In 2020, China had a youth literacy rate of about **** percent. In contrast, Afghanistan's youth literacy rate stood at **** percent in 2021.Indicators for the literacy rateAn indicator which can be seen to affect the literacy rate is the governmental effort in investing in education. The amount of funds invested into the education sector is a factor which can determine a country’s state of education, as the amount of money being spent on education would have an impact on resources, learning environment, and teaching quality. Singapore’s student-teacher ratio in primary education is significantly lower than that of South Asian countries. For instance, Nepal had 20.3 students for every teacher in 2019. Meanwhile, Singaporean teachers only had around **** students on average as of 2020. Notably, South Asia, together with sub-Saharan Africa, had a much higher illiteracy rate compared to the East Asian and Pacific region in 2022. The importance of literacyThe literacy rate indicates the percentage of people within a population who can read and write. This enables them to identify, understand and interpret materials with various contexts. Ensuring literacy for all pupils is a part of the Sustainable Development Goals (SDG) for quality education. This in turn stimulates economic and societal growth for the future.

Between 2018 and 2022, Seychelles was the country with the highest adult literacy rate in Africa, at around ** percent. São Tomé and Príncipe and Namibia followed with a literacy rate of approximately ** percent and ** percent, respectively. The average rate on the continent stood at roughly ** percent. Moreover, Southern Africa had the highest literacy levels among African regions.

The average for 2021 based on 58 countries was 94.32 percent. The highest value was in Romania: 100 percent and the lowest value was in Burkina Faso: 66.65 percent. The indicator is available from 1970 to 2023. Below is a chart for all countries where data are available.

The average for 2021 based on 13 countries was 86.52 percent. The highest value was in Uzbekistan: 100 percent and the lowest value was in Afghanistan: 37 percent. The indicator is available from 1970 to 2023. Below is a chart for all countries where data are available.

The statistic shows the degree of adult literacy in China from 1982 to 2020. In 2020, the literacy rate, which is defined as people aged 15 and above who can read and write, had reached about 97.15 percent in China.

Global literacy rates

By 2020, around 86.8 percent of the world population aged 15 years and above had been able to read and write. While in developed regions this figure ranged a lot higher, only around 67 percent of the population in Sub-Saharan Africa was literate. Countries with the lowest literacy rates are also the most underdeveloped worldwide. According to UNESCO, literacy is a human right, especially in a fast-changing and technology-driven world. In China, the literacy rate has developed from 79 percent in 1982 to 97 percent in 2020, indicating that almost one million people per year had become literate over three decades. In India, the situation was entirely different. The second most populous country in the world displayed a literacy rate of merely 76 percent in 2022.

Literacy in China

The dramatic increase in literacy in China has a lot to do with the efficacy of numerous political, economic and educational policies. In 1982, compulsory education was written into the Chinese constitution, postulating a nine-year compulsory education funded by the government. As is shown by the graph above, there was a large gender gap in literacy rate in China as of 1982. Though this gap still existed in 2020, it was narrowed down to three percent, starting from 28 percent in 1982. Since 1990, the national education policy was directed at females, especially from poor and/or minority families. Over the past years, China has achieved gender parity in primary schooling.

However, regional literacy disparities in China should not to be overlooked. Regions with a strong economic background tend to display illiteracy rates below national average. In contrast, economically underdeveloped regions have a much larger share of people who cannot read nor write. Tibet for instance, a region where 92 percent of the population belong to an ethnic minority, showed the highest illiterate rate nationwide, with around 34 percent in 2022.

In the past five decades, the global literacy rate among adults has grown from 67 percent in 1976 to 87.36 percent in 2023. In 1976, males had a literacy rate of 76 percent, compared to a rate of 58 percent among females. This difference of over 17 percent in 1976 has fallen to just seven percent in 2020. Although gaps in literacy rates have fallen across all regions in recent decades, significant disparities remain across much of South Asia and Africa, while the difference is below one percent in Europe and the Americas. Reasons for these differences are rooted in economic and cultural differences across the globe. In poorer societies, families with limited means are often more likely to invest in their sons' education, while their daughters take up a more domestic role. Varieties do exist on national levels, however, and female literacy levels can sometimes exceed the male rate even in impoverished nations, such as Lesotho (where the difference was over 17 percent in 2014); nonetheless, these are exceptions to the norm.

