72 datasets found
  1. Education, health and care plans: England 2022

    • gov.uk
    Updated May 12, 2022
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    Department for Education (2022). Education, health and care plans: England 2022 [Dataset]. https://www.gov.uk/government/statistics/education-health-and-care-plans-england-2022
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    Dataset updated
    May 12, 2022
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Education
    Area covered
    England
    Description

    This publication provides data on the number of children and young people with a statement of special educational needs (SEN) or education, health and care (EHC) plan in England.

    It also provides data on the administration of statements of SEN and EHC plans, including:

    • the number of EHC plans in place in January 2022
    • the number of EHC plans made for the first time during the 2021 calendar year
    • the number and percentage of EHC plans that were issued within 20 weeks

    It is based on the statutory SEN2 data collection.

  2. 2

    COSMO

    • datacatalogue.ukdataservice.ac.uk
    Updated Apr 9, 2024
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    Anders, J., University College London, Centre for Education Policy and Equalising Opportunities; Calderwood, L., University College London, UCL Institute of Education, Centre for Longitudinal Studies; Crawford, C., University College London, Centre for Education Policy and Equalising Opportunities; Cullinane, C., Sutton Trust; Goodman, A., University College London, UCL Institute of Education, Centre for Longitudinal Studies; Macmillan, L., University College London, Centre for Education Policy and Equalising Opportunities; Patalay, P., University College London, UCL Institute of Education, Centre for Longitudinal Studies; Wyness, G., University College London, Centre for Education Policy and Equalising Opportunities (2024). COSMO [Dataset]. http://doi.org/10.5255/UKDA-SN-9158-2
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    Dataset updated
    Apr 9, 2024
    Dataset provided by
    UK Data Servicehttps://ukdataservice.ac.uk/
    Authors
    Anders, J., University College London, Centre for Education Policy and Equalising Opportunities; Calderwood, L., University College London, UCL Institute of Education, Centre for Longitudinal Studies; Crawford, C., University College London, Centre for Education Policy and Equalising Opportunities; Cullinane, C., Sutton Trust; Goodman, A., University College London, UCL Institute of Education, Centre for Longitudinal Studies; Macmillan, L., University College London, Centre for Education Policy and Equalising Opportunities; Patalay, P., University College London, UCL Institute of Education, Centre for Longitudinal Studies; Wyness, G., University College London, Centre for Education Policy and Equalising Opportunities
    Area covered
    England
    Description
    The COVID Social Mobility and Opportunities Study (COSMO) is a longitudinal cohort study, a collaboration between the UCL Centre for Education Policy and Equalising Opportunities (CEPEO), the UCL Centre for Longitudinal Studies (CLS), and the Sutton Trust. The overarching aim of COSMO is to provide a representative data resource to support research into how the COVID-19 pandemic affected the life chances of pupils with different characteristics, in terms of short-term effects on educational attainment, and long-term educational and career outcomes.

    The topics covered by COSMO include, but are not limited to, young people's education experiences during the pandemic, cancelled assessments and education and career aspirations. They have also been asked for consent for linking their survey data to their administrative data held by organisations such as the UK Department for Education (DfE). Linked data is planned to be made available to researchers through the ONS Secure Research Service.

    Young people who were in Year 11 in the 2020-2021 academic year were drawn as a clustered and stratified random sample from the National Pupil Database held by the DfE, as well as from a separate sample of independent schools from DfE's Get Information about Schools database. The parents/guardians of the sampled young people were also invited to take part in COSMO. Data from parents/guardians complement the data collected from young people.

    Further information about the study may be found on the COVID Social Mobility and Opportunities Study (COSMO) webpage.

    COSMO Wave 2, 2022-2023
    All young people who took part in Wave 1 (see SN 9000) were invited to the second Wave of the study, along with their parents (whether or not they took part in Wave 1).

    Data collection in Wave 2 was carried out between October 2022 and April 2023 where young people and parents/guardians were first invited to a web survey. In addition to online reminders, some non-respondents were followed up via face-to-face visits or telephone calls over the winter and throughout spring. Online ‘mop-up’ fieldwork was also carried out to invite all non-respondents into the survey one last time before the end of fieldwork.

