Statistics Norway

Division for Education Statistics

Oterveien 23

2211 Kongsvinger

Norway

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 years permanently residing in Norway (excluding Svalbard).

Individuals living in institutions were excluded.

The total number of people in the target population is 3 632 935.

The whole of Norway, with the exception of Svalbard, is covered.

The Norwegian AES 2022 was conducted from 7 November 2022 to 29 January 2023.

The data collection period for the first round and the second round of AES in Norway were May 2007-August 2007 and March 2012-August 2012 respectively. The third round of AES collected data from October 2016 to February 2017.

In all waves, the reference period are the last 12 months prior to the day of the data collection.

Not applicable.

Number, EUR.

The Norwegian AES 2022 was conducted from 7 November 2022 to 29 January 2023.

The reference period is the last 12 months prior to the day of the data collection.

At European level:

Basic legal act: Regulation (EU) 2019/1700

Implementing act: Commission Implementing Regulation (EU) 2021/861

At national level:

The statistics are developed, produced and disseminated pursuant to Act no. 32 of 21 June 2019 relating to official statistics and Statistics Norway (the Statistics Act). 

Not applicable.

Interviewers and everyone who works at Statistics Norway have a duty of confidentiality. Statistics Norway has its own data protection officer.

Statistics Norway does not publish figures where there is a risk of identifying individual data about persons or households.

The ‘[suppression, rounding up/down, perturbation]’ method is used in these statistics to ensure this.

More information can be found on Statistics Norway’s website under Methods in official statistics, in the ‘Confidentiality’ section.

The data transmitted are de-identified. Anonymization of micro data in order to assure that no individual can be identified.

Not applicable.

Not applicable.

Not applicable.

Every 6 years.

There was an ad-hoc news release when national results from AES 2022 were published on 29.11.2023.

It can be found here: https://www.ssb.no/utdanning/voksenopplaering/statistikk/voksnes-laering/artikler/Arbeidsledige%20%C3%B8nsker%20%C3%A5%20delta%20i%20flere%20utdannings-%20og%20l%C3%A6ringsaktiviteter

National results were published on the 29.11.2023.

Results were accompanied by a news article, and it is planned to write one more article on the results in the course of 2024.

Published tables can be found here: https://www.ssb.no/en/utdanning/voksenopplaering/statistikk/voksnes-laering

AES microdata is shared and disseminated through Sikt – Norwegian Agency for Shared Services in Education and Research.

Statistics based on AES can be found in the following folders of Eurostat's online database.

• Participation in education and training (last 12 months) (trng_aes_12m0)
• Participation in informal learning (last 12 months) (trng_aes_12m4)
• Access to information on education and training (last 12 months) (trng_aes_12m1)
• Time spent on education and training (last 12 months) (trng_aes_12m2)
• Obstacles to participation in education and training (last 12 months) (trng_aes_12m3)
• Self-reported language skills (educ_lang_00)

Please consult Eurostat database.

Not applicable.

Pre-approved research units may apply for access to anonymous micro data.

None.

Not applicable.

Final methodological and implementation report (Statistics Norway, 2023).

Not applicable.

A methodological and implementation report on improving the Norwegian AES 2022 was published 13th of September 2023.

It can be found here: https://www.ssb.no/en/utdanning/voksenopplaering/artikler/final-methodological-and-implementation-report

Several filters and checks for extreme values were implemented in the questionnaires to limit the number of errors. These checks comprised both data entry validity controls and logical consistency checks comparing the information entered for one question with other answers provided by the respondent. The edited dataset was weighted using a method for estimating final weights that was developed by the Division for Statistical Methods and Standards.

AES is an important source of internationally comparable data on participation in education and training. The survey might be challenging for the respondents, especially if they have participated in a lot of different training activities, and it can be difficult to remember all details from the different activities. As a consequence, we have observed an increase in non-response rates for questions on non-formal education activities. This can lead to an increase in uncertainty for some indicators related to non-formal education activities. 

A national methodological and implementation report on AES 2022 was published September 2023.

See table 12.1 “User needs” in annex “NO - QR tables 2022 AES (excel)”.

Not available - no user satisfaction survey has been conducted.

Requirements for data items are met, all variables as required in the legislation are covered.

Not applicable.

