United Kingdom UK: School Enrollment: Secondary: Private: % of Total Secondary data was reported at 70.828 % in 2015. This records an increase from the previous number of 69.494 % for 2014. United Kingdom UK: School Enrollment: Secondary: Private: % of Total Secondary data is updated yearly, averaging 27.445 % from Dec 1999 (Median) to 2015, with 17 observations. The data reached an all-time high of 70.828 % in 2015 and a record low of 24.869 % in 2007. United Kingdom UK: School Enrollment: Secondary: Private: % of Total Secondary data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Education Statistics. Private enrollment refers to pupils or students enrolled in institutions that are not operated by a public authority but controlled and managed, whether for profit or not, by a private body such as a nongovernmental organization, religious body, special interest group, foundation or business enterprise.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

School locations in Nottinghamshire. This data only includes publicly accessible schools and academies, and does not contain independent (private) schools.

The number of schools in an LEA by school type (whether state maintained, nursery, primary, secondary, private, special school etc.) Source: Department for Children Schools and Families (DCSF) Publisher: Department for Children Schools and Families (DCSF) Geographies: County/Unitary Authority, Government Office Region (GOR), National Geographic coverage: England Time coverage: 2006, 2007 Type of data: Administrative data

Price quote data (for locally collected data only) and consumption segment indices that underpin consumer price inflation statistics, giving users access to the detailed data that are used in the construction of the UK’s inflation figures. The data are being made available for research purposes only and are not an accredited official statistic. From October 2024, private school fees and part-time education classes have been included in the consumption segment indices file. For more information on the introduction of consumption segments, please see the Consumer Prices Indices Technical Manual, 2019. Note that this dataset was previously called the consumer price inflation item indices and price quotes dataset.

Semi-structured interviews with 91 young women aged between 14-18 years (with 56 interviewed twice) - total of 147 interviews. Interviews were undertaken in 4 different independent / private schools in one area of England - School A, B, C and D.A three-year, longitudinal study was conducted in four private schools in England. The aim of the research was to examine how social location, measured in terms of social class and being educated in the private sector, shapes possibilities for agentic practice among young women. Ninety-one young women aged 14-18 years were interviewed, with 56 being re-interviewed 12-24 months later. The study facilitated the collection of narratives by young women about their experiences of education, peer and family.relationships, and their aspirations for the future. Young women from Years 10-13 were invited to participate in an in-depth interview with the Principal Investigator - using a quiet space within the school grounds. A loosely-structured interview schedule was used for both interviews. The first interview (with 91 young women) asked young women to describe themselves and their families, explored reasons for choosing the particular school they were at, describing some experiences/moments/events where they felt good about themselves/proud of themselves and other events/experiences when they have felt less good in the past 6-12 months. Participants were also asked to discuss their future aspirations (short-, medium, and longer-term). During the second interview (with 56 of the 91 young women) - they were asked to reflect on the 12-24 months since they had last been interviewed and to comment on positive and negatives changes, elements of their lives they felt confident about and less confident about, their future aspirations and their reflections on their schooling experiences. All interviews were audio-recorded with permission and then transcribed and anonymised by the same professional transcriber.

The data contain information on 837 low-cost for-profit private schools (LCPS) from three districts in Punjab, Pakistan: Faisalabad, Gujranwala, and Sialkot. The past few decades have seen an exponential increase in the growth of these LCPS globally, and in countries like Pakistan and India, the private sector now commands a large and quickly increasing share of the market. Over forty percent of primary school enrolment in Pakistan is now in LCPS, and students in private schools in Pakistan far out-perform those in public schools. Yet, firm innovation and expansion is constrained for private schools, likely due to a range of supply-side and market level failures. The main research questions this study and the uploaded dataset seek to answer are: (1) To what extent are schools constrained by finance, and does the type of financing vehicle (loan vs equity) matter? (2) Is LCPS quality improvement constrained by a lack of access to appropriate quality-enhancing products and services, i.e. educational support services (ESS)? (3) Is there a positive interaction between access to finance and the provision of appropriate innovative investment opportunities? The dataset includes topics such as school administration, facilities, fees, enrolment, student population, finances, and financial expectations and literacy. Schools are uniquely identified using the variables mauza (administrative district) code and school code. While most of the variables are school-level, there are a few individual-level data pieces that were collected from the school owner. For each school we interviewed only one owner, therefore both schools and school owners are identified using the same mauza code and school code ID.