    Latest edition information:
    For the second edition (April 2024), a standalone dataset from the Keeping in Touch (KIT) exercise carried out after the completion of Wave 2, late 2023 have been deposited. This entailed a very short questionnaire for updating contact details and brief updates on young people's lives. A longitudinal parents dataset has also been deposited, to help data users find core background information from parents who took part in either Wave 1 or Wave 2 in one place. Finally, the young people's dataset has been updated (version 1.1) with additional codes added from some open-ended questions. The COSMO Wave 1 Data User Guide Version 1.1 explains these updates in detail. A technical report and accompanying appendices has also been deposited.

    Further information about the study may be found on the COSMO website.

  3. s

    Best political party for handling education poll UK 2024-2025

    • statista.com
    Updated Sep 8, 2025
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    Statista (2025). Best political party for handling education poll UK 2024-2025 [Dataset]. https://www.statista.com/statistics/710245/political-parties-best-at-education-policies/
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    Dataset updated
    Sep 8, 2025
    Dataset authored and provided by
    Statista
    Time period covered
    Jul 29, 2024 - Sep 22, 2025
    Area covered
    United Kingdom
    Description

    In September 2025, 18 percent of people in the UK thought that the Labour Party would be the best at handling education, compared with 13 percent who believed that the Conservatives would be the best and 10 percent who thought Reform UK would handle the issue best.

  4. How higher education (HE) statistics are used

    • gov.uk
    Updated Jul 31, 2009
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    Department for Business, Innovation & Skills (2009). How higher education (HE) statistics are used [Dataset]. https://www.gov.uk/government/statistics/how-he-statistics-are-used
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    Dataset updated
    Jul 31, 2009
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Business, Innovation & Skills
    Description

    The Department for Business, Innovation and Skills (BIS)

    The key statistic in the “Participation Rates in Higher Education” Statistical First Release (SFR) is the Higher Education Initial Participation Rate (HEIPR).

    HEIPR was used by BIS (and former Departments) and Her Majesty’s Treasury to track progress on the former Skills PSA target to “Increase participation in Higher Education towards 50 per cent of those aged 18 to 30, with growth of at least a percentage point every two years to the academic year 2010-11”. For example, it was reported in the http://www.bis.gov.uk/assets/biscore/corporate/migratedD/publications/D/DIUS-Annual%20Report-2009">Departmental annual report.

    HEIPR has been quoted in http://www.parliament.the-stationery-office.co.uk/pa/cm200809/cmselect/cmpubacc/226/22605.htm">Public Accounts Committees around increasing and widening participation in higher education

    HEIPR has been quoted extensively by the http://news.bbc.co.uk/1/hi/education/8596504.stm">Press

    BIS receives enquiries (including Freedom of Information (FoI) requests) from the public about HEIPR, including from the following groups:

    • academic researchers
    • higher education sector
    • local authorities - students
    • Members of Parliament (via Parliamentary Questions).

    The Higher Education Statistics Agency (HESA)

    Figures in the HESA SFRs are high profile and are frequently used in the press and other external publications to illustrate: trends in university entry and graduation, often in the context of current higher education policies; graduate employment/unemployment rates, average salaries, and job quality. Members of the public also often request these figures. Some examples of media coverage are included below:

    Higher Education student enrolments and qualifications

    Destinations of leavers from Higher Education

    These statistical outputs are not used to measure progress on any government targets, but the data that underpin them are of importance to funding bodies, Higher Education Institutions, and potential students:

    Potential Students – sources such as the http://unistats.direct.gov.uk/">Unistats website use qualifier and graduate employment information to inform students when they are making their choice of what course to study and at which university.

    Figures from the HESA statistical outputs are often u

  5. u

    The Political Economies of School Exclusion and Their Consequences:...

    • datacatalogue.ukdataservice.ac.uk
    Updated Apr 17, 2025
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    Thompson, I, University of Oxford (2025). The Political Economies of School Exclusion and Their Consequences: Qualitative Data, 2021-2023 [Dataset]. http://doi.org/10.5255/UKDA-SN-857678
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    Dataset updated
    Apr 17, 2025
    Authors
    Thompson, I, University of Oxford
    Area covered
    United Kingdom
    Description

    The main objective of this research was to develop a multi-disciplinary understanding of the political economies and consequences of school exclusion across the UK through a home-international comparison.

    The motivation for the study was the need to understand the great differences in the rates of permanent school exclusions and suspensions in different parts of the UK. with numbers rising rapidly in England but remaining relatively low or falling in Northern Ireland, Scotland and Wales.

