16 datasets found
  1. Pupil absence in schools in England: autumn 2022 and spring 2023

    • gov.uk
    Updated Oct 19, 2023
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    Department for Education (2023). Pupil absence in schools in England: autumn 2022 and spring 2023 [Dataset]. https://www.gov.uk/government/statistics/pupil-absence-in-schools-in-england-autumn-2022-and-spring-2023
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    Dataset updated
    Oct 19, 2023
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Education
    Area covered
    England
    Description

    Absence statistics relating to the autumn and spring terms.

    It provides information on the levels of overall, authorised and unauthorised absence in:

    • state-funded primary schools
    • state-funded secondary schools
    • state-funded special schools
    • pupil referral units

    It includes information on absence rates, persistent absence and pupils not attending in circumstances related to COVID-19. The release uses pupil-level absence data that we collect in the school census.

  2. Pupil absence in schools in England: autumn 2023 and spring 2024

    • gov.uk
    Updated Oct 17, 2024
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    Department for Education (2024). Pupil absence in schools in England: autumn 2023 and spring 2024 [Dataset]. https://www.gov.uk/government/statistics/pupil-absence-in-schools-in-england-autumn-2023-and-spring-2024
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    Dataset updated
    Oct 17, 2024
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Education
    Area covered
    England
    Description

    Absence statistics relating to the autumn term 2023 and spring term 2024.

    This release provides information on the levels of overall, authorised and unauthorised absence in state-funded:

    • primary schools
    • secondary schools
    • special schools

    It includes:

    • reasons for absence
    • absence by pupil characteristic
    • rates of persistent and severe absence

    We have presented information separately on absence levels in state funded alternative provision, including pupil referral units.

    The release uses pupil-level absence data that we collect in the school census.

  3. g

    Number of students 16-64 years of age by region of the of educational...

    • gimi9.com
    Updated Oct 12, 2021
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    (2021). Number of students 16-64 years of age by region of the of educational institution, sex, type of studies the autumn term and the location of the educational institution in relation to the municipality of residence. Year 1999 - 2023 | gimi9.com [Dataset]. https://gimi9.com/dataset/eu_https-statistikdatabasen-scb-se-dataset-tab3734
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    Dataset updated
    Oct 12, 2021
    License

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

    Description

    Participation in education of the adult population, number by region, sex, type of studies, place of school in relation to municipality of residence and year

  4. e

    Population 16-64 years of age by residencial region, sex, age, type of...

    • data.europa.eu
    json
    Updated Jul 14, 2025
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    Statistikmyndigheten SCB - Statistiska centralbyrån (2025). Population 16-64 years of age by residencial region, sex, age, type of studies the autumn term. Year 1993 - 2023 [Dataset]. https://data.europa.eu/data/datasets/https-statistikdatabasen-scb-se-dataset-tab3732~~1?locale=en
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    jsonAvailable download formats
    Dataset updated
    Jul 14, 2025
    Dataset authored and provided by
    Statistikmyndigheten SCB - Statistiska centralbyrån
    License

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

    Description

    Participation in education of the adult population, number by region, sex, age, type of studies and year

  5. Area SEND inspections and outcomes in England: management information autumn...

    • gov.uk
    Updated May 25, 2023
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    Ofsted (2023). Area SEND inspections and outcomes in England: management information autumn term 2022 to 2023 [Dataset]. https://www.gov.uk/government/statistical-data-sets/area-send-inspections-and-outcomes-in-england-management-information-autumn-term-2022-to-2023
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    Dataset updated
    May 25, 2023
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Ofsted
    Area covered
    England
    Description

    Management information for area SEND, showing inspection and re-visit outcomes for autumn term in 2022 to 2023 academic year and all inspection and re-visit outcomes up to 31 December 2022.

    These figures are not official statistics.

    https://assets.publishing.service.gov.uk/media/646cbde0382a5100139fc5d0/Management_information_area_SEND_-_as_at_31_December_2022.ods">Area SEND inspections and outcomes in England: management information autumn term 2022 to 2023

    ODS, 51.9 KB

    This file is in an OpenDocument format

  6. d

    Woody phenology and weather data related to Trelease Woods, Urbana, IL, USA...