Coefficients of variation were estimated using Python. It is important to note that the estimation method used calculates coefficients of variations based on the assumption that the sample is a simple random sample, whereas Norway used stratification when drawing the sample.

Coefficients of variation suggest a high level of accuracy of the estimates. The accuracy does, however, vary. Estimates based on a high number of observations are more accurate than those based on few observations.

A stratified sampling based on age and level of education attainment was used. The share of eligible persons in the different strata corresponds well to the share of these groups of the total population.

The weighted unit non-response rate is calculated using sampling weights for each stratum, calculated as (number of individuals in the population)/(number of individuals in the sample).

See information in table 13.3.3.1 “Unit non-response - rate” in annex “NO - QR tables 2022 AES (excel)”.

See table 13.2.1 “Sampling errors - indicators for 2022 AES key statistics” in annex “NO - QR tables 2022 AES (excel)”.

Estimation of standard error (SE) is performed using a Python script developed by the Division for Education statistics at Statistics Norway. For categorical indicators standard error is estimated using the following equation

For the numerical indicators on "average amount paid by a participant for all expenses related to non-formal learning activities", the following equation is used:

SE = σ/√n,

where σ is the standard deviation of the weighted amount paid by a participant and n is the number of respondents considered for the indicator. 

Coefficients of variation are calculated by dividing the standard error by the estimated value of the indicator. 

Confidence intervals are ±1.96*SE

 See items 13.3.1-13.3.4.

The sampling frame was made up from the Statistics Norway population database, a continuously updated copy of the Central Population Register kept for statistical purposes. However, there is a small number of persons who have left the country but are still registered as residing in Norway, and on the other hand, there are people living in Norway illegally and not being registered. A total of 7000 individuals were sampled. 2000 in the age range 18-24 years and 5000 in the age range 25-69 years. To sample the age range 25-69 years, the sub-population was stratified by educational attainment and age. Categories of educational attainment was chosen to be ISCED 0-2 or no education, ISCED 3-4 and ISCED 5-8. The age categories was chosen to be 25-34 years, 35-54 years and 55-69 years. 

Data were weighted and calibrated against population totals. Age ranges 18-24 years and 25-69 years, were weighted separately. 

The age range 18-24 years was weighted according to two dimensions. The first dimension is sex and status on formal education activity, i.e. whether individuals were registered as students. The second dimension is geographical region.

The age range 25-69 years was also weighted according to two dimensions. For this age range the first dimension included employment status, sex, age and education attainment level. The second dimension is geographical region. 

See table 13.3.1.1 “Over-coverage - rate” in annex “NO - QR tables 2022 AES (excel)”.

Not applicable.

Several automatic checks were implemented in the web-questionnaire to prevent erroneous answers. The web-questionnaire was tested by experts in order to control whether these checks and the filters work correctly, as well as it was checked whether all concepts and definitions are understandable. 

Non-response can be due to a failure in contacting the individual, a refusal or another reason (rejected interviews, inability to respond, etc.).

The overall non-response rate is 50%, but there are significant differences according to educational attainment. The non-response rate is higher among those with low educational attainment and lower among those with higher educational attainment.

To reduce unit non-response, a multi-mode design was used. First, the sample was divided into 15 groups.

All sampled individuals got a digital information letter inviting them to respond to the survey on WEB (CAWI). Technical and professional assistance were available by phone and e-mail. If they did not respond to the questionnaire respondents would be reminded twice through SMS or email, with an interval of five days. If sampled individuals still did not respond, a notice that they would be contacted by an interviewer by phone was sent out through SMS or email. Individuals had the option to decline the invitation for a telephone assisted interview (CATI), and were still allowed to participate in the survey through WEB. If sampled individuals still did not respond after the CATI invitation, a new reminder to participate through CAWI was sent though SMS or email a few days after the CATI interview was scheduled. 

The overall unit non-response rate is estimated to be 50% and 49%, unweighted and weighted respectively. 

For non-response rates for sub-groups of the population see table 13.3.3.1 “Unit non-response - rate” in annex “NO - QR tables 2022 AES (excel)”.

See table 13.3.3.2 “Item non-response rate” in annex “NO - QR tables 2022 AES (excel)”.