    The research was undertaken by the multi-disciplinary (criminology, economics, education, law, psychology, psychiatry, sociology) and multi-site (the universities of Oxford, Cardiff, Edinburgh, Queen’s Belfast, and the LSE) Excluded Lives Research Team. The research was organised into two work strands: A. Landscapes of Exclusion; and B. Experiences of Exclusion. In Strand A work packages examined: the ways in which policies and legal frameworks shape interventions designed to prevent exclusions; the financial costs associated with exclusion; and patterns and characteristics of exclusion. Strand B work packages focussed on families’, pupils’ and professionals’ experiences of the risks and consequences of exclusion.

    The data were collected from representative local educational authorities (4 in England, 2 in both Scotland and Wales) and across NI. Our sampling strategy for schools used modelled data, whereby we calculated the rates of exclusions for schools after controlling for pupil characteristics to estimate whether schools had above or below expected levels of exclusion based on their pupil characteristics. For the purposes of sampling, we used the number of temporary exclusions officially recorded over a five-to-seven-year period (depending on the availability of national data in each of the UK jurisdictions). School and local authority staff were selected on the basis of their roles. This data set comprises of interviews from across the UK with Headteachers, Alternative Provision providers in England and Scotland, and national policymakers in Scotland.

    The main aim of PolESE is to develop a multi-disciplinary understanding of the political economies and consequences of school exclusion across the UK. There are great differences in the rates of permanent school exclusion in different parts of the UK with numbers rising rapidly in England but remaining relatively low or falling in Northern Ireland, Scotland and Wales. For example, in the last available figures (2016/7) there were 7,720 permanent exclusions in England compared to just five in Scotland. However, these figures do not account for many informal and illegal forms of exclusion. In this research, home international comparisons of historical and current policy, practice and legal frameworks relating to school exclusion will be conducted for the first time. Previous research and official statistics show that school exclusions are far more likely to affect pupils with special needs, from low income families, and particular ethnic backgrounds. Exclusions have long and short term consequences in terms of academic achievement, well-being, mental health, and future economic and employment prospects. PolESE is designed to highlight ways in which fairer and more productive outcomes can be achieved for pupils, their families, and professionals by comparing the ways in which policy and practice around exclusions differ in the four jurisdictions.

    PolESE will be undertaken by the multi-disciplinary (criminology, disability studies, economics, education, human geography, law, psychiatry, sociology) and multi-site (Oxford, Cardiff, Edinburgh, Belfast, Reading, LSE) Excluded Lives group established in 2014. In education, policy discourse has tended to find individual reasons for exclusion rather than develop an understanding of exclusion in the wider context of education, social policy and the law. Education policy has also largely ignored the work conducted by school and welfare professionals that attempts to address disruptive behaviour to prevent more serious incidents. In contrast, PolESE assumes that school exclusion cannot be treated as separate from the general welfare and education systems. Preliminary work has illustrated that pressures on schools to perform well in examination league tables can lead to the exclusion of pupils whose predicted attainment would weaken overall school performance, leaving these pupils on the social margins of schooling. Exclusion is a process, rather than a single incident, that can only be fully understood when examined from multiple professional and disciplinary perspectives.

    The research is organised into three work strands. Strand A, Landscapes of Exclusion, is designed examine the ways in which legal frameworks, policies, and practices of regulation shape systemic practice; and the patterns, characteristics and consequences of exclusion. Strand B, Experiences of Exclusion, will focus on families', pupils' and professionals' experiences of the risks and consequences of exclusion. Strand C, Costs and Integration, will examine the financial costs associated with exclusion; it will also integrate findings within and across jurisdictions to ensure that the learning is continuous as the research develops a coherent multi-disciplinary understanding of the political economies of exclusion. 1. The cost of exclusions at individual, institutional and system level (psychological, educational, sociological, economic, criminological, political lenses); 2. Rights and entitlements (legal, moral, social policy, political lenses); 3. Landscapes of exclusion (geographical, sociological, political lenses); 4. Protection and wellbeing (psychological, social work, legal and social policy lenses).

    Researchers will engage directly with the Third Sector, professionals at school, local authority and jurisdiction government levels, as well as with disadvantaged and excluded pupils and their families.

