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 ** percent of the population.

In 2023, the United Kingdom had the most students learning English as a foreign language and accounted for ** percent of the total worldwide. ****** in the list was Australia, where ** percent of students studying English as a foreign language were hosted.

Using data from reports such as the "English Proficiency Index" (EDU) from Education First, one can see the significant impact of culture, education and globalization on the ability of citizens of different countries to speak English.

In 2023, the growth in the number of students learning English as a foreign language was significant. New Zealand recorded a percentage growth of *** percent between 2022 and 2023.

In 2025, there were around 1.53 billion people worldwide who spoke English either natively or as a second language, slightly more than the 1.18 billion Mandarin Chinese speakers at the time of survey. Hindi and Spanish accounted for the third and fourth most widespread languages that year. Languages in the United States The United States does not have an official language, but the country uses English, specifically American English, for legislation, regulation, and other official pronouncements. The United States is a land of immigration, and the languages spoken in the United States vary as a result of the multicultural population. The second most common language spoken in the United States is Spanish or Spanish Creole, which over than 43 million people spoke at home in 2023. There were also 3.5 million Chinese speakers (including both Mandarin and Cantonese),1.8 million Tagalog speakers, and 1.57 million Vietnamese speakers counted in the United States that year. Different languages at home The percentage of people in the United States speaking a language other than English at home varies from state to state. The state with the highest percentage of population speaking a language other than English is California. About 45 percent of its population was speaking a language other than English at home in 2023.

This statistic shows the results of a survey conducted in the Middle East and North Africa region in 2015 on the percentage of people who use the English language to access different types of media. According to the survey, ** percent of respondents in Egypt used English to access the internet, as opposed to ***** percent who used English to access TV.

In 2022, Australia had the highest distribution of English language learning student weeks, totaling ** percent. The second-placed country in the list was Canada, with their share of English language student weeks totaling just short of ** percent of the countries surveyed.

Proportion of Twitter posts in most select languages by article author country.

The data collected aim to test whether English proficiency levels in a country are positively associated with higher democratic values in that country. English proficiency is sourced from statistics by Education First’s "EF English Proficiency Index" which covers countries' scores for the calendar year 2022 and 2021. The EF English Proficiency Index ranks 111 countries in five different categories based on their English proficiency scores that were calculated from the test results of 2.1 million adults. While democratic values are operationalized through the liberal democracy index from the V-Dem Institute annual report for 2022 and 2021. Additionally, the data is utilized to test whether English language media consumption acts as a mediating variable between English proficiency and democracy levels in a country, while also looking at other possible regression variables. In order to conduct the linear regression analyses for the dats, the software that was utilized for this research was Microsoft Excel.The raw data set consists of 90 nation states in two years from 2022 and 2021. The raw data is utilized for two separate data sets the first of which is democracy indicators which has the regression variables of EPI, HDI, and GDP. For this table set there is a total of 360 data entries. HDI scores are a statistical summary measure that is developed by the United Nations Development Programme (UNDP) which measures the levels of human development in 190 countries. The data for nominal gross domestic product scores (GDP) are sourced from the World Bank. Having strong regression variables that have been proven to have a positive link with democracy in the data analysis such as GDP and HDI, would allow the regression analysis to identify whether there is a true relationship between English proficiency and democracy levels in a country. While the second data set has a total of 720 data entries and aims to identify English proficiency indicators the data set has 7 various regression variables which include, LDI scores, Years of Mandatory English Education, Heads of States Publicly speaking English, GDP PPP (2021USD), Common Wealth, BBC web traffic and CNN web traffic. The data for years of mandatory English education is sourced from research at the University of Winnipeg and is coded in the data set based on the number of years a country has English as a mandatory subject. The range of this data is from 0 to 13 years of English being mandatory. It is important to note that this data only concerns public schools and does not extend to the private school systems in each country. The data for heads of state publicly speaking English was done through a video data analysis of all heads of state. The data was only used for heads of state who had been in their position for at least a year to ensure the accuracy of the data collected; with a year in power, for heads of state that had not been in their position for a year, data was taken from the previous head of state. This data only takes into account speeches and interviews that were conducted during their incumbency. The data for each country’s GDP PPP scores are sourced from the World Bank, which was last updated for a majority of the countries in 2021 and is tied to the US dollar. Data for the commonwealth will only include members of the commonwealth that have been historically colonized by the United Kingdom. Any country that falls under that category will be coded as 1 and any country that does not will be coded as 0. For BBC and CNN web traffic that data is sourced by using tools in Semrush which provide a rough estimate of how much web traffic each news site generates in each country. Which will be utilized to identify the average number of web traffic for BBC News and CNN World News for both the 2021 and 2022 calendar. The traffic for each country will also be measured per capita, per 10 thousand people to ensure that the population density of a country does not influence the results. The population of each country for both 2021 and 2022 is sourced from the United Nations revision of World Population Prospects of both 2021 and 2022 respectively.

