Methodology and Quality Update

Latest Update on Methodology and Quality

07/01/2026

Statistical Presentation

Data description

The Adult Skills and Learning Survey provides comprehensive statistical data on the participation of the population aged 15 years and over in education in the Kingdom of Saudi Arabia. The survey aims to measure education characteristics, educational attainment, and literacy, thereby supporting the monitoring of relevant national and international indicators related to human development.
The Adult Skills and Learning Statistics Publication is a survey conducted to collect data on the main characteristics as follows: 
•    Youth participation rate (aged 15–24) or (aged 15–64) in formal and non-formal education and training.
•    Mean years of schooling of the population (aged 25 years and over).
•    Educational attainment rate of the population (aged 25 years and over).
•    Upper secondary completion rate.
•    Adult literacy rate of the population (aged 15 years and over).
Data is also used to estimates:
•    Youth participation rate in formal and non-formal education and training.  
•    Participation rate of the population (aged 15–64) in formal and non-formal education and training.
•    Percentage of the population (aged 25 years and over) participating in training by educational attainment. 
•     Percentage of the population (aged 17 years and over) enrolled in higher education by field of study.
•    Percentage of the population (aged 15 years and over) interested in participating in education and training in the next three years.
•    Percentage of the population (aged 15 and above) participating in training by entities providing training programs. 
•    Percentage of the population (aged 15 years and over) participating in training by training funder. 
•    Percentage of the population (aged 15 years and over) participating in training by training mode. 
•    Educational attainment rate of the population (aged 25 years and over).
•    Educational attainment rate of women (aged 25–64) by highest educational qualification.
•    Educational attainment rate of the population (aged 25 years and over) with secondary education or higher.
•    Percentage of the population (aged 25–34) with higher education.
•    Percentage of the population (aged 25 years and over) with higher education by field of study.
•    Mean years of schooling of the population (aged 25 years and over). 
•    Upper secondary completion rate. 
•    Adult literacy rate of the population (aged 15 years and over).
The results are presented through statistical tables, charts, and analytical publications.

Classifications

The following classifications are applied in the Adult Skills and Learning Statistics Publication.
The National Classification for Economic Activities (ISIC4):
The statistical classification based on the International Standard of Industrial Classification of All Economic Activities (ISIC4) is used to describe the productive activities of an establishment.
Saudi Standard Classification of Occupations(ISCO_08):
A statistical classification based on the International Classification  (ISCO_08) that provides a system for the classification and compilation of professional information obtained through censuses, statistical surveys, and administrative records.
This classification is used in the Adult Skills and Learning Survey to classify employed persons according to their occupations.
Saudi Classification of Specializations and Educational Levels (SASCED-20):
A statistical classification issued by the Ministry of Education in 2020, based on the International Standard Classification of Education (ISCED 2011) and (ISCED 2013) for education and training. It serves as the reference classification for organizing educational programmes and qualifications according to their educational levels and fields of study. The classification is comprehensive, covering all educational programmes, levels, and modes of education, and spans all stages of education from early childhood education through to postgraduate levels, representing the broad field of education. The classification was issued by the Ministry of Education in 2020.
This classification is used in the Adult Skills and Learning Survey to classify individuals aged 15 years and over according to their fields of study and levels of education.
National Code of Countries and Nationalities (3166 ISO – codes Country):
A statistical classification based on the international standard  (ISO 3166_Country codes), which is a standard issued by the International Organization for Standardization (ISO of the UN), and this classification gives numeric and literal codes for the world’s (248) countries, based on the classification of countries.
This classification is used in the Adult Skills and Learning Survey to classify individuals as Saudi and non-Saudi.
Metadata is collected through interviews, so that outputs can be produces in accordance with all relevant classifications.
The classifications are available on the GASTAT’s website: https://www.stats.gov.sa/classifications 