    • search.dataone.org
    • data.niaid.nih.gov
    • +1more
    Updated Aug 1, 2025
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    Carol Augspurger; David Zaya (2025). Woody phenology and weather data related to Trelease Woods, Urbana, IL, USA 1993-2023 [Dataset]. http://doi.org/10.5061/dryad.3j9kd51p1
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    Dataset updated
    Aug 1, 2025
    Dataset provided by
    Dryad Digital Repository
    Authors
    Carol Augspurger; David Zaya
    Time period covered
    Jan 1, 2022
    Area covered
    Urbana, Illinois
    Description

    In this study, weekly phenological observations throughout spring and autumn were made annually over 30 years for 22 woody plant taxa of multiple growth forms in Trelease Woods, a mature old-growth deciduous forest remnant near Urbana, Illinois, USA. The growth forms included canopy trees, saplings, sub canopy treelets, shrubs, and vines. Data collection began in the spring of 1993 and continued through the end of autumn 2023. The phenological data set is paired with weather data collected from a nearby weather station in Champaign, Illinois. These two data sets were used to determine if dates of phenological events and durations of phenophases were changing over time, possibly in connection with changing weather related to global climate change. To supplement these phenological data, two older phenological data sets are made available here. First, Charles Smith, Woods Custodian at the University of Illinois, made comparable observations from 1949 to 1964 of seven of the same phenologic..., Field observations of spring phenology of mature individuals of 22 woody taxa (21 species and 1 genus which may have represented multiple species) were made in Trelease Woods, Champaign Co., Illinois, USA from 1993-2023. Also, observations were made of saplings of three of the canopy tree species. The study site is the north half of a 24.5 ha fragment of temperate mature deciduous forest, dominated by sugar maple near Urbana, Illinois, USA. Â Elevation varies by less than 5 m across the study area. The phenological status of each individual was recorded by the same observer (CKA) weekly from February to June of each year. Measurements were recorded and later analyzed, at the individual plant level. Within each of three vegetative phases, Bud Swell (BS), Bud Burst (BB), and Leaf Expansion (LE), three dates were noted (e.g., BS1 (1/3 of units exhibit event), BS2 (2/3 completed event), BS3 (all completed event), each date being one event; see Appendix S1: Table S1 for event summaries); the ..., , # Woody Phenology and Weather Data related to Trelease Woods, Urbana, IL, USA 1993-2023

    Authors

    Carol K. Augspurger, Department of Plant Biology, University of Illinois Urbana-Champaign, carolaug@illinois.edu

    David N. Zaya, Illinois Natural History Survey, University of Illinois Urbana-Champaign, dzaya1@illinois.edu

    References

    Augspurger, C. K. and D. N. Zaya. 2020a. Concordance of long-term shifts with climate warming varies among phenological events and herbaceous species. Dryad. Dataset. https://doi.org/10.5061/dryad.mcvdncjxh

    Augspurger, C. K. and D. N. Zaya. 2020b. Concordance of long-term shifts with climate warming varies among phenological events and herbaceous species. Ecological Monographs 90: e01421.

    Hopkins, A. D. 1920a. The Bioclimatic Law. Journal of the Washington Academy of Sciences 10:34–40.

    Hopkins, A. D. 1920b. The Bioclimatic Law. Monthly Weather...

  7. Is AI the New Plato?: AI Benefits and Drawbacks for Study Survey - Autumn...

    • figshare.com
    pdf
    Updated Dec 16, 2023
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    Edward A. S. Ross; Jackie Baines (2023). Is AI the New Plato?: AI Benefits and Drawbacks for Study Survey - Autumn 2023 [Dataset]. http://doi.org/10.6084/m9.figshare.24842058.v2
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    pdfAvailable download formats
    Dataset updated
    Dec 16, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Edward A. S. Ross; Jackie Baines
    License

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

    Description

    These surveys were collected during general AI ethics tutorials with students in the Classics and Modern Languages Departments at the University of Reading over the 2023 Autumn Term. The results of these surveys was used to support findings related to the effects of AI education on student opinion and usage of generative AI tools.This project, "ChatGPT: A Conversational Language Study Tool", has been reviewed by the University of Reading University Research Ethics Committee and has been given a favourable ethical opinion for conduct.