Proportion of Facebook posts in select languages by article author country.

This Dataset, in 29 files of xlsx format, contains the data of all metrics and accumulated information as they are described in the methodology, results and discussion section of the research article "Exploring the Dominance of the English Language on the Websites of EU Countries".

This statistic shows the results of a 2018 survey, broken down by country, which asked young people in the European Union how many languages they could read or write in. As can be seen in the statistic, knowledge of other languages varies quite a lot between different countries. In the United Kingdom, ** percent of respondents advised that they can only read or write in *** language, compared with *** percent of Danish youths.

Migrants can be considered as having made positive steps towards resettlement or integration when they are empowered to gain employment, contribute to the local and national economy and to make other positive contributions to their communities. Therefore, this indicator seeks to measure one key aspect of integration by identifying the proportion of non-English speaking third country nationals in a Local Authority area able to access and progress in English for Speakers of Other Languages (ESOL) courses, as measured by course waiting lists and attainment levels.

Dataset population: Persons aged 3 and over

Main language (detailed)

The language that is a person's first or preferred language.

This information helps central government, local authorities and the NHS to allocate resources and provide services for non-English speakers, e.g. English teaching and translation services. It is a better indicator than country of birth, which was previously used to forecast the additional cost of providing services to people whose first language is not English.

The data are also used to assess the impact of English or Welsh language ability on employment and other social inclusion indicators.

Information on the number of British Sign Language users helps with service planning and assists in developing policies to address the needs of the deaf community.

These statistics are used by public service providers to effectively target the delivery of their services, for example in the provision of translation and interpretation services, the availability of English language lessons, and the distribution of official information leaflets in alternative languages.

In 2023, the United Kingdom had the most students learning English as a foreign language. There were approximately ******* students who were learning English as a second language that year, followed by Australia with almost ******* foreign students. The third place ranking was completed by the U.S., with around ******* students learning English as a foreign language. The global English learning market Learning English has become increasingly important for young people, especially in terms of international communication, increasing employability at multinational firms or securing work abroad, and specializing in fields as a global expert. The United Kingdom had both the highest number of students learning English as a foreign language and the shared highest distribution of English language learning revenue. In the past few years, the English language learning market has experienced a decrease in revenue, perhaps partially due to more free online platforms becoming accessible, as well as more companies and schools implementing English learning systems. 2022, however, has shown signs of improvement in terms of revenue. In 2020, revenues generated by the English learning market were dramatically lower due to travel restrictions implemented to limit the spread of COVID-19, as this trend continued into 2021. The global language services industry Over the course of the past two decades, the need for bilingual and multilingual skills has increased substantially. In an increasingly globalized world that is becoming more and more connected over time, people have been motivated to learn additional languages to suit both personal and professional demands. The market size of the global language services industry has grown to reflect this, with expected revenues of around ** billion U.S. dollars projected for 2022.

Delayed or impaired language development is a common developmental concern, yet there is little agreement about the criteria used to identify and classify language impairments in children. Children's language difficulties are at the interface between education, medicine and the allied professions, who may all adopt different approaches to conceptualising them. Our goal in this study was to use an online Delphi technique to see whether it was possible to achieve consensus among professionals on appropriate criteria for identifying children who might benefit from specialist services. We recruited a panel of 59 experts representing ten disciplines (including education, psychology, speech-language therapy/pathology, paediatrics and child psychiatry) from English-speaking countries (Australia, Canada, Ireland, New Zealand, United Kingdom and USA). The starting point for round 1 was a set of 46 statements based on articles and commentaries in a special issue of a journal focusing on this topic. Panel members rated each statement for both relevance and validity on a seven-point scale, and added free text comments. These responses were synthesised by the first two authors, who then removed, combined or modified items with a view to improving consensus. The resulting set of statements was returned to the panel for a second evaluation (round 2). Consensus (percentage reporting 'agree' or 'strongly agree') was at least 80 percent for 24 of 27 round 2 statements, though many respondents qualified their response with written comments. These were again synthesised by the first two authors. The resulting consensus statement is reported here, with additional summary of relevant evidence, and a concluding commentary on residual disagreements and gaps in the evidence base.