Statistical concepts and definitions

Terms and concepts of Adult Skills and Learning Statistics Publication:
•    Learning:
The individual acquisition or modification of information, knowledge, understanding, attitudes, values, skills, competencies, or behavior through experience, practice, study, or instruction.
•    Formal learning:
Formal education and training are defined as education provided by the system of schools, colleges, universities, and other formal educational institutions, which usually constitute a continuous “ladder” of full-time education for children and young people, starting between the ages of 5 and 7 and continuing up to the ages of 20 or 25. In some countries, at the upper levels of this “ladder”, there are organized programmes that combine part-time work with part-time participation in the regular school and university system. 
•    Non-formal learning: 
Non-formal education and training are defined as any organized and sustained learning activities that do not fully correspond to the definition of formal education provided above. Therefore, non-formal learning can occur both within and outside educational institutions, meeting the learning needs of people of all ages. Depending on national contexts, it may cover educational programmes aimed at adult literacy, life skills, work-related skills, and general culture.
•    Learning:
The individual acquisition or modification of information, knowledge, understanding, attitudes, values, skills, competencies, or behavior through experience, practice, study, or instruction.
•    Learning modes:
-    Virtually (online):
A mode of distance education delivered through the Internet, in which the learner is spatially and/or temporally separated from the instructor.
-    In-person:
Education or training that takes place with the learner present within an integrated educational system, which includes the essential elements of the educational process, such as direct interaction between the instructor and the learner, or among learners themselves, within the premises of the educational institution.
-    Hybrid (virtual and in-person):
A mode of e-learning that combines conventional education and distance education within the approved learning hours.
•    Educational attainment:
The highest level of education, as defined by ISCED, successfully completed by an individual. It is usually measured with reference to the highest educational programme successfully completed, typically certified by a recognized qualification. Intermediate qualifications are classified at a lower level than the level of the programme itself.
•    Literacy rate: 
The number of literate persons in a specific age group, expressed as a percentage of the total population in that age group.
•    Mean years of schooling:
The average number of years of schooling attained by persons aged 25 years and over, converted from levels of educational attainment using the official durations for each level of education.

Data sources

The primary data source for the Adult Skills and Learning Statistics Publication is the Adult Skills and Learning Survey 2025. 
The main variables published for the Adult Skills and Learning Statistics Publication are:
•    Sex.
•    Nationality.
•    Age groups.

Designing the data collection tool

The data were collected using a questionnaire prepared and designed by specialists at the General Authority for Statistics. The data collection instrument was developed in an electronic format (CAPI) to ensure ease of use by field researchers. In its design, international recommendations, standards, and definitions were taken into account. The questionnaire was also shared with relevant stakeholders to obtain their views and feedback. Furthermore, the questions were formulated clearly and scientifically to standardize the wording and guidance of questions. 
The questionnaire includes several sections, including: 
•    Demographic characteristics.
•    Participant demographic information.
•    Educational attainment.
•    Education.
•    Training.
•    Basic skills.
•    Challenges in enrolling in education or training.
•    Desire to enroll in education or training.
•    Barriers to enrollment in education or training.
•    Work.
•    General health.
Method of calculating the indicators:

Review and Correction Rules:

Audit and control rules have been established in the form to ensure that the data collected is consistent, accurate, and logical. These rules were designed by establishing logical relationships between responses, questions, and different variables to help the field researcher detect any errors directly during data entry.
To ensure the quality of the Adult Skills and Learning Survey data, three types of review and correction rules were established, as follows:
•    Navigation rules between sections and fields:
Special rules were programmed to control automated navigation between sections and fields based on the respondent’s inputs, totaling 17 rules.
•    Error rules:
 These are rules that cannot be bypassed during the data entry process; therefore, the field researcher is required to revise the data by referring back to the respondent to verify its accuracy. The number of such rules exceeds 19.
•    Alert rules (warnings):
These rules are designed to verify the correctness of the data entered by the researcher. The field researcher may override them if the data accuracy is confirmed, with a total of approximately 35 rules.