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Dataset Overview 📝

The dataset includes the following key indicators, collected for over 200 countries:

• Government Expenditure on Education (% of GDP): Shows the percentage of a country’s GDP allocated to education.
• Literacy Rate (Adult Total): Represents the percentage of the population aged 15 and above who can read and write.
• Primary Completion Rate: The percentage of children who complete their primary education within the official age group.
• Pupil-Teacher Ratio (Primary and Secondary Education): Indicates the average number of students per teacher at the primary and secondary levels.
• School Enrollment Rates (Primary, Secondary, Tertiary): Reflects the percentage of the relevant age group enrolled in schools across different education levels.

Data Source 🌐

World Bank: This dataset is compiled from the World Bank's educational database, providing reliable, updated statistics on educational progress worldwide.

Potential Use Cases 🔍 This dataset is ideal for anyone interested in:

Educational Research: Understanding how education spending and policies impact literacy, enrollment, and overall educational outcomes. Predictive Modeling: Building models to predict educational success factors, such as completion rates and literacy. Global Education Analysis: Analyzing trends in global education systems and how different countries allocate resources to education. Policy Development: Helping governments and organizations make data-driven decisions regarding educational reforms and funding.

Key Questions You Can Explore 🤔

How does government expenditure on education correlate with literacy rates and school enrollment across different regions? What are the trends in pupil-teacher ratios over time, and how do they affect educational outcomes? How do education indicators differ between low-income and high-income countries? Can we predict which countries will achieve universal primary education based on current trends?

Important Notes ⚠️ - Missing Data: Some values may be missing for certain years or countries. Consider using techniques like forward filling or interpolation when working with time series models. - Data Limitations: This dataset provides global averages and may not capture regional disparities within countries.

Abstract

The PIRLS 2006 aimed to generate a database of student achievement data in addition to information on student, parent, teacher, and school background data for the 47 areas that participated in PIRLS 2006.

Geographic coverage

Nationally representative

Analysis unit

Units of analysis in the study are schools, students, parents and teachers.

Universe

PIRLS is a study of student achievement in reading comprehension in primary school, and is targeted at the grade level in which students are at the transition from learning to read to reading to learn, which is the fourth grade in most countries. The formal definition of the PIRLS target population makes use of UNESCO's International Standard Classification of Education (ISCED) in identifying the appropriate target grade:

"…all students enrolled in the grade that represents four years of schooling, counting from the first year of ISCED Level 1, providing the mean age at the time of testing is at least 9.5 years. For most countries, the target grade should be the fourth grade, or its national equivalent."

ISCED Level 1 corresponds to primary education or the first stage of basic education, and should mark the beginning of "systematic apprenticeship of reading, writing, and mathematics" (UNESCO, 1999). By the fourth year of Level 1, students have had 4 years of formal instruction in reading, and are in the process of becoming independent readers. In IEA studies, the above definition corresponds to what is known as the international desired target population. Each participating country was expected to define its national desired population to correspond as closely as possible to this definition (i.e., its fourth grade of primary school). In order to measure trends, it was critical that countries that participated in PIRLS 2001, the previous cycle of PIRLS, choose the same target grade for PIRLS 2006 that was used in PIRLS 2001. Information about the target grade in each country is provided in Chapter 9 of the PIRLS 2006 Technical Report.

