Abstract copyright UK Data Service and data collection copyright owner.

As the UK went into the first lockdown of the COVID-19 pandemic, the team behind the biggest social survey in the UK, Understanding Society (UKHLS), developed a way to capture these experiences. From April 2020, participants from this Study were asked to take part in the Understanding Society COVID-19 survey, henceforth referred to as the COVID-19 survey or the COVID-19 study.

The COVID-19 survey regularly asked people about their situation and experiences. The resulting data gives a unique insight into the impact of the pandemic on individuals, families, and communities. The COVID-19 Teaching Dataset contains data from the main COVID-19 survey in a simplified form. It covers topics such as

• Socio-demographics
• Whether working at home and home-schooling
• COVID symptoms
• Health and well-being
• Social contact and neighbourhood cohesion
• Volunteering

The resource contains two data files:

• Cross-sectional: contains data collected in Wave 4 in July 2020 (with some additional variables from other waves);
• Longitudinal: Contains mainly data from Waves 1, 4 and 9 with key variables measured at three time points.

Key features of the dataset

• Missing values: in the web survey, participants clicking "Next" but not answering a question were given further options such as "Don't know" and "Prefer not to say". Missing observations like these are recorded using negative values such as -1 for "Don't know". In many instances, users of the data will need to set these values as missing. The User Guide includes Stata and SPSS code for setting negative missing values to system missing.

• The Longitudinal file is a balanced panel and is in wide format. A balanced panel means it only includes participants that took part in every wave. In wide format, each participant has one row of information, and each measurement of the same variable is a different variable.

• Weights: both the cross-sectional and longitudinal files include survey weights that adjust the sample to represent the UK adult population. The cross-sectional weight (betaindin_xw) adjusts for unequal selection probabilities in the sample design and for non-response. The longitudinal weight (ci_betaindin_lw) adjusts for the sample design and also for the fact that not all those invited to participate in the survey, do participate in all waves.

• Both the cross-sectional and longitudinal datasets include the survey design variables (psu and strata).

A full list of variables in both files can be found in the User Guide appendix.

Who is in the sample?

All adults (16 years old and over as of April 2020), in households who had participated in at least one of the last two waves of the main study Understanding Society, were invited to participate in this survey. From the September 2020 (Wave 5) survey onwards, only sample members who had completed at least one partial interview in any of the first four web surveys were invited to participate. From the November 2020 (Wave 6) survey onwards, those who had only completed the initial survey in April 2020 and none since, were no longer invited to participate

The User guide accompanying the data adds to the information here and includes a full variable list with details of measurement levels and links to the relevant questionnaire.

Main Topics:

• Socio-demographics;
• Whether working at home and home-schooling;
• COVID symptoms;
• Health and well-being;
• Social contact and neighbourhood cohesion;
• Volunteering.

The Cambridge Centre for Business Research Survey of Knowledge Exchange Activity with Universities by United Kingdom Companies, 2017-2021 contains the results of an online survey of directors of UK companies in 2020-2021.

The survey was designed to assess the extent and nature of the knowledge exchange interactions of their companies with the university sector. It covers the three-year period to March 2020 prior to the Covid-19 pandemic and questions relating to the subsequent impact of the pandemic on knowledge exchange patterns. The researchers inquired about 33 modes of interaction grouped into four broad categories. These were commercialisation (3 modes), people-based (10 modes), problem-solving (12 modes) and community-based (4 modes).

The survey covers a sample of 3,823 companies in all sectors, regions and countries of the UK and employment sizes ranging from micro-firms less than 10 employees, to the largest public listed corporations. The response rate was 4.4 per cent and a detailed response bias analyses by survey wave and prompt wave showed largely insignificant sample response bias compared to the sampling frame drawn from the FAME database of all UK companies.

The dataset provides a unique source of data on a critical period of challenge for knowledge exchange in the UK. David Sweeney, the then Executive Director of Research England which sponsored the survey commented on an initial report of results in 2022 that "This report which has an exclusive focus on company interactions with universities, is an important addition to our understanding of the collaboration process" (The Changing State of Business-University Interactions in the UK. Centre for Business Research and NCUB. 2022 p2).