Questionnaire test (cognitive test)

Cognitive testing was conducted on a number of questionnaire items. The interview sample consisted of a random sample of households distributed across the regions of the Kingdom of Saudi Arabia. 
During the cognitive testing process, the following evaluation pillars were taken into consideration: The overall concept of the question, clarity of question wording, clarity of terms used in the question, appropriateness of the response options, participants’ ability to answer the questions effectively, and the extent to which participants were willing to disclose their answers. This process resulted in a report summarizing the full findings of the cognitive test.

Statistical population

The statistical population of the Adult Skills and Learning Statistics Publication consists of the population of the Kingdom of Saudi Arabia, specifically the civilian population who are not institutional residents and who reside in private dwellings, aged 15 years and over. Accordingly, institutional residents such as those in hospitals, prisons, and care homes are excluded. The target population also does not include full-time members of the armed forces.
With regard to non-Saudi households, eligibility requires that the household occupying the dwelling has resided in the Kingdom for at least six months at the time of the survey.
It should be noted that the sampling unit is the dwelling, and the household occupying the dwelling is considered the unit of study through which data are collected, while the individual aged 15 years and over represents the statistical unit on which the survey’s characteristics and statistical indicators are measured.

Sample Design

Sample type:
A three-stage stratified systematic cluster random sample was used, and stratification was carried out as follows:
•    Governorates were used as actual strata due to the need to produce survey indicators separately for each governorate.
•    The degree of urbanization (urban, rural) was used as the actual strata.
To ensure adequate statistical representation of the different categories of the target population.
Sampling frame:
The survey relied on the sampling frame derived from the Saudi Census 2022 data.
Primary sampling unit:
The sampling unit is the dwelling, the household is considered the unit of study, and the individual aged 15 years and over is the unit of statistical analysis.
Sample size and allocation:
The sample size amounted to 30,814 households distributed across 1,419 enumeration areas, covering all thirteen administrative regions of the Kingdom. The sample within each region was allocated using the probability proportional to size (PPS) method based on the number of households.

Sample size estimation formula:
The sample size was calculated using the following formula for each administrative region separately:

Where:

•    : Sample size for each stratum ℎ  (study domain).
•     : Estimated design effect for each stratum ℎ  (study domain).
•     : Expected response rate for each stratum ℎ (study domain).
•     : The allowable margin of error in estimating the participation rate in formal and non-formal education for the population aged 15 years and over for each stratum h (study domain).
•    : Estimated proportion of the participation rate in formal and non-formal education for the population aged 15 years and over in stratum h (study domain).
•   α : Confidence level coefficient for the stated proportion for each stratum ℎ (study domain). 
•     : It is the population size for each stratum ℎ (domain of study).
Distribution of the sample at the level of administrative regions:

Statistical precision level:
The sample size was calculated using the following parameters and specifications:
The estimates calculated from the sample have a specified level of precision and a defined coefficient of variation (CV). The allowable coefficient of variation used in calculating the sample size at the Kingdom level was less than 1%, while at the administrative region level, the allowable coefficient of variation ranged between 5.9% and 16.1%.
An expected response rate of 60% was assumed. However, after calculating the sample size and comparing it with the sample size from the previous survey cycle (2024), and upon reviewing the coefficient of variation (CV) observed in the previous cycle, the response rates used in calculating the sample size were adjusted in light of the actual response rates from the previous cycle. This adjustment ensured that the resulting sample size and the resulting coefficients of variation complied with the specifications set out in item (1) above.
 A confidence level of (1−α) = 0.95 was used in calculating the estimates.
Coverage and representation:
The sample covers all administrative regions of the Kingdom, excluding institutional residents, full-time members of the armed forces, and households that are not eligible according to the definition of the target population. 

Statistical unit (sampling unit)

The statistical unit for which data are collected directly in the Adult Skills and Learning Survey is the individual aged 15 years and over.