Number of three and four year olds taking up early education sessions in private, voluntary and independent nursery and primary schools Source: Department for Education and Skills (DfES), Learning and Skills Council (LSC). Publisher: Department for Children Schools and Families (DCSF) Geographies: County/Unitary Authority, Government Office Region (GOR), National Geographic coverage: England Time coverage: 2005 Type of data: Administrative data

Results of the annual Independent School Census. Includes pupil numbers by stage and figures for additional support needs. Also includes teacher statistics. Source agency: Scottish Government Designation: National Statistics Language: English Alternative title: Independent School Census

This census is a statutory annual collection of data from independent schools and covers approximately 2,400 registered schools. It takes place every year in January. The purpose of the collection is three-fold: it collects data needed for the Department's function as regulator of independent schools; it collects statistical data needed for purposes such as pupil projections; and it collects data on qualification aims. No data relating to individual pupils is collected but data relating to individual staff and members of proprietor bodies is collected.

Abstract copyright UK Data Service and data collection copyright owner.Understanding Society (the UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex, and the survey research organisations Kantar Public and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991. The Understanding Society COVID-19 Study is a regular survey of households in the UK. The aim of the study is to enable research on the socio-economic and health consequences of the COVID-19 pandemic, in the short and long term. The surveys started in April 2020 and took place monthly until July 2020. From September 2020 they take place every other month. They complement the annual interviews in the Understanding Society study.This dataset contains school code variables for the Understanding Society COVID-19 study (SN 8644).A file is provided for the fifth web wave of the Understanding Society COVID-19 study, the only one that school information has currently been gathered for. For each child it contains: state school code, country of state school, private school name and private school town variables for both mother and father responses. A child personal identification serial number (pidp_c) is also provided for matching to the main data in SN 8644.In addition, this dataset contains a file of school code variables that can be matched to a dataset released with the main Understanding Society COVID-19 study containing data taken from waves 10 and 11 of the main Understanding Society survey specifically for the respondents in the Understanding Society COVID-19 study. Child school codes are only available for Wave 11 as they are only collected in odd-numbered waves. For each child it contains the state school code and country of state school variables as well as a personal identification serial number (pidp) and a household identification serial number for wave 11 (jk_hidp). Further details on the files in this dataset can be found in the Understanding Society COVID-19 User Guide.Additional information can be found on the Understanding Society COVID-19 website, including Data documentation. A list of Understanding Society COVID-19 Research Outputs (regularly updated) is also available. New edition informationFor the second edition (January 2021), both previously deposited files have been revised to include a significant number of additional school codes resulting from manual coding. For further details please refer to the UKHLS COVID-19: Data Changes document, included in the main COVID-19 study (SN 8644).

United Kingdom UK: School Enrollment: Primary: Private: % of Total Primary data was reported at 17.817 % in 2015. This records an increase from the previous number of 13.990 % for 2014. United Kingdom UK: School Enrollment: Primary: Private: % of Total Primary data is updated yearly, averaging 4.842 % from Dec 1981 (Median) to 2015, with 30 observations. The data reached an all-time high of 17.817 % in 2015 and a record low of 3.968 % in 1981. United Kingdom UK: School Enrollment: Primary: Private: % of Total Primary data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Education Statistics. Private enrollment refers to pupils or students enrolled in institutions that are not operated by a public authority but controlled and managed, whether for profit or not, by a private body such as a nongovernmental organization, religious body, special interest group, foundation or business enterprise.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Table shows numbers of all Schools and Pupils by Type of School.