The survey dataset contains many variables comparable with a similar previous postal survey of an earlier period by two members of the current research team. The data from this is available from the Data Archive under SN 6464 - Cambridge Centre for Business Research Survey of Knowledge Exchange Activity by United Kingdom Businesses, 2005-2009.

Abstract copyright UK Data Service and data collection copyright owner.

Understanding Society (the UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex, and the survey research organisations Verian Group (formerly Kantar Public) and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

The Understanding Society COVID-19 Study is a regular survey of households in the UK. The aim of the study is to enable research on the socio-economic and health consequences of the COVID-19 pandemic, in the short and long term. The surveys started in April 2020 and took place monthly until July 2020. From September 2020 they take place every other month. They complement the annual interviews in the Understanding Society study.

This dataset contains school code variables for the Understanding Society COVID-19 study (SN 8644).

A file is provided for the fifth web wave of the Understanding Society COVID-19 study, the only one that school information has currently been gathered for. For each child it contains: state school code, country of state school, private school name and private school town variables for both mother and father responses. A child personal identification serial number (pidp_c) is also provided for matching to the main data in SN 8644.

In addition, this dataset contains a file of school code variables that can be matched to a dataset released with the main Understanding Society COVID-19 study containing data taken from waves 10 and 11 of the main Understanding Society survey specifically for the respondents in the Understanding Society COVID-19 study. Child school codes are only available for Wave 11 as they are only collected in odd-numbered waves. For each child it contains the state school code and country of state school variables as well as a personal identification serial number (pidp) and a household identification serial number for wave 11 (jk_hidp). Further details on the files in this dataset can be found in the Understanding Society COVID-19 User Guide.

Additional information can be found on the Understanding Society COVID-19 website, including Data documentation. A list of Understanding Society COVID-19 Research Outputs (regularly updated) is also available.

New edition information
For the second edition (January 2021), both previously deposited files have been revised to include a significant number of additional school codes resulting from manual coding. For further details please refer to the UKHLS COVID-19: Data Changes document, included in the main COVID-19 study (SN 8644).

Main Topics:

This study contains school code variables for the Understanding Society COVID-19 study.

Abstract copyright UK Data Service and data collection copyright owner.

The Active Lives Children and Young People Survey, which was established in September 2017, provides a world-leading approach to gathering data on how children engage with sport and physical activity. This school-based survey is the first and largest established physical activity survey with children and young people in England. It gives anyone working with children aged 5-16 key insight to help understand children's attitudes and behaviours around sport and physical activity. The results will shape and influence local decision-making as well as inform government policy on the PE and Sport Premium, Childhood Obesity Plan and other cross-departmental programmes. More general information about the study can be found on the Sport England Active Lives Survey webpage and the Active Lives Online website, including reports and data tables.

The Active Lives Children and Young People Survey, 2019-2020 began as the usual school-based survey (i.e. completed at school as part of lessons). From 20 March 2020, schools, colleges and nurseries were closed in the UK due to the COVID-19 pandemic and remained closed until 1 June 2020, when there was a phased reopening for reception, and Years 1 and 6. The Active Lives survey fieldwork in Spring term finished two weeks early before the end of term, in line with the school closures.

Due to the closure of schools, the survey had to be adapted for at home completion. The adaptions involved minor questionnaire changes (e.g. to ensure the wording was appropriate for both the new lockdown situation and to account for the new survey completion method at home) and communication changes. For further details on the changes, please see the accompanying technical report. The circumstances and adaptations resulted in a delay to survey fieldwork re-starting. This means that the data does not cover the full lockdown period, and instead re-starts from mid-May 2020 (when the survey was relaunched). Sample targets were also reduced as a result of the pandemic, resulting in a smaller proportion of summer term responses for 2019-20 when compared to previous years. As part of Sport England’s official publication, an additional Coronavirus report was produced, which outlines changes during the ‘easing restrictions’ phase of lockdown from mid-May to the end of July, comparing the summer term in 2020 with summer 2019. Due to the reduced summer term sample, it is recommended to analyse within term and/or school phase for academic year 2019-20.