Data collection

Data for the Adult Skills and Learning Survey were collected using Computer-Assisted Telephone Interviewing (CATI), whereby eligible respondents within the selected households were contacted using the telephone numbers recorded in the sampling frame. This method enabled efficient access to respondents, reduced data entry errors, and allowed the application of automated validation rules during the interview.
A standardized questionnaire equipped with logical skip patterns, real-time alert messages, and data entry controls was used to ensure data quality during data collection.
Data collection from administrative records: 
This does not apply to this survey, as the Adult Skills and Learning Survey relies on primary survey data collected directly from respondents, and no data from administrative records or official databases are integrated.
Validation applied during data entry (for all sources): 
A set of quality checks was applied during data entry, including:
•    Validity and consistency checks between variables.
•    Verification of data completeness and ensuring that mandatory fields are completed.
•    Logical checks for valid ranges and permissible values.
•    Prevention of duplication and detection of conflicting data.
Review and Correction Rules: 
Automated validation and editing rules were implemented within the data collection system, including real-time alert messages for interviewers when illogical values were entered, in addition to subsequent reviews conducted by supervision teams using the data management tools approved by the Authority.
Alert rules:
•    Immediate alert when a mandatory field is left blank.
•    Alert triggered when inconsistencies are detected between related responses (such as literacy and educational attainment).
Error rules: 
•    Error triggered when inconsistencies exist between related responses (such as age and educational attainment).
Skip / routing rules:
•    Automatic navigation between questions based on the respondent’s answers.
•    Skipping non-applicable questions according to individual characteristics (such as age and educational status).

Data collection frequency 

Data collection for the Adult Skills and Learning Statistics is conducted on an annual basis.

Reference area

The Adult Skills and Learning Statistics Publication covers the 13 administrative regions of the Kingdom of Saudi Arabia.

Reference period (time reference)

The data of the Adult Skills and Learning Survey refer to the 2025 reference year, and its results represent the statistical phenomenon during the data collection period extending from 28 September to 9 November 2025.
It should be noted that the data collected in the Adult Skills and Learning Survey refer to different time periods depending on the nature of the statistical variable, as follows:
•    Demographic and educational characteristics of individuals: Refer to a specific point in time represented by the date of interviewing with the individual.
•    Participation in formal and non-formal education and training: Refer to a time period covering the twelve months preceding the date of the interview.
•    Participation in training activities: Refer to the twelve months preceding the date of the interview.
•    Desire to participate in future education or training: Refers to a specified future period represented by the three years following the date of the interview.
All reference periods associated with the different variables were defined and documented to ensure clarity in the interpretation of results and accuracy in statistical comparisons.

Base period

Not applicable.

Measurement unit

The data of the Adult Skills and Learning Survey include several units of measurement that vary according to the statistical variable, as follows:
•    Percentage:
Such as participation rates in formal and non-formal education, and educational attainment rates.
•    Rates:
Such as mean years of schooling.
The units of measurement for each statistical indicator were standardized across all tables and publications, with the unit of measurement clearly indicated in table titles and outputs, ensuring ease of understanding and comparability.

Time coverage

The data of the Adult Skills and Learning Survey cover an annual time period, whereby the results of each release represent the status of the target population during the survey reference year.
Data are available from 2024 to 2025.

Publication frequency

The results of the Adult Skills and Learning Statistics are published on an annual basis in accordance with the approved statistical plan.

Statistical processing

Error detection

Rigorous processes were implemented to detect errors in the data collected during the telephone survey and stored in the data lake. This was achieved through automating the data collection tool and establishing the necessary constraints and procedures to control and manage the entered data, in order to ensure quality, accuracy, and consistency. In addition, supporting methods were used to measure quality indicators and examine the data to detect anomalies using clear validation rules, including the following:
First: Missing value errors:
•    Identification of required fields.
•    Cases of non-response.
Second: Duplication errors:
•    Verification of the absence of duplicate records using unique identifiers.
Third: Automatically correctable outlier errors:
•    Correction of illogical values using computational and standard rules.
Fourth: Errors requiring manual intervention:
•    Individual review of outlier cases by specialists.
•    Documentation of the cause of the error and implementation of appropriate corrective action.

Data integration and matching from multiple sources 

Not applicable, as Adult Skills and Learning Statistics rely on a single primary data source only.