  8. Anatomy lecture learning modality exam performance

    • data.niaid.nih.gov
    • datadryad.org
    zip
    Updated Nov 5, 2024
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    Kristin Stover; Sarah Beam; Richard Thompson (2024). Anatomy lecture learning modality exam performance [Dataset]. http://doi.org/10.5061/dryad.2rbnzs7zn
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    zipAvailable download formats
    Dataset updated
    Nov 5, 2024
    Dataset provided by
    The Ohio State University
    University of Alaska System
    Authors
    Kristin Stover; Sarah Beam; Richard Thompson
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Description

    We investigated the effect of three different lecture delivery modalities in a foundational anatomy course on student exam performance, including: (1) asynchronous recordings, (2) passive lecture with a student’s choice to view synchronously or asynchronously, and (3) active lecturing, again with student’s viewing choice. Active lectures incorporated gapped lecturing, drawing, practice questions, and active study technique suggestions. We compared four-unit exams that were similar across the four semesters investigated. This data set has been de-identified. Methods Data was gathered across four semesters and represents individual student exam scores. The sample population included all students enrolled in Anatomy 2300 and was a non-random sampling approach based on their participation within the course of Human Anatomy at The Ohio State University – Columbus Campus during the Autumn 2021 (n = 512), Spring 2022 (n = 612), Autumn 2022 (n = 656), and Spring 2023 (n = 695) semesters, resulting in a total sample size of 2,543 students. A post hoc power analysis was conducted using G*Power, yielding a power of 0.99, larger than the recommended power of 0.8 for statistical analyses. The margin of error was 0.03, and the correlation between measures was 0.76. The sample size required to achieve this power calculation was 1511.11. Each semester, four in-person proctored unit exams were given via Carmen, OSU’s Canvas Learning Management System (Instructure Inc., Salt Lake City, UT), with a lockdown browser, to evaluate the progress of the student. Exam questions were subject to minimal changes between different semesters, with the questions covering the same content and learning objectives each semester. Questions were mapped directly to lecture objectives with even distribution among the lectures within the unit and checked by the course director and lecture teaching assistant. Each question and bank were validated by the course director, lecture teaching assistant and at least one graduate teaching assistant. Questions included multiple choice first and second order questions, as well as matching and identification questions. All questions had answer options, there were no fill in the blanks. Many questions were banked so that a student would receive a random question out of two to six options covering the same lecture objective. Exam statistics were reviewed after each exam. If the discrimination index, which divides students into three groups based on their score on the whole quiz and displays those groups by who answered the question correctly, as calculated by Canvas, was less than 0.2 and less than 50 percent of the class answered correctly, everyone was given credit, and the question was re-written for the following semester. This was done for an average of one out of 50 questions on each unit exam. All exam scores were de-identified and assigned a record code to match each piece of data to their individual records. The Anatomy 2300 students come from Health Science, University Exploration, Arts and Sciences, Dental Hygiene, Pre-Nursing, Health and Rehabilitation Sciences, Pre-Optometry, Pre-Pharmacy, Pre-Dental and Exercise Science programs. All students were enrolled together into an in-person 55-minute lecture every Monday, Wednesday, and Friday. Pre-recorded lectures were used during the Autumn 2021 semester (Semester 1 in Table 1, Figure 2). During the Spring 2022 (Semester 2), Autumn 2022 (Semester 3), and Spring 2023 (Semester 4) semesters, these lectures were conducted via a Zoom webinar and were also recorded and posted online for students to review at their leisure.

  9. Pupil attendance in schools

    • gov.uk
    Updated Aug 7, 2025
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    Department for Education (2025). Pupil attendance in schools [Dataset]. https://www.gov.uk/government/statistics/pupil-attendance-in-schools
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    Dataset updated
    Aug 7, 2025
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Education
    Description

    This publication provides information on the levels of overall, authorised and unauthorised absence in state-funded:

    • primary schools
    • secondary schools
    • special schools

    State-funded schools receive funding through their local authority or direct from the government.

    It includes daily, weekly and year-to-date information on attendance and absence, in addition to reasons for absence. The release uses regular data automatically submitted to the Department for Education by participating schools.

    The attached page includes links to attendance statistics published since September 2022.

  10. Number of students at universities Germany 2023/2024, by federal state

    • statista.com
    Updated Jan 13, 2025
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    Statista (2025). Number of students at universities Germany 2023/2024, by federal state [Dataset]. https://www.statista.com/statistics/1114719/students-number-universities-by-federal-state-germany/
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    Dataset updated
    Jan 13, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Germany
    Description

    In the winter semester of 2023/2024, which starts in the autumn, there were 405,492 students enrolled in Bavarian universities. North Rhine-Westphalia boasted the highest university student numbers among German federal states, with approximately 717,963 students.

