Among the states in India, Kerala had the highest literary rate with ** percent in 2011. Chandigarh, Himachal Pradesh and the capital territory of Delhi followed Kerala with above average literacy rates. Notably, all the leading states in the country had more literate males than females at the time of the census.

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.

As of March 2020, around 4.46 million Mexicans over 15 years of age were unable to write or read, approximately 4.74 percent. Mexico State, the federal entity with the highest share of the population, also registered the highest number of literate people with over 12 million.

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• The Healthcare IT market size is expected to be worth around USD 1728 Bn by 2032
• According to a report by UNESCO, countries in South and South-West Asia have the highest number of illiterate adults in the world, estimated at 388 million.
• Approximately 36% of adult Americans possess only basic or below basic health literacy skills.
• Only 12% of Americans are considered proficient in their health literacy skills.
• Health literacy levels in China increased from 6.48% of the population in 2008 to 23.15% in 2020.
• A recent study analyzing global health literacy research from 1995 to 2020 identified the United States, Australia, and the United Kingdom as major contributors to the international collaboration network on health literacy.
• Mental health has been the most active research field in recent years in the context of health literacy.

Literacy Rate: Tamil Nadu data was reported at 80.100 % in 12-01-2011. This records an increase from the previous number of 73.450 % for 12-01-2001. Literacy Rate: Tamil Nadu data is updated decadal, averaging 58.525 % from Dec 1961 (Median) to 12-01-2011, with 6 observations. The data reached an all-time high of 80.100 % in 12-01-2011 and a record low of 36.390 % in 12-01-1961. Literacy Rate: Tamil Nadu data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Education Sector – Table IN.EDA001: Literacy Rate.

The statistic displays the main states and union territories in India with the highest number of illiterate people in 2011. In that year, Uttar Pradesh was at the top of the list, with more than ** million illiterate people, followed by the state of Bihar with over ** million people.

This dataset tracks annual reading and language arts proficiency from 2011 to 2022 for State College Area High School vs. Pennsylvania and State College Area School District

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.

Graph and download economic data for Expenditures: Reading by Highest Education: Less Than College Graduate: High School Graduate with Some College (CXUREADINGLB1405M) from 2012 to 2023 about book, no college, secondary schooling, secondary, expenditures, education, and USA.

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.

The statistic depicts the literacy rate in Mexico from 2008 to 2020. The literacy rate measures the percentage of people ages 15 and above who can read and write. In 2020, Mexico's literacy rate was around 95.25 percent. The source does not provide data for 2019.Education in MexicoThe literacy rate is commonly defined as the share of people in a country who are older than 15 years and are able to read and write. In Mexico, a state with more than 115 million inhabitants, the literacy rate is above 90 percent, making it significantly higher than the global average. More than 70 percent of Mexico’s population is older than 15 years, a figure than has been quite consistent over the last ten years. Mexico’s compulsory education comprises grades 1 to 9, with an optional secondary education up to grade 12. Literacy is considered basic education. The lowest literacy rates can be found in African countries, the highest in Europe. Additionally, the literacy rate is one of the factors that determines a country’s ranking on the Human Development Index of the United Nations, which ranks the overall well-being of a country’s population. Apart from literacy, it also includes factors such as per-capita income, health and life expectancy and others. Mexico is currently not among the countries with the highest Human Development Index value.

Abstract

The National Family Health Surveys (NFHS) programme, initiated in the early 1990s, has emerged as a nationally important source of data on population, health, and nutrition for India and its states. The 2005-06 National Family Health Survey (NFHS-3), the third in the series of these national surveys, was preceded by NFHS-1 in 1992-93 and NFHS-2 in 1998-99. Like NFHS-1 and NFHS-2, NFHS-3 was designed to provide estimates of important indicators on family welfare, maternal and child health, and nutrition. In addition, NFHS-3 provides information on several new and emerging issues, including family life education, safe injections, perinatal mortality, adolescent reproductive health, high-risk sexual behaviour, tuberculosis, and malaria. Further, unlike the earlier surveys in which only ever-married women age 15-49 were eligible for individual interviews, NFHS-3 interviewed all women age 15-49 and all men age 15-54. Information on nutritional status, including the prevalence of anaemia, is provided in NFHS3 for women age 15-49, men age 15-54, and young children.