Although countries were expected to include all students in the target grade in their definition of the population, sometimes it was not possible to include all students who fell under the definition of the international desired target population. Consequently, occasionally a country's national desired target population excluded some section of the population, based on geographic or linguistic constraints. For example, Lithuania's national desired target population included only students in Lithuanian-speaking schools, representing approximately 93 percent of the international desired population of students in the country. PIRLS participants were expected to ensure that the national defined population included at least 95 percent of the national desired population of students. Exclusions (which had to be kept to a minimum) could occur at the school level, within the sampled schools, or both. Although countries were expected to do everything possible to maximize coverage of the national desired population, school-level exclusions sometimes were necessary. Keeping within the 95 percent limit, school-level exclusions could include schools that:

• were geographically remote,
• had very few students,
• had a curriculum or structure different from the mainstream education system, or
• were specifically for students with special needs.

The difference between these school-level exclusions and those at the previous level is that these schools were included as part of the sampling frame (i.e., the list of schools to be sampled). Th ey then were eliminated on an individual basis if it was not feasible to include them in the testing.

In many education systems, students with special educational needs are included in ordinary classes. Due to this fact, another level of exclusions is necessary to reach an eff ective target population-the population of students who ultimately will be tested. These are called within-school exclusions and pertain to students who are unable to be tested for a particular reason but are part of a regular classroom. There are three types of within-school exclusions.

• Intellectually disabled students
• Functionally disabled students
• Non-native language speakers

Students eligible for within-school exclusion were identified by staff at the schools and could still be administered the test if the school did not want the student to feel out of place during the assessment (though the data from these students were not included in any analyses). Again, it was important to ensure that this population was as close to the national desired target population as possible. If combined, school-level and within-school exclusions exceeded 5 percent of the national desired target population, results were annotated in the PIRLS 2006 International Report (Mullis, Martin, Kennedy, & Foy, 2007). Target population coverage and exclusion rates are displayed for each country in Chapter 9 of the PIRLS 2006 Technical Report. Descriptions of the countries' school-level and within-school exclusions can be found in Appendix B of the PIRLS 2006 Technical Report.

Kind of data

Sample survey data [ssd]

Sampling procedure

The basic sample design used in PIRLS 2006 is known as a two-stage stratified cluster design, with the first stage consisting of a sample of schools, and the second stage consisting of a sample of intact classrooms from the target grade in the sampled schools. While all participants adopted this basic two-stage design, four countries, with approval from the PIRLS sampling consultants, added an extra sampling stage. The Russian Federation and the United States introduced a preliminary sampling stage, (first sampling regions in the case of the Russian Federation and primary sampling units consisting of metropolitan areas and counties in the case of the United States). Morocco and Singapore also added a third sampling stage; in these cases, sub-sampling students within classrooms rather than selecting intact classes.

For countries participating in PIRLS 2006, school stratification was used to enhance the precision of the survey results. Many participants employed explicit stratification, where the complete school sampling frame was divided into smaller sampling frames according to some criterion, such as region, to ensurea predetermined number of schools sampled for each stratum. For example, Austria divided its sampling frame into nine regions to ensure proportional representation by region (see Appendix B for stratification information for each country). Stratification also could be done implicitly, a procedure by which schools in a sampling frame were sorted according to a set of stratification variables prior to sampling. For example, Austria employed implicit stratification by district and school size within each regional stratum. Regardless of the other stratification variables used, all countries used implicit stratification by a measure of size (MOS) of the school.

All countries used a systematic (random start, fixed interval) probability proportional-to-size (PPS) sampling approach to sample schools. Note that when this method is combined with an implicit stratification procedure, the allocation of schools in the sample is proportional to the size of the implicit strata. Within the sampled schools, classes were sampled using a systematic random method in all countries except Morocco and Singapore, where classes were sampled with probability proportional to size, and students within classes sampled with equal probability. The PIRLS 2006 sample designs were implemented in an acceptable manner by all participants.

Sampling deviation

8 National Research Coordinators (NRCs) encountered organizational constraints in their systems that necessitated deviations from the sample design. In each case, the Statistics Canada sampling expert was consulted to ensure that the altered design remained compatible with the PIRLS standards.

