Census 2021 data on international student population of England and Wales by country of birth, passport held, age, sex and other characteristics.

These datasets are part of the release: The changing picture of long-term international migration, England and Wales: Census 2021. Figures may differ slightly in future releases because of the impact of removing rounding and applying further statistical processes.

Figures are based on geography boundaries as of 1 April 2022.

This release includes comparisons to the folllowing 2011 Census data:

• Students in full-time education
• International students (by Region)
• International students by country of birth
• International students by Top 100 countries of birth

Quality notes can be found here

Quality information about demography and migration can be found here

Quality information about labour market can be found here

Usual resident

A usual resident is anyone who on Census Day, 21 March 2021 was in the UK and had stayed or intended to stay in the UK for a period of 12 months or more, or had a permanent UK address and was outside the UK and intended to be outside the UK for less than 12 months.

International student

An international student is defined as someone who was a usual resident in England and Wales and meets all the following criteria:

• in-full-time education
• non-UK-born
• non-UK passport holder
• aged 17 years or over upon most recent arrival in the UK
• aged 18 years or over on Census Day.

Country of birth

The country in which a person was born. The following country of birth classifications are used in this dataset:

• Country of birth 12a: Political groupings of countries by EU membership and geographical location for non-EU countries.
• Country of birth 190a: Individual countries. This classification includes geographical groupings for low volume countries.
• Country of birth (3 categories): These categories have been derived from country of birth 12a and include all UK countries in "Europe: United Kingdom", all EU countries in "Europe: EU countries" and all remaining countries including British Overseas territories in "Non-EU countries (including British Overseas)".

More information about country of birth classifications can be found here.

Passports held

The country or countries that a person holds, or is entitled to hold, a passport for. Where a person recorded having more than one passport, they were counted only once, categorised in the following priority order: 1. UK passport, 2. Irish passport, 3. Other passport. The following classifications were created for this dataset for comparability with other international migration releases:

• Passports held (4 categories): High level political groupings of passport held by EU membership and geographical location for non-EU countries.
• Passports held (12 categories): Political groupings of passport held by EU membership and geographical location for non-EU countries.
• Passports held (150 categories): Individual countries for passport held. This classification includes geographical groupings for low volume countries.

More information can be found here

Economic activity status

The economic activity status of a person on Census Day, 21 March 2021. The following classification is used in this dataset:

• Economic activity status classification status_12a

Industry

The industry worked in for those in current employment. The following classification was used for this dataset:

• Industry (current) classification 22a

Student accommodation

Student accommodation breaks down household type by typical households used by students. This includes communal establishments, all student households, households containing a single family, households containing multiple families, living with parents and living alone.

More information can be found here

Second address indicator

The second address indicator is used to define an address (in or out of the UK) a person stays at for more than 30 days per year that is not their place of usual residence. Second addresses typically include: armed forces bases, addresses used by people working away from home, a student’s home address, the address of another parent or guardian, a partner’s address, a holiday home. There are 3 categories in this classification.

Detailed description can be found here

Main language (detailed)

This is used to define a person's first or preferred language. This breaks down the responses given in the write-in option "Other, write in (including British Sign Language)". There are 95 categories in the primary classification.

More details can be found here

Proficiency in English language

Proficiency in English language is used to determine how well a person whose main language is not English (English or Welsh in Wales) feels they can speak English. There are a total number of 6 categories in this classification.

More details can be found here

This bulletin is the annual first release of HESA student data. For the first time it draws upon data from the revised student data collection (delivered by the Data Futures programme). A comprehensive quality assessment has been undertaken on the dataset and this is detailed in our accompanying 2022/23 student data quality report. A detailed list of findings is available in the data quality and insights resource, which is also accompanied by provider specific data notes.

The coverage of data is detailed in the notes section of this release. In summary, we cover data about higher education students and qualifiers from the following types of providers within the UK:

Higher education (HE) providers in England registered with the Office for Students (OfS) in the Approved (fee cap) or Approved categories; Publicly funded HE providers in Wales, Scotland and Northern Ireland; and Further education (FE) colleges in Wales.

This bulletin also includes information from the HESA Aggregate Offshore record which can be seen in Figure 12. This separate record counts students studying wholly outside the UK who are either registered with the reporting HE provider or who are studying for an award of the reporting HE provider.