The survey identifies how participation varies across different activities and sports, by regions of England, between school types and terms, and between different demographic groups in the population. The survey measures levels of activity (active, fairly active and less active), attitudes towards sport and physical activity, swimming capability, the proportion of children and young people that volunteer in sport, sports spectating, and wellbeing measures such as happiness and life satisfaction. The questionnaire was designed to enable analysis of the findings by a broad range of variables, such as gender, family affluence and school year.

The following datasets have been provided:

1. Main dataset: includes responses from children and young people from school years 3 to 11, as well as responses from parents of children in years 1-2. The parents of children in years 1-2 provide behavioural answers about their child’s activity levels, they do not provide attitudinal information. Using this main dataset, full analyses can be carried out into sports and physical activity participation, levels of activity, volunteering (years 5 to 11), etc. Weighting is required when using this dataset (wt_gross / wt_gross.csplan files are available for SPSS users who can utilise them).
2. Year 1-2 dataset: includes responses from children in school years 1-2 directly, providing their attitudinal responses (e.g. whether they like playing sport and find it easy). Analysis can be carried out into feelings towards swimming, enjoyment for being active, happiness etc. Weighting is required when using this dataset (wt_gross / wt_gross.csplan files are available for SPSS users who can utilise them).
3. Teacher dataset – this .sav file includes response from the teachers at schools selected for the survey. Analysis can be carried out into school facilities available, length of PE lessons, whether swimming lessons are offered, etc. Weighting was formerly not available, however, as Sport England have started to publish the Teacher data, from December 2023 we decide to apply weighting to the data. The Teacher dataset now includes weighting by applying the ‘wt_teacher’ weighting variable.

For further information about the variables available for analysis, and the relevant school years...

Abstract copyright UK Data Service and data collection copyright owner.

Understanding Society (the UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex, and the survey research organisations Verian Group (formerly Kantar Public) and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

The Understanding Society: Calendar Year Dataset, 2020, is designed to enable cross-sectional analysis of individuals and households relating specifically to their annual interviews conducted in the year 2020, and, therefore, combine data collected in three waves (Waves 10, 11 and 12). It has been produced from the same data collected in the main Understanding Society study and released in the longitudinal datasets SN 6614 (End User Licence) and SN 6931 (Special Licence). Such cross-sectional analysis can, however, only involve variables that are collected in every wave in order to have data for the full sample panel. The 2020 dataset is the first of a series of planned Calendar Year Datasets to facilitate cross-sectional analysis of specific years. Full details of the Calendar Year Dataset sample structure (including why some individual interviews from 2021 are included), data structure and additional supporting information can be found in the document '8987_calendar_year_dataset_2020_user_guide'.

As multi-topic studies, the purpose of Understanding Society is to understand short- and long-term effects of social and economic change in the UK at the household and individual levels. The study has a strong emphasis on domains of family and social ties, employment, education, financial resources, and health. Understanding Society is an annual survey of each adult member of a nationally representative sample. The same individuals are re-interviewed in each wave approximately 12 months apart. When individuals move they are followed within the UK and anyone joining their households are also interviewed as long as they are living with them. The fieldwork period for a single wave is 24 months. Data collection uses computer-assisted personal interviewing (CAPI) and web interviews (from wave 7), and includes a telephone mop up. From March 2020 (the end of wave 10 and 2nd year of wave 11), due to the coronavirus pandemic, face-to-face interviews were suspended and the survey has been conducted by web and telephone only, but otherwise has continued as before. One person completes the household questionnaire. Each person aged 16 or older participates in the individual adult interview and self-completed questionnaire. Youths aged 10 to 15 are asked to respond to a paper self-completion questionnaire. In 2020 an additional frequent web survey was separately issued to sample members to capture data on the rapid changes in people’s lives due to the COVID-19 pandemic (see SN 8644). The COVID-19 Survey data are not included in this dataset.

Further information may be found on the Understanding Society main stage webpage and links to publications based on the study can be found on the Understanding Society Latest Research webpage.

Co-funders
In addition to the Economic and Social Research Council, co-funders for the study included the Department of Work and Pensions, the Department for Education, the Department for Transport, the Department of Culture, Media and Sport, the Department for Community and Local Government, the Department of Health, the Scottish Government, the Welsh Assembly Government, the Northern Ireland Executive, the Department of Environment and Rural Affairs, and the Food Standards Agency.