School types included in this publication are State-Funded Primary, Secondary and Special schools, Independent schools, Pupil Referral Units, and Alternative Provision.

See DfE website

Full daily dataset of all schools and pupil numbers are available from the DFE EduBase site

Cartogram created from this data:

Abstract copyright UK Data Service and data collection copyright owner.The Family Resources Survey (FRS) has been running continuously since 1992 to meet the information needs of the Department for Work and Pensions (DWP). It is almost wholly funded by DWP. The FRS collects information from a large, and representative sample of private households in the United Kingdom (prior to 2002, it covered Great Britain only). The interview year runs from April to March.The focus of the survey is on income, and how much comes from the many possible sources (such as employee earnings, self-employed earnings or profits from businesses, and dividends; individual pensions; state benefits, including Universal Credit and the State Pension; and other sources such as savings and investments). Specific items of expenditure, such as rent or mortgage, Council Tax and water bills, are also covered.Many other topics are covered and the dataset has a very wide range of personal characteristics, at the adult or child, family and then household levels. These include education, caring, childcare and disability. The dataset also captures material deprivation, household food security and (new for 2021/22) household food bank usage. The FRS is a national statistic whose results are published on the gov.uk website. It is also possible to create your own tables from FRS data, using DWP’s Stat Xplore tool. Further information can be found on the gov.uk Family Resources Survey webpage. Safe Room Access FRS data In addition to the standard End User Licence (EUL) version, Safe Room access datasets, containing unrounded data and additional variables, are also available for FRS from 2005/06 onwards - see SN 7196, where the extra contents are listed. The Safe Room version also includes secure access versions of the Households Below Average Income (HBAI) and Pensioners' Incomes (PI) datasets. The Safe Room access data are currently only available to UK HE/FE applicants and for access at the UK Data Archive's Safe Room at the University of Essex, Colchester. Prospective users of the Safe Room access version of the FRS/HBAI/PI will need to fulfil additional requirements beyond those associated with the EUL datasets. Full details of the application requirements are available from Guidance on applying for the Family Resources Survey: Secure Access.FRS, HBAI and PIThe FRS underpins the related Households Below Average Income (HBAI) dataset, which focuses on poverty in the UK, and the related Pensioners' Incomes (PI) dataset. The EUL versions of HBAI and PI are held under SNs 5828 and 8503 respectively. The secure access versions are held within the Safe Room FRS study under SN 7196 (see above). The FRS aims to: support the monitoring of the social security programme; support the costing and modelling of changes to national insurance contributions and social security benefits; provide better information for the forecasting of benefit expenditure. From April 2002, the FRS was extended to include Northern Ireland. Detailed information regarding anonymisation within the FRS can be found in User Guide 2 of the dataset documentation. Edition History: For the second edition (July 2009), correction was made to variables TOTCAPBU and TOTCAPB2. Edits made to the PENPROV table were reviewed and new edits, based on revised criteria, applied to the dataset (see Penprov note for details). For the third edition (October 2014) the data have been re-grossed following revision of the FRS grossing methodology to take account of the 2011 Census mid-year population estimates. New variable GROSS4 has been added to the dataset. Main Topics: Household characteristics (composition, tenure type); tenure and housing costs including Council Tax, mortgages, insurance, water and sewage rates; welfare/school milk and meals; educational grants and loans; children in education; informal