Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.
Directorate Social Statistics - Science, Technology, Education
1.3. Contact name
Restricted from publication
1.4. Contact person function
Restricted from publication
1.5. Contact mail address
1.6. Contact email address
Restricted from publication
1.7. Contact phone number
Restricted from publication
1.8. Contact fax number
Restricted from publication
2.1. Metadata last certified
16 January 2024
2.2. Metadata last posted
16 January 2024
2.3. Metadata last update
16 January 2024
3.1. Data description
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
The strict confidentiality provisions of the Austrian Federal Statistic Act 2000 regulate the handling of sensitive data relating to individuals and organisations.
7.2. Confidentiality - data treatment
The Statistics Act contains measures for the protection of the right to confidentiality of individuals and organisations as well as measures for ensuring the confidentiality of micro data. These include the deletion of names and addresses at the earliest possible moment and the obligation of secrecy imposed on persons entrusted with tasks of official statistics. Compliance with confidentiality provisions is monitored by a data protection agent who acts as an internal controlling body.
8.1. Release calendar
Press release is planned for the 09.01.2024. A release calendar is available on the website of Statistics Austria.
Tables with main results will be made available on the homepage of Statistics Austria in the 1st quarter of 2024. Microdata for scientific use will be provided through the Austrian Micro Data Center (AMDC) in the 1st quarter of 2024. A comprehensive print publication will be available in the 4th quarter of 2024.
Every 6 years.
10.1. Dissemination format - News release
Press release is planned for 09.01.2024.
10.2. Dissemination format - Publications
Tables with main results are planned to be made available on the homepage of Statistics Austria on 09.01.2024. Moreover, a research report with all main results will be published on the homepage of Statistics Austria in the 4th quarter of 2024 that can be downloaded for free.
10.3. Dissemination format - online database
Excluding EUROSTAT online database, no other online database will be available for Austrian AES results.
10.3.1. Data tables - consultations
Not applicable.
10.4. Dissemination format - microdata access
Anonymized microdata for scientific use will be provided through the Austrian Micro Data Center (AMDC) in the first quarter of 2024.
10.5. Dissemination format - other
None.
10.5.1. Metadata - consultations
Not applicable.
10.6. Documentation on methodology
National standard documentation about AES 2022/23 will be published in 2024.
10.6.1. Metadata completeness - rate
Not applicable.
10.7. Quality management - documentation
National standard documentation about AES 2022/23 will be published in 2024.
11.1. Quality assurance
Preparation:
Cognitive interviews on certain variables and expert comments of the national working group on adult education were taken into consideration for the national questionnaire.
Pre-Testing (CAPI and CAWI) was undertaken and the interviewers took part at trainings at Statistics Austria.
Paper interview guidelines about the survey were available.
Website with information about the Adult Education Survey with FAQ, questionnaire etc. was set on the homepage of Statistics Austria.
Fieldwork:
Respondents got printed advance notifications with information on the AES.
By using computer-assisted interview-techniques a system of checks and warnings operative directly in the interview situation was applied.
Daily monitoring reports on response rate were carried out.
Reminders and follow-ups were administered during the fieldwork period.
Data processing:
The test procedures based on the predetermined checking rules referred to the AES manual (Eurostat) were undertaken.
Further plausibility checks (e.g. highest level of education, field of education, HATYEAR, JOBTIME etc.) took place in order to verify that the data respectively the codes don´t contain errors.
11.2. Quality management - assessment
Strengths:
The Adult Education Survey provides extensive and deepening data about adult education and learning activities.
Coherence with previous results of AES.
The usability of the questionnaire was tested and evaluated in both modes.
Interviewers participated in a training course which covered alle themes, concepts and objectives of the survey.
Respondents were able to ask for help via a hotline.
Weaknesses:
There were two filter errors present in the first wave of data collection:
Respondents mistakenly were able to select „not stated/ I don´t know“ for NFENUM (Number of non-formal learning activities). The list in which participants named their non-formal education activities and the following random selection of these activities was tied with a filter to NFENUM. Therefore, for some respondents (n = 284 of a total of N = 4389 participants with NFE = 1) the detailed questions about non-formal education are missing.
