Statistics Sweden

Department of social statistics and analysis

SSA/AU/UTB, 701 89 Örebro

The Adult Education Survey (AES) covers adults’ participation in education and training (formal - FED, non-formal - NFE and informal learning - INF). The 2022 AES focuses on people aged 18-69. The reference period for the participation in education and training is the twelve months prior to the interview.

Information available from the AES is grouped around the following topics:

• Participation in formal education, non-formal education and training and informal learning
• Volume of instruction hours
• Characteristics of the learning activities
• Reasons for participating
• Obstacles to participation
• Access to information on learning possibilities and guidance
• Employer financing and costs of learning
• Self-reported language skills

For further information see the 2022 AES legislation (http://ec.europa.eu/eurostat/web/education-and-training/legislation) and the 2022 AES implementation manual (http://ec.europa.eu/eurostat/web/education-and-training/methodology).

- Classification of Learning Activities (CLA, 2016 edition)
- International Standard Classification of Education 2011 (ISCED 2011)
- Classification of Occupations 2008 (ISCO 08)
- Classification of economic activities Rev. 2 (NACE Rev. 2)

AES covers all economic sectors.

Definitions as well as the list of variables covered are available in the 2022 AES implementation manual (http://ec.europa.eu/eurostat/web/education-and-training/methodology).

Individuals, non-formal learning activities.

Individuals aged 18-69 living in private households.

The country of Sweden.

2007 pilot testing (10/2005 - 03/2006)

2011 AES (03/2012 - 11/2011)

2016 AES (09/2016 - 03/2017)

2022 AES (05/09/2022 - 22/01/2023)

Not applicable.

Number, EUR.

Fieldwork period for 2022 AES: 05/09/2022 - 22/01/2023.

At European level:
Basic legal act: Regulation (EU) 2019/1700
Implementing act: Commission Implementing Regulation (EU) 2021/861

At national level:
Not applicable.

Not applicable.

Strict internal rules are in place at Statistics Sweden to protect data and personal integrity. There are several laws that control the handling of microdata based on individuals, for example:

- The publicity and privacy Act 2009:400 (Offentlighets- och sekretesslagen 2009:400);

- The personal data Act 1998:204 (Personuppgiftslagen 1998:204);

- The EU General Data Protection Regulation (GDPR), the Official Statistics Act (2001:99) and the Official Statistics Ordinance (2001:100).

Statistics Sweden guarantees confidentiality of data by publishing only aggregated and un-identifiable data. If micro-data is provided to third part, the same laws about confidentiality apply for third part.

Furthermore, in order to avoid publication of figures which are statistically unreliable, Statistics Sweden conceals estimates with less than 10 unweighted counts in the cell or less than 30 unweighted counts in the marginal sum.

Statistics Sweden ensures strict protection of individual data. A system of rules, documentation and relevant organisational structure ensures the security and integrity of confidential data. The methods for protecting confidential data are continuously revised and improved. All Statistics Sweden employees working with microdata are obliged to keep confidential statistical information secret.

Statistical information is published in accordance with an approved release calendar and will be available on December 6 2023.

Publications will be made available on http://www.scb.se/UF0538

The data is disseminated to all users via www.scb.se.

The data are simultaneously published to all interested parties by issuing a press release announcing the availability of the report and tables on the AES. The press release is issued in Swedish and English only.

The database of indicators is available in Swedish.

Every 6 years.

New publications linked to AES data will be available on http://www.scb.se/UF0538 on December 6 2023.

All publications linked to AES data are available on http://www.scb.se/UF0538.

Online database linked to AES data for 2012, 2016 and 2022 will be available on http://www.scb.se/UF0538 on December 6 2023.

Not applicable.

Customized tables can be requested and de-identified microdata can be disseminated after approval of an internal review of the request.

Not applicable. 

Not applicable.

Will be made available on http://www.scb.se/UF0538 on December 6 2023.

