This statistic presents the leading European countries by their level of English proficiency as of March 2019. According to data provided by Klazz, Sweden had the highest percentage of people who were proficient in English at 71 percent of the population.

Argentina scored 562 out of a maximum of 800 points in the English Proficiency Index 2023. That was the highest score among all Latin American countries included in the survey. The Argentine capital, Buenos Aires, also received the highest English proficiency score among all the Latin American cities analyzed. Mexico and Haiti received the lowest scores in the region.

In 2024, South Korea scored 523 points on the English Proficiency Index (EPI), which corresponds to a moderate English language proficiency level. According to the source, the capital city, Seoul, had the highest points in the EPI among other South Korean cities.

National Assessment of Adult Literacy, 2003 (NAAL:2003), is a study that is part of the National Assessment of Adult Literacy program. NAAL:2003 (https://nces.ed.gov/naal/) is a cross-sectional assessment that collected information about English literacy among American adults age 16 and older. The study was conducted using direct assessment from 19,000 adults 16 or older, in their homes and some in prisons from the 50 states and District of Columbia. Households and prison inmates were sampled in 2003. The weighted response rate was 62.1 percent for households and 88.3 percent for prison inmates. Key statistics produced from NAAL:2003 include reading skills, general literacy, relationships, demographics, and background characteristics.

As of 2019, around 72 percent of young women and 78 percent of young men in Nigeria were literate in English. This means they could understand, read, and write a short, simple statement, for instance, on their everyday life in English.

This data was compiled by the Washington Military Department on June 27, 2019. The Limited English Proficiency (LEP) information is summarized at the county level as well as at the census track/ county subdivision layer level. County level data was derived from the 2016 Office of Financial Management (OFM) study which provided an estimate of population with limited English proficiency at the state and county levels. The census tract data are derived from the 2015 census update and indicates language spoken at home and ability to speak English for those over five years old. All data displayed indicate a population of at least 1,000 or 5% of the population.LEPCountyv2 = Limited English Proficiency County version 2 – from OFM census dataLEPCSDv2 = Limited English Proficiency County Subdivision version 2 – data drawn from US Census 2010

LEPtractsv2 = Limited English Proficiency Census Tracts version 2 – data drawn from US Census 2010Attribute DescriptionCounty - County nameLanguage - Limited English Proficiency Language(s) spoken for the corresponding polygon - each Language is followed by a number to indicate a sequence number for each data fieldSym - Symbology field used to symbolize the polygons - holds the total count of LEP languages spoken for that polygonAFFGEOID - American Fact Finder Geospatial ID used to link tabular data to the polygons - consists of the -- Census block identifier; a concatenation of 2010 Census state FIPS code, 2010 Census county FIPS code, 2010 Census tract code, and 2010 Census block numberName - County Subdivision name from American Fact Finder (AFF) dataLanguage - Limited English Proficiency Language(s) spoken for the corresponding polygon - each Language is followed by a number to indicate a sequence number for each data fieldSym - Symbology field used to symbolize the polygons - holds the total count of LEP languages spoken for that polygonNAMELSAD10 2010 Census translated legal/statistical area description and the block group numberAFFGEOID - American Fact Finder Geospatial ID used to link tabular data to the polygons - consists of the -- Census block identifier; a concatenation of 2010 Census state FIPS code, 2010 Census county FIPS code, 2010 Census tract code, and 2010 Census block numberDisplay Label - Geographic name for each polygon from AFFSym - Symbology field used to symbolize the polygons - holds the total count of LEP languages spoken for that polygonLanguage - Limited English Proficiency Language(s) spoken for the corresponding polygon - each Language is followed by a number to indicate a sequence number for each data field