These country specific deviations from sample design are detailed in Appendix B of the PIRLS 2006 Technical Report (page 231) attached as Related Material.

Mode of data collection

Face-to-face [f2f]

Research instrument

• PIRLS Background Questionnaires By gathering information about children’s experiences together with reading achievement on the PIRLS test, it is possible to identify the factors or combinations of factors that relate to high reading literacy. An important part of the PIRLS design is a set of questionnaires targeting factors related to reading literacy. PIRLS administered four questionnaires: to the tested students, to their parents, to their reading teachers, and to their school principals.

• Student Questionnaire Each student taking the PIRLS reading assessment completes the student questionnaire. The questionnaire asks about aspects of students’ home and school experiences - including instructional experiences and reading for homework, self-perceptions and attitudes towards reading, out-of-school reading habits, computer use, home literacy resources, and basic demographic information.

• Learning to Read (Home) Survey The learning to read survey is completed by the parents or primary caregivers of each student taking the PIRLS reading assessment. It addresses child-parent literacy interactions, home literacy resources, parents’ reading habits and attitudes, homeschool connections, and basic demographic and socioeconomic indicators.

• Teacher Questionnaire The reading teacher of each fourth-grade class sampled for PIRLS completes a questionnaire designed to gather information about classroom contexts for developing reading literacy. This questionnaire

As of 2021, South Africa's total literacy rate was around 90 percent, which means 90 percent of all South Africans could read and write. There is literally no definitionThe literacy rate measures the percentage of people aged 15 and above who can read and write. There is no common definition for what counts as being literate; individual countries use individual assessments and standards to define it. Despite this, the literacy rate is an important indicator of the standard of education and thus the standard of living in a country. Sub-standard Sub-SaharaAlthough its educational system does not have the best reputation, South Africa’s literacy rate is well above average among their geographical peers in Sub-Saharan Africa. Illiteracy is still a significant global problem, and Sub-Saharan Africa is not among the leading regions when it comes to literacy and education. In 2011, 32 million children of primary school age did not go to school in that region, but projections see enrollment figures increasing in the future – if true, this could not only improve the region’s literacy rates, but also its standard of living and human progress in general.

The country reported to have read books most regularly in 2017 was China, where a survey among internet users across ** countries revealed that ** percent of respondents read a book every day or most days, and ** percent read at least once a week. Conversely, just ** percent of South Korean respondents were reading books on a daily basis. Other countries with a low share of those aged 15 years or above reading daily included Belgium, Japan, the Netherlands and Mexico.

Age and reading habits

It is surprising how much age can affect reading habits, even on a global level. In Germany, more 12 to 13-year-olds read daily or several times per week than their slightly older peers. Meanwhile, in the United Kingdom, a survey showed that more teenagers and Millennials said that they would be happy without books than adults aged 34 or older. More than double the percentage of adults in Colombia aged 65 or above read a book every day than those aged between 12 and 25 years.

The number of books read over the past year in the United States was overall higher among adults aged 18 to 34 than older generations, and in Canada the share of children reading books for fun halved with the approach of teenage years. Whilst ** percent of children aged between six and eight years old were reading for pleasure multiple times per week, among ** to 17-year-olds this figure amounted to just ** percent. Meanwhile, the opposite was true of going online for fun, which increased sharply with age and replaced the activity of reading.

South Africa ZA: Literacy Rate: Adult: % of People Aged 15 and Above data was reported at 94.368 % in 2015. This records an increase from the previous number of 94.140 % for 2014. South Africa ZA: Literacy Rate: Adult: % of People Aged 15 and Above data is updated yearly, averaging 92.895 % from Dec 1980 (Median) to 2015, with 9 observations. The data reached an all-time high of 94.368 % in 2015 and a record low of 76.200 % in 1980. South Africa ZA: Literacy Rate: Adult: % of People Aged 15 and Above data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank: Education Statistics. Adult literacy rate is the percentage of people ages 15 and above who can both read and write with understanding a short simple statement about their everyday life.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Abstract

PIRLS provides internationally comparative data on how well children read by assessing students’ reading achievement at the end of grade four. PIRLS 2016 is the fourth cycle of the study and collects considerable background information on how education systems provide educational opportunities to their students, as well as the factors that influence how students use this opportunity. In 2016 PIRLS was extended to include ePIRLS – an innovative assessment of online reading.