Imputation and calibration

Sample weights:
Sampling weights are factors used in analyzing data collected from a sample rather than from the entire population. Their purpose is to correct for biases resulting from differences in selection probabilities among households in the sample. This helps ensure that the analysis results are more accurately representative of the population.
Main uses of sampling weights:
Bias correction: Adjusting for biases resulting from unequal selection probabilities among members of the population.
Population representation: Ensuring that the results derived from the sample accurately reflect the true characteristics of the population.
Calculation of sampling weights:
When drawing the sample using the SPSS program,    design weights are automatically calculated at the household level and appear under the name “SampleWeight_Final”.
The design weight is expressed as the inverse of the selection probability of each individual in the sample; if it is not available, it can be calculated as follows:
If the selection probability of individual i from stratum h is denoted by   , then the weight of the individual selected in the sample is calculated as follows:  

Where:
•    m = Number of enumeration areas in the sample for each stratum.
•    M = Number of enumeration areas in the frame for each stratum.

Where:
•    n = Number of households in the sample for each enumeration area.
•    N = Number of households in the frame for each enumeration area.

Weight adjustment:
Adjustment due to the exclusion of part of the population:
Weight adjustment to compensate for non-response or missing data to ensure proper representation of the sample. This adjustment is made after data collection and identifying the response cases, and is calculated using the following formula :

Where:
•      : The non−response adjusted weight for household i in stratum h 
•    :  The design weight for household i  in stratum h.
•    :  The adjustment factor for each enumeration area m in stratum h, which is calculated as follows:  

Where:
R represents the responses and NR represents the non-responses .
Weight calibration (final weights):
When the survey indicators relate to individuals, the weights are calibrated (adjusted) to align with the population distribution based on known characteristics such as age, sex, nationality, and administrative region. This ensures adequate representation and coverage of the sample according to these characteristics. In cases where under-representation or insufficient numbers of responding individuals are observed for the aforementioned characteristics, two options are available:
•    The first: option is to merge weight calibration classes that have no sample or contain a very small sample with other classes that have a high response rate.
•    The second: option is to use the raking weights method instead of post-stratification.
Calculation of weights for individuals aged 15 years and over using the raking weights method.

Objective: A two-dimensional raking procedure will be implemented to calibrate the sample weights to population estimates, with calibration conducted using two levels.
•    At the Kingdom level:
calibration classes were created based on a combination (code) of five-year age groups, nationality, and sex, and were labeled as (dim2). 
•    At the administrative region level (ADMIN):
 calibration classes were created based on a combination (code) of the administrative region code, age groups (15–39 and 40+), nationality, and sex. and referred to as (dim1).
The program consists of the following main components:
•    Reading the data file (Member_ETS) and the population projection files (dimension1) and (dimension2).
•    Trimming (capping) of design weights to eliminate outliers in the weights.
•    Specification of the sample design.
•    Calibration of the trimmed weights.
•    Review of the calibrated (final) weights.
•    Saving the calibrated (final) weights to an Excel file.
Table of survey response outcomes after the data collection process is as follows:

Seasonal adjustments

Not applicable, only final results will be published.

Adjustment of preliminary results 

Not applicable, only final results will be published.

Resources used

Quality dimensions

Suitability

A criterion that indicates the extent to which the product meets users’ needs.

User needs 

The General Authority for Statistics is keen to systematically and regularly collect users’ feedback on the statistical product and microdata through multiple channels aimed at assessing satisfaction levels and improving the quality of statistical products in line with users’ needs.
Summary of user satisfaction measurement procedures.
User satisfaction is measured using a set of tools, including:
•    Electronic user satisfaction surveys available through the statistical dissemination website.
•    Workshops and consultative meetings with government entities and relevant stakeholders.
•    Analysis of inquiries, feedback, and complaints received through official communication channels.
Internal users at the General Authority for Statistics for Adult Skills and Learning Statistics Publication data:
•    Social statistics:
-    Population, gender and diversity.
-    Living conditions, lifestyles and justice statistics.
-    Labor market statistics.
-    Health and education statistics.
Several external users and beneficiaries greatly benefit from the Adult Skills and Learning Statistics Publication, including:
•    Government entities.
•    Regional and international organizations.
•    Research institutions.
•    Media.
•    Individuals.
Key variables most utilized by external users:

