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Quarterly Labour Force Survey Household Dataset, July - September, 2025
No full textAbstract copyright UK Data Service and data collection copyright owner.BackgroundThe Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The LFS was first conducted biennially from 1973-1983. Between 1984 and 1991 the survey was carried out annually and consisted of a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter (data were then collected seasonally). From 1992 quarterly data were made available, with a quarterly sample size approximately equivalent to that of the previous annual data. The survey then became known as the Quarterly Labour Force Survey (QLFS). From December 1994, data gathering for Northern Ireland moved to a full quarterly cycle to match the rest of the country, so the QLFS then covered the whole of the UK (though some additional annual Northern Ireland LFS datasets are also held at the UK Data Archive). Further information on the background to the QLFS may be found in the documentation.Household datasetsUp to 2015, the LFS household datasets were produced twice a year (April-June and October-December) from the corresponding quarter's individual-level data. From January 2015 onwards, they are now produced each quarter alongside the main QLFS. The household datasets include all the usual variables found in the individual-level datasets, with the exception of those relating to income, and are intended to facilitate the analysis of the economic activity patterns of whole households. It is recommended that the existing individual-level LFS datasets continue to be used for any analysis at individual level, and that the LFS household datasets be used for analysis involving household or family-level data. From January 2011, a pseudonymised household identifier variable (HSERIALP) is also included in the main quarterly LFS dataset instead.Change to coding of missing values for household seriesFrom 1996-2013, all missing values in the household datasets were set to one '-10' category instead of the separate '-8' and '-9' categories. For that period, the ONS introduced a new imputation process for the LFS household datasets and it was necessary to code the missing values into one new combined category ('-10'), to avoid over-complication. This was also in line with the Annual Population Survey household series of the time. The change was applied to the back series during 2010 to ensure continuity for analytical purposes. From 2013 onwards, the -8 and -9 categories have been reinstated.LFS DocumentationThe documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each volume alongside the appropriate questionnaire for the year concerned. However, LFS volumes are updated periodically by ONS, so users are advised to check the ONS LFS User Guidance page before commencing analysis.Additional data derived from the QLFSThe Archive also holds further QLFS series: End User Licence (EUL) quarterly datasets; Secure Access datasets (see below); two-quarter and five-quarter longitudinal datasets; quarterly, annual and ad hoc module datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.End User Licence and Secure Access QLFS Household datasetsUsers should note that there are two discrete versions of the QLFS household datasets. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. Secure Access household datasets for the QLFS are available from 2009 onwards, and include additional, detailed variables not included in the standard EUL versions. Extra variables that typically can be found in the Secure Access versions but not in the EUL versions relate to: geography; date of birth, including day; education and training; household and family characteristics; employment; unemployment and job hunting; accidents at work and work-related health problems; nationality, national identity and country of birth; occurrence of learning difficulty or disability; and benefits. For full details of variables included, see data dictionary documentation. The Secure Access version (see SN 7674) has more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.Changes to variables in QLFS Household EUL datasetsIn order to further protect respondent confidentiality, ONS have made some changes to variables available in the EUL datasets. From July-September 2015 onwards, 4-digit industry class is available for main job only, meaning that 3-digit industry group is the most detailed level available for second and last job.Review of imputation methods for LFS Household data - changes to missing valuesA review of the imputation methods used in LFS Household and Family analysis