The results of PIRLS 2016 demonstrate a number of positive developments in reading literacy worldwide. For the first time in the history of the study, as many as 96 percent of fourth graders from over 60 education systems achieved above the PIRLS low international benchmark.

Geographic coverage

Nationally representative samples of approximately 4,000 students from 150 to 200 schools participated in PIRLS 2016. About 319,000 students, 310,000 parents, 16,000 teachers, and 12,000 schools participated in total.

Analysis unit

The unit of analysis describes:

• Schools

• Students

• Parents

• Teachers

Universe

All students enrolled in the grade that represents four years of schooling counting from the first year of ISCED Level 1, providing the mean age at the time of testing is at least 9.5 years.

All students enrolled in the target grade, regardless of their age, belong to the international target population and should be eligible to participate in PIRLS. Because students are sampled in two stages, first by randomly selecting a school and then randomly selecting a class from within the school, it is necessary to identify all schools in which eligible students are enrolled. Essentially, eligible schools for PIRLS are those that have any students enrolled in the target grade, regardless of type of school.

Kind of data

Sample survey data [ssd]

Sampling procedure

PIRLS is designed to provide valid and reliable measurement of trends in student achievement in countries around the world, while keeping to a minimum the burden on schools, teachers, and students. The PIRLS program employs rigorous school and classroom sampling techniques so that achievement in the student population as a whole may be estimated accurately by assessing just a sample of students from a sample of schools. PIRLS assesses reading achievement at fourth grade. The PIRLS 2016 cycle also included PIRLS Literacy-a new, less difficult reading literacy assessment, and ePIRLS-an extension of PIRLS with a focus on online informational reading.

PIRLS employs a two-stage random sample design, with a sample of schools drawn as a first stage and one or more intact classes of students selected from each of the sampled schools as a second stage. Intact classes of students are sampled rather than individuals from across the grade level or of a certain age because PIRLS pays particular attention to students’ curricular and instructional experiences, and these typically are organized on a classroom basis. Sampling intact classes also has the operational advantage of less disruption to the school’s day-to-day business than individual student sampling.

SAMPLE SIZE

For most countries, the PIRLS precision requirements are met with a school sample of 150 schools and a student sample of 4,000 students for each target grade. Depending on the average class size in the country, one class from each sampled school may be sufficient to achieve the desired student sample size. For example, if the average class size in a country were 27 students, a single class from each of 150 schools would provide a sample of 4,050 students (assuming full participation by schools and students). Some countries choose to sample more than one class per school, either to increase the size of the student sample or to provide a better estimate of school level effects.

For countries choosing to participate in both PIRLS and PIRLS Literacy, the required student sample size is doubled-i.e., around 8,000 sampled students. Countries could choose to select more schools or more classes within sampled schools to achieve the required sample size. Because ePIRLS is designed to be administered to students also taking PIRLS, the PIRLS sample size requirement remains the same for countries choosing also to participate in ePIRLS.

PIRLS STRATIFIED TWO-STAGE CLUSTER SAMPLE DESIGN

The basic international sample design for PIRLS is a stratified two-stage cluster sample design, as follows:

• First Sampling Stage. For the first sampling stage, schools are sampled with probabilities proportional to their size (PPS) from the list of all schools in the population that contain eligible students. The schools in this list (or sampling frame) may be stratified (sorted) according to important demographic variables. Schools for the field test and data collection are sampled simultaneously using a systematic random sampling approach. Two replacement schools are also pre-assigned to each sampled school during the sample selection process, and these replacement schools are held in reserve in case the originally sampled school refuses to participate. Replacement schools are used solely to compensate for sample size losses in the event that the originally sampled school does not participate. School sampling is conducted for each country by Statistics Canada with assistance from IEA Hamburg, using the sampling frame provided by the country’s National Research Coordinator.