End User Licence and Special Licence versions:
There are two versions of the Calendar Year 2020 data. One is available under the standard End User Licence (EUL) agreement, and the other is a Special Licence (SL) version. The SL version contains month and year of birth variables instead of just age, more detailed country and occupation coding for a number of variables and various income variables have not been top-coded (see xxxx_eul_vs_sl_variable_differences for more details). Users are advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements. The SL data have more restrictive access conditions; prospective users of the SL version will need to complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables in order to get permission to use that version. The main longitudinal versions of the Understanding Society study may be found under SNs 6614 (EUL) and 6931 (SL).

Low- and Medium-level geographical identifiers produced for the mainstage longitudinal dataset can be used with this Calendar Year 2020 dataset, subject to SL access conditions. See...

The Open University (OU) dataset is an open database containing student demographic and click-stream interaction with the virtual learning platform. The available data are structured in different CSV files. You can find more information about the original dataset at the following link: https://analyse.kmi.open.ac.uk/open_dataset.

We extracted a subset of the original dataset that focuses on student information. 25,819 records were collected referring to a specific student, course and semester. Each record is described by the following 20 attributes: code_module, code_presentation, gender, highest_education, imd_band, age_band, num_of_prev_attempts, studies_credits, disability, resource, homepage, forum, glossary, outcontent, subpage, url, outcollaborate, quiz, AvgScore, count.

Two target classes were considered, namely Fail and Pass, combining the original four classes (Fail and Withdrawn and Pass and Distinction, respectively). The final_result attribute contains the target values.

All features have been converted to numbers for automatic processing.

Below is the mapping used to convert categorical values to numeric:

• code_module: 'AAA'=0, 'BBB'=1, 'CCC'=2, 'DDD'=3, 'EEE'=4, 'FFF'=5, 'GGG'=6
• code_presentation: '2013B'=0, '2013J'=1, '2014B'=2, '2014J'=3
• gender: 'F'=0, 'M'=1
• highest_education: 'No_Formal_quals'=0, 'Post_Graduate_Qualification'=1, 'HE_Qualification'=2, 'Lower_Than_A_Level'=3, 'A_level_or_Equivalent'=4
• IMBD_band: 'unknown'=0, 'between_0_and_10_percent'=1, 'between_10_and_20_percent'=2, 'between_20_and_30_percent'=3, 'between_30_and_40_percent'=4, 'between_40_and_50_percent'=5, 'between_50_and_60_percent'=6, 'between_60_and_70_percent'=7, 'between_70_and_80_percent'=8, 'between_80_and_90_percent'=9, 'between_90_and_100_percent'=10
• age_band: 'between_0_and_35'=0, 'between_35_and_55'=1, 'higher_than_55'=2
• disability: 'N'=0, 'Y'=1
• student's outcome: 'Fail'=0, 'Pass'=1

For more detailed information, please refer to:

Casalino G., Castellano G., Vessio G. (2021) Exploiting Time in Adaptive Learning from Educational Data. In: Agrati L.S. et al. (eds) Bridges and Mediation in Higher Distance Education. HELMeTO 2020. Communications in Computer and Information Science, vol 1344. Springer, Cham. https://doi.org/10.1007/978-3-030-67435-9_1