Not applicable.

Will be made available on http://www.scb.se/UF0538 on December 6 2023.

Statistics Sweden uses an internal operational support system that reflects a similar logic to Deming's Plan-Do-Check-Adjust (PDCA) cycle. The operational support system contains information on how to achieve sufficient quality at each stage of a statistical survey. Statistics Sweden has also produced a quality policy that describes how we conduct our quality work at SCB to achieve quality in products, services and processes. This document is in Swedish and can be found in the appendix "Quality policy".

The quality of the implementation of the survey is considered good. However, the fact that 54.2% of the sample represents non-respondents is a problem that cannot be ignored. Regarding the large questionnaire and the cognitive burden - educational activities in the last 12 months - the 45.8 per cent response rate is a good result given the negative trend in response rates in surveys conducted by Statistics Sweden. The response rate in the LFS is around 45 per cent. Thanks to the introduction of CAWI, the response rate remained at a relatively good level compared to if we had only used CATI.

The survey theme - education - seems to be interesting for people that have been participating in education recently, but not interesting for others according to information from the interviewers. This might be problematic due to non-response bias. According to response rates between strata it seems that educational attainment has a large impact of the willingness to response. According to logistic regression with respect to the willingness to response significant p-values occur for educational attainment, employment, age group, marital status.

In previous AES surveys both CAPI and CATI have been used but in the 2016 AES only CATI was used. This is because CAPI is a method that in principle is no longer used at Statistics Sweden. In AES 2022, CATI and CAWI were used where CATI accounted for 27 per cent of the response rate and CAWI 73 per cent.

The most problematic part of the survey is the length of the questionnaire. The amount of time spent on the details of learning activities is excessive if the respondent participated in 2 or more learning activities. The reference period of 12 months is in many cases too long for respondents to remember all learning activities they took part in so the number of non-formal learning activities or the participation rate in non-formal education are probably underestimated.

Proxy interviews were not allowed, but interviews with authorized interpreters as third part were conducted, 46 in total in AES 2022.

The relevance of an instrument must be assessed in the light of user needs. In the case of EU Adult Education Survey (AES), the main users are the following:

• Institutional users such as the Ministry of Education, the Commission of Education or other policy makers at European and national level.
• Statistical users in Eurostat or in national statistical offices.
• Researchers who have access to microdata.
• End users - including the media - interested in adult participation in education and training at both national and European level.

The AES 2022 was carried out in collaboration with the Swedish Ministry of education to fulfil their needs. The Swedish Ministry of education is the most important user. Due to the extensive questionnaire demanded in the Regulation 1700/2019 a decision was made not to extend the questionnaire with national issues. The most requested statistics from other users are participation rates in educational activities broken down in sub-groups of ISCO and NACE in more detailed levels, but that would increase the sample size excessively and it´s not possible with respect to the financial budget. The AES 2022 data can be merged with administrative registers to fulfil other needs. No measures of the user satisfaction are available.

All variables requested in the 2022 AES Regulation 1700/2019 are covered in the dataset.

Not applicable.

Sample size was calculated in order to fulfil pre-defined criteria according to sample and precision requirements defined in Commission regulation (EU) No 1700/2019, on the basis of the AES 2016 results and expected confidence intervals for each strata. The strata were constructed by age, sex and educational attainment for persons aged over 25 and by age and sex for persons under 25. Weighting procedures with calibration technique were used to adjust for unit non-response.

Regarding measurements errors, there may be some underreporting of participation in non-formal education and training activities due to:

• The reference period of 12 months which is in many cases too long for respondents to remember all learning activities they took part in.
• Misunderstanding of the definition of non-formal education.

Sampling error is considered feasible for AES 2022.

See table 13.2.1 “Sampling errors - indicators for 2022 AES key statistics” in annex “SE - QR tables 2022 AES (excel)”.

The indicators are computed in a Statistics Sweden proprietary software ETOS through the software SAS.

