest available year (2008-2011)
49. Do low secondary enrollments relate
to low national income per capita?
Low gross national
income (GNI) per capita
does not necessarily
lead to low secondary
NERs. Low income
countries (<$1025 GNI
pc) have NERs ranging
from 10.2% (Niger) to
85% (Tajikistan).
All countries with a GNI
pc over $10,000 have a
NER over 70% except
Liechtenstein and
Uruguay.
Almost all countries with
secondary NERs less
than 50% have a GNI pc
less than $3000. The
exceptions are
Swaziland and Angola.
There is no clear association between low national
income per capita and low secondary enrolment rates.
R² = 0.179
0
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80
NetEnrollmentRate.Secondary.AllProgrammes.Total
GNI per capita, Atlas method (current US$)
Source: UNESCO Institute for Statistics in EdStats, Nov. 2012
Note: Data is for the most recent year between 2009 and 2011.
CAR, Burundi, Mozambique, Burkina Faso
Niger
Norway
Angola
Suriname
Macao, SAR China
Switzerland,
Qatar,
Luxembourg
50. 0.92
0.94
0.95
0.96 0.96 0.96
0.75
0.80
0.85
0.90
0.95
1.00
1.05
1.10
2000 2002 2004 2006 2008 2010
GenderParityIndex(GPI)forNetEnrolmentRate.Secondary
Source: UNESCO Institute for Statistics in EdStats, Oct. 2012; No data
available for SSA and MNA for 2010. SSA 2008 data is from 2007.
WLD EAP ECA LAC MNA SAS SSA
Which regions have reached gender
parity in secondary enrollments?
Globally, the gender
parity index (GPI) for
secondary net enrollment
rate (NER) has been
increasing from 0.92 in
2000 to 0.96 in 2010.
ECA is the only region
within +/- 0.05 of gender
parity (1.0).
LAC has consistently had
higher female NERs.
EAP has reversed from a
male bias (0.96) in 2000
to a female bias (1.06) in
2010.
SAS has greatly
decreased gender
disparity over time.
SSA has maintained a
male bias 0.80 since
2000.
Gender disparities in secondary enrollments vary
greatly across regions.
Female Bias
Male Bias
51. 0.40
0.50
0.60
0.70
0.80
0.90
1.00
1.10
1.20
1.30
1.40
GenderParityIndex(GPI)forGrossEnrolmentRatio.Secondary
Source: UNESCO Institute for Statistics in EdStats, October 2012:
Data points are the most recent year with data available (2008-2011)
Does gender parity exist in secondary
enrollments in most countries?
Just over half (52%) of
countries with data are
within 0.05 of gender
parity in secondary
enrollments.
Unlike primary
enrollments, more
countries have a female
bias in secondary
enrolments. 85
countries have GPIs
higher than 1 while 71
countries have GPIs
less than 1.
6 countries have
perfect gender parity
(1.0):
Slovenia, Mauritius, Sw
aziland, Japan, Indones
ia, and Cyprus.
More countries have higher female secondary GERs
than male secondary GERs.
Female Bias
Male Bias
52. Which countries have the largest gender
disparities in secondary enrolments?
In 9 of 10
countries, the
male GER is
much higher than
the female GER.
In Lesotho – the
female GER is
higher than the
male rate.
8 of 10 countries
are in SSA. 1 is in
South Asia and 1
is in MNA.
Of the 20
countries with the
greatest gender
disparity, 5 have a
female bias.
14 of the top 20
are in SSA.
10 Countries with the Largest Gender
Disparities in Secondary Enrolments
(2008-2011)
GPI
Absolute
value from 1
1 Chad 0.42 0.58
2 Afghanistan 0.51 0.49
3 Central African Republic 0.55 0.45
4 Congo, Dem. Rep. 0.58 0.42
5 Guinea 0.59 0.41
6 Lesotho 1.38 0.38
7 Yemen, Rep. 0.62 0.38
8 Niger 0.66 0.34
9 Angola 0.69 0.31
10 Mali 0.71 0.29
Source: UNESCO Institute for Statistics in EdStats, October 2012; Notes: Data are
2010 GPIs for Secondary Gross Enrolment Rates except Guinea (2009), CAR
(2011), and Mali (2011); Data were not available for 52 of 213 countries.