  11. f

    University of Reading Classical Languages Teaching Content and Expectations...

    • figshare.com
    pdf
    Updated Dec 16, 2023
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    Edward A. S. Ross; Jackie Baines (2023). University of Reading Classical Languages Teaching Content and Expectations Survey - Summer 2023 [Dataset]. http://doi.org/10.6084/m9.figshare.24829953.v2
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Dec 16, 2023
    Dataset provided by
    figshare
    Authors
    Edward A. S. Ross; Jackie Baines
    License

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

    Description

    This survey was a pilot study to gather opinions about AI from teaching staff in the Classics Department at the University of Reading. The results of this survey were used to develop the department's AI policy and citation guide for the 2023 Autumn Term.This project, "ChatGPT: A Conversational Language Study Tool", has been reviewed by the University of Reading University Research Ethics Committee and has been given a favourable ethical opinion for conduct.

  12. EVA Survey on Finnish Values and Attitudes Autumn 2023

    • services.fsd.tuni.fi
    zip
    Updated May 15, 2025
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    Finnish Business and Policy Forum (EVA) (2025). EVA Survey on Finnish Values and Attitudes Autumn 2023 [Dataset]. http://doi.org/10.60686/t-fsd3827
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    zipAvailable download formats
    Dataset updated
    May 15, 2025
    Dataset provided by
    Finnish Social Science Data Archive
    Authors
    Finnish Business and Policy Forum (EVA)
    Area covered
    Finland
    Description

    The study charted Finnish people's values and attitudes. The themes of the Autumn 2023 survey included politics in Finland, the reform of labour market legislation, racism, security and threats, international politics, presidential powers and role, and the future of Ukraine. First, the respondents were presented with attitudinal statements concerning a variety of social topics, such as politics, the labour market, entrepreneurship, Finland's foreign relations, hate speech, presidential powers and Finland's NATO membership. Next, the respondents' views on politics and politicians in Finland were examined with a series of attitudinal statements (e.g. 'Power is concentrated in too few hands, small circle of true decision-makers”, 'Listen carefully to citizens' opinions and carry out the will of the people”). The respondents' opinions on the reformation of labour legislation were surveyed by asking whether various labour market issues (e.g. political strikes, use of fixed-term contracts) should be regulated more loosely or strictly in the future or whether the legislation should remain the same as at present. The respondents' perception of their household's financial situation and their outlook on their own futures were also charted. On the topic of racism, the respondents were asked how big of an issue they considered racism to be in Finnish society, how racism they thought Finland was at the moment, how important it was to them that racism was not tolerated in Finland, and to what degree they found certain behaviours and actions to be racist (e.g. discrimination based on ethnic background, overlooking the job application of a person due to a name which indicates a minority ethnicity background, humour and entertainment involving ethnic, cultural, linguistic or religious minorities). Additionally, the respondents were asked how concerned they were about certain security threats (e.g. a military attack on Finland, a global economic crisis, efforts to destabilise Finnish society by hybrid influencing, violence by political extremist groups). Views on the powers, policies and roles of the Finnish President were investigated. Opinions on presidential power were surveyed by asking the respondents how much power the president should have in areas such as foreign and security policy, EU affairs, national defence, economic policy, labour market issues, and social and health policy. The respondents were also asked how suitable different roles (e.g. 'moral leader, who raises public debate on important issues and uses their authority to promote them”, 'international relations professional, who has an in-depth understanding of international politics and focuses on them”, 'a strong commander-in-chief, who is familiar with the armed forces and capable of making military decisions”) were for next the President of Finland in their opinion. The respondents' views were charted on what model of separation of powers between the government and the President was appropriate for Finland. The respondents were asked about their views on several influential countries in world politics (e.g. China, Russia, USA, the UK, Germany, Japan). The respondents' views on Russia, China and USA were surveyed with a more detailed series of statements that charted, for example, whether the countries were important trading partners or major military threats. Views on the Russian invasion of Ukraine and the ongoing war were also investigated with a series of statements (e.g. 'The threat of the war spreading to other countries is receding”, 'Ukraine will retake all the territories captured by Russia, including the Crimean Peninsula”, 'Nuclear weapons will not be deployed”). Finally, opinions were charted on Finland's NATO membership, Finland's EU membership and the currency change to euro. Background variables included the respondent's gender, age group, number of inhabitants in the municipality of residence, region (NUTS3), type of employer, working hours, type of employment contract, education, economic activity and occupational status, employment sector, trade union membership, what political party R would vote for in parliamentary elections, self-perceived social class, mother tongue and annual gross income of the R's household.