• Second Sampling Stage. The second sampling stage consists of the selection of one (or more) intact class from the target grade of each participating school. Class sampling in each country is conducted by the National Research Coordinator using the Within-School Sampling Software (WinW3S) developed by IEA Hamburg and Statistics Canada. Having secured a sampled school’s agreement to participate in the assessment, the National Research Coordinator requests information about the number of classes and teachers in the school and enters it in the WinW3S database.

Classes smaller than a specified minimum size are grouped into pseudo-classes prior to sampling. The software selects classes with equal probabilities within schools. All students in each sampled class participate in the assessment. Sampled classes that refuse to participate may not be replaced.

For countries participating in both PIRLS and PIRLS Literacy, students within a sampled class are randomly assigned either a PIRLS or PIRLS Literacy booklet through a booklet rotation system. This is done to ensure that PIRLS and PIRLS Literacy are administered to probabilistically equivalent samples. In countries taking part in ePIRLS, all students assessed in PIRLS are expected to participate in ePIRLS.

STRATIFICATION

Stratification consists of arranging the schools in the target population into groups, or strata, that share common characteristics such as geographic region or school type. Examples of stratification variables used in PIRLS include region of the country (e.g., states or provinces); school type or source of funding (e.g., public or private); language of instruction; level of urbanization (e.g., urban or rural area); socioeconomic indicators; and school performance on national examinations.

In PIRLS, stratification is used to:

• Improve the efficiency of the sample design, thereby making survey estimates more reliable

• Apply different sample designs, such as disproportionate sample allocations, to specific groups of schools (e.g., those in certain states or provinces)

• Ensure proportional representation of specific groups of schools in the sample School stratification can take two forms: explicit and implicit. In explicit stratification, a separate school list or sampling frame is constructed for each stratum and a sample of schools is drawn from that stratum. In PIRLS, the major reason for considering explicit stratification is disproportionate allocation of the school sample across strata. For example, in order to produce equally reliable estimates for each geographic region in a country, explicit stratification by region may be used to ensure the same number of schools in the sample for each region, regardless of the relative population size of the regions.

Implicit stratification consists of sorting the schools by one or more stratification variables within each explicit stratum, or within the entire sampling frame if explicit stratification is not used. The combined use of implicit strata and systematic sampling is a very simple and effective way of ensuring a proportional sample allocation of students across all implicit strata. Implicit stratification also can lead to improved reliability of achievement estimates when the implicit stratification variables are correlated with student achievement.

National Research Coordinators consult with Statistics Canada and IEA Hamburg to identify the stratification variables to be included in their sampling plans. The school sampling frame is sorted by the stratification variables prior to sampling schools so that adjacent schools are as similar as possible. Regardless of any other explicit or implicit variables that may be used, the school size is always included as an implicit stratification variable.

SCHOOL SAMPLING FRAME

One of the National Research Coordinator’s most important sampling tasks is the construction of a school sampling frame for the target population. The sampling frame is a list of all schools in the country that have students enrolled in the target grade and is the list from which the school sample is drawn. A well-constructed sampling frame provides complete coverage of the national target population without being contaminated by incorrect or duplicate entries or entries that refer to elements that are not

Bhutan BT: Literacy Rate: Youth: % of People Age 15-24 data was reported at 98.000 % in 2022. This records an increase from the previous number of 93.000 % for 2017. Bhutan BT: Literacy Rate: Youth: % of People Age 15-24 data is updated yearly, averaging 89.500 % from Dec 2005 (Median) to 2022, with 4 observations. The data reached an all-time high of 98.000 % in 2022 and a record low of 74.000 % in 2005. Bhutan BT: Literacy Rate: Youth: % of People Age 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bhutan – Table BT.World Bank.WDI: Social: Education Statistics. Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;Weighted average;