This dataset provides Census 2021 estimates that classify schoolchildren and full-time students aged 5 years and over in England and Wales by student accommodation and by age. The estimates are as at Census Day, 21 March 2021.

Estimates for single year of age between ages 90 and 100+ are less reliable than other ages. Estimation and adjustment at these ages was based on the age range 90+ rather than five-year age bands. Read more about this quality notice.

Area type

Census 2021 statistics are published for a number of different geographies. These can be large, for example the whole of England, or small, for example an output area (OA), the lowest level of geography for which statistics are produced.

For higher levels of geography, more detailed statistics can be produced. When a lower level of geography is used, such as output areas (which have a minimum of 100 persons), the statistics produced have less detail. This is to protect the confidentiality of people and ensure that individuals or their characteristics cannot be identified.

Coverage

Census 2021 statistics are published for the whole of England and Wales. Data are also available in these geographic types:

• country - for example, Wales
• region - for example, London
• local authority - for example, Cornwall
• health area – for example, Clinical Commissioning Group
• statistical area - for example, MSOA or LSOA

Student accommodation type

Combines the living situation of students and school children in full-time education, whether they are living:

• alone
• in a student household
• with parents
• in a communal establishment, split by university and other communal establishment type
• in other household types

It also includes whether these households contain one or multiple families.

This variable is comparable with the student accommodation variable but splits the communal establishment type into “university” and “other” categories.

Age

A person’s age on Census Day, 21 March 2021 in England and Wales. Infants aged under 1 year are classified as 0 years of age.

This bulletin is the annual first release of HESA student data. It draws upon data from the revised student data collection (delivered by the Data Futures programme) and marks the second year of reporting using the new data model. Once again, a comprehensive quality assessment has been undertaken on the dataset and this is detailed in our accompanying student data quality report. A detailed list of findings is available in the data quality and insights resource, which is also accompanied by provider specific data notes. The coverage of data is detailed in the notes section of this release. In summary, we cover data about higher education students and qualifiers from the following types of providers within the UK: -Higher education (HE) providers in England registered with the Office for Students (OfS) in the Approved (fee cap) or Approved categories; -Publicly funded HE providers in Northern Ireland and Scotland; and -Providers in Wales that are funded directly for higher education provision by Medr and providers in Wales that return data to HESA about specifically designated courses. This bulletin also includes information from the HESA Aggregate Offshore record which can be seen in Figure 12. This separate record counts students studying wholly outside the UK who are either registered with the reporting HE provider or who are studying for an award of the reporting HE provider.

Abstract copyright UK Data Service and data collection copyright owner.

Next Steps (also known as the Longitudinal Study of Young People in England (LSYPE1)) is a major longitudinal cohort study following a nationally representative group of around 16,000 who were in Year 9 attending state and independent schools in England in 2004, a cohort born in 1989-90.

The first seven sweeps of the study were conducted annually (2004-2010) when the study was funded and managed by the Department for Education (DfE). The study mainly focused on the educational and early labour market experiences of young people.

In 2015 Next Steps was restarted, under the management of the Centre for Longitudinal Studies (CLS) at the UCL Faculty of Education and Society (IOE) and funded by the Economic and Social Research Council. The Next Steps Age 25 survey was aimed at increasing the understanding of the lives of young adults growing up today and the transitions out of education and into early adult life.

The Next Steps Age 32 Survey took place between April 2022 and September 2023 and is the ninth sweep of the study. The Age 32 Survey aimed to provide data for research and policy on the lives of this generation of adults in their early 30s. This sweep also collected information on many wider aspects of cohort members' lives including health and wellbeing, politics and social participation, identity and attitudes as well as capturing personality, resilience, working memory and financial literacy.

Next Steps survey data is also linked to the National Pupil Database (NPD), the Hospital Episode Statistics (HES), the Individualised Learner Records (ILR) and the Student Loans Company (SLC).

There are now two separate studies that began under the LSYPE programme. The second study, Our Future (LSYPE2) (available at the UK Data Service under GN 2000110), began in 2013 and will track a sample of over 13,000 young people annually from ages 13/14 through to age 20.

Further information about Next Steps may be found on the CLS website.

Secure Access datasets:

Secure Access versions of Next Steps have more restrictive access conditions than Safeguarded versions available under the standard End User Licence (see 'Access' section).

Secure Access versions of the Next Steps include:

• sensitive variables from the questionnaire data for Sweeps 1-9. These are available under Secure Access SN 8656.
  