EDFacts Title III/Limited English Proficiency, 2010-11 (EDFacts T3/LEP:2010-11), is one of 17 'topics' identified in the EDFacts documentation (in this database, each 'topic' is entered as a separate study); program data is available since 2005 at . EDFacts T3/LEP:2010-11 (ed.gov/about/inits/ed/edfacts) annually collects cross-sectional data from states to support oversight and reporting of programs for the education of limited English proficient students as contained in Title I and Title III of the Elementary and Secondary Education Act (ESEA), as amended. Title III also provides programs for students who are immigrants at the SEA and LEA levels. EDFacts T3/LEP:2010-11 data were collected using the EDFacts Submission System (ESS), a centralized portal and their submission by states is mandatory and required for benefits. Not submitting the required reports by a state constitutes a failure to comply with law and may have consequences for federal funding to the state. Key statistics produced from EDFacts T3/LEP:2010-11 are from 13 data groups: AMAO I LEP Making Progress, AMAO II LEP English Attainment, AMAO III AYP for LEP, Immigrant, LEP Enrolled, LEP Students in LEP Program, LEP English Language Proficiency Results, LEP English Language Proficiency Test, Title III Teachers, Title III LEP English Language Proficiency Results, Title III LEP English Language Proficiency Test, Title III LEP Students Served, and Title III Former LEP Students. For the purposes of this system, data groups are referred to as 'variables', as a result of the structure and format of EDFacts' data.

Singapore scored 631 out of a maximum of 800 points in the English Proficiency Index 2022, the highest score across the selected Asian countries and territories. In contrast, Thailand reached an English Proficiency Index score of 416 that year.

Using Census data, the Low English Proficiency Populations Index shows Census blocks classified into five categories based on the population of persons with low English proficiency as a percentage of the total population. Persons with low English proficiency are persons identified by the Census as speaking English less than “very well.” An index score of five indicates a higher density of persons with low English proficiency.

Estonia's English Proficiency Index was the highest among CEE and CIS countries in 2023. An average respondent in the country received 621 index points, meaning that their CEFR level was comparable to C1. CIS countries reported lower proficiency levels, with respondents in Armenia and Azerbaijan receiving a score comparable to B2 and B1, respectively.

According to Cognitive Market Research, the global English Proficiency Test market size is USD 2965.5 million in 2024. It will expand at a compound annual growth rate (CAGR) of 9.70% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 1186.20 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.9% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 889.65 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 682.07 million in 2024 and will grow at a compound annual growth rate (CAGR) of 11.7% from 2024 to 2031.
Latin America had a market share for more than 5% of the global revenue with a market size of USD 148.28 million in 2024 and will grow at a compound annual growth rate (CAGR) of 9.1% from 2024 to 2031.
Middle East and Africa hada market share of around 2% of the global revenue and was estimated at a market size of USD 59.31 million in 2024 and will grow at a compound annual growth rate (CAGR) of 9.4% from 2024 to 2031.
Employers category is experiencing the fastest growth in the English Proficiency Test Market. The rising trend of multinational companies and the global nature of business operations necessitate a workforce proficient in English.

Market Dynamics of English Proficiency Test Market

Key Drivers for English Proficiency Test Market

Increasing Global Mobility of Students and Professionals to Increase the Demand Globally

The increasing global mobility of students and professionals is a significant driver in the English Proficiency Test Market. As educational institutions worldwide, particularly in English-speaking countries, attract a growing number of international students, the need for standardized English proficiency assessments becomes critical. Similarly, professionals seeking employment opportunities in multinational corporations or pursuing career advancements in global markets must demonstrate their English language capabilities. This trend is fueled by globalization and the widespread recognition of English as the lingua franca of business, academia, and technology, thereby boosting the demand for reliable and comprehensive English proficiency tests.

Rising Demand for English in Non-English Speaking Regions to Propel Market Growth

The rising demand for English language skills in non-English speaking regions is another crucial driver of the English Proficiency Test Market. As countries in Asia, Latin America, and Europe increasingly integrate into the global economy, proficiency in English becomes a valuable asset for individuals and businesses. Governments and educational systems in these regions are incorporating English language education into their curricula, and companies are investing in language training for their employees to enhance competitiveness. This growing emphasis on English proficiency is creating substantial opportunities for test providers to expand their offerings and cater to a broader audience, further propelling market growth.