See table 13.2.1 “Sampling errors - indicators for 2022 AES key statistics” in annex “SE - QR tables 2022 AES (excel)”.

For details see items 13.3.1 - 13.3.5 below.

A small amount of over-coverage was identified, just under 0.4 per cent. The level of under-coverage is unknown. The identified over-coverage objects are removed from the effective sample and the over-coverage and the under-coverage are assumed to be of equal size. The coverage errors are assumed to be small in relation to other sources of errors.

See table 13.3.1.1 “Over-coverage - rate” in annex “SE - QR tables 2022 AES (excel)”.

Not applicable.

Two questionaries were developed, since AES 2022 is a CAWI and CATI survey. The development was done in close co-operation with experts in measurement technology. When the variables and definitions in the EU Regulation 1700/2019 were covered, the questionnaire was tested through six cognitive interviews with potential frame elements. After small adjustments, the questionnaires were programmed into two electronic versions, one for CAWI and one for CATI. The questionaries were pre-tested and adjusted. The CATI version was also tested by interviewers. When the final questionnaire was finished a half-day interviewer training took place, only days before the start of the field work.

The interviewers got an interviewer manual with explanatory notes about the study in general and the questions in particular. The CATI version of the questionnaire had some instructions to help the interviewer with common definitions and other explanations. The CAWI version of the questionnaire also had some instructions to help the respondent with common definitions and other explanations.

For details see the following items.

See table 13.3.3.1 “Unit non-response - rate” in annex “SE - QR tables 2022 AES (excel)”.

See table 13.3.3.2 “Item non-response rate” in annex “SE - QR tables 2022 AES (excel)”.

The AES 2022 questionnaire (CATI/CAWI) contained many logical checks and controls as well as pop-up notifications for improbable data values (outliers, logical inconsistencies etc.). These were embedded in the CATI/CAWI system and corrected by the interviewer or respondent and therefore not possible to quantify. 

The electronic questionnaire had fixed response options for most of the questions. The processing errors for these variables are considered low. Some variables, JOBISCO, LOCNACE, FED, NFEFIELD1, NFEFIELD2 and also unusual LANGUAGES are collected as open ended answer and were coded after the interview by coding experts with additional information from administrative register to help the encoders. The software used for coding is called PRISMA, same as used in LFS.

A lot of processing was done in order to create the final dataset. This work was done in SPSS with saved syntax for all work, for documentation and traceability. The final dataset with the variables in Regulation 1700/2019 was validated through STRUVAL/CONVAL checking tool. The data contains only valid values.

Not applicable.

See also table 14.2 “Project phases - dates” in annex “SE - QR tables 2022 AES (excel)”.

Not applicable.

See table 14.2 “Project phases - dates” in annex “SE - QR tables 2022 AES (excel)”.

The AES 2022 dataset was delivered in time. All deadlines are met.

See table 14.2 “Project phases - dates” in annex “SE - QR tables 2022 AES (excel)”.

Not applicable.

The survey is output harmonized, but not input harmonized. It means that all the datasets from different countries have the same set of variables and definitions of variables and value quantities, but for example the data collection method may differ between countries. There might be mode effects and other input issues (different questionnaires with different ways to capture the output variable, different logical checks and controls etc.) that affect the geographical comparability.

AES 2022 data are fully comparable between national regions.

Some additional variables/information related to COVID-19 were collected.

See also table 15.1 “Deviations from 2022 AES concepts and definitions” in annex “SE - QR tables 2022 AES (excel)”.

Not applicable.

AES 2007 was conducted through about 60 % CAPI and 40 % CATI. In 2011 there was 40 % CAPI and 60 % CATI and in 2016 Statistics Sweden no longer used CAPI as data collection method so it was 100 % CATI which might have affected the comparability over time. We suspect that it impacted participation rate estimates negatively and maybe also other variables. Also, between 2011 and 2016 most persons got rid of home telephones and only had a mobile phone which affected the behaviour during the CATI interview. AES is running only every sixth year and it´s hard to keep the data collection unchanged. Comparison over time should be done with this in mind and conclusions drawn carefully.