Between the data collection and the beginning of statistical analysis for the production of statistics, data must undergo a certain processing: coding, data entry, data editing, imputation, etc.

Raw data were coded according to the AES manual using Python scripts. Data were validated before submission to Eurostat using their integrated validation programme. The programme contains checks for field level errors, checks of the simple coherence between values of a variable and possible allowed entries, and record level errors, checking the consistency of variables for a given record. Moreover, the tool checks the overall structure of the country dataset. 

Not applicable.

The reference period for the 2022 AES is the 12 months leading up to the interview.

29.11.2023

29.11.2023

See table 14.2 “Project phases - dates” in annex “NO - QR tables 2022 AES (excel)”.

Not applicable.

See table 15.1 “Deviations from 2022 AES concepts and definitions” in annex “NO - QR tables 2022 AES (excel)”.

No additional variables related to COVID-19 were collected.

Not applicable.

Indicators on details on non-formal education activities will not be comparable to previous round because of a high item non-response rate. 

A specific example of this is the indicator "share of job-related activities in non-formal education (for those aged 25-64)". This indicator is not comparable with previous rounds because of a high rate of item non-response in the 2022 survey. 

General participation rates are comparable.

See table 15.2 “Comparability - over time” in annex “NO - QR tables 2022 AES (excel)”.

Not applicable.

Since 2003, the Learning Conditions Monitor (LCM) has been a supplementary survey to the Labour Force Survey in the first quarter of each year. The LCM covers the population aged 15-66 years and the concept of non-formal training is defined differently than on AES (guided on-the-job training is excluded), but there is considerable consistency between results from the LCM and AES. Results from the LCM are available here: https://www.ssb.no/en/utdanning/voksenopplaering/statistikk/livslang-laering.

See also table 15.3 “Coherence - cross-domain” in annex “NO - 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.

Administering the survey is burdensome and staff from several different divisions within Statistics Norway are involved in the survey. Preparation of the field work is done by the Division for Social Surveys, whereas the Division for Education Statistics is responsible for editing the data. Moreover, the Division for User contact is involved in providing assistance to respondents having questions about the survey or experiencing problems with the web questionnaire. Overall, the different divisions spent around 2300 hours on the survey.

For the fieldwork, both CAWI and CATI interviews were used. 983 hours were spent on conducting CATI interviews.

The average time for a CATI interview was 20 minutes.

Not applicable.

Not applicable.

Not applicable.

The sampling frame was made up from the Statistics Norway population database, a continuously updated copy of the Central Population Register kept for statistical purposes. Updates of the register are done in part by the local population registries that register all residents in a municipality and by The Norwegian Tax Administration, which has administrated the register since 1991. The quality of the Central Population Register is very good for statistical purposes. However, there is a small number of persons who have left the country but are still registered as residing in Norway, and on the other hand, there are people living in Norway illegally and not being registered. A total of 7000 individuals was sampled. 2000 in the age range 18-24years and 5000 in the age range 25-69 years. The latter sub-population (25-69 years) was stratified by educational attainment and three age groups (25-34 years, 35-54 years, 55-69 years).

Data were weighted and calibrated against population totals. Age ranges 18-24 years and 25-69 years, were weighted separately. 

The age range 18-24 years was weighted according to two dimensions. The first dimension is sex and status on formal education activity, i.e. whether individuals were registered as students. The second dimension is geographical region.

The age range 25-69 years was also weighted according to two dimensions. For this age range the first dimension included employment status, sex, age and education attainment level. The second dimension is geographical region. 

See also table 18.1 “Source data” in annex “NO - QR tables 2022 AES (excel)”.

Every 6 years.

See also table 18.1 “Source data” in annex “NO - QR tables 2022 AES (excel)”.

Several filters and checks for extreme values were implemented in the questionnaires to limit the number of errors. These checks comprised both data entry validity controls and logical consistency checks comparing the information entered for one question with other answers provided by the respondent. These checks worked well. The post-data collection processing was done by the Division for Education Statistics. Raw data was coded and edited according to the code book in the Eurostat Manual for AES. These data were checked with the control program provided by Eurostat.

See item 18.1 for weighting.

No imputation was done.

See table 18.5.1 “Imputation - rate” in annex “NO - QR tables 2022 AES (excel)”.

Not applicable.

Not applicable.

None.