  13. Study of Teachers' Work-Related Well-Being

    • zenodo.org
    Updated May 21, 2025
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    Lauri Hietajärvi; Lauri Hietajärvi; Olli-Pekka Heinimäki; Olli-Pekka Heinimäki; Katariina Salmela-aro; Katariina Salmela-aro (2025). Study of Teachers' Work-Related Well-Being [Dataset]. http://doi.org/10.5281/zenodo.14801687
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    Dataset updated
    May 21, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Lauri Hietajärvi; Lauri Hietajärvi; Olli-Pekka Heinimäki; Olli-Pekka Heinimäki; Katariina Salmela-aro; Katariina Salmela-aro
    License

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

    Description

    NOTE: Version 2 provides the updated numbers for this data set.

    The primary aim of this research project is to study teachers’ work-related well-being in Finland, and its relationship with various work-related demands and resources. Study of teachers' work-related well-being in Finland has been conducted from 2020 onwards. An online questionnaire distributed biannually enables a comprehensive examination of teachers’ well-being across different regional and educational contexts. Beginning 2024, the study expands to include longitudinal research.

    Since 2020, an online questionnaire has been distributed biannually to OAJ (the Trade Union of Education in Finland) members towards the end of each spring and autumn semester. The respondents include teachers from all across Finland, representing a wide range of educational levels. This broad data collection enables a comprehensive examination of teachers’ well-being across different regional and educational contexts.

    Initially, responses were collected anonymously, enabling the tracking of well-being trends over time. Beginning in Spring 2024, the study expanded to include the collection of contact information from consenting participants, setting the stage for future longitudinal research.

    Data was collected between 2020–2024 as follows:

    • Spring 2020: 1 182 participants.
    • Autumn 2020: 1 502 participants
    • Spring 2021: 1 336 participants.
    • Autumn 2021: 1 046 participants.
    • Spring 2022: 476 participants.
    • Autumn 2022: 687 participants
    • Spring 2023: 1 628 participants.
    • Autumn 2023: 1 396 participants.
    • Spring 2024: 1 182 participants.

    Information about the data set can be found at: https://www.helsinki.fi/en/researchgroups/motivation-learning-and-well-being-in-digital-era/study-of-teachers-work-related-well-being

    This research is conducted by the University of Helsinki in collaboration with the Trade Union of Education in Finland (OAJ).

    The study is led by Academy Professor Katariina Salmela-Aro (katariina.salmela-aro@helsinki.fi). For inquiries, please contact University Lecturer Lauri Hietajärvi (lauri.hietajarvi@helsinki.fi) or Postdoctoral Researcher Olli-Pekka Heinimäki (olli-pekka.heinimaki@helsinki.fi).

    This research has been funded by the Strategic Research Council as part of the EduRESCUE research project and by the Academy of Finland for the EDUCA research flagship.

  14. Coronavirus (COVID-19) data on funding claims by institutions

    • gov.uk
    • s3.amazonaws.com
    Updated Jul 3, 2025
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    Education and Skills Funding Agency (2025). Coronavirus (COVID-19) data on funding claims by institutions [Dataset]. https://www.gov.uk/government/publications/coronavirus-covid-19-data-on-funding-claims-by-institutions
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    Dataset updated
    Jul 3, 2025
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Education and Skills Funding Agency
    Description

    The Education and Skills Funding Agency (ESFA) closed on 31 March 2025. All activity has moved to the Department for Education (DfE). You should continue to follow this guidance.

    This page outlines payments made to institutions for claims they have made to ESFA for various grants. These include, but are not exclusively, COVID-19 support grants. Information on funding for grants based on allocations will be on the specific page for the grant.

    Claim-based grants included

    Senior mental health lead training

    Financial assistance towards the cost of training a senior member of school or college staff in mental health and wellbeing in the 2021 to 2022, 2022 to 2023, 2023 to 2024 and 2024 to 2025 financial years. The information provided is for payments up to the end of March 2025.