resulted in a change from the January-March 2015 quarter onwards. It was no longer considered appropriate to impute any personal characteristic variables (e.g. religion, ethnicity, country of birth, nationality, national identity, etc.) using the LFS donor imputation method. This method is primarily focused to ensure the 'economic status' of all individuals within a household is known, allowing analysis of the combined economic status of households. This means that from 2015 larger amounts of missing values ('-8'/-9') will be present in the data for these personal characteristic variables than before. Therefore if users need to carry out any time series analysis of households/families which also includes personal characteristic variables covering this time period, then it is advised to filter off 'ioutcome=3' cases from all periods to remove this inconsistent treatment of non-responders. Occupation data for 2021 and 2022 data filesThe ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.Main Topics:The LFS household datasets cover:characteristics of the household: number of people of working age; number of people over working age; number of children aged 0 to 4; number of children aged 5 to 15; number of dependent children (i.e. those in full-time education) aged 16 to 18economic activity in the household: number of people in employment; number of people in full-time employment; number of people in part-time employment; unemployed; economically inactive; students; sick or disabled; economically inactive but would like to work and are not seeking work because they do not believe there is work available ('discouraged workers'); care of dependants</ul
Quarterly Labour Force Survey, January - March, 2025
No full textAbstract copyright UK Data Service and data collection copyright owner.BackgroundThe Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The Annual Population Survey, also held at the UK Data Archive, is derived from the LFS.The LFS was first conducted biennially from 1973-1983, then annually between 1984 and 1991, comprising a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter. From 1992 it moved to a quarterly cycle with a sample size approximately equivalent to that of the previous annual data. Northern Ireland was also included in the survey from December 1994. Further information on the background to the QLFS may be found in the documentation.The UK Data Service also holds a Secure Access version of the QLFS (see below); household datasets; two-quarter and five-quarter longitudinal datasets; LFS datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.LFS DocumentationThe documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each user guide volume alongside the appropriate questionnaire for the year concerned (the latest questionnaire available covers July-September 2022). Volumes are updated periodically, so users are advised to check the latest documents on the ONS Labour Force Survey - User Guidance pages before commencing analysis. This is especially important for users of older QLFS studies, where information and guidance in the user guide documents may have changed over time.LFS response to COVID-19From April 2020 to May 2022, additional non-calendar quarter LFS microdata were made available to cover the pandemic period. The first additional microdata to be released covered February to April 2020 and the final non-calendar dataset covered March-May 2022. Publication then returned to calendar quarters only. Within the additional non-calendar COVID-19 quarters, pseudonymised variables Casenop and Hserialp may contain a significant number of missing cases (set as -9). These variables may not be available in full for the additional COVID-19 datasets until the next standard calendar quarter is produced. The income weight variable, PIWT, is not available in the non-calendar quarters, although the person weight (PWT) is included. Please consult the documentation for full details.Occupation data for 2021 and 2022 data filesThe ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.2024 ReweightingIn February 2024, reweighted person-level data from July-September 2022 onwards were released. Up to July-September 2023, only the person weight was updated (PWT23); the income weight remains at 2022 (PIWT22). The 2023 income weight (PIWT23) was included from the October-December 2023 quarter. Users are encouraged to read the ONS methodological note of 5 February, Impact of reweighting on Labour Force Survey key indicators: 2024, which includes important information on the 2024 reweighting exercise.End User Licence and Secure Access QLFS dataTwo versions of the QLFS are available from UKDS. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes country and Government Office Region geography, 3-digit Standard Occupational Classification (SOC) and 3-digit industry group for main, second and last job (from July-September 2015, 4-digit industry class is available for main job only).The Secure Access version contains more detailed variables relating to:age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent childfamily unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of familynationality and country of originfiner detail geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district, and other categories;health: including main health problem, and current and past health problemseducation and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeshipsindustry: including industry, industry class and industry group for main, second and last job, and industry made redundant fromoccupation: including 5-digit industry subclass and 4-digit SOC for main, second and last job and job made redundant fromsystem variables: including week number when interview took place and number of households at addressother additional detailed variables may also be included.The Secure Access datasets (SNs 6727 and 7674) have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.Latest edition informationFor the second edition (December 2025), the following Heath and Safety Executive (HSE) variables were added to the data file: ACCDNT, ACCKIND, ACCURH1-4, AWARE, ILLWRK, NUMILL, ROAD, SITEDI1-6, SITEFR1-7, TYPILL, TYPINJ, WCHJB and WCHJB3.Main Topics:The QLFS questionnaire comprises a 'core' of questions which are included in every survey, together with some 'non-core' questions which vary from quarter to quarter.The questionnaire can be split into two main parts. The first part contains questions on the respondent's household, family structure, basic housing information and demographic details of household members. The second part contains questions covering economic activity, education and health, and also may include a few questions asked on behalf of other government departments (for example the Department for Work and Pensions and the Home Office). Until 1997, the questions on health covered mainly problems which affected the respondent's work. From that quarter onwards, the questions cover all health problems. Detailed questions on income have also been included in each quarter since 1993. The basic questionnaire is revised each year, and a new version published, along with a transitional version that details changes from the previous year's questionnaire.</div
Gambling Survey for Great Britain: Year 1, 2023
No full textAbstract copyright UK Data Service and data collection copyright owner.The Gambling Survey for Great Britain (GSGB) is a push-to-web survey (with a paper questionnaire option) that collects data on gambling participation. The GSGB is commissioned by the Gambling Commission and carried out by the National Centre for Social Research and the University of Glasgow. Data collection for the first year of the survey was conducted in 2023. The aims of the GSGB are to: collect data on a wide range of up-to-date gambling behaviours, including participation and adverse consequences of gambling;provide a rolling programme of data collection to give the Commission the ability to gain timely insights and respond to emerging trends;contribute to the evidence base on gambling behaviours and impacts, and help identify gaps and priorities, and;produce and publish official statistics on gambling participation and prevalence statistics in accordance with the standards set out by the Office for Statistics Regulation in the Code of Practice for Statistics.Users should note that findings from the GSGB are not directly comparable with prior surveys used for gambling statistics, such as the Health Surveys for England and Scotland and the British Gambling Prevalence (BGPS) series that ran from 2007-2010 (held at the UKDS under SNs 5836, 6639 and 6843). This is because the new push-to-web methodology uses a different approach compared to the methodologies used in prior surveys, and GSGB development provides an opportunity to refresh and update questions.December 2025A correction to the ‘Gambled in the past 12 months’ derived variables is currently being made. Please use these variables with caution until the corrected data is made available early in 2026. Main Topics:Topics covered include:Lifestyle – leisure activities, internet useGambling participation in the last 12 monthsFeelings about gambling and reasons for gamblingTypologies (only included in the web questionnaire)Gambling binges in the last 12 months (only included in the web questionnaire)Problem Gambling Severity Index (PGSI)Consequences of own gamblingGambling participation in the past 4 weeksGambling attitudesConsequences of others’ gamblingHealth and wellbeing (including smoking, drinking, suicidality)DemographicsHousehold informationConsent to future contact</ul