  6. Schools, pupils and their characteristics - School characteristics

    • explore-education-statistics.service.gov.uk
    Updated Jun 8, 2023
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    Department for Education (2023). Schools, pupils and their characteristics - School characteristics [Dataset]. https://explore-education-statistics.service.gov.uk/data-catalogue/data-set/3e278b1d-ab17-43b3-93df-b45a79f20c77
    Explore at:
    Dataset updated
    Jun 8, 2023
    Dataset authored and provided by
    Department for Educationhttps://gov.uk/dfe
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Number of schools in England, by type, phase, denomination, admission policy, gender, urban/rural and academy status including headcounts and fte, language, fsm, age and national curriculum year breakdowns

  7. o

    Round 5 - Teacher surveys

    • portal.sds.ox.ac.uk
    bin
    Updated Feb 6, 2023
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    Giang Thai (2023). Round 5 - Teacher surveys [Dataset]. http://doi.org/10.25446/oxford.21636923.v1
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    binAvailable download formats
    Dataset updated
    Feb 6, 2023
    Dataset provided by
    University of Oxford
    Authors
    Giang Thai
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The folder contains datasets of teacher surveys, including teachers of primary school grade 3 and grade 4, and teachers of lower secondary school grade 9. The data was collected in Vietnam in 2020.

  8. Number of fines issues to parents for unauthorized school absence England...

    • statista.com
    Updated Jul 18, 2025
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    Statista (2025). Number of fines issues to parents for unauthorized school absence England 2016-2024 [Dataset]. https://www.statista.com/statistics/1553188/england-school-absence-parental-fines/
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    Dataset updated
    Jul 18, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United Kingdom, England
    Description

    There were ******* penalty notices issued to parents for unauthorized school absence in England during the 2023/24 academic year, the highest during this time period. The vast majority of these fines were related to unauthorized family holiday absence, with just over ****** for arriving late or other reasons.

  9. o

    Impact of district education policies on learning: PPG Selectivity

    • portal.sds.ox.ac.uk
    xlsx
    Updated Feb 6, 2023
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    Asri Yusrina; Luhur Bima (2023). Impact of district education policies on learning: PPG Selectivity [Dataset]. http://doi.org/10.25446/oxford.21583029.v1
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    xlsxAvailable download formats
    Dataset updated
    Feb 6, 2023
    Dataset provided by
    University of Oxford
    Authors
    Asri Yusrina; Luhur Bima
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This study forms part of the teams Reform Area B workstream that focusses on decentralisation and district innovations through four specially selected innovative districts that will be used as "learning laboratories" to generate findings. In each district, the team studies a particular system innovation and its impact on learning outcomes. Some of these innovations are co-designed with the district government.

  10. u

    Data from: Employment and retention of BAME teachers in England

    • rdr.ucl.ac.uk
    zip
    Updated May 30, 2023
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    Antonina Tereshchenko; Manuela Mendoza Horvitz (2023). Employment and retention of BAME teachers in England [Dataset]. http://doi.org/10.5522/04/13365959
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    zipAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    University College London
    Authors
    Antonina Tereshchenko; Manuela Mendoza Horvitz
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    England
    Description

    This research produced evidence on the issue of minority ethnic teacher retention in England in 2019/20 academic year. Focusing on the perspectives of 24 minority ethnic teachers from different demographics and professional backgrounds, we investigated in interviews why minority ethnic teachers leave schools that employ high numbers of minority ethnic staff and enrol students from similar backgrounds, and what should be done to support their retention.

  11. f

    A Critical Teacher Education Experience in the State of Goiás, Brazil

    • scielo.figshare.com
    xls
    Updated Jun 1, 2023
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    Rosane Rocha Pessoa; Maria Eugênia Sebba Ferreira de Andrade; Edilson Pimenta Ferreira (2023). A Critical Teacher Education Experience in the State of Goiás, Brazil [Dataset]. http://doi.org/10.6084/m9.figshare.6857231.v1
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    SciELO journals
    Authors
    Rosane Rocha Pessoa; Maria Eugênia Sebba Ferreira de Andrade; Edilson Pimenta Ferreira
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Brazil
    Description

    ABSTRACT One of the Brazilian government initiatives to improve basic education was to create the National Network of Continuing Education for Teaching Professionals of Public Basic Education in 2011. Our extension program in this network was implemented in 2013 in 10 towns of the state of Goiás and counted on 21 teacher educators and 110 teacher-participants. Part of the empirical material of one of these teacher educators will be analyzed in this article, focusing on the discourses of seven female teacher-participants about their previous language teacher education experiences and about the first two months of the extension course. The qualitative discussion draws on theorizations from Critical Discourse Analysis and Teacher Education in Brazil, and shows that discourses on language teacher education, English teaching, and English were problematized.