A special feature of NFHS-3 is the inclusion of testing of the adult population for HIV. NFHS-3 is the first nationwide community-based survey in India to provide an estimate of HIV prevalence in the general population. Specifically, NFHS-3 provides estimates of HIV prevalence among women age 15-49 and men age 15-54 for all of India, and separately for Uttar Pradesh and for Andhra Pradesh, Karnataka, Maharashtra, Manipur, and Tamil Nadu, five out of the six states classified by the National AIDS Control Organization (NACO) as high HIV prevalence states. No estimate of HIV prevalence is being provided for Nagaland, the sixth high HIV prevalence state, due to strong local opposition to the collection of blood samples.

NFHS-3 covered all 29 states in India, which comprise more than 99 percent of India's population. NFHS-3 is designed to provide estimates of key indicators for India as a whole and, with the exception of HIV prevalence, for all 29 states by urban-rural residence. Additionally, NFHS-3 provides estimates for the slum and non-slum populations of eight cities, namely Chennai, Delhi, Hyderabad, Indore, Kolkata, Meerut, Mumbai, and Nagpur. NFHS-3 was conducted under the stewardship of the Ministry of Health and Family Welfare (MOHFW), Government of India, and is the result of the collaborative efforts of a large number of organizations. The International Institute for Population Sciences (IIPS), Mumbai, was designated by MOHFW as the nodal agency for the project. Funding for NFHS-3 was provided by the United States Agency for International Development (USAID), DFID, the Bill and Melinda Gates Foundation, UNICEF, UNFPA, and MOHFW. Macro International, USA, provided technical assistance at all stages of the NFHS-3 project. NACO and the National AIDS Research Institute (NARI) provided technical assistance for the HIV component of NFHS-3. Eighteen Research Organizations, including six Population Research Centres, shouldered the responsibility of conducting the survey in the different states of India and producing electronic data files.

The survey used a uniform sample design, questionnaires (translated into 18 Indian languages), field procedures, and procedures for biomarker measurements throughout the country to facilitate comparability across the states and to ensure the highest possible data quality. The contents of the questionnaires were decided through an extensive collaborative process in early 2005. Based on provisional data, two national-level fact sheets and 29 state fact sheets that provide estimates of more than 50 key indicators of population, health, family welfare, and nutrition have already been released. The basic objective of releasing fact sheets within a very short period after the completion of data collection was to provide immediate feedback to planners and programme managers on key process indicators.

Geographic coverage

• National (29 states )
• Regional (for HIV Prevalence : Andhra Pradesh, Karnataka, Maharashtra, Manipur, and Tamil Nadu)
• Local (population and health indicators for slum and non-slum populations for eight cities, namely Chennai, Delhi, Hyderabad, Indore, Kolkata, Meerut, Mumbai, and Nagpur)

Analysis unit

• Household
• Women age 15-49
• Men age 15-59

Universe

The population covered by the 2005 DHS is defined as the universe of all ever-married women age 15-49, NFHS-3 included never married women age 15-49 and both ever-married and never married men age 15-54 as eligible respondents.

Kind of data

Sample survey data

Sampling procedure

SAMPLE SIZE

Since a large number of the key indicators to be estimated from NFHS-3 refer to ever-married women in the reproductive ages of 15-49, the target sample size for each state in NFHS-3 was estimated in terms of the number of ever-married women in the reproductive ages to be interviewed.

The initial target sample size was 4,000 completed interviews with ever-married women in states with a 2001 population of more than 30 million, 3,000 completed interviews with ever-married women in states with a 2001 population between 5 and 30 million, and 1,500 completed interviews with ever-married women in states with a population of less than 5 million. In addition, because of sample-size adjustments required to meet the need for HIV prevalence estimates for the high HIV prevalence states and Uttar Pradesh and for slum and non-slum estimates in eight selected cities, the sample size in some states was higher than that fixed by the above criteria. The target sample was increased for Andhra Pradesh, Karnataka, Maharashtra, Manipur, Nagaland, Tamil Nadu, and Uttar Pradesh to permit the calculation of reliable HIV prevalence estimates for each of these states. The sample size in Andhra Pradesh, Delhi, Maharashtra, Tamil Nadu, Madhya Pradesh, and West Bengal was increased to allow separate estimates for slum and non-slum populations in the cities of Chennai, Delhi, Hyderabad, Indore, Kolkata, Mumbai, Meerut, and Nagpur.