Burkina Faso BF: International Migrant Stock: % of Population data was reported at 3.892 % in 2015. This records a decrease from the previous number of 4.311 % for 2010. Burkina Faso BF: International Migrant Stock: % of Population data is updated yearly, averaging 4.310 % from Dec 1990 (Median) to 2015, with 6 observations. The data reached an all-time high of 4.480 % in 2000 and a record low of 3.892 % in 2015. Burkina Faso BF: International Migrant Stock: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Burkina Faso – Table BF.World Bank.WDI: Population and Urbanization Statistics. International migrant stock is the number of people born in a country other than that in which they live. It also includes refugees. The data used to estimate the international migrant stock at a particular time are obtained mainly from population censuses. The estimates are derived from the data on foreign-born population--people who have residence in one country but were born in another country. When data on the foreign-born population are not available, data on foreign population--that is, people who are citizens of a country other than the country in which they reside--are used as estimates. After the breakup of the Soviet Union in 1991 people living in one of the newly independent countries who were born in another were classified as international migrants. Estimates of migrant stock in the newly independent states from 1990 on are based on the 1989 census of the Soviet Union. For countries with information on the international migrant stock for at least two points in time, interpolation or extrapolation was used to estimate the international migrant stock on July 1 of the reference years. For countries with only one observation, estimates for the reference years were derived using rates of change in the migrant stock in the years preceding or following the single observation available. A model was used to estimate migrants for countries that had no data.;United Nations Population Division, Trends in Total Migrant Stock: 2008 Revision.;Weighted average;

Curated databases of the project "Academic publishing requires linguistically inclusive policies."

"CuratedDatabase_Guidelines.txt" and "CuratedDatabase_Survey.txt" contain information about the linguistic policies of journals in biological sciences. Their information was collected from author guidelines and surveys to editors-in-chief, respectively. Additional information from the journal was extracted from the 2020 Journal Citation Reports (JCR).

Description, data type, and scoring options of the databases' fields (columns)

"CuratedDatabase_Guidelines.txt"'

• Collaborator: Anonymised identifier of collaborator who collected the information. Categorical.
• SurveyAnswer: Whether the editor-in-chief of the editor accepted the request to complete the survey. Categorical. YES, NO.
• Journal_JCR: Anonymised identifier of the journal name. Text.
• ImpactFactor_JCR: Impact Factor of the journal as per JCR. Numeric.
• OA_JCR: Percentage of Golden Open Access articles as per JCR. Numeric.
• Discipline_JCR: Discipline of the journal as per JCR. Categorical.
• CountryPublication_JCR: Country or region of publication of the journal as per JCR. Categorical.
• LanguageCountry: Language of the country where the journal is published. Categorical. English, Non-English.
• IssuesPerYear_JCR: Regularity as number of issues published by year as per JCR. Numeric.
• PublisherType: Business model of the journal's publisher. Categorical. Profit, Non-profit.
• SocietyJournal: Whether the journal is published on behalf of a scientific society. Categorical. 0 for NO, 1 for YES.
• Language: Languages in which the journal publish content. Text.
• RegionalGlobal: Whether the journal explicitly target to a global or regional audience. Categorical. Global, Regional.
• LinguisticDiversityEditors: Proportion of editors that are based in countries where English is not predominantly spoken. Numeric.
• EnglishEditingService: Type of English editing services that the journal provides to authors. Categorical. 0 for NONE, 1 for COMMERCIAL, 2 for FREE.
• AdditionalSupport: Additional support that journals offer to authors. Text.
• AdditionalLanguageGuidelines: Whether the author guidelines are available in languages other than English. Categorical. 0 for ONLY ENGLISH, 1 for ADDITIONAL LANGUAGES IN SOME SECTIONS, 2 for ADDITIONAL LANGUAGES.
• LanguageGuidelines: If apply, languages in which the author guidelines are available.
• LinguisticInclusivityStatement: Whether the journal clearly states that a paper will not be rejected solely by the perceived quality of English. Categorical. NO, YES.
• AdditionalLanguageManuscripts: Whether the journal publish entire manuscripts in languages other than English. Categorical. 0 for NO, 1 for YES.
• AdditionalLanguageAbstract: Whether the journal publish abstracts in languages other than English. Categorical. 0 for NO, 1 for YES.
• WhereSecondAbstract: If apply, the format in which the journal publish abstracts in languages other than English. Categorical.
• ProofReadingAL: If apply, whether the non-English content is proofread. Categorical.
• ReferencesAdditionalLanguage: Whether the journal publish references in languages other than English. Categorical. 0 for PROHIBITED/NO-MENTION, 1 for ALLOWED, 2 for ENCOURAGED.
• AutomaticTranslationTools: Whether the journal's website implement machine translation tools to read the manuscripts in languages other than English. 0 for NO, 1 for YES.