care (given and received); childcare; occupation and employment; health restrictions on work; travel to work; children's health; wage details; self-employed earnings; personal and occupational pension schemes; income and benefit receipt; income from pensions and trusts, royalties and allowances, maintenance and other sources; income tax payments and refunds; National Insurance contributions; earnings from odd jobs; children's earnings; interest and dividends; investments; National Savings products; assets. Standard Measures Standard Occupational Classification Multi-stage stratified random sample Face-to-face interview Computer Assisted Personal Interviewing 2006 2007 ABSENTEEISM ACADEMIC ACHIEVEMENT ADMINISTRATIVE AREAS AGE APARTMENTS APPLICATION FOR EMP... APPOINTMENT TO JOB ATTITUDES BANK ACCOUNTS BEDROOMS BONDS BUILDING SOCIETY AC... BUSES BUSINESS RECORDS CARE OF DEPENDANTS CARE OF THE DISABLED CARE OF THE ELDERLY CARS CHARITABLE ORGANIZA... CHILD BENEFITS CHILD CARE CHILD DAY CARE CHILD MINDERS CHILD MINDING CHILD SUPPORT PAYMENTS CHILD WORKERS CHILDREN CHRONIC ILLNESS CIVIL PARTNERSHIPS COHABITATION COLOUR TELEVISION R... COMMERCIAL BUILDINGS COMMUTING CONCESSIONARY TELEV... CONSUMPTION COUNCIL TAX CREDIT UNIONS Consumption and con... DAY NURSERIES DEBILITATIVE ILLNESS DEBTS DISABILITIES DISABILITY DISCRIMI... DISABLED CHILDREN DISABLED PERSONS DOMESTIC RESPONSIBI... ECONOMIC ACTIVITY ECONOMIC VALUE EDUCATION EDUCATIONAL BACKGROUND EDUCATIONAL FEES EDUCATIONAL GRANTS EDUCATIONAL INSTITU... EDUCATIONAL VOUCHERS ELDERLY EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ENDOWMENT ASSURANCE ETHNIC GROUPS EXPENDITURE EXTRACURRICULAR ACT... FAMILIES FAMILY MEMBERS FINANCIAL DIFFICULTIES FINANCIAL INSTITUTIONS FINANCIAL RESOURCES FINANCIAL SUPPORT FOOD FREE SCHOOL MEALS FRIENDS FRINGE BENEFITS FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... FURTHER EDUCATION Family life and mar... GENDER GIFTS GRANDPARENTS GRANTS HEADS OF HOUSEHOLD HEALTH HEALTH SERVICES HEARING IMPAIRED PE... HEARING IMPAIRMENTS HIGHER EDUCATION HOLIDAY LEAVE HOME BASED WORK HOME OWNERSHIP HOME SHARING HOURS OF WORK HOUSEHOLD BUDGETS HOUSEHOLD HEAD S OC... HOUSEHOLDS HOUSING HOUSING FACILITIES HOUSING FINANCE HOUSING TENURE INCOME INCOME TAX INDUSTRIES INSURANCE INSURANCE PREMIUMS INTEREST FINANCE INVESTMENT INVESTMENT RETURN Income JOB DESCRIPTION JOB HUNTING JOB SEEKER S ALLOWANCE LANDLORDS LEAVE LOANS LODGERS MANAGERS MARITAL STATUS MARRIED WOMEN MARRIED WOMEN WORKERS MATERNITY LEAVE MATERNITY PAY MEDICAL PRESCRIPTIONS MORTGAGE PROTECTION... MORTGAGES MOTORCYCLES NEIGHBOURS Northern Ireland OCCUPATIONAL PENSIONS OCCUPATIONAL QUALIF... OCCUPATIONS ONE PARENT FAMILIES ONLINE BANKING OVERTIME PARENTS PART TIME COURSES PART TIME EMPLOYMENT PARTNERSHIPS BUSINESS PASSENGERS PATERNITY LEAVE PENSION CONTRIBUTIONS PENSIONS PHYSICALLY DISABLED... PHYSICIANS POVERTY PRIVATE EDUCATION PRIVATE PERSONAL PE... PRIVATE SCHOOLS PROFITS QUALIFICATIONS RATES REBATES REDUNDANCY REDUNDANCY PAY REMOTE BANKING RENTED ACCOMMODATION RENTS RESIDENTIAL MOBILITY RETIREMENT ROOM SHARING ROOMS ROYALTIES SAVINGS SAVINGS ACCOUNTS AN... SCHOLARSHIPS SCHOOL MILK PROVISION SCHOOLCHILDREN SCHOOLS SEASONAL EMPLOYMENT SECONDARY EDUCATION SECONDARY SCHOOLS SELF EMPLOYED SEWAGE DISPOSAL AND... SHARES SHIFT WORK SICK LEAVE SICK PAY SICK PERSONS SOCIAL CLASS SOCIAL HOUSING SOCIAL SECURITY SOCIAL SECURITY BEN... SOCIAL SECURITY CON... SOCIAL SERVICES SOCIAL SUPPORT SOCIO ECONOMIC STATUS SPECIAL EDUCATION SPECTACLES SPOUSES STATE EDUCATION STATE HEALTH SERVICES STATE RETIREMENT PE... STUDENT HOUSING STUDENT LOANS STUDENTS STUDY SUBSIDIARY EMPLOYMENT SUPERVISORS SUPERVISORY STATUS Social stratificati... TAXATION TELEPHONES TELEVISION LICENCES TELEVISION RECEIVERS TEMPORARY EMPLOYMENT TENANCY AGREEMENTS TENANTS HOME PURCHA... TERMINATION OF SERVICE TIED HOUSING TIME TOP MANAGEMENT TRAINING TRANSPORT FARES TRAVEL CONCESSIONS TRAVEL PASSES UNEARNED INCOME UNEMPLOYED UNEMPLOYMENT BENEFITS UNFURNISHED ACCOMMO... UNWAGED WORKERS VISION IMPAIRMENTS VISUALLY IMPAIRED P... VOCATIONAL EDUCATIO... VOLUNTARY WORK WAGES WATER RATES WIDOWED WORKING MOTHERS WORKING WOMEN property and invest...