The user satisfaction measurement tools were designed to cover the following aspects:
•    Quality of statistical content (accuracy, coverage, and clarity).
•    Ease of access to and use of data.
•    Relevance and reliability in meeting users’ needs.
•    Timeliness of dissemination and level of detail in statistical outputs.
The measurement results are analyzed on a regular basis to derive user satisfaction indicators, such as:
•    Percentage of users satisfied with the statistical product.
•    Assessment of specific aspects (clarity, ease of use, and timeliness of dissemination).
Actions taken to improve user satisfaction.
Based on the results of user satisfaction assessments, the following actions are taken:
•    Implementation of continuous improvement plans for statistical products.
•    Development of interactive channels to receive suggestions and feedback.
•    Enhancement of transparency in sharing improvements responsive to users’ feedback.
•    Engagement of users at early stages of statistical product development.
Notes to end users:
An effective mechanism is available to receive and follow up on feedback and complaints through the Authority’s official channels.

Completeness 

The data of the Adult Skills and Learning Survey exhibit a high level of completeness, as data were collected for most key variables in accordance with the approved sample design. Any limited data gaps are attributable to partial non-response to certain questions.
Data completeness was ensured through the use of a questionnaire containing mandatory fields, the application of validation and alert rules during data collection, continuous supervision and follow-up, and the use of statistical imputation methods when necessary.
The key variables include demographic characteristics, educational attainment, participation in education and training, and mean years of schooling. Data coverage was reviewed against relevant national and international requirements.
The data cover all administrative regions and target groups as defined by the statistical population, and there are no significant gaps that would affect the quality of statistical analysis.

Accuracy and reliability 

A measure that indicates how close the estimates or calculations are to the true or exact values that reflect reality.

Overall accuracy 

Accuracy is defined as the extent to which the estimated value of a statistical indicator is close to the true value of the target population.
Accuracy is assessed through the analysis of error sources into two main components:
•    Sampling errors:
This type of error arises from using a sample instead of a complete enumeration, and it is the only component of total error that can be measured quantitatively. It is statistically expressed using the relative standard error (RSE) and confidence intervals (CI).
•    Non-sampling errors:
Non-sampling errors include all errors that may occur at any stage of the survey, except those arising from sampling.
They are classified into four main types:
•    Coverage errors:
Errors occur due to a mismatch between the sampling frame and the target population, resulting in over-coverage (such as housing units that have been merged into another dwelling) or under-coverage.
•    Measurement errors:
Errors arise from deviations between the recorded value and the true value of a characteristic and are attributable to factors such as researcher performance.
•    Processing errors:
Errors that occur during the data preparation stages after data collection and before analysis, including processes such as coding, data entry, editing, and imputation.
•    Non-response errors:
Errors occur due to systematic differences between the characteristics of respondents and non-respondents. Their impact on bias is assessed through the analysis of non-response rates (such as refusals or inability to contact).

Timeliness and punctuality 

A standard that measures the time gap between the availability of information and the occurrence of the event.
However, timeliness reflects the time difference between the date of data publication and the target date when it is actually published.

Timeliness 

The General Authority for Statistics is keen to apply internationally recognized standards regarding the announcement and clarification of the timing of statistical releases on its official website through the statistical calendar, as well as adherence to the announced publication time. In the event of any delay, the schedule will be updated accordingly.

Punctuality 

Publication is carried out in accordance with the release dates specified in the Statistical Calendar for the Adult Skills and Learning Statistics Publication, available on the General Authority for Statistics website.
The data are available at the expected time, as scheduled in the statistical release calendar, If the publication is delayed, reasons shall be provided.

Coherence and comparability

A standard that refers to the necessity of internal and temporal consistency of statistics, their logical coherence, and their comparability and integration across different regions and sources.