This qualitative data-set is of young people's spatial imaginaries within the UK context. It contains interviews carried out with young people aged 16/17 years across different geographic contexts. In particular, interviews focussed around the importance and significance of place, including: i) the role place has on the choices of young people who are socially and educationally similar but located in geographically diverse areas; ii) ways in which economically, socially, culturally or politically distinct places act as pull or push factors for different social groups; iii) what social, cultural, or economic importance particular localities hold for different groups.The creation of a fairer society through social mobility is high on the political agenda in the UK. It is often assumed that widening participation in higher education (HE), through various policies and initiatives, will equate to a fairer and more socially mobile society. Yet, while more disadvantaged groups are now progressing to HE, social mobility remains weak, suggesting that this is an over-simplified picture of the ways in which social inequalities are (re)produced in countries like the UK. The geographical (im)mobility of young people at this key transition point is rarely alluded to here, in terms of its significance in shaping social (im)mobility. In spatially diverse countries like the UK, access to universities, key labour markets, social networks, and other valuable resources often necessitate some degree of geographical mobility. In addressing social inequalities in wider society, it is therefore crucial to understand the nature of student flows across diverse parts of the UK, including the rationales different young people have for their (im)mobility to and from different places. There is already some evidence to suggest that the costs of HE study can deter the most disadvantaged young people from moving away for their studies, but what other place-based factors, including the cultural, social, and economic characteristics of localities might be important in shaping student (im)mobility? This interdisciplinary project will undertake an innovative and far-reaching programme of policy relevant research addressing the mobility patterns of UK HE students. The value of this research has been endorsed by all four UK HE Funding Councils, the UK Government's Social Mobility and Child Poverty Commission (Chaired by Rt. Hon. Alan Milburn), The Sutton Trust, and Universities UK. These organisations are members of the project stakeholder group and will be closely involved in the research and dissemination programme, ensuring that the research addresses areas of policy relevance and reaches a wide audience. This novel research will uncover, for the first time, the nature of student flows within and across the four countries of the UK, together with rich and in-depth understandings about how they are shaped. Taking into account the socially, economically, politically and culturally diverse nature of UK society, the project will seek to understand the placed nature of educational decision making in particular. This unique work is interdisciplinary in nature, drawing on, and contributing to, the academic disciplines of geography, education, and sociology. The research is mixed methods and organised around two distinct but sequential phases, which include large scale quantitative analysis of UK-wide student records data (phase 1) that will frame the collection of new qualitative data (phase 2). Phase 1 will involve advanced spatial analysis to examine student flows at country, region, and locality levels, producing innovative graphics displaying these spatial movements in visual form. This analysis will explore patterns and relationships between student movements and social as well as spatial characteristics. In the second phase, qualitative research will take place in 10 purposefully selected case study schools across the UK, selected on the basis of criteria developed from the quantitative analysis. To explore the sorts of factors shaping young people's mobility patterns, data collection will involve interviews with young people, two members of their social network, as well as observation of their school contexts. These rich qualitative data will dig beneath the surface of the quantitative patterns, capturing how young people's subjective experiences of space and their own geographical imaginaries impact on their geographic (im)mobility. It will explore how these relationships to place and mobility intentions are constructed and influenced by their individual biographies, social network and school. The data collection method involved semi-structured individual interviews with young people (aged 16/17) living in the UK which lasted around 45minutes to 1hour. The sample of young people (n. 112) was purposefully selected on the basis of those in school-based sixth forms and who indicated they wished to progress to university. Interviews were loosely structured around key topics which also allowed participants to express themselves in their own terms and discuss topics from their own vantage points. Interviews were transcribed verbatim and pseudonyms applied to people and places.

Understanding Society, (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex and the survey research organisations Verian Group (formerly Kantar Public) and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

Understanding Society (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex and the survey research organisations Kantar Public and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

The Understanding Society COVID-19 Study, 2020-2021 is a regular survey of households in the UK. The aim of the study is to enable research on the socio-economic and health consequences of the COVID-19 pandemic, in the short and long term. The surveys started in April 2020 and took place monthly until July 2020. From September 2020 they took place every other month until March 2021 and the final wave was fielded in September 2021. They complement the annual interviews of the Understanding Society study. The data can be linked to data on the same individuals from previous waves of the annual interviews (SN 6614) using the personal identifier pidp. However, the most recent pre-pandemic (2019) annual interviews for all respondents who have taken part in the COVID-19 Study are included as part of this data release. Please refer to the User Guide for further information on linking in this way and for geographical information options.

Latest edition information

For the eleventh edition (December 2021), revised April, May, June, July, September, November 2020, January 2021 and March 2021 data files for the adult survey have been deposited. These files have been amended to address issues identified during ongoing quality assurance activities. All documentation has been updated to explain the revisions, and users are advised to consult the documentation for details. In addition new data from the September 2021 web survey have been deposited.

Abstract copyright UK Data Service and data collection copyright owner.

Understanding Society (the UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex, and the survey research organisations Verian Group (formerly Kantar Public) and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

Understanding Society (the UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex, and the survey research organisations Kantar Public and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

The Understanding Society: Innovation Panel, Special Licence Access, Higher Education Codes dataset contains higher education institution identification codes for Waves 13 onwards. For a full description of the variables available in this dataset please refer to the Understanding Society: Innovation Panel Higher Education Codes User Guide.