Restraint Factor for the English Proficiency Test Market

High Cost of Test Preparation and Registration Fees to Limit the Sales

A significant restraint in the English Proficiency Test Market is the high cost of test preparation and registration fees. Many potential test-takers, especially students and professionals from developing countries, find these costs prohibitive. The expense of preparatory courses, study materials, and the tests themselves can deter individuals from taking the exams, limiting their opportunities for education and employment in English-speaking regions. This financial barrier not only affects individuals but also impacts the overall market growth, as it reduces the number of people who can afford to demonstrate their English proficiency through standardized tests.

Impact of Covid-19 on the English Proficiency Test Market

The COVID-19 pandemic has had a profound impact on the English Proficiency Test Market, disrupting traditional testing methods and accelerating the shift towards digital solutions. With the closure of physical testing centers and travel restrictions, many test providers faced significant challenges in administering exams. This led to a rapid adoption of online and remote testing platforms, which allowed candidates to take exams from the safety...

Cuba CU: Literacy Rate: Adult Female: % of Females Aged 15 and Above data was reported at 99.717 % in 2021. This records an increase from the previous number of 96.353 % for 2019. Cuba CU: Literacy Rate: Adult Female: % of Females Aged 15 and Above data is updated yearly, averaging 99.859 % from Dec 2002 (Median) to 2021, with 4 observations. The data reached an all-time high of 100.000 % in 2012 and a record low of 96.353 % in 2019. Cuba CU: Literacy Rate: Adult Female: % of Females Aged 15 and Above data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Cuba – Table CU.World Bank.WDI: Social: 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 (UIS). UIS.Stat Bulk Data Download Service. Accessed September 30, 2024. https://apiportal.uis.unesco.org/bdds.;Weighted average;

