United Kingdom UK: Over-Age Students: Primary: % of Enrollment data was reported at 1.126 % in 2015. This records an increase from the previous number of 1.067 % for 2014. United Kingdom UK: Over-Age Students: Primary: % of Enrollment data is updated yearly, averaging 1.594 % from Dec 1971 (Median) to 2015, with 31 observations. The data reached an all-time high of 7.386 % in 1979 and a record low of 0.000 % in 2003. United Kingdom UK: Over-Age Students: Primary: % of Enrollment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Education Statistics. Over-age students are the percentage of those enrolled who are older than the official school-age range for primary education.; ; UNESCO Institute for Statistics; ;

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 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.

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 Next Steps Linked Education Dataset (ILR), England: Secure Access (SN 8577) includes data files from the Department for Education’s Individualised Learner Records (ILR) for those cohort members who provided consent to education linkage in the age 25 sweep. The ILR contains information about learners and their learning undertaken in further education (FE) in England. The following linked ILR data are available:

• Learner data - includes one learner record for each learner on a programme of study at an FE provider and contains information specific to the learner. A learner record includes: prior attainment level, mode of attendance and destination of learner after completion of learning.
• Learning aims data - each learner record has associated with it one or more learning aim records. There is one learning aim record for each learning aim that a learner is studying. A learning aim record includes information such as aim type, programme type, funding model and learning outcomes.
  

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 Census 2021 estimates that classify all usual residents aged 5 years and over in England and Wales with a schoolchild/student indicator. The estimates are as at Census Day, 21 March 2021.

Schoolchild or full-time student indicator (3 categories)

Indicates whether a person aged 5 years and over was in full-time education on Census Day, 21 March 2021. This includes schoolchildren and adults in full-time education.

Schoolchildren and students in full-time education studying away from home are treated as usually resident at their term-time address.

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. However, you can choose to filter areas by:

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

Lower Tier Local Authorities

Lower tier local authorities provide a range of local services. In England there are 309 lower tier local authorities. These are made up of non-metropolitan districts (181), unitary authorities (59), metropolitan districts (36) and London boroughs (33, including City of London). In Wales there are 22 local authorities made up of 22 unitary authorities. Of these local authority types, only non-metropolitan districts are not additionally classified as upper tier local authorities.

Full resource found at: https://sparcopen.org/our-work/big-deal-knowledge-base Sourcing: Pricing Data: Individual entries are linked to third party resources within the database; non-linked entries come from Freedom of Information requests (courtesy of Ted Bergstrom and Paul Courant). FTE Data: UK Higher Education Statistics Agency for UK FTE (HE student enrollment FTE + HE staff); DOE IPEDS for US FTE (“Full-time equivalent fall enrollment” + “Total FTE staff”); Universities Canada and COPPUL for Canadian FTE (student data only). Institutional Categories: Carnegie Classification of Institutions of Higher Education.

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.

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.

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

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.

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.

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

Interested parties can now request extracts of data from the NPD using an improved application process accessed through the following website; GOV.UK The first version of the NPD, including information from the first pupil level School Census matched to attainment information, was produced in 2002. The NPD is one of the richest education datasets in the world holding a wide range of information about pupils and students and has provided invaluable evidence on educational performance to inform independent research, as well as analysis carried out or commissioned by the department. There are a range of data sources in the NPD providing information about children’s education at different phases. The data includes detailed information about pupils’ test and exam results, prior attainment and progression at each key stage for all state schools in England. The department also holds attainment data for pupils and students in non-maintained special schools, sixth form and further education colleges and (where available) independent schools. The NPD also includes information about the characteristics of pupils in the state sector and non-maintained special schools such as their gender, ethnicity, first language, eligibility for free school meals, awarding of bursary funding for 16-19 year olds, information about special educational needs and detailed information about any absences and exclusions. Extracts of the data from NPD can be shared (under strict terms and conditions) with named bodies and third parties who, for the purpose of promoting the education or well-being of children in England, are:- • Conducting research or analysis • Producing statistics; or • Providing information, advice or guidance. The department wants to encourage more third parties to use the data for these purposes and produce secondary analysis of the data. All applications go through a robust approval process and those granted access are subject to strict terms and conditions on the security, handling and use of the data, including compliance with the Data Protection Act. Anyone requesting access to the most sensitive data will also be required to submit a business case. More information on the application process including the User Guide, Application Form, Security Questionnaire and a full list of data items available can be found from the NPD web page at:- https://www.gov.uk/national-pupil-database-apply-for-a-data-extract

Colleges, commercial and charitable providers and other institutions provide an annual funding return to the EFA which is recorded and held currently in Excel spreadsheets. This data consists of outturn information including the number of students actually recruited and the funding relating to them. For commercial and charitable providers (CCPs) funded on contract this also holds a variance against students and funding actually allocated in that academic year, and the reconciliation values for the payments to CCPs. Grant-in-aid institutions are not usually subject to funding reconciliation adjustments to their allocation payments.