Similarly, the variable WANT was tied to the same question (NFENUM) which also led to missing variables in the obstacles part of the survey (n = 304 of a total of N = 7826).
In total n = 403 of a total of N = 7826 respondents have missing values in either or both of these key variables.
In agreement with EUROSTAT and because NFENUM is a mandatory variable, NFENUM was set to the number of agreements in the variables NFECOURSE, NFEWORKSHOP, NFEGUIDEDJT and NFELESSON for these respondents.
Non-formal activities might be affected by remembrance problems; especially volume of instruction time and costs could be concerned by measurement problems.
12.1. Relevance - User Needs
The main user groups for Austrian AES data are:
Policy makers at European level (e.g. European Commission, European Parliament, other European agencies)
Policy makers at national level (e.g. ministries)
Social actors (e.g. employers' associations, trade unions)
Media
Researchers, students
International organisations (OECD, UN)
AES results are an important source of information to policy makers at the national level. Results serve as a benchmark for adult learning in the population and give direction and incentive to further improve participation in adult education.
12.2. Relevance - User Satisfaction
There are no measures available at national level to analyse user satisfaction on 2022 AES.
12.3. Completeness
The dataset covers all variables as requested by the legislation.
12.3.1. Data completeness - rate
Not applicable.
13.1. Accuracy - overall
Sample size was calculated in order to fulfil pre-defined criteria according to sample and precision requirements defined in the EU regulation. The survey faced relative high unit- and item- non-response rates, but complex methods for weighting and imputation (see table 18.5.1 “Imputation - rate” in annex “AT - QR tables 2022 AES (excel)” were employed to prevent any systematic bias. We assume a high accuracy of our estimates.
13.2. Sampling error
The requirement for the sampling error in the regulation was met by the sample, see table 13.2.1 “Sampling errors - indicators for 2022 AES key statistics” in annex “AT - QR tables 2022 AES (excel)”.
13.2.1. Sampling error - indicators
See table 13.2.1 “Sampling errors - indicators for 2022 AES key statistics” in annex “AT - QR tables 2022 AES (excel)”.
For the calculation of variation measures bootstrap weights were generated with respect to the survey design. Implementation took place with the surveyed package in R.
13.3. Non-sampling error
Non-sampling errors are covered by items 13.3.1 - 13.3.5 below.
13.3.1. Coverage error
390 persons were identified as over-coverage which is 2.1 percent of the sample.
13.3.1.1. Over-coverage - rate
See table 13.3.1.1 “Over-coverage - rate” in annex “AT - QR tables 2022 AES (excel)”.
13.3.1.2. Common units - proportion
Not applicable.
13.3.2. Measurement error
In order to reduce measurement errors Pre-Testing (CAPI and CAWI) was undertaken and the interviewers took part in trainings at Statistics Austria (before the fieldwork started).
Additionally, a system of checks and warnings was implemented into the E-Questionnaire according to the validation rules.
Systematic errors are not known.
13.3.3. Non response error
Overall, the response rate surpassed the anticipated target. However, consistent with the typical pattern in AES, response rates were higher among younger and more educated participants (especially in CAWI-Mode). To mitigate bias, using the experience from previous AES surveys efforts were made to ensure that groups with traditionally low response rates were adequately represented in the sample. Furthermore, the following measures were implemented to address non-response bias:
Unit Non-Response:
Respondents were given the option of receiving a gift, either in the form of a shopping voucher or by choosing to make a donation to a natural reserve project.
CAWI respondents received a pre-incentive in the form of a special two Euro coin.
Printed advance notifications containing information about the AES were sent to respondents, allowing them to schedule a telephone interview appointment.
Multiple contact attempts were made to reach respondents.
Reminders and follow-ups were sent out.
Respondents were permitted to switch between modes (CAWI-CAPI).