    COVID-19 16 to 19 tuition fund 2020 to 2021 and 2021 to 2022

    Funding for eligible 16 to 19 institutions to deliver small group and/or one-to-one tuition for disadvantaged students and those with low prior attainment to help support education recovery from the COVID-19 pandemic.

    Due to continued pandemic disruption during academic year 2020 to 2021 some institutions carried over funding from academic year 2020 to 2021 to 2021 to 2022.

    Therefore, any considerations of spend or spend against funding allocations should be considered across both years.

    School funding: exceptional costs associated with coronavirus (COVID-19)

    Financial assistance available to schools to cover increased premises, free school meals and additional cleaning-related costs associated with keeping schools open over the Easter and summer holidays in 2020, during the coronavirus (COVID-19) pandemic.

    Coronavirus (COVID-19) free school meals: additional costs

    Financial assistance available to meet the additional cost of the provision of free school meals to pupils and students where they were at home during term time, for the period January 2021 to March 2021.

    Alternative provision: year 11 transition funding

    Financial assistance for alternative provision settings to provide additional transition support into post-16 destinations for year 11 pupils from June 2020 until the end of the autumn term (December 2020). This has now been updated to include funding for support provided by alternative provision settings from May 2021 to the end of February 2022.

    Coronavirus (COVID-19) 2021 qualifications fund for schools and colleges

    Financial assistance for schools, colleges and other exam centres to run exams and assessments during the period October 2020 to March 2021 (or for functional skills qualifications, October 2020 to December 2020). Now updated to include claims for eligible costs under the 2021 qualifications fund for the period October 2021 to March 2022.

    <a href="https://www.gov.uk/guidan

  15. DESNZ Public Attitudes Tracker: Spring 2024

    • gov.uk
    Updated Jul 3, 2024
    + more versions
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    Department for Energy Security and Net Zero (2024). DESNZ Public Attitudes Tracker: Spring 2024 [Dataset]. https://www.gov.uk/government/statistics/desnz-public-attitudes-tracker-spring-2024
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    Dataset updated
    Jul 3, 2024
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Energy Security and Net Zero
    Description

    The DESNZ Public Attitudes Tracker is a nationally representative annual survey of adults (aged 16+) in the UK that tracks public awareness, attitudes and behaviours relating to the policies of the Department for Energy Security and Net Zero (DESNZ), such as energy and climate change.

    This report provides a summary of the headline findings from the Spring 2024 wave of the Tracker, which ran from 18 March to 22 April 2024.

    The Spring 2024 wave is the tenth wave in a series of surveys which began in autumn 2021. Between Autumn 2021 and Summer 2023, surveys were conducted every quarter, although there was no wave in Autumn 2023. From Spring 2024, the survey moved to a triannual design with waves conducted every spring, summer and winter.

    Headline findings for Spring 2024

    Two summary self-reported measures are used in this report:

    • ‘awareness’ encompasses all respondents who said they had heard of a particular concept or technology, including those who said ‘hardly anything but I’ve heard of this’, ‘a little’, ‘a fair amount’ or ‘a lot’
    • ‘knowledge’ encompasses those who said that they know ‘a fair amount’ or ‘a lot’

    Net Zero and climate change

    • There has been a small increase in awareness of the concept of Net Zero: 91% of people said they had heard of the concept compared to 89% in Winter 2023. The level of knowledge also increased over this period from 50% to 53%.
    • Unchanged from Winter 2023, 80% of people said they were very or fairly concerned about climate change, with 37% very concerned. However, there has been a gradual decline in levels of concern over time from Autumn 2021 when 85% were concerned.