The details in this dataset can be linked to the main Understanding Society datasets SN 6849 (End User Licence), SN 7083 (Special Licence) and SN 7332 (Secure Access) using the crosswave personal identifier pidp. The institution identifiers in the data files can be used to link to publicly available datasets published by HESA and elsewhere.

These data have more restrictive access conditions than those available under the standard End User Licence (see 'Access' section below). Those users who wish to make an application for these data should contact the Help Desk for further details.

Latest Edition Information

For the 1st edition (November 2024), Higher Education institution data has been removed from all applicable waves (13 to 16) of the EUL (SN 6849), Special Licence (SN 7083) and Secure Access (SN 7332) versions of the Innovation Panel and released in this new Special Licence dataset.

Main Topics:

Variables include higher education institution identifiers for linking to Waves 13 onwards of Understanding Society: Innovation Panel.

Number of pupils on roll by year group in Calderdale Secondary Schools (Academies and Local Authority Maintained Schools); the data source is the termly school census. Academy data is only available from October 2015 onwards. The dataset for Academies and Local Authority Maintained Schools is being published as one dataset from October 2016. May 2020 is missing because this census was cancelled by the government due to the Covid-19 pandemic.

Other schools data

This bulletin has been produced by HESA and has been released according to the arrangements approved by the UK Statistics Authority. The data presented in this bulletin is based on the 2017/18 Graduate Outcomes survey. The statistics in this bulletin are derived by HESA from data collected from all publicly funded HE providers in the UK (including The Open University), alternative providers that submit student data to HESA and further education colleges in England, Wales and Northern Ireland. For the 2017/18 release of Graduate Outcomes, the dataset was initially coded using SOC 2010, which was the current framework during census week for all four cohorts of the first year of data collection. SOC 2020, which updated the SOC framework to reflect a changing labour market, was released on 14 February 2020, after the SOC coding of 2017/18 data to SOC 2010 was largely complete. HESA rapidly analysed the new framework and determined that it was suitable for use with the Graduate Outcomes survey. Given the scale of work involved it was not possible to introduce SOC 2020 in time for the initial dissemination of the 2017/18 results. In order to ensure that graduates are coded according to the most up-to-date framework, HESA committed to adopt SOC 2020 from the 2018/19 Graduate Outcomes dataset. At the same time, we undertook to recode the 2017/18 dataset to SOC 2020 to ensure a consistent time-series. We have now completed the work of re-basing our coding approach to follow the SOC 2020 framework, and have re-coded the data and quality-assured our results.

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.

Main Topics:

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

Number of pupils with Special Education Needs in Calderdale Secondary Schools (Academies and Local Authority Maintained Schools); the data source is the termly school census. Academy data is only available from October 2015 onwards. The dataset for Academies and Local Authority Maintained Schools is being published as one dataset from October 2016. May 2020 is missing because this census was cancelled by the government due to the Covid-19 pandemic.

Also see - Other schools data

DfE Special Educational Needs (SEND) Report on LG Inform - report presents the statistics on SEND available for Calderdale, compared to comparison group of All English metropolitan boroughs.

ShimFall&ADL dataset

Version 1.0 (2020-06-19)

Please cite as: "T. Althobaiti, S. Katsigiannis, N. Ramzan, Triaxial accelerometer-based Fall and Activities of Daily Life detection using machine learning, Sensors, 20(13), 3777, 2020. doi: 10.3390/s20133777"

Disclaimer
While every care has been taken to ensure the accuracy of the data included in the ShimFall&ADL dataset, the authors and the University of the West of Scotland do not provide any guaranties and disclaim all responsibility and all liability (including without limitation, liability in negligence) for all expenses, losses, damages (including indirect or consequential damage) and costs which you might incur as a result of the provided data being inaccurate or incomplete in any way and for any reason. 2020, University of the West of Scotland, Scotland, United Kingdom.

Contact
For inquiries regarding the ShimFall&ADL dataset, please contact:
Dr Stamos Katsigiannis, Stamos.Katsigiannis@uws.ac.uk, University of the West of Scotland
Prof. Naeem Ramzan, Naeem.Ramzan@uws.ac.uk, University of the West of Scotland

Acknowledgment

The authors would like to thank Md. Hasan Shahriar for the data collection under his MSc project.