This publication combines information from the school census (state-funded schools), school level annual school census (independent schools) and general hospital school census on pupils with special educational needs (SEN).Data at school level including number of pupils by SEN provision and type of need.

This dataset tracks annual reduced-price lunch eligibility from 2002 to 2023 for Britain Elementary School vs. Texas and Irving Independent School District

Abstract copyright UK Data Service and data collection copyright owner. The Secondary School Survey: Uganda, 2017 study measures the overall school quality of the state and non-state sector in Uganda. Data was collected on four types of schools: government USE schools, government non-USE schools, private USE schools, and private non-USE schools. The survey took place between July and August 2017, using a team of 25 enumerators, with 5 days of training taking place in Kampala. Data was collected using Android tablets and the “Survey to Go” app. This survey involved administering several instruments: Students questionnaire (to 6 students per school); Parent questionnaire (in a sub-sample of 60 schools); Lesson observation and teacher questionnaire (2 lessons per school); School Manager / Head Teacher questionnaire; Focus group discussions with school Boards of Governors and parents. Overall, a representative sample of 200 schools was collected. Main Topics: Main topics covered include student learning outcomes and quality perception; parents’ decision; teachers and teaching quality; class observations. Multi-stage stratified random sample Face-to-face interview Telephone interview Observation

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

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

This dataset contains school code variables for the Understanding Society COVID-19 study (https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=8644">SN 8644).

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

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

Additional information can be found on the https://www.understandingsociety.ac.uk/topic/covid-19">Understanding Society COVID-19 website, including https://www.understandingsociety.ac.uk/documentation/covid-19">Data documentation. A list of https://www.understandingsociety.ac.uk/research/publications/subject/Covid%2019">Understanding Society COVID-19 Research Outputs (regularly updated) is also available.