The target sample size for HIV tests was estimated on the basis of the assumed HIV prevalence rate, the design effect of the sample, and the acceptable level of precision. With an assumed level of HIV prevalence of 1.25 percent and a 15 percent relative standard error, the estimated sample size was 6,400 HIV tests each for men and women in each of the high HIV prevalence states. At the national level, the assumed level of HIV prevalence of less than 1 percent (0.92 percent) and less than a 5 percent relative standard error yielded a target of 125,000 HIV tests at the national level.

Blood was collected for HIV testing from all consenting ever-married and never married women age 15-49 and men age 15-54 in all sample households in Andhra Pradesh, Karnataka, Maharashtra, Manipur, Tamil Nadu, and Uttar Pradesh. All women age 15-49 and men age 15-54 in the sample households were eligible for interviewing in all of these states plus Nagaland. In the remaining 22 states, all ever-married and never married women age 15-49 in sample households were eligible to be interviewed. In those 22 states, men age 15-54 were eligible to be interviewed in only a subsample of households. HIV tests for women and men were carried out in only a subsample of the households that were selected for men's interviews in those 22 states. The reason for this sample design is that the required number of HIV tests is determined by the need to calculate HIV prevalence at the national level and for some states, whereas the number of individual interviews is determined by the need to provide state level estimates for attitudinal and behavioural indicators in every state. For statistical reasons, it is not possible to estimate HIV prevalence in every state from NFHS-3 as the number of tests required for estimating HIV prevalence reliably in low HIV prevalence states would have been very large.

SAMPLE DESIGN

The urban and rural samples within each state were drawn separately and, to the extent possible, unless oversampling was required to permit separate estimates for urban slum and non-slum areas, the sample within each state was allocated proportionally to the size of the state's urban and rural populations. A uniform sample design was adopted in all states. In each state, the rural sample was selected in two stages, with the selection of Primary Sampling Units (PSUs), which are villages, with probability proportional to population size (PPS) at the first stage, followed by the random selection of households within each PSU in the second stage. In urban areas, a three-stage procedure was followed. In the first stage, wards were selected with PPS sampling. In the next stage, one census enumeration block (CEB) was randomly selected from each sample ward. In the final stage, households were randomly selected within each selected CEB.

SAMPLE SELECTION IN RURAL AREAS

In rural areas, the 2001 Census list of villages served as the sampling frame. The list was stratified by a number of variables. The first level of stratification was geographic, with districts being subdivided into contiguous regions. Within each of these regions, villages were further stratified using selected variables from the following list: village size, percentage of males working in the nonagricultural sector, percentage of the population belonging to scheduled castes or scheduled tribes, and female literacy. In addition to these variables, an external estimate of HIV prevalence, i.e., 'High', 'Medium' or 'Low', as estimated for all the districts in high HIV prevalence states, was used for stratification in high HIV prevalence states. Female literacy was used for implicit stratification (i.e., villages were

Metric scores are not reported for n-sizes under 10. Per OSSE's policy, secondary suppression is applied to all student groups when a complementary group has an n-size under 10 or is top/bottom suppressed to prevent the calculation of suppressed data. For more on statewide assessment results, see how this is measured.

Data Source: Office of the State Superintendent of Education

Why This Matters

Learning how to read at an early age is important for children’s future. Not only is reading proficiency critical for lifelong learning, but research suggests that reading proficiency can lead to better academic performance in all subjects including math, science, and social studies.

3rd-graders who are not proficient in reading are four times more likely to not graduate high school on time and are also more likely to drop out of high school.

Nationally, fewer Black and Latino students receive proficient scores on statewide tests compared to white and Asian students. Racial disparities in socioeconomic status and resources, neighborhood and school racial segregation, and racial biases in educational spaces contribute to racial gaps in test scores.