Dataset summary
The ShimFall&ADL dataset contains recordings from 35 individuals, acquired using a chest-strapped Shimmer v2 tri-axial accelerometer, recording at a 50Hz sampling rate. Experiments were conducted in a controlled environment at a research lab in the University of the West of Scotland. Thirty five (35) healthy individuals were recruited among young or mid-aged volunteers, aged between 19 and 34 years old, having a body weight between 52 and 113 kg, and a body height between 1.45 and 1.82 m.

Participants performed the following activities of daily living (ADL):
Jumping
Lying down
Bending/picking up
Sitting to a chair
Standing up from a chair
Walking

Participants performed the following falls:
Steep (hard)
Front (soft)
Front (hard)
Left (soft)
Left (hard)
Right (soft)
Right (hard)
Back (soft)
Back (hard)

Data
Each ".dat" file in the dataset corresponds to one event for one individual and contains 101 accelerometer samples corresponding to the event. Each row of the file corresponds to one 3-channel sample, dividing the x, y, z axes values using the "\t" character, as follows:
Row 1: x1\ty1\tz1
Row 2: x2\ty2\tz2
...
Row N: xN\tyN\tzN

The files within the dataset are named as follows:
adl_

For example, the file "adl_standingfromchair_18.dat" corresponds to the accelerometer recording of the 18th participant, performing the "standing up from chair" ADL. The file, "leftfall_soft_11.dat" corresponds to the accelerometer recording of the 11th participant, performing a soft left fall.

Additional information
For additional information regarding the creation of the ShimFall&ADL dataset, please refer to the associated publication: "T. Althobaiti, S. Katsigiannis, N. Ramzan, Triaxial accelerometer-based Fall and Activities of Daily Life detection using machine learning, Sensors, 20(13), 3777, 2020. doi: 10.3390/s20133777"

This project uses interview data to investigate the implications, implementation and consequences of Brexit for UK universities, including the effects in relation to migration, international education and financial sustainability. The generic research questions are: 1) What are the perceived implications of Brexit for UK universities as leaders and others see it? 2) What are the principal responses of universities and what are their capabilities to monitor, judge, strategies, respond, initiate and make internal changes, in relation to Brexit? 3) How do these factors vary by UK nation; university mission, status, resources; and discipline? The dataset includes 124 semi-structured transcripts of semi-structured interviews conducted between November 2017 to September 2018. Participants were from 12 universities in the UK. This project is part of the ESRC’s 'The UK in a Changing Europe' initiative which supports research into the relationship between the UK and the European Union (EU).UK universities are extensively engaged in Europe, in collaborative research and infrastructure and through EU citizen staff and students. The UK’s departure from the EU has many potential consequences for UK universities and their staffing, research, international education and financial sustainability.