This dataset is based on original survey data from 224 Chinese undergraduate students who are studying in China and the UK. This dataset is to explore how UK-based and China-based Chinese students’ smoking behaviours are affected by their social networks, particularly their friends and family members, to address an empirical gap by testing the validity of three social network mechanisms: person-to-person contact, social support, and social stress, and to identify how studying abroad influences smoking behaviours by comparing these smoking behaviours for Chinese students in China.

Background: Obesity is a multifaceted condition influenced by genetic, lifestyle, and cultural factors. The prevalence of obesity has risen globally, with distinct challenges faced by South Asian populations in the UK, due to genetic predispositions and dietary shifts. This study evaluated the impact of an educational intervention designed for medical students to increase understanding of obesity in the South Asian community.Approach: Participants were recruited via the medical school online platform and signed written consent forms. The study did not require ethics approval. Participants completed a Likert confidence scale questionnaire before the small group teaching intervention, and then after it, to assess the impact of the session. Written free text comments after the session illustrated participant thoughts on the intervention and how well they felt the medical school taught on ethnic minority health. The dataset is a spreadsheet that records participants' responses to questionnaireEvaluation: The intervention significantly improved participant confidence in understanding and awareness of obesity in the South Asian community. Free text comments highlighted positive engagement and suggested areas for improvement. All participants believed their medical school lacked sufficient teaching on obesity in ethnic minorities and expressed an ardent desire for more teaching in this area.Implications: This study underscores the need for tailored undergraduate medical teaching on obesity in diverse ethnic groups, particularly South Asians. It highlights the inadequacies of a one-size-fits-all approach in addressing obesity within ethnic minority communities. Future work should explore the readiness of medical students across the UK to study obesity and the management of it in ethnic minorities.The data set includes the consent form and feedback form used for the study, as well as anonymised feedback data from the study. The Wilcoxon signed rank test is also included, as well as evidence that an ethics application was not needed for the study.

These datasets were generated as part of a study investigating whether participation in an international, collaborative learning experience—specifically the “Global Classroom Project”—would lead to increases in students’ Cultural Intelligence (CQ) and their satisfaction with the learning experience. The main hypothesis was that students involved in this project would show significant increases in overall CQ and its sub-dimensions (motivational, cognitive, metacognitive, and behavioural), and that higher levels of CQ would be positively associated with greater student satisfaction.

Two datasets are included:

Intervention Group Dataset: This dataset contains matched pre- and post-intervention data from 56 undergraduate psychology students who participated in the Global Classroom Project across three academic years (2021/2022, 2022/2023, and 2023/2024) at three institutions: Opole University (Poland), Leeds Trinity University (UK), and Taylors University (Malaysia). Students worked in intercultural teams and completed an online presentation comparing psychological concepts across the three cultures.

Control Group Dataset: This smaller dataset includes matched pre- and post-data from 6 students in a control group at the UK university who did not participate in the international project.

In both datasets, participants completed two instruments:

Expanded Cultural Intelligence Scale (E-CQS) (Van Dyne et al., 2012), a validated 39-item self-report tool measuring four CQ dimensions on a 7-point Likert scale: motivational, cognitive, metacognitive, and behavioural.

Student Satisfaction Scale, a self-developed 18-item measure assessing satisfaction with the international learning experience (administered only in the intervention group), using a 5-point Likert scale.

Statistical analyses showed that participants in the intervention group experienced significant gains in overall CQ and various sub-dimensions, as well as a positive relationship between CQ and satisfaction. No significant changes were found in the control group, except a small increase in behavioural CQ.

These datasets can be used to explore the development of Cultural Intelligence through international education. The intervention dataset is particularly suited for secondary analyses of trends across cohorts, countries, and CQ dimensions, while the control dataset supports comparison of outcomes for students without intercultural exposure. Both datasets are anonymised, clearly labelled, and formatted for compatibility with common statistical software.

This dataset provides Census 2022 estimates for Economic activity in Scotland.

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

The quality assurance report can be found here

This dataset provides Census 2021 estimates that classify usual residents in England and Wales by their use of a second address, and whether the second address is inside or outside the UK. The estimates are as at Census Day, 21 March 2021.

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

Second address indicator (3 categories)

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

If a person with a second address was staying there on census night, they were classed as a visitor to the second address but counted as a usual resident at their home address.