Title VI of the Civil Rights Act and the Executive Order on Environmental Justice (#12898) do not provide specific guidance to evaluate EJ issues within a region's transportation planning process. Therefore, MPOs must devise their own methods for ensuring that EJ issues are investigated and evaluated in transportation decision-making. In 2001, DVRPC developed an EJ technical assessment to identify direct and disparate impacts of its plans, programs, and planning process on defined population groups in the Delaware Valley region. This assessment, called the Indicators of Potential Disadvantage Methodology, is utilized in a variety of DVRPC plans and programs. DVRPC currently assesses the following population groups, defined by the U.S. Census Bureau:YouthOlder AdultsFemaleRacial MinorityEthnic MinorityForeign-BornDisabledLimited English ProficiencyLow-IncomeCensus tables used to gather data from the 2018-2022 American Community Survey 5-Year EstimatesUsing U.S. Census American Community Survey data, the population groups listed above are identified and located at the census tract level. Data is gathered at the regional level, combining populations from each of the nine counties, for either individuals or households, depending on the indicator. From there, the total number of persons in each demographic group is divided by the appropriate universe (either population or households) for the nine-county region, providing a regional average for that population group. Any census tract that meets or exceeds the regional average level, or threshold, is considered an EJ-sensitive tract for that group.Census tables used to gather data from the 2018-2022 American Community Survey 5-Year Estimates.For more information and for methodology, visit DVRPC's website:http://www.dvrpc.org/GetInvolved/TitleVI/For technical documentation visit DVRPC's GitHub IPD repo: https://github.com/dvrpc/ipdSource of tract boundaries: 2020 US Census Bureau, TIGER/Line ShapefilesNote: Tracts with null values should be symbolized as "Insufficient or No Data".Data Dictionary for Attributes:(Source = DVRPC indicates a calculated field)FieldAliasDescriptionSourceyearIPD analysis yearDVRPCgeoid2011-digit tract GEOIDCensus tract identifierACS 5-yearstatefp2-digit state GEOIDFIPS Code for StateACS 5-yearcountyfp3-digit county GEOIDFIPS Code for CountyACS 5-yeartractceTract numberTract NumberACS 5-yearnameTract numberCensus tract identifier with decimal placesACS 5-yearnamelsadTract nameCensus tract name with decimal placesACS 5-yeard_classDisabled percentile classClassification of tract's disabled percentage as: well below average, below average, average, above average, or well above averagecalculatedd_estDisabled count estimateEstimated count of disabled populationACS 5-yeard_est_moeDisabled count margin of errorMargin of error for estimated count of disabled populationACS 5-yeard_pctDisabled percent estimateEstimated percentage of disabled populationACS 5-yeard_pct_moeDisabled percent margin of errorMargin of error for percentage of disabled populationACS 5-yeard_pctileDisabled percentileTract's regional percentile for percentage disabledcalculatedd_scoreDisabled percentile scoreCorresponding numeric score for tract's disabled classification: 0, 1, 2, 3, 4calculatedem_classEthnic minority percentile classClassification of tract's Hispanic/Latino percentage as: well below average, below average, average, above average, or well above averagecalculatedem_estEthnic minority count estimateEstimated count of Hispanic/Latino populationACS 5-yearem_est_moeEthnic minority count margin of errorMargin of error for estimated count of Hispanic/Latino populationACS 5-yearem_pctEthnic minority percent estimateEstimated percentage of Hispanic/Latino populationcalculatedem_pct_moeEthnic minority percent margin of errorMargin of error for percentage of Hispanic/Latino populationcalculatedem_pctileEthnic minority percentileTract's regional percentile for percentage Hispanic/Latinocalculatedem_scoreEthnic minority percentile scoreCorresponding numeric score for tract's Hispanic/Latino classification: 0, 1, 2, 3, 4calculatedf_classFemale percentile classClassification of tract's female percentage as: well below average, below average, average, above average, or well above averagecalculatedf_estFemale count estimateEstimated count of female populationACS 5-yearf_est_moeFemale count margin of errorMargin of error for estimated count of female populationACS 5-yearf_pctFemale percent estimateEstimated percentage of female populationACS 5-yearf_pct_moeFemale percent margin of errorMargin of error for percentage of female populationACS 5-yearf_pctileFemale percentileTract's regional percentile for percentage femalecalculatedf_scoreFemale percentile scoreCorresponding numeric score for tract's female classification: 0, 1, 2, 3, 4calculatedfb_classForeign-born percentile classClassification of tract's foreign born percentage as: well below average, below average, average, above