Interviewers were provided with specific instructions, including additional information about the study's concept and specific questions.
Item Non-Response:
Considerable item non-response was mainly observed for variables concerning monetary values. In such cases, the K-nearest neighbour method was employed for imputation.
13.3.3.1. Unit non-response - rate
See table 13.3.3.1 “Unit non-response - rate” in annex “AT - QR tables 2022 AES (excel)”.
13.3.3.2. Item non-response - rate
See table 13.3.3.2 “Item non-response rate” in annex “AT - QR tables 2022 AES (excel)”.
13.3.4. Processing error
The questionnaire provided fixed response options for most questions, minimizing processing errors. However, certain variables (HATFIELD, JOBISCO, LOCNACE, FEDFIELD, NFEFIELD1, and NFEFIELD2) allowed for open-ended responses, which were coded by Statistics Austria's coding experts post-interview.
13.3.5. Model assumption error
No model calculated.
14.1. Timeliness
The reference period for the 2022 AES were the 12 months prior to the interview.
14.1.1. Time lag - first result
1st quarter of 2024.
14.1.2. Time lag - final result
Not applicable.
14.2. Punctuality
No deviations. See table 14.2 “Project phases - dates” in annex “AT - QR tables 2022 AES (excel)”.
14.2.1. Punctuality - delivery and publication
Not applicable.
15.1. Comparability - geographical
See table 15.1 “Deviations from 2022 AES concepts and definitions” in annex “AT - QR tables 2022 AES (excel)”.
No additional variables related to COVID-19 were collected.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable.
15.2. Comparability - over time
Despite changing modes (from mainly CAPI to mainly CAWI) results between AES 2022/23 and AES 2016/17 and between both modes are coherent. A pilot study was conducted in March of 2022 and logistical regression did not reveal any significant effect of modes on respondent answer behaviour. A detailed report of the pilot can be found in the annex below.
See table 15.2 “Comparability - over time” in annex “AT - QR tables 2022 AES (excel)”.
See table 15.3 “Coherence - cross-domain” in annex “AT - QR tables 2022 AES (excel)”.
15.3.1. Coherence - sub annual and annual statistics
Not applicable.
15.3.2. Coherence - National Accounts
Not applicable.
15.4. Coherence - internal
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.
The average time for answering the questionnaire CAPI/CAWI was 21 minutes.
17.1. Data revision - policy
Not applicable.
17.2. Data revision - practice
Not applicable.
17.2.1. Data revision - average size
Not applicable.
18.1. Source data
1) Sampling frame is the Central Register of Registration (ZMR) and the sampling unit is a single person; data from the Central Register of Registrations (ZMR) concerning valid main residence registrations has been forwarded quarterly to Statistics Austria since 2002. Processing of the databases is based on a uniform concept for classifying registration results for the purposes of demographic analyses. The sample was drawn in two parts with the reporting dates 30.06.2022 and 30.09.2022, respectively. The delayed drawing of the second sample made it possible to adjust sampling for low response groups in the first half of the fieldwork period.
2) The survey is based upon a stratified random sample. The total sample size was determined by precision requirements as defined in the regulation. Thus the net sample was fixed with a size around 5000 persons for the population between 25 and 69 years and 2000 persons for the population between 18 and 24 years. The strata are defined by interviewer region and 3 groups with different NFE participation probabilities. These 3 groups use the variables age, gender, nationality and education.
See also table 18.1 “Source data” in annex “AT - QR tables 2022 AES (excel)”.
18.2. Frequency of data collection
Every 6 years.
18.3. Data collection
See attached files and also table 18.1 “Source data” in annex “AT - QR tables 2022 AES (excel)”.
A system of checks and warnings was implemented into the E-questionnaire. Pop-ups for invalid or implausible values directly informed the respondent or interviewer to recheck or correct their answers.