This statistic shows the illiteracy rate in China in 2023, by region. Illiterate population refers to the proportion of the population aged 15 and older who are unable to read or have difficulty in reading. In 2023, the illiteracy rate in the Chinese Yunnan province had amounted to 6.14 percent. Illiteracy in China Literacy poses the basis for all other forms of education. Literacy skills are essential for the promotion of sustainable development, both in terms of economic progress and social advance. People with good literacy skills enjoy a better living standard and have better chances in the job market. In comparison with other countries in the Asia Pacific region, literacy in China is relatively high. China’s literacy rate has increased from 66 percent in 1982 to 97.2 percent in 2020. A distinctive gap between gender literacy existed as early as 1982, but gender differences in literacy had become less significant by 2020. This change had been facilitated by education reforms in China, namely mandatory free primary school education has helped to virtually eradicate illiteracy in China. As of 2017, 100 percent of primary-school-age children in China had been enrolled in school, making it one of the countries with the highest primary school enrollment rates worldwide. Regional disparities in literacy However, regional disparities in literacy rate still persist in China. Literacy in regions with a strong economic background tends to be higher than in underdeveloped regions. The literacy rate in Tibet had been at a staggering 29 percent compared with a national average of 3.4 percent in China.

Literacy in India has been increasing as more and more people receive a better education, but it is still far from all-encompassing. In 2023, the degree of literacy in India was about 77 percent, with the majority of literate Indians being men. It is estimated that the global literacy rate for people aged 15 and above is about 86 percent. How to read a literacy rateIn order to identify potential for intellectual and educational progress, the literacy rate of a country covers the level of education and skills acquired by a country’s inhabitants. Literacy is an important indicator of a country’s economic progress and the standard of living – it shows how many people have access to education. However, the standards to measure literacy cannot be universally applied. Measures to identify and define illiterate and literate inhabitants vary from country to country: In some, illiteracy is equated with no schooling at all, for example. Writings on the wallGlobally speaking, more men are able to read and write than women, and this disparity is also reflected in the literacy rate in India – with scarcity of schools and education in rural areas being one factor, and poverty another. Especially in rural areas, women and girls are often not given proper access to formal education, and even if they are, many drop out. Today, India is already being surpassed in this area by other emerging economies, like Brazil, China, and even by most other countries in the Asia-Pacific region. To catch up, India now has to offer more educational programs to its rural population, not only on how to read and write, but also on traditional gender roles and rights.

Azerbaijan Literacy Rate: Youth: % of People Age 15-24 data was reported at 100.000 % in 2023. This stayed constant from the previous number of 100.000 % for 2019. Azerbaijan Literacy Rate: Youth: % of People Age 15-24 data is updated yearly, averaging 100.000 % from Dec 1999 (Median) to 2023, with 14 observations. The data reached an all-time high of 100.000 % in 2023 and a record low of 100.000 % in 2023. Azerbaijan Literacy Rate: Youth: % of People Age 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Azerbaijan – Table AZ.World Bank.WDI: Social: Education Statistics. Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;Weighted average;

In 2023, ***** percent of people aged 15 years and above in Africa were able to read and write a simple statement and understand it. Regionally, Southern Africa presented the highest literacy rate, at around ** percent. North and East Africa had similar shares of literate people, at over ** percent. In contrast, **** percent and ** percent of the adult population in Central and West Africa could read and write.

Abstract

The 2009 Tonga Early Grade Reading Assessment (EGRA) was conducted in a sample of 1,203 students from 60 randomly-selected primary schools in the Kingdom of Tonga. The Tonga EGRA was carried out in November, 2009 by consultants and staff of the Ministry of Education, Women's Affairs and Culture (MEWAC) with financial support from the Australian Agency for International Development (AusAID), the New Zealand Agency for International Development (NZAID), and the Education for All - Fast Track Initiative (EFA-FTI). Technical assistance and management support was provided by the World Bank.