average, or well above averagecalculatedfb_estForeign-born count estimateEstimated count of foreign born populationACS 5-yearfb_est_moeForeign-born count margin of errorMargin of error for estimated count of foreign born populationACS 5-yearfb_pctForeign-born percent estimateEstimated percentage of foreign born populationcalculatedfb_pct_moeForeign-born percent margin of errorMargin of error for percentage of foreign born populationcalculatedfb_pctileForeign-born percentileTract's regional percentile for percentage foreign borncalculatedfb_scoreForeign-born percentile scoreCorresponding numeric score for tract's foreign born classification: 0, 1, 2, 3, 4calculatedle_classLimited English proficiency percentile classClassification of tract's limited english proficiency percentage as: well below average, below average, average, above average, or well above averagecalculatedle_estLimited English proficiency count estimateEstimated count of limited english proficiency populationACS 5-yearle_est_moeLimited English proficiency count margin of errorMargin of error for estimated count of limited english proficiency populationACS 5-yearle_pctLimited English proficiency percent estimateEstimated percentage of limited english proficiency populationACS 5-yearle_pct_moeLimited English proficiency percent margin of errorMargin of error for percentage of limited english proficiency populationACS 5-yearle_pctileLimited English proficiency percentileTract's regional percentile for percentage limited english proficiencycalculatedle_scoreLimited English proficiency percentile scoreCorresponding numeric score for tract's limited english proficiency classification: 0, 1, 2, 3, 4calculatedli_classLow-income percentile classClassification of tract's low income percentage as: well below average, below average, average, above average, or well above averagecalculatedli_estLow-income count estimateEstimated count of low income (below 200% of poverty level) populationACS 5-yearli_est_moeLow-income count margin of errorMargin of error for estimated count of low income populationACS 5-yearli_pctLow-income percent estimateEstimated percentage of low income (below 200% of poverty level) populationcalculatedli_pct_moeLow-income percent margin of errorMargin of error for percentage of low income populationcalculatedli_pctileLow-income percentileTract's regional percentile for percentage low incomecalculatedli_scoreLow-income percentile scoreCorresponding numeric score for tract's low income classification: 0, 1, 2, 3, 4calculatedoa_classOlder adult percentile classClassification of tract's older adult percentage as: well below average, below average, average, above average, or well above averagecalculatedoa_estOlder adult count estimateEstimated count of older adult population (65 years or older)ACS 5-yearoa_est_moeOlder adult count margin of errorMargin of error for estimated count of older adult populationACS 5-yearoa_pctOlder adult percent estimateEstimated percentage of older adult population (65 years or older)ACS 5-yearoa_pct_moeOlder adult percent margin of errorMargin of error for percentage of older adult populationACS 5-yearoa_pctileOlder adult percentileTract's regional percentile for percentage older adultcalculatedoa_scoreOlder adult percentile scoreCorresponding numeric score for tract's older adult classification: 0, 1, 2, 3, 4calculatedrm_classRacial minority percentile classClassification of tract's non-white percentage as: well below average, below average, average, above average, or well above averagecalculatedrm_estRacial minority count estimateEstimated count of non-white populationACS 5-yearrm_est_moeRacial minority count margin of errorMargin of error for estimated count of non-white populationACS 5-yearrm_pctRacial minority percent estimateEstimated percentage of non-white populationcalculatedrm_pct_moeRacial minority percent margin of errorMargin of error for percentage of non-white populationcalculatedrm_pctileRacial minority percentileTract's regional percentile for percentage non-whitecalculatedrm_scoreRacial minority percentile scoreCorresponding numeric score for tract's non-white classification: 0, 1, 2, 3, 4calculatedtot_ppTotal population estimateEstimated total population of tract (universe [or denominator] for youth, older adult, female, racial minoriry, ethnic minority, & foreign born)ACS 5-yeartot_pp_moeTotal population margin of errorMargin of error for estimated total population of tractACS 5-yeary_classYouth percentile classClassification of tract's youth percentage as: well below average, below average, average, above average, or well above averagecalculatedy_estYouth count estimateEstimated count of youth population (under 18 years)ACS 5-yeary_est_moeYouth count margin of errorMargin of error for estimated count of youth populationACS 5-yeary_pctYouth population percentage estimateEstimated percentage of youth population (under 18 years)calculatedy_pct_moeYouth population percentage margin of