National testing:
The national version of the AES questionnaire data set underwent transformation into the default EU code book structure using statistical software (R). Testing procedures adhered to pre-established checking rules outlined in the AES manual (Eurostat), supplemented by additional plausibility checks (e.g., highest level of education, field of education, HATYEAR, JOBTIME, etc.) to ensure the absence of data or coding errors. Additionally, data were compared to LFS and previous AES data to ensure plausibility.
Eurostat testing:
The final data set underwent validation through the online checking tools STRUVAL and CONVAL, and thus only contain verified and valid values.
18.5. Data compilation
Weighting:
Weighting was performed by iterative proportional fitting according to the distribution of the number of persons in AgeGroups(4) X Education(5) X Gender, AgeGroups(10) X Gender, Gender X Occupational Status and NUTS2. Different non-response models were tested, however since the models performed poorly it was decided to skip the step.
Imputation:
Imputation was performed using the k-nearest neighbour method for the variables (HHINCOME, NFEPAIDVAL1, NFEPAIDVAL2 and LANGMOTH1).
18.5.1. Imputation - rate
See table 18.5.1 “Imputation - rate” in annex “AT - QR tables 2022 AES (excel)”.
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
Population stock - third quarter of 2022 - aged 18 to 69: 6 135 974 persons.
Sample drawn from Central Register of Registration (ZMR): 18 751 persons.
Respondents in final data set transmitted to Eurostat: 7 826.
Austria.
Persons living in collective households are excluded.
The fieldwork period took place between 01.10.2022 and 31.03.2023.
The reference period are the 12 months prior to the interview.
Sample size was calculated in order to fulfil pre-defined criteria according to sample and precision requirements defined in the EU regulation. The survey faced relative high unit- and item- non-response rates, but complex methods for weighting and imputation (see table 18.5.1 “Imputation - rate” in annex “AT - QR tables 2022 AES (excel)” were employed to prevent any systematic bias. We assume a high accuracy of our estimates.
Number, EUR.
Weighting:
Weighting was performed by iterative proportional fitting according to the distribution of the number of persons in AgeGroups(4) X Education(5) X Gender, AgeGroups(10) X Gender, Gender X Occupational Status and NUTS2. Different non-response models were tested, however since the models performed poorly it was decided to skip the step.
Imputation:
Imputation was performed using the k-nearest neighbour method for the variables (HHINCOME, NFEPAIDVAL1, NFEPAIDVAL2 and LANGMOTH1).
1) Sampling frame is the Central Register of Registration (ZMR) and the sampling unit is a single person; data from the Central Register of Registrations (ZMR) concerning valid main residence registrations has been forwarded quarterly to Statistics Austria since 2002. Processing of the databases is based on a uniform concept for classifying registration results for the purposes of demographic analyses. The sample was drawn in two parts with the reporting dates 30.06.2022 and 30.09.2022, respectively. The delayed drawing of the second sample made it possible to adjust sampling for low response groups in the first half of the fieldwork period.
2) The survey is based upon a stratified random sample. The total sample size was determined by precision requirements as defined in the regulation. Thus the net sample was fixed with a size around 5000 persons for the population between 25 and 69 years and 2000 persons for the population between 18 and 24 years. The strata are defined by interviewer region and 3 groups with different NFE participation probabilities. These 3 groups use the variables age, gender, nationality and education.
See also table 18.1 “Source data” in annex “AT - QR tables 2022 AES (excel)”.
Every 6 years.
The reference period for the 2022 AES were the 12 months prior to the interview.
See table 15.1 “Deviations from 2022 AES concepts and definitions” in annex “AT - QR tables 2022 AES (excel)”.
No additional variables related to COVID-19 were collected.
Despite changing modes (from mainly CAPI to mainly CAWI) results between AES 2022/23 and AES 2016/17 and between both modes are coherent. A pilot study was conducted in March of 2022 and logistical regression did not reveal any significant effect of modes on respondent answer behaviour. A detailed report of the pilot can be found in the annex below.
See table 15.2 “Comparability - over time” in annex “AT - QR tables 2022 AES (excel)”.