Comparability - geographical

•    Locally (across regions):
The data are comparable across all administrative regions in the Kingdom, due to the use of unified official geographic classifications and the application of consistent methodology and data collection tools nationwide, including the Unified Saudi Classification for Educational Levels & Specializations.
•    Internationally:
The data are internationally comparable, aligning with international standards and classifications such as the ISCED, and linking results to unified international indicators like the Sustainable Development Goals (SDG 4).
•    Interpretation of differences:
Any changes in administrative boundaries, as well as variations in coverage and data quality, are documented to account for discrepancies in results across regions or in comparison with other countries.

Comparability - over time 

The Adult Skills and Learning Survey was launched in 2024, marking the base year for the survey's time series.
There have been no significant methodological changes during the available time period since the survey's inception. Accordingly, the time series is fully consistent and comparable across subsequent years, with unified concepts and definitions, a consistent sample design, standardized data collection instruments, and a consistent reference periods.
There are no breaks or time gaps within the time series since the inception of the survey, and no changes have been identified that would affect data consistency or the interpretation of time trends.

Coherence- Cross domain

The survey data are comparable with other education and population statistics released by official entities, as a result of the use of consistent statistical concepts, definitions, and methodologies.
Consistency was verified through:
•    Comparison of key indicators with results from other relevant surveys or official statistics.
•    Review of values and ratios to ensure their plausibility and consistency with general trends.
•    Analysis of potential differences between outputs prior to publication.
Potential differences and their causes:
Some limited differences may appear between the survey results and the outputs of other sources, which can be attributed to:
•    Differences in measurement tools or question wording.
•    Differences in sample design or target population.
•    Differences in reference periods or statistical estimation methodologies.
These differences are not considered unjustified inconsistencies; rather, they are explainable methodological differences that do not affect the reliability or usability of the results.

Coherence- Sub-annual and annual statistics 

The Adult Skills and Learning Survey is annual in nature, and no quarterly or monthly statistics are produced under this statistical product. Accordingly, the concept of coherence between annual and sub-annual statistics does not apply to this survey.

Coherence- National Accounts 

This does not apply to the Adult Skills and Learning Survey in relation to the national accounts, due to differences in the scope of measurement and statistical objectives. The survey focuses on educational characteristics and does not address macroeconomic variables or financial flows that form the basis of the national accounts.

Coherence- Internal 

The outputs of the Adult Skills and Learning Survey exhibit a high level of internal consistency, as the statistics produced within the same dataset are coherent and do not show any unjustified inconsistencies.
Internal consistency was verified through a review of the logical sequence of the data and by ensuring that averages, distributions, and percentages are consistent with the aggregate figures across different tables and indicators.
No significant issues in internal consistency were identified. In the event that limited discrepancies were identified during the review, they were documented and addressed prior to publication and do not affect the interpretation or reliability of the results.

Accessibility and clarity

The accessibility of data for users, the availability of detailed or aggregated data, as well as the availability of the methodology and quality report.

Press releases

The announcements for each publication are available on the statistical calendar as mentioned in 10.1. The press releases can be viewed on the website of GASTAT on the link: 
Press release

Publications

The General Authority for Statistics issues the Adult Skills and Learning Statistics Publication regularly in accordance with a pre-prepared dissemination plan, and it is published on the Authority’s website. GASTAT is keen to publish its publications in a way that serves all users of different types, including publications in different formats that contain (publication tables, data graphs, indicators, the methodology and quality report) in both English and Arabic.
The results of the Adult Skills and Learning Statistics Publication are available at:
Adult Skills and Learning Statistics

Online database

The data will be made available through the General Authority for Statistics portal and the Statistical Database (SDB) upon completion of the approved dissemination procedures.
 GASTAT (stats.gov.sa)