EVA Survey on Finnish Values and Attitudes Autumn 2024
No full textTutkimuksessa kartoitettiin suomalaisten arvoja ja asenteita. Tällä kertaa teemoina ovat luottamus yhteiskunnallisia toimijoita kohtaan, tiedotusvälineet, tekoälyn käyttö, julkinen talous, verotus, sijoittaminen sekä Yhdysvaltojen presidentinvaalit 2024. Aluksi vastaajille esitettiin väittämiä yhteiskunnan eri osa-alueilta. Ne käsittelivät muiden muassa politiikkaa, eläkejärjestelmää, vaaleja ja Suomen suhteita Yhdysvaltoihin. Seuraavaksi kysyttiin, kuinka suurta luottamusta vastaaja tuntee yhteiskunnassa vaikuttavia eri toimijoita kohtaan. Tiedusteltiin myös, mihin suuntaan vastaajat arvioivat esimerkiksi Suomen talouden, julkisen velan määrän, työllisyyden ja ulkoisen turvallisuuden kehittyvän lähivuosina. Näkemyksiä suomalaista uutisvälineistä kartoitettiin useilla kysymyksillä. Vastaajat arvioivat esimerkiksi eri uutisvälineiden tapahtumista välittämän kuvan totuudenmukaisuutta, uutisvälineiden väitettyä politisoitumista sekä perinteisten tiedotusvälineiden luonnehdintoja. Kysyttiin myös ulkomaisten uutisvälineiden seuraamisesta. Tekoälyyn liittyen kysyttiin eri tekoälyn verkkosovellusten tuttuudesta ja mahdollisesta käytöstä. Tekoälyä käyttäneiltä kysyttiin ensisijaisesta käyttötarkoituksesta, käytön vaikutuksesta tehtävän hoitoon kuluneeseen aikaan ja tuotoksen laatuun sekä tekoälyn käytöstä työtehtävissä. Kysyttiin myös, miten työnantaja suhtautuu tekoälyn käyttöön työtehtävissä. Julkiseen talouteen liittyen tiedusteltiin vastaajien ajatuksia mahdollisista lisätoimista ja menoleikkauksista, joilla julkista taloutta voidaan tasapainottaa. Kysyttiin myös verotuksen muutostarpeista ja perintöveron poistamisesta sekä työeläkejärjestelmän rahoituksesta. Lisäksi kysyttiin vastaajien suhtautumisesta sijoittamiseen sekä heidän omista sijoituksistaan osakkeisiin ja sijoitusrahastoihin. Yhdysvaltojen presidentinvaaleihin liittyen vastaajia pyydettiin arvioimaan, millaisia erilaisia vaikutuksia Trumpin ja Harrisin valinnalla presidentiksi olisi esimerkiksi Yhdysvaltain talouteen sekä rauhaan ja konflikteihin maailmassa. Lisäksi kysyttiin, miten vastaajat suhtautuvat Suomen Nato- ja EU-jäsenyyteen sekä euroon. Taustamuuttujia olivat sukupuoli, ikäryhmä, elämänvaihe, asuinkunnan koko, asuinkunta, asuinmaakunta, perus- ja ammatillinen koulutus, ammattiryhmä, työnantajatyyppi, työsuhde, toimiala, puoluekanta (mitä puoluetta äänestäisi, jos eduskuntavaalit pidettäisiin nyt), ammatillinen keskusjärjestö, yhteiskuntaluokka, äidinkieli, talouden bruttotulot ja vähemmistöön kuuluminen.The study charted Finnish people's values and attitudes. The themes of the Autumn 2024 survey included trust in various influencing institutions in Finnish society, the media, the use of artificial intelligence, public finances, taxation, investment, and the 2024 United States presidential election. First, the respondents were presented with a variety of attitudinal statements concerning, among other topics, politics, the pension system, elections, and Finland's relations with the United States. The respondents were asked to indicate their level of trust in different institutions. They were also asked about how Finland's economy, public debt levels, employment and security will develop in the coming years. The next set of questions focused on the Finnish media. The respondents were asked to evaluate, for example, the news accuracy, the alleged politicisation of the news media, and the characteristics of traditional media. The use of foreign news sources were also surveyed. The respondents were asked about their familiarity with and use of various AI-based online applications. Those who had used AI were asked about their primary purpose for doing so, the impact on task efficiency and output quality, and whether they used AI in their work. The study also charted employers' attitudes towards the use of AI in professional tasks. Financial matters were studied with questions relating taxation change needs and the rebalancing of public finance. Views on expenditure cuts to different public sectors and services were surveyed. Furthermore, the study examined attitudes towards investing and respondents' own investments in stocks and mutual funds. Finally, the respondents were asked to assess the potential impacts of either Trump or Harris being elected President of the United States, particularly in terms of the US economy and global peace and conflict. Opinions were also charted on Finland's NATO membership, Finland's EU membership and the adoption of the 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, minority status and annual gross income of the R's household