"CuratedDatabase_Survey.txt"

• Journal_JCR: Anonymised identifier of the journal name. Text.
• ImpactFactor_JCR: Impact Factor of the journal as per JCR. Numeric.
• OA_JCR: Percentage of Golden Open Access articles as per JCR. Numeric.
• SocietyJournal: Whether the journal is published on behalf of a scientific society. Categorical. 0 for NO, 1 for YES.
• LinguisticDiversityEditors: Proportion of editors that are based in countries where English is not predominantly spoken. Numeric.
• AdditionalLanguageManuscripts: Whether the journal publish entire manuscripts in languages other than English. Categorical. 0 for NO, 1 for YES.
• EnglishEditingService: Type of English editing services that the journal provides to authors. Categorical. 0 for NONE, 1 for COMMERCIAL, 2 for FREE.
• ReferencesAdditionalLanguage: Whether the journal publish references in languages other than English. Categorical. 0 for PROHIBITED/NO-MENTION, 1 for ALLOWED, 2 for ENCOURAGED.
• InstructionsReviewers: Whether reviewers are instructed to avoid recommending the rejection manuscripts solely based on the perceived standard of English. 0 for NO, 1 for YES.
• InstructionsEditors: Whether editors are instructed to avoid rejecting manuscripts solely based on the perceived standard of English. 0 for NO, 1 for YES.
• YearStartLinguisticPolicies: For journals that publish content in languages other than English, the year in which those policies were implemented. Numeric. Values "1920" correspond to "Before 1920."
• AdditionalLanguageAbstract: Whether the journal publish abstracts in languages other than English. Categorical. 0 for NO, 1 for YES.

United States US: International Migrant Stock: Total data was reported at 46,627,102.000 Person in 2015. This records an increase from the previous number of 44,183,643.000 Person for 2010. United States US: International Migrant Stock: Total data is updated yearly, averaging 21,371,383.500 Person from Dec 1960 (Median) to 2015, with 12 observations. The data reached an all-time high of 46,627,102.000 Person in 2015 and a record low of 10,825,599.000 Person in 1960. United States US: International Migrant Stock: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Population and Urbanization Statistics. International migrant stock is the number of people born in a country other than that in which they live. It also includes refugees. The data used to estimate the international migrant stock at a particular time are obtained mainly from population censuses. The estimates are derived from the data on foreign-born population--people who have residence in one country but were born in another country. When data on the foreign-born population are not available, data on foreign population--that is, people who are citizens of a country other than the country in which they reside--are used as estimates. After the breakup of the Soviet Union in 1991 people living in one of the newly independent countries who were born in another were classified as international migrants. Estimates of migrant stock in the newly independent states from 1990 on are based on the 1989 census of the Soviet Union. For countries with information on the international migrant stock for at least two points in time, interpolation or extrapolation was used to estimate the international migrant stock on July 1 of the reference years. For countries with only one observation, estimates for the reference years were derived using rates of change in the migrant stock in the years preceding or following the single observation available. A model was used to estimate migrants for countries that had no data.; ; United Nations Population Division, Trends in Total Migrant Stock: 2012 Revision.; Sum;

Dataset population: Persons aged 3 and over

Age

Age is derived from the date of birth question and is a person's age at their last birthday, at 27 March 2011. Dates of birth that imply an age over 115 are treated as invalid and the person's age is imputed. Infants less than one year old are classified as 0 years of age.

Main language

The language that is a person's first or preferred language.

This information helps central government, local authorities and the NHS to allocate resources and provide services for non-English speakers, for example English teaching and translation services. It is a better indicator than country of birth, which was previously used to forecast the additional cost of providing services to people whose first language is not English.

The data are also used to assess the impact of English or Welsh language ability on employment and other social inclusion indicators.

Information on the number of British Sign Language users helps with service planning and assists in developing policies to address the needs of the deaf community.

These statistics are used by public service providers to effectively target the delivery of their services, for example in the provision of translation and interpretation services, the availability of English language lessons, and the distribution of official information leaflets in alternative languages.

Sex

The classification of a person as either male or female.