53. Which countries have decreased gender
disparity in secondary the most?
These countries have
moved from 0.19 to
0.34 percentage
points closer to
gender parity (1) over
time.
Sweden and St. Lucia
improved from a large
female bias (1.26)
toward gender parity.
The other countries
have improved from a
male bias (0.40 to
0.85) toward gender
parity.
3 of 10 countries are
within 0.05 of gender
parity in the most
recent year.
10 Countries with the Most
Improvement Toward Gender
Parity in Secondary Enrollments
Percentage
Points
Improved
2000/
2001
GPI
Most
current
GPI
1 Cambodia 0.34 0.57 0.90
2 Sweden 0.27 1.26 0.99
3 St. Lucia 0.27 1.26 0.99
4 Mozambique 0.23 0.64 0.87
5 Senegal 0.21 0.66 0.88
6 Yemen, Rep. 0.21 0.41 0.62
7 India 0.20 0.72 0.92
8 Bhutan 0.19 0.85 1.04
9 Guinea 0.19 0.40 0.59
10 Turkey 0.19 0.73 0.91
Source: UNESCO Institute for Statistics in EdStats, October. 2012;
Notes: Most current GPI data for most countries is from 2010;
Guinea and Turkey are 2009; Mozambique data is 2011.
54. Do income disparities exist in lower
secondary enrolment rates in SAS and MNA?
Source: Demographic and Health Surveys and Multiple Indicator Cluster Surveys In World Inequality Database on Education (WIDE), Nov. 2012
South Asia (SAS)
Middle East and North Africa (MNA)
% of the population in the official age range of lower secondary education not in school
55. Do rural/urban disparities exist in lower
secondary enrolment rates in LAC?
Source: Demographic and Health Surveys and Multiple Indicator Cluster Surveys In World Inequality Database on Education (WIDE), Nov. 2012
Percentage of the population in the official age range of
lower secondary education not in school
% of the population in the official age range of lower secondary education not in school
56. Do regional disparities exist in lower
secondary enrolment rates in Asia?
Source: Demographic and Health Surveys and Multiple Indicator Cluster Surveys In World Inequality Database on Education (WIDE), Nov. 2012
% of the population in the official age range of lower secondary education not in school
58. How many youth are enrolled?
Tertiary – Gross Enrolment Rates (GER)
Around 30% of tertiary
age youth were enrolled
in tertiary education
2010. This figure was a
10 percentage point
improvement over 2000
(19%).
ECA has consistently
had the highest tertiary
GERs of any region.
Over half (55.6%) of
tertiary age youth were
enrolled in 2010 which is
a 17 percentage point
increase over 2000.
EAP has more than
doubled its tertiary GER
over time.
SSA lags behind other
regions with 6.8% of
youth enrolled in 2010.
Almost ¾ of tertiary age youth around the world
are not enrolled in tertiary education.
19.1
21.5
23.5
24.9
27.0
29.2
0
10
20
30
40
50
60
2000 2002 2004 2006 2008 2010
GrossEnrolmentRate.Tertiary.Total(%)
Source: UNESCO Institute for Statistics in EdStats, November 2012
EAP ECA LAC MNA SAS SSA WLD
59. Which countries have the lowest
tertiary enrollment rates?
These countries have
less than 4% of tertiary
age students enrolled in
tertiary education.
33 countries have less
than 10 percent of
tertiary age youth
enrolled.
50 countries have more
than half of tertiary age
youth enrolled.
8 countries have tertiary
GERs higher than 80%
and 4 countries have
tertiary GERs higher than
90%: Finland, the United
States, Cuba, and
Korea, Rep.
10 Countries with the Lowest
Tertiary Gross Enrollment Rates
(2008-2011)
1 Turks and Caicos Islands 0.08
2 Malawi 0.72
3 Niger 1.51
4 Eritrea 1.99
5 Tanzania 2.11
6 Chad 2.17
7 Central African Republic 2.57
8 Burundi 3.25
9 Afghanistan 3.33
10 Dominica 3.57
Source: UNESCO Institute for Statistics in EdStats, Nov. 2012
Notes: Figures are most recent year with data between 2008-2011.
