14 semi-structured interviews conducted with legal services professionals in England over the period 2019-20. Interviewees were drawn from law firms, legal technology companies, law libraries, and legal data providers. The interviews explored in what ways does a lack of appropriate educational provision currently present a barrier to (a) law firms in adopting new technologies, and (b) computer scientists in proceeding efficiently within the rule of law; and how might this need best be addressed to allow those working in these sectors to interact innovatively and efficiently?The proposed research will explore the potential and limitations of using artificial intelligence (AI) in support of legal services. AI's capabilities have made enormous recent leaps; many expect it to transform how the economy operates. In particular, activities relying on human knowledge to create value, insulated until now from mechanisation, are facing dramatic change. Amongst these are professional services, such as law. Like other professions, legal services contribute to the economy both through revenues of service providers and through benefits provided to clients. For large business clients, who can choose which legal regime will govern their affairs, UK legal services are an export good. For small businesses and citizens, working within the domestic legal system, UK legal services affect costs directly. Yet unlike other professions, the legal system has a dual role in society. Beyond the law's role in governing economic order, the legal system is more fundamentally a structure for social order. It sets out rules agreed on by society, and also the limits of politicians' ability to enact these rules. Consequently, the stakes for AI's implementation in UK legal services are high. If mishandled, it could threaten both economic success and governance more generally. Yet if executed effectively, it is an opportunity to improve legal services not only for export but also for citizens and domestic small businesses. Our research seeks to identify how constraints on the implementation of AI in legal services can be relaxed to unlock its potential for good. One major challenge is the need for 'complementary' adjustments. Adopting a disruptive new technology like AI requires changes in skills, training, and working practices, without which the productivity gains will be muted. We will investigate training and educational needs for lawyers' engagement with technology and programmers' engagement with law. With private sector partners, we will develop education and training packages that respond to these needs for delivery by both universities and private-sector firms. We will investigate emerging business models deploying AI in law, and identify best practice in governance and strategy. Finally, we will compare skills training and technology transfer in the UK with countries such as the US, Hong Kong and Singapore, and ask what UK policymakers can learn from these competitors. To the extent that these issues are also faced by other high-value professional services, these parts of our results will also have relevance for them. However, the dual role of the legal system poses unique challenges that justify a research package focusing primarily on this sector. There are constitutional limits to how far law's operation can be adjusted for economic reasons: we term this second constraint 'legitimacy'. We will map how automation in dispute resolution might trigger constitutional legal challenges, how these challenges relate to types of dispute resolution technology and types of claim, and use the resulting matrix to identify opportunities for maximum benefit from automation in dispute resolution. A third constraint is the limits of technological possibility. AI systems rely on machine learning, which reaches answers by identifying patterns in very large amounts of data. Its limitations are the size of the datasets needed, and its inability to provide an explanation for how the answer was reached. This poses particular difficulties for law, where many applications require or benefit from reasons being given. We will explore the possibility for frontier AI technologies to deliver legal reasoning. The research will involve a mix of disciplinary inputs, reflecting the multi-faceted nature of the problem: Law, Computer Science, Economics, Education, Management and Political Economy. Working closely with private-sector partners will ensure our research benefits from insights into, and testing against, real requirements. Interviews conducted primarily face-to-face with a smaller number remotely. Interviewees were sent a list of topics for discussion in advance of the interview. Interviews focused on these topics but were only semi-structured so as to permit discussion of other topics raised by the subjects.

Forecast: Total Tertiary Education Graduates in Social Sciences, Business and Law in the UK 2024 - 2028 Discover more data with ReportLinker!

A list of all independent schools and special post-16 institutions for children with special educational needs or disabilities (SEND) approved under section 41 of the Children and Families Act 2014 in England and Wales.

You can filter the list by local authority or by type of setting.

Our guide for independent special schools and special post-16 institutions explains how to apply for approval under section 41.

Voluntary removal

Contact hns.sos@education.gov.uk to request removal from the approved list, stating your reason. We will remove your institution in the next update and notify local authorities. The published list includes all removed institutions.

Once removed, you cannot re-apply for one full academic year.

Other special schools

Details of all special schools in England are available on the https://www.get-information-schools.service.gov.uk/Search">Department for Education’s Get Information about Schools system. This includes:

• maintained schools
• academies
• independent schools
• non-maintained schools

The SEND guide for parents and carers explains how parents can ask for one of these schools or special post-16 institutions to be named in their child’s education, health and care plan.