The District Response

The Office of the State Superintendent of Education (OSSE) has awarded additional funding to Local Education Agencies (LEAs) for English language arts (ELA) High-Impact Tutoring (HIT) and ELA High Quality Instructional Materials (HQIM).

DC Public Schools’ Five-year Strategic Plan identifies key actions for supporting literacy education including setting a goal of 80% of students passing or meet/exceeding performance expectations on the state ELA assessment.

OSSE offers an array of instructional materials, distance learning tools, and educational resources to promote English language arts and literacy education.

The highest literacy rates in Nigeria were registered in the southern regions of the country. In the South West, 89 percent of males and 80.6 percent of females were literate as of 2018. Also, the south zones showed the lowest percentage differences between male and female literacy. Female literacy rate in Nigeria is among the highest in West Africa. The highest female literacy rates were registered in Cabo Verde and Ghana, while Nigeria ranked third.

The National Science Foundation (NSF) Surveys of Public Attitudes monitored the general public's attitudes toward and interest in science and technology. In addition, the survey assessed levels of literacy and understanding of scientific and environmental concepts and constructs, how scientific knowledge and information were acquired, attentiveness to public policy issues, and computer access and usage. Since 1979, the survey was administered at regular intervals (occurring every two or three years), producing 11 cross-sectional surveys through 2001. Data for Part 1 (Survey of Public Attitudes Multiple Wave Data) were comprised of the survey questionnaire items asked most often throughout the 22-year survey series and account for approximately 70 percent of the original questions asked. Data for Part 2, General Social Survey Subsample Data, combine the 1983-1999 Survey of Public Attitudes data with a subsample from the 2002 General Social Survey (GSS) (GENERAL SOCIAL SURVEYS, 1972-2002: [CUMULATIVE FILE] [ICPSR 3728]) and focus solely on levels of education and computer access and usage. Variables for Part 1 include the respondents' interest in new scientific or medical discoveries and inventions, space exploration, military and defense policies, whether they voted in a recent election, if they had ever contacted an elected or public official about topics regarding science, energy, defense, civil rights, foreign policy, or general economics, and how they felt about government spending on scientific research. Respondents were asked how they received information concerning science or news (e.g., via newspapers, magazines, or television), what types of television programming they watched, and what kind of magazines they read. Respondents were asked a series of questions to assess their understanding of scientific concepts like DNA, probability, and experimental methods. Respondents were also asked if they agreed with statements concerning science and technology and how they affect everyday living. Respondents were further asked a series of true and false questions regarding science-based statements (e.g., the center of the Earth is hot, all radioactivity is manmade, electrons are smaller than atoms, the Earth moves around the sun, humans and dinosaurs co-existed, and human beings developed from earlier species of animals). Variables for Part 2 include highest level of math attained in high school, whether the respondent had a postsecondary degree, field of highest degree, number of science-based college courses taken, major in college, household ownership of a computer, access to the World Wide Web, number of hours spent on a computer at home or at work, and topics searched for via the Internet. Demographic variables for Parts 1 and 2 include gender, race, age, marital status, number of people in household, level of education, and occupation.

The state of Uttar Pradesh had the highest number of literate people without educational attainment in India in 2011, with over 5.3 million people. Uttar Pradesh located in the north of India is one of the most populous state in the country.

A survey conducted in the United States in August 2023 found that digital literacy among U.S. adults varied depending on the age group. Younger generations, aged 18 to 29, showed a much higher awareness of digital topics, such as online privacy, and an understanding of generative AI. However, there was a notable gap between them and individuals 65 and older. For example, only 26 percent of respondents older than 65 years could identify an example of two-factor authentication, compared to 68 percent of younger respondents.

According to a survey on the state of digital literacy in 2022, DI Yogyakarta has the highest digital literacy Index score among other provinces in Indonesia with **** points. The same survey found that Indonesia's digital literacy index score increased from **** in 2020 to **** in 2022.

This dataset tracks annual reading and language arts proficiency from 2011 to 2022 for Corl Street Elementary School vs. Pennsylvania and State College Area School District

The statistic shows various occasions for reading among consumers in the United States in 2017, by ethnicity. During the survey, 91 percent of Black or African American respondents stated that they read on the weekend.