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

Abstract copyright UK Data Service and data collection copyright owner.The Young Lives survey is an innovative long-term project investigating the changing nature of childhood poverty in four developing countries. The study is being conducted in Ethiopia, India, Peru and Vietnam and has tracked the lives of 12,000 children over a 20-year period, through 5 (in-person) survey rounds (Round 1-5) and, with the latest survey round (Round 6) conducted over the phone in 2020 and 2021 as part of the Listening to Young Lives at Work: COVID-19 Phone Survey.Round 1 of Young Lives surveyed two groups of children in each country, at 1 year old and 5 years old. Round 2 returned to the same children who were then aged 5 and 12 years old. Round 3 surveyed the same children again at aged 7-8 years and 14-15 years, Round 4 surveyed them at 12 and 19 years old, and Round 5 surveyed them at 15 and 22 years old. Thus the younger children are being tracked from infancy to their mid-teens and the older children through into adulthood, when some will become parents themselves.The 2020 phone survey consists of three phone calls (Call 1 administered in June-July 2020; Call 2 in August-October 2020 and Call 3 in November-December 2020) and the 2021 phone survey consists of two additional phone calls (Call 4 in August 2021 and Call 5 in October-December 2021) The calls took place with each Young Lives respondent, across both the younger and older cohort, and in all four study countries (reaching an estimated total of around 11,000 young people).The Young Lives survey is carried out by teams of local researchers, supported by the Principal Investigator and Data Manager in each country.Further information about the survey, including publications, can be downloaded from the Young Lives website. School Survey: A school survey was introduced into Young Lives in 2010, following the third round of the household survey, in order to capture detailed information about children’s experiences of schooling. It addressed two main research questions:how do the relationships between poverty and child development manifest themselves and impact upon children's educational experiences and outcomes?to what extent does children’s experience of school reinforce or compensate for disadvantage in terms of child development and poverty? The survey allows researchers to link longitudinal information on household and child characteristics from the household survey with data on the schools attended by the Young Lives children and children's achievements inside and outside the school. A wide range of stakeholders, including government representatives at national and sub-national levels, NGOs and donor organisations were involved in the design of the school survey, so the researchers could be sure that the ‘right questions’ were being asked to address major policy concerns. This consultation process means that policymakers already understand the context and potential of the Young Lives research and are interested to utilise the data and analysis to inform their policy decisions. The survey provides policy-relevant information on the relationship between child development (and its determinants) and children’s experience of school, including access, quality and progression. This combination of household, child and school-level data over time constitutes the comparative advantage of the Young Lives study. The School Survey data are held separately for each country. The India data are available from the UK Data Archive under SN 7478, the Peru data have been archived under SN 7479, and the Vietnam data are available from SN 7663. A further round of school surveys took place during the 2016-2017 school year. The Ethiopia survey is available under SN 8358, the India survey under SN 8359 and the Vietnam survey under SN 8360. Further information is available from the Young Lives School Survey webpages. Main Topics: The survey included data collection at the school, class and pupil level, and involved the Principal, the teacher of Grade 4 and 5 class, and pupil. The instruments included in the survey are: Principal questionnaire. Administered individually by fieldworkers to principals.School site observation. Fieldworker completed through observation of school site during their time in the school.Teacher questionnaire. Administered individually by fieldworkers to teacher of YL child's class.Pupil questionnaire. Administered to the whole class. Fieldworker led and directed. Collected background data on the Pupil, as well as information on attitudes to school.Pupil assessments in Maths and Amharic. Administered to the whole class. Fieldworker led and directed. Multi-stage stratified random sample Face-to-face interview Self-completion Educational measurements Observation 2012 2013 ACADEMIC ABILITY AGE ANIMALS ATTITUDES BILINGUALISM BUILDING SERVICES CLASS SIZE COGNITIVE PROCESSES CONSUMER GOODS Compulsory and pre ... EDUCATIONAL ADMINIS... EDUCATIONAL ADMINIS... EDUCATIONAL ADMISSION EDUCATIONAL ATTENDANCE EDUCATIONAL BACKGROUND EDUCATIONAL CERTIFI... EDUCATIONAL EQUIPMENT EDUCATIONAL FACILITIES EDUCATIONAL FEES EDUCATIONAL GROUPING EDUCATIONAL RESOURCES EDUCATIONAL TESTS EDUCATIONAL TIMETABLES EMPLOYMENT HISTORY EXTRACURRICULAR ACT... Education Ethiopia FAITH SCHOOLS FAMILY MEMBERS GENDER GOVERNING BOARDS ED... HOMEWORK HOUSEWORK ILL HEALTH INCOME INTERNET ACCESS JOB EVALUATION LANGUAGE SKILLS LANGUAGES LANGUAGES USED AT HOME LAVATORIES LITERACY MATHEMATICS EDUCATION MEALS NUMERACY OBSERVATION DATA CO... PARENTAL ROLE PLAYGROUNDS PRE PRIMARY EDUCATION PRIVATE SCHOOLS READING ACTIVITY READING TESTS ROOMS RURAL AREAS SCHOOL BUILDINGS SCHOOL CLASSES SCHOOL MEALS SCHOOL TIME SCHOOLCHILDREN SCHOOLS SCHOOLTEACHERS SIBLINGS SOCIAL ATTITUDES STATE SCHOOLS STRUCTURAL ELEMENTS... STUDENT ATTITUDE STUDENT PARTICIPATION TEACHER STUDENT REL... TEACHER TRAINING TEACHING AIDS TEACHING MATERIALS TEACHING METHODS TEXTBOOKS TIME TRADE UNION MEMBERSHIP TRAVELLING TIME URBAN AREAS WAGES Youth