This dataset was created through an anonymous survey of solicitors in England and Wales, conducted between 12 November 2019 and 13 January 2020. Respondents answered a series of questions regarding their use of AI technology, as well as their training for and attitudes to the use of technology in their work. After discarding partial responses, the dataset comprises a total of 353 valid responses.The proposed research will explore the potential and limitations of using artificial intelligence (AI) in support of legal services. AI's capabilities have made enormous recent leaps; many expect it to transform how the economy operates. In particular, activities relying on human knowledge to create value, insulated until now from mechanisation, are facing dramatic change. Amongst these are professional services, such as law. Like other professions, legal services contribute to the economy both through revenues of service providers and through benefits provided to clients. For large business clients, who can choose which legal regime will govern their affairs, UK legal services are an export good. For small businesses and citizens, working within the domestic legal system, UK legal services affect costs directly. Yet unlike other professions, the legal system has a dual role in society. Beyond the law's role in governing economic order, the legal system is more fundamentally a structure for social order. It sets out rules agreed on by society, and also the limits of politicians' ability to enact these rules. Consequently, the stakes for AI's implementation in UK legal services are high. If mishandled, it could threaten both economic success and governance more generally. Yet if executed effectively, it is an opportunity to improve legal services not only for export but also for citizens and domestic small businesses. Our research seeks to identify how constraints on the implementation of AI in legal services can be relaxed to unlock its potential for good. One major challenge is the need for 'complementary' adjustments. Adopting a disruptive new technology like AI requires changes in skills, training, and working practices, without which the productivity gains will be muted. We will investigate training and educational needs for lawyers' engagement with technology and programmers' engagement with law. With private sector partners, we will develop education and training packages that respond to these needs for delivery by both universities and private-sector firms. We will investigate emerging business models deploying AI in law, and identify best practice in governance and strategy. Finally, we will compare skills training and technology transfer in the UK with countries such as the US, Hong Kong and Singapore, and ask what UK policymakers can learn from these competitors. To the extent that these issues are also faced by other high-value professional services, these parts of our results will also have relevance for them. However, the dual role of the legal system poses unique challenges that justify a research package focusing primarily on this sector. There are constitutional limits to how far law's operation can be adjusted for economic reasons: we term this second constraint 'legitimacy'. We will map how automation in dispute resolution might trigger constitutional legal challenges, how these challenges relate to types of dispute resolution technology and types of claim, and use the resulting matrix to identify opportunities for maximum benefit from automation in dispute resolution. A third constraint is the limits of technological possibility. AI systems rely on machine learning, which reaches answers by identifying patterns in very large amounts of data. Its limitations are the size of the datasets needed, and its inability to provide an explanation for how the answer was reached. This poses particular difficulties for law, where many applications require or benefit from reasons being given. We will explore the possibility for frontier AI technologies to deliver legal reasoning. The research will involve a mix of disciplinary inputs, reflecting the multi-faceted nature of the problem: Law, Computer Science, Economics, Education, Management and Political Economy. Working closely with private-sector partners will ensure our research benefits from insights into, and testing against, real requirements. The survey was run anonymously using the Qualtrics platform. Invitations to participate were distributed by email to 10,000 randomly-selected solicitors. In order to increase survey participation, subsequent survey invitations were sent to under-represented groups of respondents. Further details of survey methodology, participant information, and the survey questions are included in the data documentation.

Security guidance for schools, colleges, and universities to safeguard students, staff, and premises.

Comprehensive dataset containing 98 verified Law school businesses in United Kingdom with complete contact information, ratings, reviews, and location data.

The Department for Education is committed to continuous improvement in its handling of complaints about schools. The completed report covers complaints that relate to state funded schools including academies and free schools, received by the department in the period 1st August 2012 to July 2013. Prior to July 2012 some complaints about schools were handled by the Secretary of State for Education, some were handled as a pilot by the Local Government Ombudsman(LGO). The Education Act 2011 rationalised the LGO arrangements . In July 2012 the powers of the LGO to consider school complaints were repealed, so that all complainants in England could complain to the Secretary of State about a school. During the passage of the Education Act 2011, the department commissioned independent research about its handling of complaints about schools. This report covers those findings and can be located here:- https://www.gov.uk/government/publications/complaints-about-schools-customer-satisfaction-survey-2013

Forecast: Female Tertiary Education Graduates in Social Sciences, Business and Law in the UK 2024 - 2028 Discover more data with ReportLinker!