    Renewable energy

    • At 84%, overall support for renewable energy has increased slightly since Winter 2023 (82%) but remains below the peak (since tracking began) of 88% in Autumn 2022. Overall opposition remained very low at 2%.
    • While overall support for renewable energy was high, support varied for specific types of renewable energy developments. Support remained highest for solar (88% supported overall), followed by wave and tidal (83%) and off-shore wind (83%). Slightly lower levels of support were reported for onshore wind (77%) and biomass (70%).
    • Attitudes to renewable energy remained largely consistent with Spring 2022 and 2023: 74% agreed that renewable energy developments provide economic benefits to the UK, and 82% agreed that it is important for renewable energy developments to directly benefit local communities in which they are located.
    • Consistent with previous years, 43% of people were happy for an onshore wind farm to be constructed in their local area, with 13% not happy and 28% offering no opinion either way. Objection to a local wind farm was highest in the East of England (19%), the South East (17%), and in rural areas (20% compared with 12% in urban areas).
    • More than half of people were accepting of local solar panel farms: 53% of people would be happy for this, 9% unhappy, and 27% offered no opinion either way. Objection to solar panel farms was higher in the East Midlands (17%), East of England (16%), and in rural areas (17% compared with 7% in urban areas).
    • The main reasons for being happy about the development of local onshore wind and solar panel farms were that they would ‘provide sustainable power provision’ (wind: 77%, solar: 79%), and are ‘important for reducing emissions’ (wind: 68%, solar: 67%). The main reasons for being unhappy included concerns about the ‘impact on plant and animal life’ (wind: 56%, solar: 57%) and ‘impacts on appearance and views’ (wind: 64%, solar: 51%).

    Energy infrastructure and energy security

    • Awareness of fusion energy has remained unchanged from Spring 2023 at 67%, while knowledge has increased to 20% from 18%. Both measures have increased over the longer period since tracking began in autumn 2021 (62% awareness, 15% knowledge).
    • There has been a decline in awareness of small modular reactors (43%, down from 51% in Autumn 2022) with a similar decline in knowledge (9%, down from 12%).
    • Twice as many people opposed (41%) than supported (21%) the construction of a nuclear power station in their local area; this question was asked for the first time in Spring 2024. The primary reason for opposition was fear over safety and security (80% of all who objected to this).
    • Awareness of hydrogen currently being used as a fuel in some industrial processes had increased between Spring 2022 and Spring 2024 from 75% to 80%, with a similar longer-term rise in awareness of the potential future uses of hydrogen (from 73% to 78%).
    • Awareness (69%) and

  16. w

    GDP deflators at market prices, and money GDP October 2024 (Autumn Budget...

    • gov.uk
    Updated Oct 31, 2024
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    HM Treasury (2024). GDP deflators at market prices, and money GDP October 2024 (Autumn Budget 2024) [Dataset]. https://www.gov.uk/government/statistics/gdp-deflators-at-market-prices-and-money-gdp-october-2024-autumn-budget-2024
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    Dataset updated
    Oct 31, 2024
    Dataset provided by
    GOV.UK
    Authors
    HM Treasury
    Description

    A series for the GDP deflator in index form is produced by the Treasury from data provided by the Office for National Statistics (ONS) and the Office for Budget Responsibility (OBR). GDP deflator outturn are based on the ONS Quarterly National Accounts release (at the end of each quarter). However, a more recent version of ONS GDP outturn may be used depending on when the OBR updates its GDP deflator forecasts (usually at Budget and Autumn Statement).

    Forecasts covering periods 2024-25 to 2029-30 (2024 to 2029) are from the OBR as at the Autumn Budget 30 October 2024.

    Outturn data covering the years 1955-56 to 2023-24 (1955 to 2023) are based on the Quarterly National Accounts, 30 September 2024.

    GDP deflators for financial years 1955-56 to 2023-24 have been taken directly from ONS series L8GG. GDP deflators for calendar years 1955 to 2023 have been taken from ONS series MNF2. Non-seasonally adjusted money GDP for calendar and financial years are taken from ONS series BKTL. For financial years only, seasonally adjusted money GDP series YBHA has also been included.

    The next GDP deflator update will be after the ONS Quarterly National Accounts release of 23 December 2024.

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Department for Education (2023). Pupil absence in schools in England: autumn 2022 and spring 2023 [Dataset]. https://www.gov.uk/government/statistics/pupil-absence-in-schools-in-england-autumn-2022-and-spring-2023
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Pupil absence in schools in England: autumn 2022 and spring 2023

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Dataset updated
Oct 19, 2023
Dataset provided by
GOV.UKhttp://gov.uk/
Authors
Department for Education
Area covered
England
Description

Absence statistics relating to the autumn and spring terms.

It provides information on the levels of overall, authorised and unauthorised absence in:

  • state-funded primary schools
  • state-funded secondary schools
  • state-funded special schools
  • pupil referral units

It includes information on absence rates, persistent absence and pupils not attending in circumstances related to COVID-19. The release uses pupil-level absence data that we collect in the school census.

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