• National Pupil Database (NPD) linked data at Key Stages 2, 3, 4 and 5, England. These are available under SN 7104.
• Linked Individualised Learner Records learner and learning aims datasets for academic years 2005 to 2014, England. These are available under SN 8577.
  
• detailed geographic indicators for Sweep 1 and Sweep 8 (2001 Census Boundaries) - available under SN 8189 and geographic indicators for Sweep 8 (2011 Census Boundaries) - available under SN 8190. The Sweep 1 geography file was previously held under SN 7104.
• Linked Health Administrative Datasets (Hospital Episode Statistics) for years 1998-2017 held under SN 8681.
• Linked Student Loans Company Records for years 2007-2021 held under SN 8848.

When researchers are approved/accredited to access a Secure Access version of Next Steps, the Safeguarded (EUL) version of the study - Next Steps: Sweeps 1-9, 2004-2023 (SN 5545) - will be automatically provided alongside.

The Student Loans Company (SLC) is a non-profit making government-owned organisation that administers loans and grants to students in colleges and universities in the UK. The Next Steps: Linked Administrative Datasets (Student Loans Company Records), 2007 - 2021: Secure Access includes data on higher education loans for those Next Steps participant who provided consent to SLC linkage in the age 25 sweep. The matched SLC data contains information about participant's applications for student finance, payment transactions posted to participant's accounts, repayment details and overseas assessment details.

The study includes four datasets:

Applicant: SLC data on cohort member’s application for student finance between academic years 2007 and 2020

Payments: SLC data on payment transactions made to cohort member between financial years 2007 and 2021.

Repayments: SLC data on cohort member’s repayment transactions between financial years 2009 and 2021.

Overseas: SLC data on overseas assessment for cohort member between 2007 and 2020

Data product is provided by ASL Marketing. It contains current college students who are attending colleges and universities nationwide. Connect with this market by: Class Year Field of Study Home/School address College Attending Ethnicity School Type Region Sports Conference Gender eSports Email

Provides provisional statistics showing how applications for student support in higher education are progressing through the processing stages and showing the number of payments made to students in this cycle. These statistics cover applications assessed by Student Finance England who assess all applications for English students.

Source agency: Business, Innovation and Skills

Designation: Official Statistics not designated as National Statistics

Language: English

Alternative title: student loans

This project investigated UK secondary school students’ views of inequality and their sense of agency concerning their occupational prospects, using questionnaire and interview data. The data came from 78 students from three secondary schools in England between Year 7 and Year 13 who were aged between 12 and 19. The three schools were in areas with different socioeconomic characteristics – an affluent town in the London commuter belt (School A), a city in the east of England (School B) and a town to the east of London (School C). School A had a lower than national average free school meals (FSM) rate, whereas both School B and School C had a higher than national average FSM rate.

18 participants were from School A, 38 from School B and 22 from School C. While all 18 students in School A and all 22 students in School C participated in both the questionnaire and follow-up interview stages, in School B 37 participants filled in the questionnaire and, of these, 22 took part in the interviews. One student from School B who did not fill in a questionnaire took part in the interview, making the total interviews from School B 23. One student from School C did not want to have their interview audio-recorded; therefore, their interview transcript does not exist.

As a result, the dataset in total contains 77 questionnaires and 62 interview transcripts. The PDF files are questionnaire files and the word document files are interview transcripts. A file name (for both the pdf files and word document files) begins with ‘Y’ that is followed by a number which indicates a school year and this is followed by two letters that indicate a code for an individual participant, while the letter A, B or C immediately after a hyphen indicates School A, B or C respectively.

United Kingdom UK: Secondary Education: Pupils: % Female data was reported at 49.596 % in 2015. This records a decrease from the previous number of 49.805 % for 2014. United Kingdom UK: Secondary Education: Pupils: % Female data is updated yearly, averaging 49.195 % from Dec 1971 (Median) to 2015, with 45 observations. The data reached an all-time high of 49.921 % in 2013 and a record low of 48.422 % in 1971. United Kingdom UK: Secondary Education: Pupils: % Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s UK – Table UK.World Bank: Education Statistics. Female pupils as a percentage of total pupils at secondary level includes enrollments in public and private schools.; ; 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).

The Quality Review is a process that evaluates how well schools are organized to support student learning and teacher practice. It was developed to assist New York City Department of Education (NYCDOE) schools in raising student achievement by looking behind a school’s performance statistics to ensure that the school is engaged in effective methods of accelerating student learning.