Purple = 2011; Black = 2010; Blue = 2009; Green = 2008.
Data were not available for 72 of 214 countries.
60. Which countries have improved
tertiary enrolment rates the most?
These countries
have improved
their tertiary gross
enrolment rates by
27 to 70
percentage points
between 1999-
2001 and 2009-
2011.
7 countries more
than doubled their
tertiary GER –
Cuba, Venezuela,
Cyprus,
Montenegro,
Czech Rep.,
Romania, and
Armenia.
All of the countries
are in LAC or ECA.
10 Countries with the Most
Improvement in Tertiary
Gross Enrollment Rates
Percentage
Points
Improved
1999-
2001
GER
2009-
2011
GER
%
Improved
1 Cuba 70.0 25.2 95.2 277.8
2 Venezuela, RB 49.8 28.3 78.1 175.6
3 Cyprus 33.0 21.6 54.6 152.8
4 Montenegro 31.1 16.6 47.6 187.9
5 Czech Republic 30.5 30.1 60.7 101.5
6 Romania 30.5 28.4 58.8 107.4
7 Uruguay 29.5 33.8 63.3 87.4
8 Ukraine 27.1 52.4 79.5 51.8
9 Belarus 27.0 55.9 83.0 48.3
10 Armenia 26.6 24.9 51.5 106.7
Source: UNESCO Institute for Statistics in EdStats, Nov. 2012;
Notes: Most recent data year available was used from 2008-2011.
Data were not available for 97 of 214 countries.
61. Gross Enrollment Ratio. Tertiary
Source: UNESCO Institute for Statistics in EdStats, Nov. 2012
Note: Data displayed is for the latest available year (2008-2011)
The maps displayed were produced by EdStats. The boundaries, colors, denominations and any
other information shown on this map do not imply, on the part of the World Bank Group, any
judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries.
The maps are for reference only.
62. Do countries with higher income per capita
have higher tertiary enrollment rates?
Most countries with
gross national income
(GNI) per capita less
than $1000 have
tertiary GERs less than
11%. Tajikistan (20%)
and Kyrgyz Rep (49%)
are the two exceptions.
Countries with GNI pc
more than $20,000
have tertiary GERs
higher than 50%
except for Qatar
(10%), Luxembourg
(10.5%), Brunei
(17.2%), and
Liechtenstein (36.0%).
Most countries with a GNI pc higher than $20,000
have tertiary GERs higher than 50%.
R² = 0.202
0
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80
Grossenrolmentratio.Tertiary(ISCED5and6).Total
GNI per capita, Atlas method (current US$)
Source: UNESCO Institute for Statistics in EdStats, Nov. 2012
Note: Data is for the most recent year between 2009 and 2011.
Slovenia
Brunei
Norway
Switzerland
United States
Finland
Oman
Luxembourg, Qat
ar
Belarus
63. Which regions have reached gender
parity in tertiary enrollments?
In 2000, the world gender
parity index (GPI) for
tertiary enrollments was
1.0 – perfect gender
parity. Since then, female
GERs have been higher
than male GERs, and the
GPI has been moving
above 1.0.
MNA is the only region
within +/- 0.05 of gender
parity in 2010. LAC and
ECA have consistently
had higher female
GERs, and EAP has
reversed from a male
bias to a female bias.
SAS and SSA have
maintained a strong male
bias in tertiary
enrolments over time.
Gender disparities in tertiary enrolment rates vary
greatly across regions.
1.00
1.02
1.04
1.06 1.07 1.08
0.60
0.65
0.70
0.75
0.80
0.85
0.90
0.95
1.00
1.05
1.10
1.15
1.20
1.25
1.30
2000 2002 2004 2006 2008 2010
GenderParityIndex(GPI)forGrossEnrolmentRate.Tertiary
Source: UNESCO Institute for Statistics in EdStats, Oct. 2012
WLD EAP ECA LAC MNA SAS SSA
Female Bias
Male Bias
64. Does gender parity exist in tertiary
enrollments in most countries?