  12. u

    Primary studies evaluating school lotteries: data used for the meta-analysis...

    • rdr.ucl.ac.uk
    xlsx
    Updated Jun 17, 2020
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    Constanza Gonzalez Parrao (2020). Primary studies evaluating school lotteries: data used for the meta-analysis of the effect of schools under these admission policies on student academic outcomes [Dataset]. http://doi.org/10.5522/04/12076719.v1
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    xlsxAvailable download formats
    Dataset updated
    Jun 17, 2020
    Dataset provided by
    University College London
    Authors
    Constanza Gonzalez Parrao
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    The file consists of three spreadsheets. This first one is the dataset. It contains information extracted from primary studies that were part of the quantitative synthesis of a systematic review of school randomised admissions. The second tab is the codebook, including a brief description of each variable extracted or assessed from the primary studies, and its corresponding values. The third sheet shows the APA bibliographic reference and access link for each of the primary studies included in the meta-analysis.These data were used for one of the research chapters of the author's PhD thesis, available here https://discovery.ucl.ac.uk/id/eprint/10096351

  13. u

    ICOSS Study

    • datacatalogue.ukdataservice.ac.uk
    Updated Mar 15, 2000
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    Levacic, R., Open University, School of Education, Centre for Educational Policy and Management (2000). ICOSS Study [Dataset]. http://doi.org/10.5255/UKDA-SN-4111-1
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    Dataset updated
    Mar 15, 2000
    Dataset provided by
    UK Data Servicehttps://ukdataservice.ac.uk/
    Authors
    Levacic, R., Open University, School of Education, Centre for Educational Policy and Management
    Area covered
    England
    Description

    The ICOSS (Impact of Competition on Secondary Schools) study, based in the Open University's Centre for Educational Policy and Management, is investigating the impact of competitive pressures on secondary schools in England. The Survey on School Competition, 1992-1997 is part of the study.
    Secondary school headteachers from six local education authority (LEA) areas were surveyed on their perceptions of the degree of competition facing their school and its impact on pupil recruitment and school budgets since 1992, when national league tables of examination results were first published. The schools contacted comprised all grant-maintained (GM) and LEA maintained secondary schools (excepting special schools) in the six LEA areas.
    LEAs were selected in order to include in the database a wide range of school types so as to provide an adequate basis for generalisation of results. The LEAs include county and metropolitan authorities to give urban and rural schools and a diversity of socio-economic backgrounds and school systems (i.e. a selective system and a concentration of GM schools in some of the LEA areas).
    The survey was intended to give headteachers the opportunity to comment on the effects of educational policies which have had the aim of creating a more competitive climate and to contribute to the broader aims of the ICOSS study.
    Further information about the ICOSS study may be found on the website:
    http://soe.open.ac.uk/CEPAM/research/ICOSS/index.htm .

  14. Data from: Critical language teaching in a dynamic language policy terrain:...

    • scielo.figshare.com
    xls
    Updated Jun 4, 2023
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    Jonathan Luke (2023). Critical language teaching in a dynamic language policy terrain: lessons from the Brazilian Science without Borders student mobility programme [Dataset]. http://doi.org/10.6084/m9.figshare.6858104.v1
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    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    SciELOhttp://www.scielo.org/
    Authors
    Jonathan Luke
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    ABSTRACT This article reports on a case study of English language learning in higher education, considering the impact of language policies embedded within a mobility scholarship programme on the practices of language teachers. Based on a larger ethnographic study following the experiences of several undergraduate members of one cohort of Brazil’s Science without Borders programme for students in science and technological fields, this article describes how several language teachers engaged with the power relations of the frequently shifting policy terrain of the programme. It concludes with a discussion of possibilities for teachers in similar situations who endeavour to take a critical approach to language teaching and explores some of the tactics they might employ against those policies which they see as incompatible with their practices.