In 2015 we did a stand alone pilot survey, testing CATI against CAWI which indicated no significant differences in core variables such as participation rate in formal or non-formal education. We did not test open answer questions. In the AES 2022 we introduced CAWI as an alternative to CATI. Unfortunately, respondents did not prefer to type in open answers so all open answer variables have a higher level of item non-response. Also, the crucial variables on the five NFE-activities and the in-depth variables on the two selected NFE-activities are missing for these records. We started with a question about the name and if no name was given, no further questions about the activity were asked. In the planning of the survey we discussed how to handle this potential issue and thought our soft warning would reduce it to a negligible issue. Our intention was to delete these activities in the data cleaning phase and not count them in. But since the main indicator “Participating in non-formal education (NFE)” is affected with about 5 percent points depending if we include or exclude these activities, after discussion, it was decided to keep the records in the final dataset, resulting in item non-response for some variables.

NFEACTxx_TYPE it determined by the questions in the Swedish questionnaire so these variables have no item non-response. But unfortunately for the other 4 variables NFEACTxx_PURP, NFEACTxx_WORKTIME, NFEACTxx_PAIDBY, item non-response is about 8-10 percent out of the total response set (excluding code -2). 

Among the two randomly selected activities NFENBHOURS1 and NFENBHOURS2 have 22-24 percent item non-response (excluding code -2) which is the highest values. Most variables about the two randomly selected activities have more than 10 percent item non-response.

Comparisons between these NFE variables over time can be misleading because of the high item-non response in 2022.

See also table 15.2 “Comparability - over time” in annex “SE - QR tables 2022 AES (excel)”.

Not applicable.

See table 15.3 “Coherence - cross-domain” in annex “SE - QR tables 2022 AES (excel)”.

Not applicable.

Not applicable.

AES results for a given data collection round are based on the same microdata and results are calculated using the same estimation methods, therefore the data are internally coherent.

Average CATI interview took about 29 min.

Not applicable.

Not applicable.

Not applicable.

Sample frame age 25-69 years

The sample frame for persons aged 25-69 years, born 1953-01-01-1997-12-31, is taken from the Total population register (RTB) on 2022-01-31. A total of 5 877 947 persons are retrieved from RTB. The sample frame is stratified by age, gender and level of education. The sample is allocated with known response rates from 2016 survey so that the expected number of responses is similar to a proportional allocation. This is so that the weights will ultimately vary as little as possible. It should be favourable for overall precision. The response rate for persons aged 25-69 achieves the expected precision requirement. In total, 7 400 people were sampled. In 2016 we attempted to achieve equal response rates in different strata by focusing the data collection towards the strata that were performing poorly, but this resulted in an overall negative response rate. It was decided in AES 2022 to accept lower precision in some groups, but taking into account that non-response is expected to be different per stratum.

Weighting procedures: The ETOS software (variance estimation programme developed by Statistics Sweden) was used for calibration in order to reduce non-response bias.

 Factors used:

• Strata (18 groups, see table above)
• Country of birth (2 groups)
• Marital status (2 groups)
• Activity status (3 groups)
• Income (5 quartiles)
• Participation in formal education (2 groups)

Sample frame aged 18-24

The sampling frame for persons aged 18-24, born 1998-01-01-2004-08-31, was obtained from the Total population register (RTB) on 31 January 2022. A total of 777 047 persons were retrieved from RTB. The sampling frame is stratified by age and gender. Level of education is not used here because the register of educational attainment level (UREG) data is at least 1 year old at the time of data collection and there are lots of changes in the level of education for this age group. In total, 3,300 people were drawn from the sampling frame. Using auxiliary information from the register of persons in formal education (RPU) for estimation, it is considered to fulfil the precision requirements for formal education. The response rate for persons aged 18-24 years fulfils the expected precision requirement. 