Only 9 countries are
within +/-0.05 of
gender parity in
tertiary enrollments.
63% of countries
have a female bias in
tertiary enrolments
vs. 37% with higher
male enrolment rates.
One country –
Vietnam – has perfect
gender parity (1.0).
In 10 countries, the
female GER more
than doubles the
male GER. These
countries are island
nations in LAC and
Qatar (see next
slide).
The majority of countries have higher female
enrolment rates than male enrolment rates in tertiary
education.
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
5.50
GenderParityIndex(GPI)forGrossEnrolmentRatio.Tertiary
Source: UNESCO Institute for Statistics in EdStats, Nov. 2012
Note: Data points are the most recent year with data available (2008-2011)
Female
Bias
Male Bias
65. Which countries have the largest gender
disparities in tertiary enrolments?
10 Countries with the Largest Male
Bias in Tertiary Enrolments
(2008-2011)
1 Chad 0.17
2 Congo, Rep. 0.21
3 Afghanistan 0.24
4 Congo, Dem. Rep. 0.31
5 Central African Republic 0.32
6 Eritrea 0.33
7 Guinea 0.33
8 Ethiopia 0.36
9 Benin 0.38
10 Niger 0.38
Source: UNESCO Institute for Statistics in EdStats, Oct. 2012;
Notes: Maroon=2011; Black = 2010; Purple = 2009; Blue = 2008;
Data were not available for 73 of 213 countries.
10 Countries with the Largest
Female Bias in Tertiary
Enrolments
(2008-2011)
1 Qatar 5.38
2 Dominica 3.35
3 Antigua and Barbuda 2.58
4 St. Lucia 2.57
5 Guyana 2.52
6 Barbados 2.38
7 Jamaica 2.28
8 Cayman Islands 2.24
9 Bermuda 2.12
10 St. Kitts and Nevis 2.10
Source: UNESCO Institute for Statistics in EdStats, Oct. 2012;
Notes: Black = 2010; Blue = 2008; Data were not available for
73 of 213 countries.
66. Do gender, income, or location disparities
exist in post-secondary attendance ratios?
Levels of gender
disparity in post-
secondary attendance
are much lower than
levels of location and
income disparity. More
girls than boys attend
post-secondary schools
in EAP, ECA, and LAC.
Rural areas have
between 5 (SSA) and 15
(LAC) percent lower
attendance ratios than
urban areas.
Income is the largest
source of disparity
across regions. Income
disparities range from 8
percentage points in
SSA to 34 in LAC.2
Income is the largest source of disparity in post-
secondary gross attendance ratios in all regions.
-5
0
5
10
15
20
25
30
35
EAP ECA LAC MNA SAS SSA
PercentagePointDifferenceinGrossAttendanceRatio.Post-Sec.
(Male-Female,Urban-Rural,andQuintile1-Quintile5)
Gender disparity
Location disparity
Income disparity
Source: Estimated by Porta (2011) using data from Demographic and Health
Surveys, Multiple Indicator Cluster Surveys, and Living Standards
Measurement Studies for 1985-2007
67. This presentation utilizes the following data sources:
1) UNESCO Institute for Statistics (UIS) data in the EdStats Query
The presentation was created with the most recent UIS data
release that included 2010 data for most indicators and 2011 data
for some countries.
The most recent regional aggregate data was from 2010.
Indicators were calculated by UIS according to definitions available
in the EdStats Query metadata.
2) Income/Gender/Location Disparity slides were based on data
and analysis extracted from:
Demographic and Health Surveys, Multiple Indicator Cluster Surveys, and
Living Standards Measurement Studies for 1985-2007; Reports were
generated through ADePT Edu by Emilio Porta (2011).
Porta, Emilio, Gustavo Arcia, Kevin Macdonald, Sergiy Radyakin, and Misha
Lokshin. 2011. Assessing Sector Performance and Inequality in Education.
Washington, DC: World Bank.
Data Sources
68. The State of Education Series
The following State of Education presentations
are available on the EdStats website:
Educational Levels:
Pre-Primary Education
Primary Education
Secondary Education
Tertiary Education
Topics:
Access
Quality
Expenditures
Literacy
Equity
Gender