Perceptions of Upper Secondary Education: Human Resources Administration in Companies 2022
No full textAineistossa on kartoitettu yritysten henkilöstöpäättäjien käsityksiä ja mielipiteitä toisen asteen koulutuksesta. Teemoja aineistossa ovat mm. toisen asteen koulutuksen suorittaneiden osaamisen ja työelämän vaatimusten kohtaaminen, työmarkkinoiden tulevaisuus sekä ammatillisen koulutuksen ja lukion arvostus. Tutkimus toteutettiin opetus- ja kulttuuriministeriön ja Skills Finland ry:n toimeksiannosta. Yritysten henkilöstöasioista päättäviltä kysyttiin heidän omaa suhtautumistaan ammatilliseen koulutukseen ja lukiokoulutukseen. Heitä pyydettiin myös arvioimaan, mihin suuntaan kummankin toisen asteen koulutuksen tarve Suomessa kehittyy lähivuosina. Seuraavaksi vastaajat kertoivat, kuinka hyvin heidän mielestään ammatillisen koulutuksen tarjonta ja työmarkkinoiden kysyntä kohtaavat. Lopuksi kysyttiin, onko heidän yritykseensä rekrytoitu kuluneena vuonna uusia työntekijöitä, ja onko näillä palkatuilla henkilöillä ollut ammatillinen tutkinto vai ylioppilastutkinto. Taustatietoja aineistossa ovat mm. yrityksen henkilökunnan määrä, pääasiallinen toimiala, maakunta ja yrityksen sijaintipaikan tyyppi, kuinka suurella osalla henkilökunnasta on ammatillinen koulutus/ylioppilastutkinto sekä vastaajan koulutus, sukupuoli ja ikäryhmä.The survey charted the perceptions and opinions of employees in personnel management in different companies regarding upper secondary education in Finland. Main themes included, among others, perceptions of how well the competence of persons who had completed upper secondary education met the requirements of working life and how general and vocational upper secondary education are appreciated. The study was commissioned by the Ministry of Education and Culture and Skills Finland. First, the respondents' own positive or negative attitudes towards upper secondary education were charted. Their perceptions of whether the need for general and vocational upper secondary education would increase in Finland over the next few years was examined. Next, the respondents described how well they think the provision of vocational education and training matched the demand of the labour market. Finally, the respondents were asked whether their company had recruited new employees in the past year, and whether these recruits had completed general or vocational upper secondary education. Background variables included the number of employees in the respondent's company, the company's industry of employment, the region (NUTS3) and type of the municipality where the company was located, the percentage of employees in the company who had general or vocational upper secondary qualifications, as well as the respondent's highest level of education, gender and age group
Perceptions of Upper Secondary Education: Parents of Ninth-Graders 2022
No full textAineistossa on kartoitettu 9.-luokkalaisten vanhempien käsityksiä ja mielipiteitä toisen asteen koulutuksesta ja lastensa jatko-opiskelusuunnitelmista. Muita teemoja aineistossa ovat mm. yhdeksäsluokkalaisten vanhempien käsitys ammatillisen koulutuksen sekä lukion arvostuksesta ja opiskeluun liittyvät mielikuvat. Tutkimus toteutettiin opetus- ja kulttuuriministeriön ja Skills Finland ry:n toimeksiannosta. Vastaajilta kysyttiin mielipiteitä opiskeluun liittyviin väittämiin, kuten kuinka tärkeää opiskelu on tulevaisuuden kannalta tai onko työ kiinnostavampaa kuin opinnot. Vanhemmilta kysyttiin, aikooko heidän yhdeksäsluokkalainen lapsensa jatkaa opiskelua peruskoulun jälkeen, missä koulutusvaihtoehdossa ja kuinka kiinnostavina he pitävät eri koulutusalavaihtoehtoja lapselleen. Vastaajat myös kertoivat, mitkä tekijät vaikuttivat heidän lapsensa jatko-opintovalintaan. Vanhemmilta kysyttiin myös, mistä he olivat saaneet tietoa peruskoulun jälkeisistä koulutusvaihtoehdoista. Taustatietoja aineistossa ovat vastaajan sukupuoli, asuinpaikkakunta, maakunta sekä oma ja puolison koulutusaste ja ammattiryhmä.The survey charted the perceptions and opinions of parents of ninth-graders regarding general and vocational upper secondary education and their child's plans after completing lower secondary education. Main themes included, among others, the parents' opinions on studying and perceptions of how