  15. Referrals, assessments and children and young people who are the subject of...

    • data.europa.eu
    • data.wu.ac.at
    html, unknown
    Updated Apr 30, 2021
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    Department for Education (2021). Referrals, assessments and children and young people who are the subject of a child protection plan, England [Dataset]. https://data.europa.eu/data/datasets/referrals_assessments_and_children_and_young_people_who_are_the_subject_of_a_child_protection_plan_e?locale=ro
    Explore at:
    unknown, htmlAvailable download formats
    Dataset updated
    Apr 30, 2021
    Dataset authored and provided by
    Department for Educationhttps://gov.uk/dfe
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    England
    Description

    This publication contains national and local authority level figures on the number of referrals, assessment and children and young people who are the subjects of child protection plans (on the child protection register). Similar information has been published in previous years based upon data collected through the Child Protection and Referrals 3 (CPR3) return however this collection has been discontinued.

    Source agency: Education

    Designation: National Statistics

    Language: English

    Alternative title: Referrals, assessments and children and young people who are the subject of a child protection plan, England

  16. o

    ELEMENTAL Spain

    • ordo.open.ac.uk
    • datasetcatalog.nlm.nih.gov
    docx
    Updated May 31, 2024
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    Marion Nao (2024). ELEMENTAL Spain [Dataset]. http://doi.org/10.21954/ou.rd.25766058.v1
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    docxAvailable download formats
    Dataset updated
    May 31, 2024
    Dataset provided by
    The Open University
    Authors
    Marion Nao
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Spain
    Description

    The current dataset on Spain is part of the ELEMENTAL project, headed by Anna Kristina Hultgren (PI), investigating the reasons for the use and rise of English for academic programmes at European higher education institutions within the context of their governance. Details of the project and resulting outputs can be viewed at the UKRI project webpage: https://gtr.ukri.org/projects?ref=MR/T021500/1.The Spain dataset comprises transcripts of semi-structured interviews between a researcher and two types of participants: participants (P) of a case study university; and participants who hold or have held ministerial or public body roles (M). In total, the collection contains 14 transcripts involving 15 participants, all of whom gave consent for the OU deposit of their deidentified transcripts.The interviews were conducted online between 2022-2023. They lasted between 40-60 mins, averaging at around 50 mins. A key to transcription conventions is provided at the beginning of each participant transcript.

  17. Department for Education business plan quarterly data summary

    • data.europa.eu
    • ckan.publishing.service.gov.uk
    • +1more
    excel xls, html
    + more versions
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    Department for Education, Department for Education business plan quarterly data summary [Dataset]. https://data.europa.eu/data/datasets/department-for-education-business-plan-quarterly-data-summary
    Explore at:
    html, excel xlsAvailable download formats
    Dataset authored and provided by
    Department for Educationhttps://gov.uk/dfe
    License

    http://reference.data.gov.uk/id/open-government-licencehttp://reference.data.gov.uk/id/open-government-licence

    Description

    The Business Plan quarterly data summaries (QDS) provide the latest data on indicators included in Departmental business plans as well as other published data and management information. The QDS follows commitments made at Budget 2011 and the Written Ministerial Statement on business plans. Their primary purpose was to make more of the management information currently held by government available to members of the public on a regular basis. The last QDS was 2012. This page also incorporates the education priorities and spending plans produced by the Department for Education from 2011 -2015.

  18. Ukrainian Public Opinion on Equal Access to Higher Education and Priorities...

    • zenodo.org
    • data.niaid.nih.gov
    bin, pdf
    Updated Apr 10, 2025
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    Ilko Kucheriv Democratic Initiatives Foundation; Kyiv International Institute of Sociology; Ilko Kucheriv Democratic Initiatives Foundation; Kyiv International Institute of Sociology (2025). Ukrainian Public Opinion on Equal Access to Higher Education and Priorities for Education Reform – A merged dataset from three nationwide representative public opinion surveys in 2021, 2023, and 2025 [Dataset]. http://doi.org/10.5281/zenodo.15189012
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    pdf, binAvailable download formats
    Dataset updated
    Apr 10, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Ilko Kucheriv Democratic Initiatives Foundation; Kyiv International Institute of Sociology; Ilko Kucheriv Democratic Initiatives Foundation; Kyiv International Institute of Sociology
    License

    Open Data Commons Attribution License (ODC-By) v1.0https://www.opendatacommons.org/licenses/by/1.0/
    License information was derived automatically

    Area covered
    Ukraine
    Measurement technique
    Method(s) of data collection: Public Opinion Poll
    Description

    The dataset includes data collected from a series of public opinion surveys conducted by the Ilko Kucheriv Democratic Initiatives Foundation in cooperation with the Kyiv International Institute of Sociology in 2021, 2023, and 2025. In total, the dataset comprises three nationwide public opinion surveys with 5,132 adult respondents. The sample is representative of the adult population residing in governmentally controlled territories of Ukraine.