Weighting procedures: The ETOS software (variance estimation programme developed by Statistics Sweden) was used for calibration in order to reduce non-response bias.

Factors used:

• Strata (4 groups, see table above)
• Municipality group (3 groups)
• Country of birth (Sweden, other) 
• Educational attainment (3 groups)
• Parental educational attainment (3 groups)
• Activity status (3 groups)
• Participation in formal education (2 groups)

See also table 18.1 “Source data” in annex “SE - QR tables 2022 AES (excel)”.

Every 6 years.

The survey was conducted using CAWI or CATI. Respondents could provide answers directly on a computer/mobile/tablet after logging in with a username and password or Bank ID/Freja or through an interview.

The sample was randomised into 3 groups in order to conduct the collection in the same way but with different starting points in time. All 3 groups were given the same procedure where they received an invitation to participate and a referral to the CAWI mode. After two weeks, a reminder was sent and interviewers started contacting all those who had not yet responded.

Respondents were able to respond online throughout the data collection period. Until the respondent responded or gave a reason for not participating, Statistics Sweden continued to contact them by telephone and through three written reminders to participate.

The mailing was sent digitally to those with a digital mailbox or by post to those without a digital mailbox. Around 70 per cent have a digital mailbox for e.g. government mail.

All participants received a gift card, about 9 EUR.

The AES 2022 consisted of two questionnaires, one for CATI and one for CAWI. The questionnaires were designed based on who is reading it, the respondent (CAWI) or the interviewer (CATI). Several questions in the web questionnaire are split into two questions while in the interviewer questionnaire there is only one question. Both questionnaires had data checks to validate some data fields for reasonableness and completeness before moving on to the next question. This was to ensure that significant errors or incomplete answers were not collected.

In order not to make the questionnaires unnecessarily complicated for the participant, the checks were limited to the most important questions. However, it was possible to bypass these softer barriers by repeatedly clicking on "continue" or in an interview the interviewer could type in '9999' for 'Not want to answer'. Unfortunately, a larger number of sample members participating through CAWI pushed past controls designed to prevent them from not naming their activity. For more information see 15.2.

ISCO 08: Information on occupation was collected by including in both questionnaires a search list of 12,000 occupations that would suggest an occupation according to the initial spelling of the occupation. If the occupation was included in the list, it was automatically coded to ISCO 08. In other cases, the open-ended response was coded to ISCO 08 by a central coding group after the data collection. The coding was performed by coding experts (the same coding staff as in the LFS) using a variety of auxiliary information. 

NACE Rev. 2: For legal reasons, we are not allowed to ask the sample person to confirm register information, but we currently have register information that is updated monthly and is therefore considered of high quality. Respondents who answered that they worked but did not have an organisation number in the register data or that the respondent answered that he/she works as a consultant were asked specific questions about the employer. Responses were coded to NACE by a central coding group after the data collection. The coding was carried out by coding experts (the same coding staff as for the LFS) using a variety of additional information.

Non-formal education: If the respondent had participated in formal education in the last 12 months, a number of questions were asked including the name of the programme, the main content of the programme, the level of the programme and the number of years the individual had studied. The answers were coded according to the Swedish Education Nomenclature (SUN2020), fields at 2-digit level, 26 groups, by a central coding group after the data collection. This coding was performed by coding experts with a lot of additional auxiliary information, such as a special dictionary containing 130,00 learning activities from previous coding material. Once the coding process was completed, the SUN2020 codes were translated into ISCED F fields.

Many variables in the AES 2022 were derived:

1. from a set of variables in the questionnaire

2. with or without additional information from administrative register

None, see table 18.5.1 “Imputation - rate” in annex “SE - QR tables 2022 AES (excel)”.

Not applicable.

Not applicable.

None.