Brexit is an unprecedented development with implications in almost every domain of UK higher education (HE) and a range of possible forms and consequences for individual UK HEIs, with marked potential for differential effects (e.g. in research capability, international students, staffing, mission, income) across the variation of HEI types. Though Brexit has many possible forms, in any form it is likely to disrupt existing projects, networks and activities, and could imply sharp reductions in staff, students and/or income, in some or all HEIs. It also calls for new and innovative lines of institutional and discipline-based development on and off shore.In an uncertain and fast changing setting characterised by multiple possibilities and sudden shocks, HEIs will be required to monitor, respond, adjust, strategize, reorient and initiate with unprecedented speed and effectiveness; to build new relations and activity portfolios in Europe and beyond; and to grapple with new challenges to human resource management, risk management, financial sustainability, mission, governance and local implementation systems. This research investigates the policy implications, implementation and consequences of Brexit for UK HE, in two priority areas identified by the Economic and Social Research Council: implications of Brexit for migration, and impacts in the economy and future trade arrangements. UK higher education institutions (HEIs) are extensively engaged in Europe and in this sector EU relations have been unambiguously positive and productive. While there is a range of possible Brexit scenarios, UK HE is closely affected by the Brexit-related policy settings for staff mobility, retention and recruitment ('migration'); for international student policy and regulation, with consequences for tuition revenues and balance sheets ('trade'); and by the effects of Brexit in research relations between UK and European HEIs. Research papers co-authored with colleagues in Europe outweigh total papers co-authored with US and other English-speaking countries, more than 20 per cent of UK R&D funding is from international sources with much from collaborative European research schemes. The role of UK universities in Europe is central to their outstanding global research performance: UK accounts for 3.2 per cent of global R&D spending, 9.5 per cent of scientific papers downloaded, 11.6 per cent of citations, and 15.9 per cent of the most highly-cited papers. EU frameworks enable many UK researchers to lead, while sharing the best ideas and people from other EU member countries. The research capacity and reputation of UK HEIs also underpins the nation's role as the world's second largest exporter of international education after the US. The government has stated that it hopes to raise education exports by almost 50 per cent to 30 billion pa in 2020. The main data collection consists of qualitative case studies in 12 UK HEIs, with participating institutions selected from all four nations and illustrating the diversity of the sector. There are 127 semi-structured interviews, with senior academic leaders of HEIs, chief financial officers, heads of human resources, executive deans in three disciplines (health, science, social science), research professors from these disciplines, and student representatives. The project also conducted policy-oriented seminars which will have both data gathering and dissemination/public discussion purposes. The practical outcomes of the research are (a) through research, public events and briefings, to draw to the attention of policy makers and public the implications of different Brexit scenarios in higher education, (b) within...

RESPOND project produced a high level of empirical material in 11 countries (Sweden, the UK, Germany, Italy, Poland, Austria, Greece, Bulgaria, Turkey, Iraq, and Lebanon) where the research is conducted between the period 2017-2020. The country teams gathered macro (policies), meso (implementation/stakeholders) and micro (individuals/asylum seekers and refuges) level data related to the thematic fields formulated in four work packages: borders, protection regimes, reception, and integration. An important contribution of this research has been its micro/individual focus which enabled the research teams to capture and understand the migration experiences of asylum seekers and refugees and their responses to the policies and obstacles that they have encountered.

Country teams conducted in total 539 interviews with refugees and asylum seekers, and more than 210 interviews with stakeholders (state and non-state actors) working in the field of migration. Additionally, the project has conducted a survey study in Sweden and Turkey (n=700 in each country), covering similar topics.

This dataset is only about the micro part of the Respond research, and reflects data derived out of 539 interviews conducted with asylum seekers and refugees in 11 countries and here presented in a quantitative form. The whole dataset is structured along the work package topics: Border, Protection, Reception and Integration.

This dataset is prepared as part of Work Package D5.6 (Dataset on Integration) the Horizon 2020 RESPOND project as a joint effort of the below listed project partners.

• • Uppsala University (dataset entries from Sweden)
• • Göttingen University (dataset entries from Germany)
• • Glasgow Caledonian University (dataset entries from the UK and Hungary)
• • Istanbul Bilgi University (dataset entries from Turkey)
• • University of Cambridge (dataset entries from the UK, Sweden and Germany)
• • Swedish Research Institute Istanbul (dataset entries from Turkey)
• • University of Florence (dataset entries from Italy)
• • Özyegin University (dataset entries from Turkey)
• • University of Aegean (dataset entries from Greece)
• • University of Warsaw (dataset entries from Poland)
• • Hammurabi Human Rights Organization (dataset entries from Iraq)
• • Lebanon Support (dataset entries from Lebanon)
• • Austrian Academy of Sciences (dataset entries from Austria)

This data relates to careers advice and guidance to year 11 and 12 pupils in Northern Ireland and their university aspirations. Data is presented for year 11 and 12 pupils on their confidence making career decisions, the support they require to achieve their career goals, their awareness of the all-age Careers Service, their knowledge of how to contact a Careers Adviser outside school and also their university aspirations. The data is derived from the Young Persons’ Behaviour and Attitudes Survey, carried out between September 2019 and February 2020.

Dataset for Study -Younie, S., Mitchell., C, Bisson, M., Crosby, S., Kukona, A., & Laird, K. (2020). Improving the efficacy of young children’s handwashing behaviour and understanding of germ transfer: The impact of A Germ’s Journey educational resources in schools and public spaces. Plos one