People from many countries have expressed interest in the tests students take for the Programme for International Student Assessment (PISA). Learning Mathematics for Life examines the link between the PISA test requirements and student performance. It focuses specifically on the proportions of students who answer questions correctly across a range of difficulty. The questions are classified by content, competencies, context and format, and the connections between these and student performance are then analysed. This analysis has been carried out in an effort to link PISA results to curricular programmes and structures in participating countries and economies. Results from the student assessment reflect differences in country performance in terms of the test questions. These findings are important for curriculum planners, policy makers and in particular teachers – especially mathematics teachers of intermediate and lower secondary school classes.

The nature of designing as well as the professional characteristics of many designers leave them vulnerable to the delay of tasks and decisions also known as procrastination. Procrastination is not discussed in design literature. Procrastination is defined as the voluntary delay or inability to complete a task or make a decision. It is often linked to the individual being overwhelmed. The dataset submitted was from a questionnaire that asked about the frequency and form of procrastination; and, influences on their behaviour when trying to undertake stages of a design process was completed by 155 design students and staff within a UK design and creative arts school. The stages included: literature review, ideation, prototyping, and report writing. The outcomes suggested chronic procrastination related to all stages of a design process, with a frequency of more than once a week. Additional questions highlighted multiple tasks were likely to overwhelm the respondents, whilst distractions such as new projects were likely to result in completing alternative tasks. An additional open question provided qualifying comments suggesting procrastination wasn’t explicitly addressed in academic design training. Two key activities to reduce the effects of procrastination were suggested: 1) prioritise tasks; and 2) reduce complexity of each task. Additional advice included: development of professional self-confidence, realistic goal planning, minimising external stimulus, controlling workflows, working in study groups, developing virtuous routines at optimal times during the day, the management of reward and consequence; and use of technology to optimise self-regulation.

Database Title:Connect-science self-reported instrumentDatabase Description:Students' self-report perceptions reflecting about science connection, science skills, science capital and scientific literacies in the context of open schoolingDatabase Citation:Okada A.; Sherborne T; Panselinas; G.; Bizoi, M; Malagrida, R; Ribeiro, S. Torres P. (2024). CONNECT - inclusive open schooling with engaging and future oriented science. CCBYSAContact email:ale.okada@open.ac.ukDatabase URL:https://ordo.open.ac.uk/projects/CONNECT_-_Inclusive_open_schooling_with_future_oriented_science/125821Information:This database provides the views of 12072 students who participated in CONNECT projectDatabase Methodology used to generated dataQuestionnaire designSemi-structured questionnaire including a combination of open-ended and closed-ended questions.Platform used for a coded questionnaire with feedback and open badgeQualtrixMultilanguage supportTargetlanguage (English, Greek, Portuguese, Romanian, Spanish in this case) toensure that respondents can understand and respond to the questions in theirpreferred language.Questionnaire implementationLogic for sore, feedback and open badge implementedLanguage selectionQualtrics allows respondents to select their preferred language before starting the survey.Data generationThe questionnaire was distributed to the target audience school studentsthrough teachers members of CONNECT project who agreed to contribute to this researchData storageAs respondents submit their responses, Qualtrics stores the data securely in its database infrastructure. Each response is associated with the respondent's unique identifier and includes the language in which the survey was completed.Data analysisExploratory factorial analysis, descriptive analyses and thematic analysis to support mixed methodsExtra InformationCreator of the Instrument used to generate this database:Okada, A. CONNECT-Science self-report instrumentThis database refers to CONNECT project:https://www.connect-science.net/Project description:inclusive open schooling with engaging and future oriented scienceFunder:European Commission No. 872814Questionnaire and database location:https://doi.org/10.21954/ou.rd.23566662Questionnaire citation:Okada A. (2024) CONNECT-science to sustainability with inclusive open schooling with engaging and future oriented science. CCBYSAJournal Article using data presented in this database:https://oro.open.ac.uk/96439/Article Citation:Okada, A.; Panselinas, G.; Bizoi, M.; Malagrida, R.; Torres, P. Fostering Transversal Skills through Open Schooling with the CARE-KNOW-DO Framework forSustainable Education. Sustainability 2024, 16, x. https://doi.org/10.3390/License:CCBYSA

Data on the educational attainment of young people who sat their GCSEs in English state schools in the 2012 to 2013 school year, from age 11 to age 22, compiled using the Longitudinal Educational Outcomes database from the Department for Education (DfE). Data are linked to the area a student lived in when they sat their GCSEs, including characteristics such as town size and income deprivation levels.