    The dataset contains questions regarding the External Independent Testing (EIT)/National Multisubject Test (NMT) and its role in ensuring equal access to higher education, as well as an assessment of key policy priorities in the field of education. Additionally, it includes key socio-demographic characteristics of respondents, such as gender, age, macro-region of residence, type of settlement, and financial situation.

    The question "Do you agree or disagree with the following statement: 'External Independent Testing (EIT)/National Multisubject Test (NMT) puts everyone on an equal footing?'" was formulated differently in 2021: "Do you agree or disagree with the following statement: 'Does the External Independent Testing (EIT) put everyone on an equal footing?'" This change occurred as the NMT temporarily replaced the EIT in 2022 due to the Russian full-scale invasion.

    Questions related to the assessment of key policy priorities in the field of education were included only in 2025.

    This dataset contains the original surveys data in SPSS (.sav) format in both Ukrainian and English. It has also been exported to an Excel file, and the contents of the corresponding XLSX file are identical to the original SAV file. The research methodology and questionnaire can be found in the Documentation section (PDF files) in English and Ukrainian. Changes over time in the perception of the External Independent Testing (EIT)/National Multisubject Test (NMT) as a means of ensuring equal access to higher education are illustrated in a graph in the Results section (PDF files).

  19. UK_HEIs_publications_Scopus_export

    • figshare.com
    txt
    Updated Jan 22, 2021
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    Olesya Mryglod (2021). UK_HEIs_publications_Scopus_export [Dataset]. http://doi.org/10.6084/m9.figshare.13625930.v1
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    txtAvailable download formats
    Dataset updated
    Jan 22, 2021
    Dataset provided by
    Figsharehttp://figshare.com/
    figshare
    Authors
    Olesya Mryglod
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    United Kingdom
    Description

    The list of UK Higher Education Institutions (HEIs) submitted to RAE2008 in SUbject category "Physics": names , Scopus search phrase, #of publications and total # o f citations in March 2020+Raw files exported from Scopus: publication data extracted in March 2020 for each HEI

  20. u

    UNESCO Education Statistics, 1970-2019

    • datacatalogue.ukdataservice.ac.uk
    Updated Dec 3, 2020
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    UNESCO Institute for Statistics (2020). UNESCO Education Statistics, 1970-2019 [Dataset]. http://doi.org/10.5257/unesco/edulit/2020-02
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    Dataset updated
    Dec 3, 2020
    Dataset provided by
    UK Data Servicehttps://ukdataservice.ac.uk/
    Authors
    UNESCO Institute for Statistics
    Time period covered
    Dec 31, 1969 - Jan 1, 2019
    Area covered
    Mauritius, India, Hong Kong, Dominica, Saotome, Bermuda, Turkey, Mozambique, Seychelles, European Union Countries (1993-)
    Description

    As the statistical branch of the United Nations Educational, Scientific and Cultural Organisation (UNESCO), the Institute for Statistics (UIS) produces cross-nationally comparable statistics on education, science and technology, culture, and communication for more than 200 countries and territories.

    The UNESCO Education Statistics dataset includes data from 1970 onwards. From pre-primary school enrolment to tertiary graduation rates, it covers all education levels and addresses key policy issues such as gender parity, teachers and education financing.

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Department for Education (2022). Education, health and care plans: England 2022 [Dataset]. https://www.gov.uk/government/statistics/education-health-and-care-plans-england-2022
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Education, health and care plans: England 2022

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2 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
May 12, 2022
Dataset provided by
GOV.UKhttp://gov.uk/
Authors
Department for Education
Area covered
England
Description

This publication provides data on the number of children and young people with a statement of special educational needs (SEN) or education, health and care (EHC) plan in England.

It also provides data on the administration of statements of SEN and EHC plans, including:

  • the number of EHC plans in place in January 2022
  • the number of EHC plans made for the first time during the 2021 calendar year
  • the number and percentage of EHC plans that were issued within 20 weeks

It is based on the statutory SEN2 data collection.

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