The Early Grade Reading Assessment (EGRA) is an oral student assessment designed to measure the most basic foundation skills for literacy acquisition in the early grades: recognizing letters of the alphabet, reading simple words, understanding sentences and paragraphs, and listening with comprehension.

The USAID Education Data for Decision Making (EdData II) project developed the EGRA methodology and has applied it in 11 countries and 19 languages. It has been adopted and used by other implementing partners in more than 30 other countries and more than 60 other languages. Data from EGRA have been used for feedback on teacher practice in rigorous but easy-to-understand ways. Many countries have shown an interest in using it as a springboard to improve reading, and have gone on to redesign their teacher training around reading.

Geographic coverage

National representative

Analysis unit

student, teacher, clusters of schools

Universe

All primary schools in the country.

Kind of data

Sample survey data [ssd]

Sampling procedure

Random stratification of schools by district; random selection of students among all classrooms in a grade tested.

On October 12 and 13, 2009, a series of preparatory meetings took place to discuss the scope and purpose of the survey. MEWAC was mainly interested in generating baseline data on average reading skills in Classes 1 to 3 to (a) identify areas where additional instruction is needed, to (b) inform the establishment of reference reading standards that can help educators monitor student's reading progression throughout the school year. With advice from the World Bank, MEWAC chose a national representative sample with contrast groups according to class level (Classes 1, 2, and 3). The final sample design did not incorporate contrast groups by school type and regions, thus, survey results can only suggest estimates by class level and gender.

The target population was defined as students enrolled in Classes 1 to 3 in primary schools implementing the national curriculum in Tongan language. Using the 2008 School Census completed in March of 2009 as a sample frame, a sample of 60 schools was selected using a stratified random design with proportional allocation based on school type -single-class (SCT), composite-class (CCT), and multi-class (MCT)- and region, to ensure all school types and regions would have a probability of selection equal to their actual distribution in the country. The final sample consisted of 1,203 students -607 girls and 596 boys- which reflects the gender parity characteristics of the target population.

Mode of data collection

Face-to-face [f2f]

Research instrument

Tonga EGRA Student test, student questionnaire, teacher questionnaire, classroom observation snapshot.

Cleaning operations

Data entry took place between January 25 and February 05, 2010.

Response rate

For the 171 teachers surveyed, the overall response rates to the survey items are above 86%. For the 1,203 students in the sample, the overall survey response rates are above 93%.

IntroductionThe success of health education programs heavily depends on the individuals’ ability to comprehend information and apply it when making decisions regarding health. Low health literacy can lead to poor health in the context of both chronic and infectious diseases, as it influences a range of health-related behaviors. Little is known about infectious disease-related health literacy in Armenia and countries of similar socio-economic profiles. We aimed to quantify the levels of infectious disease-related health literacy and knowledge among the Armenian population and explore the underlying socio-economic factors.Materials and methodsWe conducted a nationwide phone survey among 3483 adults selected via stratified two-stage probability proportional to size sampling in 2021. Descriptive statistics, simple and multivariable regression were used for the analysis.ResultsThe average age of respondents was 49.5 years. The majority were female (71.0%) and had at least 12 years of schooling (70.5%). The mean literacy score was 5.64 out of 7 (SD:1.06). The mean infectious disease knowledge score was 2.48 out of 4 (SD:1.19). Younger age, female gender, higher level of education, city residence, being employed, and having higher monthly expenditures were associated with higher mean scores of infectious disease-related health literacy and knowledge. In multivariable linear regression analysis, all the socio-demographic characteristics remained significant for both dependent variables.ConclusionsThe study results revealed population groups with a higher infectious disease-related health literacy and knowledge. Interventions should focus on groups lagging behind to engage them in proper prevention practices to protect themselves and improve health status of Armenian population.