This dataset provides Census 2022 estimates for Economic activity of full-time students aged 16 and over by age (in 5 categories) in Scotland.

Age

A person's age on Census Day, 20 March 2022. Infants aged under 1 year are classified as 0 years of age.

Economic activity

Economic activity relates to whether or not a person aged 16 and over was working or looking for work in the week before census. Rather than a simple indicator of whether or not someone was currently in employment, it provides a measure of whether or not a person was an active participant in the labour market.

A person's economic activity is derived from their 'activity last week'. This is an indicator of their status or availability for employment - whether employed, unemployed, or their status if not employed and not seeking employment. Additional information included in the economic activity classification is also derived from information about the number of hours a person works and their type of employment - whether employed or self-employed.

The census concept of economic activity is compatible with the standard for economic status defined by the International Labour Organisation (ILO). It is one of a number of definitions used internationally to produce accurate and comparable statistics on employment, unemployment and economic status.

Details of classification can be found here

Full-time students

A student is a person who is in full-time education either at school or in higher or further education.

Details of classification can be found here

The quality assurance report can be found here

This dataset provides a breakdown of the NICS Student Placement external recruitment campaign 2021 by: gender, community background, age, disability, ethnic background, sexual orientation, etc. It also includes a breakdown of internal and external candidates who were invited to interview, passed interview and offered an appointment.

Dataset population: Full-time students aged 16 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.

Economic activity

Economic activity relates to whether or not a person who was aged 16 and over was working or looking for work in the week before census. Rather than a simple indicator of whether or not someone was currently in employment, it provides a measure of whether or not a person was an active participant in the labour market.

A person's economic activity is derived from their 'activity last week'. This is an indicator of their status or availability for employment - whether employed, unemployed, or their status if not employed and not seeking employment. Additional information included in the economic activity classification is also derived from information about the number of hours a person works and their type of employment - whether employed or self-employed.

The census concept of economic activity is compatible with the standard for economic status defined by the International Labour Organisation (ILO). It is one of a number of definitions used internationally to produce accurate and comparable statistics on employment, unemployment and economic status.

Student accommodation

Student term-time accommodation for all students (i.e. schoolchildren and students aged 4 and over in full-time education) living in households and communal establishments. For students in households, the classification is derived by looking at the other members of the household, their student status and their generation in family.

Student accommodation defines the type of accommodation a schoolchild or student lives in during term-time and therefore relates only to their term-time address.

The UK’s exit from the European Union in January 2020, following a referendum in 2016, represented a significant potential rupture to EU student mobility to the UK. When the UK was an EU member, EU students were entitled to identical treatment to UK domestic students in higher education, able to finance undergraduate and master's fees through UK student loans (or pay no fees in Scotland) and access doctoral funding. After Brexit, EU students were treated like any other international student and liable for upfront and very high tuition fees. This policy shock has the potential to significantly disrupt full-degree EU student mobility to the UK. Using a comprehensive dataset of all EU full-degree enrolments in UK higher education, 2007–2023, we investigate patterns of incoming EU student mobility to the UK before and after Brexit. We find the sharp disjuncture to have both overall and more particular effects. Looking at how the shock of Brexit plays out differently across sending countries, levels and fields of study and institutional destinations provides interesting revelations about how international student mobility operates.

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 Leicester and compare this with national statistics.Further information about the census and full datasets can be found on the ONS website - https://www.ons.gov.uk/census/aboutcensus/censusproductsPopulation by household and communal establishmentThis dataset provides Census 2021 estimates that classify the population into residents of households and those residing in communal establishments. The estimates are as at Census Day, 21 March 2021.Definitions: Households - one person or a group of people (not necessarily related) living at the same address who share cooking facilities and share a living room or sitting room, or dining area. Examples include: A house or flatA caravan or other mobile or temporary structureSheltered accommodation units within an establishmentCommunal establishments - A place that provides managed full-time or part-time supervision of residential accommodation. Examples include:University halls of residence and boarding schoolsCare homes, hospitals, hospices and maternity unitsPrisons and other secure facilitiesNew communal establishments do not count as new households. For example, the building of a new block of supervised student flats would not count as an increase in the number of households.