This file set is the basis of a project in which Stephanie Pywell from The Open University Law School created and evaluated some online teaching materials – Fundamentals of Law (FoLs) – to fill a gap in the knowledge of graduate entrants to the Bachelor of Laws (LLB) programme. These students are granted exemption from the Level 1 law modules, from which they would normally acquire the basic knowledge of legal principles and methods that is essential to success in higher-level study. The materials consisted of 12 sessions of learning, each covering one key topic from a Level 1 law module.The dataset includes a Word document that consists of the text of a five-question, multiple-choice Moodle poll, together with the coding for each response option.The rest of the dataset consists of spreadsheets and outputs from SPSS and Excel showing the analyses that were conducted on the cleaned and anonymised data to ascertain students' use of, and views on, the teaching materials, and to explore any statistical association between students' studying of the materials and their academic success on Level 2 law modules, W202 and W203.Students were asked to complete the Moodle poll at the end of every session of study, of which there were 1,013. Only one answer from each of the 240 respondents was retained for Questions 3, 4 and 5, to avoid skewing the data. Some data are presented as percentages of the number of sessions studied; some are presented as percentages of the number of respondents, and some are presented as percentage of the number of respondents who meet specific criteria.Student identifiers, which have been removed to ensure anonymity, are as follows: Open University Computer User code (OUCU) and Personal Identifier (PI). These were used to collate the output from the Moodle poll with students' Level 2 module results.

The dataset represents the raw data used to create the Post-Discipline Online Syllabus Database. The database explores the use of literature by schools of professional education in North America. It forms part of a larger project titled Post-Discipline: Literature, Professionalism, and the Crisis of the Humanities, led by Dr Merve Emre with the assistance of Dr Hayley G. Toth. You can find more information about the project at https://postdiscipline.english.ox.ac.uk/. Data was collected and accurate in 2021/22.

UK Parliament petition with 122,494 signatures

The Secretary of State designates these courses as eligible for tuition fee loans under the Higher Education Short Course Loans Regulations 2022. This is under the powers of The Teaching and Higher Education Act 1998, section 22.

Information for HESC learners is available.

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.

Children looked after who were adopted during the years ending 31 March by number of adopters, legal status of adopters and by gender of adopters. Data formerly in table E3.

The Department for Education is committed to continuous improvement in its handling of complaints about schools. The completed report covers complaints that relate to state funded schools including academies and free schools, received by the department in the period 1st August 2012 to July 2013. Prior to July 2012 some complaints about schools were handled by the Secretary of State for Education, some were handled as a pilot by the Local Government Ombudsman(LGO). The Education Act 2011 rationalised the LGO arrangements . In July 2012 the powers of the LGO to consider school complaints were repealed, so that all complainants in England could complain to the Secretary of State about a school. During the passage of the Education Act 2011, the department commissioned independent research about its handling of complaints about schools. This report covers those findings and can be located here:- https://www.gov.uk/government/publications/complaints-about-schools-customer-satisfaction-survey-2013

The government has continuously backed the advancement of technical and vocational education through additional funding, the formation of new qualifications called T-Levels and the apprenticeship levy. Despite continuous government funding being pumped into the industry, revenue has still been squeezed in recent years due to unstable demand for apprenticeship starts, according to data from the DfE. Over the five years through 2024-25, industry revenue is estimated to fall at a compound annual rate of 0.8% to reach £936 million. The launch of the Apprenticeship Levy in April 2017 was expected to fund three million apprenticeships by 2020, but apprenticeship starts have been declining since 2017-18. Low unemployment because of the vast availability of jobs reduced the need for people to re- or up-skill to find work. The COVID-19 outbreak resulted in plunging apprenticeship starts in 2020-21 because of businesses’ tightened corporate training budgets and falling disposable income reduced the number that could afford pricier courses. Many apprentices were unable to complete programmes, which prevented companies from receiving government funding. As a result, revenue contracted over 2020-21, but has recovered in the three years through 2024-25. The rollout of T-Levels since 2020 has been driven by the UK’s desire to improve individuals’ technical skills and to reduce the number of individuals going to university and not securing jobs that require a degree. They have faced some criticism due to several subject pathways being pushed back or removed like beauty and hairdressing, high drop-out rates and poor quality standards of placements. Still, the government backed a 10% increase to the funding rates for T Levels for 2024-25. However, the new Labour government in July 2024 launched a review into the retraction of funding from other qualifications like BTecs that had been due to take place, deciding that 157 courses will continue until at least July 2026 or 2027. Revenue is forecast to grow by 2% in 2024-25 as demand for digital skills in the workplace and therefore technology-related apprenticeships rises. The prioritisation of vocational education has led to enhanced support for vocational and technical apprenticeships. The bumpy roll out of T Level courses will create some uncertainty for the sector, while the impact of reforming the apprenticeship levy won't be clear for a while. Moreover, the number of people aged between 16 and 25 is forecast to rise, which will support industry demand, as this age group represents the industry’s main demographic. Industry revenue is forecast to grow at a compound annual rate of 1.8% over the five years through 2029-30 to reach £1 billion.

Data on the top universities for Law in 2025.