Abstract copyright UK Data Service and data collection copyright owner. The aim of this survey was to study the educational aspirations, social and political views, political behaviour and school experiences of Venezuelan secondary school students with particular reference to the characteristics, attitudes and behaviour of activists and non-activists. Main Topics: Survey data included: background information on students; educational and occupational aspirations; views on school elections and students representatives; level of knowledge about the political system; social and political views; use of the media; views on a selected event in student politics; views on the police; political behaviour. One-stage stratified or systematic random sample disproportional stratified sample of schools and disproportional stratified sample of students in first, third and fifth grades of schools Self-completion 1971 ACHIEVEMENT AGE ASSAULT ATTITUDES BOYS SCHOOLS CITIZENSHIP SKILLS CIVIC EDUCATION COEDUCATIONAL SCHOOLS Compulsory and pre ... DEMOCRACY DEMONSTRATIONS PROT... DICTATORSHIP EDUCATIONAL ASSESSMENT EDUCATIONAL BACKGROUND EDUCATIONAL COURSES EDUCATIONAL ENVIRON... EDUCATIONAL OBJECTIVES ELECTIONS FAITH SCHOOLS FATHERS FRIENDS GIRLS SCHOOLS HOUSEHOLDS INTERNAL POLITICAL ... INTERPERSONAL INFLU... LAW LAW ENFORCEMENT LEGISLATURE MOTHERS NATIONAL BACKGROUND NATIONAL CHARACTER NATIONAL DEVELOPMENT NATIONALISM NEWSPAPER READERSHIP OBLIGATIONS OCCUPATIONAL CHOICE OCCUPATIONAL STATUS OCCUPATIONS PARENTS PATRIOTISM PLACE OF BIRTH PLACE OF RESIDENCE POLICE BRUTALITY POLICE SERVICES POLICING POLITICAL ALLEGIANCE POLITICAL ATTITUDES POLITICAL AWARENESS POLITICAL CHANGE POLITICAL INTEREST POLITICAL LEADERS POLITICAL PARTICIPA... POLITICAL REPRESENT... POLITICAL SYSTEMS POLITICS PRESIDENCY PRIVATE EDUCATION PRIVATE SCHOOLS Political behaviour... SOCIAL CHANGE SOCIAL CLASS SOCIAL INEQUALITY SOCIAL PROBLEMS SOCIAL SYSTEMS SOCIALISM STATE EDUCATION STUDENT ORGANIZATIONS STUDENT PARTICIPATION STUDENT UNREST TELEVISION PROGRAMMES VENEZUELAN POLITICA... VOTING Venezuela WOMEN Youth