general and vocational upper secondary education are appreciated. The study was commissioned by the Ministry of Education and Culture and Skills Finland. First, respondents were surveyed on the factors they thought should affect their child's choice when applying to upper secondary education (e.g. wanting to have a job with good pay, location of the school/educational facility, parents' or the child's opinions). The respondents were also asked whether their child would continue into upper secondary education after completing lower secondary school, how interesting they thought different paths of education were for their children (e.g. general or vocational upper secondary education, tenth grade) and which educational path they thought their child should choose after completing lower secondary education. If the respondents indicated that their child should choose vocational education or training after lower secondary school, they were asked which field of vocational education they thought would be suitable for their child. Finally, the sources of the respondents' information on different paths of education were charted. Background variables included the respondent's gender, municipality of residence, region of residence (NUTS3), as well as their own and their spouse's highest level of education and occupation group
GUIDE child study 2023 Finland
No full textGUIDE (Growing Up In Digital Europe: EuroCohort) will be Europe’s first comparative birth cohort survey. This Research Infrastructure that will be an important source of high quality longitudinal statistical evidence to support the development of social policies which will enhance the wellbeing of children, young people and their families across Europe for many years to come. GUIDE will be an accelerated cohort survey including a sample of new born infants as well as a sample of school age children. Both cohorts will be surveyed at regular intervals using a common questionnaire and data collection methodology until the age of 24 years. The survey consists of two questionnaires. One for the child itself and one for the parent of the child. This dataset contains the answers of the children in the country Finland
Replication Data for: Diverging Ethnic Hierarchies? Cultural Distance, Right-Wing Authoritarianism, and Social Distance Perceptions in the Netherlands.
No full textThese data were collected for and used in writing the article "Diverging Ethnic Hierarchies? Cultural Distance, Right-Wing Authoritarianism, and Social Distance Perceptions in the Netherlands" published in the Journal of International Migration and Integration. We collected these data using an online access panel in 2018. Respondents answered questions about their social distance toward different ethnic groups and completed a right-wing authoritarianism scale. Some socio-demographic information was also collected
Replication Data for: Associations between smoking behavior and cognitive functioning in a clinical sample with alcohol use disorder
No full textIn clinical addiction care, tobacco is the most commonly used substance among patients. While the harmful effects of smoking on physical health are widely recognized, its additional impact on cognitive deficits associated with alcohol consumption remains under-researched. This study aimed to investigate cognitive differences between smoking and nonsmoking individuals with alcohol use disorder (AUD). We reviewed clinical records and neurocognitive data from 100 AUD patients, assessing their smoking status and cessation. Premorbid intelligence, verbal working memory, verbal learning and long-term memory, processing speed, inhibitory control, and cognitive flexibility were assessed
LAKS-monitor 2024
No full textDe LAKS-monitor is het tevredenheidsonderzoek onder scholieren in het voortgezet onderwijs dat het LAKS sinds 2010 laat uitvoeren, met financiering van het ministerie van OCW. Tot en met 2022 werd de enquête om het schooljaar uitgezet en sinds 2023 voor het eerst op jaarlijkse basis. De LAKS-monitor is bedoeld om te weten te komen wat scholieren vinden dat er goed gaat en wat er beter kan op hun school. De resultaten uit de LAKS-monitor kunnen door leerlingenraden en onderwijsbestuurders gebruikt worden bij het verbeteren van de onderwijskwaliteit. In 2022 is de vragenlijst van de LAKS-monitor ingrijpend veranderd en de resultaten uit 2024 zijn daarom alleen met die van 2022 en 2023 te vergelijken. Meer informatie over de uitvoering van de LAKS-monitor alsook een uitgebreidere onderzoeksverantwoording van de laatste LAKS-monitor (2024) is te vinden op de portal van de LAKS-monitor: http://portal.laks-monitor.nl