Burundi BI: Literacy Rate: Adult Male: % of Males Aged 15 and Above data was reported at 81.840 % in 2022. This records an increase from the previous number of 76.000 % for 2017. Burundi BI: Literacy Rate: Adult Male: % of Males Aged 15 and Above data is updated yearly, averaging 68.500 % from Dec 1979 (Median) to 2022, with 8 observations. The data reached an all-time high of 81.840 % in 2022 and a record low of 34.000 % in 1979. Burundi BI: Literacy Rate: Adult Male: % of Males Aged 15 and Above data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Burundi – Table BI.World Bank.WDI: Social: Education Statistics. 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 (UIS). UIS.Stat Bulk Data Download Service. Accessed September 30, 2024. https://apiportal.uis.unesco.org/bdds.;Weighted average;

Table from the American Community Survey (ACS) B16003 of age by language spoken at home for the population 5 years and over in limited English-speaking households. These are multiple, nonoverlapping vintages of the 5-year ACS estimates of population and housing attributes starting in 2010 shown by the corresponding census tract vintage. Also includes the most recent release annually.King County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010. Vintage identified in the "ACS Vintage" field.The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades. Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.Vintages: 2010, 2015, 2020, 2021, 2022, 2023ACS Table(s): B16003Data downloaded from: <a href='https://data.c

This statistic shows the English language proficiency in greater China in 2017, by region or city. According to EF Education First English Proficiency Index ranking, in 2017, Shanghai ranked the highest among regions in greater China with an average English test score of 57.91.

The Delaware Valley Regional Planning Commission (DVRPC) is committed to upholding the principles and intentions of the 1964 Civil Rights Act and related nondiscrimination statutes in all of the Commission’s work, including publications, products, communications, public input, and decision-making processes. Language barriers may prohibit people who are Limited in English Proficiency (also known as LEP persons) from obtaining services, information, or participating in public planning processes. To better identify LEP populations and thoroughly evaluate the Commission’s efforts to provide meaningful access, DVRPC has produced this Limited-English Proficiency Plan. This is the data that was used to make the maps for the upcoming plan.Census tables used to gather data from the 2017 - 2021 American Community Survey 5-Year EstimatesACS 2016-2020, Table C16001: Language Spoken at Home by Ability to Speak English for the Population 5 Years and Over. ACS data are derived from a survey and are subject to sampling variablity.*Limited English Proficiency (LEP) refers to those persons that speak English less than "very well". DVRPC has mapped the below Language Groups for our Plan.SpanishRussianChineseKoreanVietnameseSource of tract boundaries: US Census Bureau. The TIGER/Line Files Please refer to U:_OngoingProjects\LEP\ACS_5YR_C16001_LEP_metadata.xlsx for full attribute look up and fields used in making the DVRPC LEP Map Series.Please contact Chris Pollard (cpollard@dvrpc.org) should you have any questions about this dataset.

The census is undertaken by the Office for National Statistics every 10 years and gives us a picture of all the people and households in England and Wales. The most recent census took place in March of 2021.The census asks every household questions about the people who live there and the type of home they live in. In doing so, it helps to build a detailed snapshot of society. Information from the census helps the government and local authorities to plan and fund local services, such as education, doctors' surgeries and roads.Key census statistics for Leicester are published on the open data platform to make information accessible to local services, voluntary and community groups, and residents. There is also a dashboard published showcasing various datasets from the census allowing users to view data for all MSOAs and compare this with Leicester overall statistics.Further information about the census and full datasets can be found on the ONS website - https://www.ons.gov.uk/census/aboutcensus/censusproductsProficiency in EnglishThis dataset provides Census 2021 estimates that classify usual residents in England and Wales by their proficiency in English. The estimates are as at Census Day, 21 March 2021.Definition: How well people whose main language is not English (English or Welsh in Wales) speak English.This dataset provides details for the MSOAs of Leicester city.

Buenos Aires, Argentina scored 584 out of a maximum of 800 points in the English Proficiency Index 2023. That was the highest score among all the Latin American cities surveyed. In that year, nine cities in the region socred in the "high proficiency" range (550-599 points).

Jordan JO: Literacy Rate: Adult: % of People Aged 15 and Above data was reported at 97.890 % in 2012. This records an increase from the previous number of 95.904 % for 2011. Jordan JO: Literacy Rate: Adult: % of People Aged 15 and Above data is updated yearly, averaging 92.200 % from Dec 1979 (Median) to 2012, with 7 observations. The data reached an all-time high of 97.890 % in 2012 and a record low of 66.797 % in 1979. Jordan JO: 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 Jordan – Table JO.World Bank.WDI: 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).