Microdata accessibility

Accurate data is unit-level disaggregated data obtained from multiple sources such as sample statistical surveys, general population and housing censuses, and administrative systems, providing detailed information about the characteristics of individuals, families, business entities, and geographical areas, supporting the construction and development of statistical indicators and scientific research.
Different types of microdata files are available to meet diverse information needs.
•    Public use: 
It consists of sets of records containing information on individuals, households, or business entities anonymized in such a way that the respondent cannot be identified either directly, such as by name, address, contact number, identity number, etc., or indirectly (by combining different – especially rare – characteristics of respondents), such as age, occupation, education, etc.
•    Scientific use:
These files are created based on specific methodologies upon the request of data users to extract datasets with defined characteristics for use in strategic studies, decision-making, and scientific research by individuals, households, and companies, while ensuring that they do not contain any direct identifiers and are subject to data confidentiality protection controls.
Qualified users who meet the standards and procedures of confidentiality protection can access the files of scientific use of accurate data through the platform "ITAHA" of the General Authority for Statistics, while the most sensitive data for use is shared by visiting the accurate data laboratory within a secure environment managed by the Authority.

References and standards

The Adult Skills and Learning Survey was implemented based on a set of approved references, methodologies, and statistical standards to ensure data quality and comparability. 
General statistical process methodology:
The statistical process was based on the Generic Statistical Business Process Model (GSBPM), which provides a unified framework for the stages of statistical data production, starting from identifying needs, through design, collection, processing, and analysis, and ending with dissemination and evaluation.
Statistical classifications adopted:
Approved national and international classifications were used, most notably:
•    Saudi classification of educational levels and specializations (based on ISCED).
•    Saudi Unified Occupational Classification (based on ISCO).
These classifications are available through the official website of the General Authority for Statistics.
Interviewer guide (fieldwork completion manual):
The field interviewer guide was adopted as a primary reference for data collection teams. It includes instructions for completing the questionnaire, clarification of statistical concepts and definitions, and procedures for handling different cases during data collection.
Standards related to indicators:
The survey indicators were based on relevant national and international statistical standards and concepts related to education, including the recommendations of concerned international organizations, to enhance the quality of the results and their international comparability.
•    Education Indicators Guide issued by the UNESCO Institute for Statistics (UIS):
Education Indicators Guide 
•    Summary of Sustainable Development Goal 4 data using household survey data 
for monitoring Sustainable Development Goal 4:
Sustainable Development Goal 4 (SDG 4)

Quality assurance

GASTAT declares that it considers the following principles: Impartiality; ensuring that the statistical product is user-oriented; maintaining the quality of processes and outputs; enhancing the effectiveness of statistical operations; and reducing the burden on respondents. 
Data is validated through procedures and quality controls that are applied during the process at various stages, such as data entry, data collection, and other final controls.

Quality assessment

The General Authority for Statistics performs all statistical activities in accordance with the national model, the Generic Statistical Business Process Model (GSBPM). Under the GSBPM, the final phase of statistical activities is the overall evaluation stage, during which the information collected in each phase or sub-process is used to prepare an evaluation report that summarizes all challenges related to the quality of each statistical process and serves as input for improvement and development actions.

Confidentiality

Confidentiality - Policy

According to Royal Decree No. 23 dated 07/12/1379, data must always be kept confidential and must be used by GASTAT for statistical purposes only.
Therefore, the data is protected in the data servers of GASTAT.

Confidentiality - Data Treatment

Data of SMEs survey are presented in right tables in order to summarize, understand, as well as extract their results. Moreover, to compare them with other data, and to obtain statistical significance about the selected study population. However, referring to such data indicated in tables is much easier than going back to check the original questionnaire that may include some data like: names and addresses of individuals, and names of data providers, which violates data confidentiality of statistical data.
“Anonymity of data” is one of the most important procedures. To keep data confidential,
GASTAT removed information on individual persons, households, or business entities such a way that the respondent cannot be identified either directly such as: (name, address, contact number, identity number etc.) or indirectly (by combining different - especially rare - characteristics of respondents) such as: (age, occupation, education etc.).

Dissemination policy

Statistical calendar

The Adult Skills and Learning Statistics Publication has been included in the statistical calendar.
Statistical Calendar

User access

One of the objectives of the General Authority for Statistics is to better meet the needs of its users; therefore, it provides them with the results of the publication immediately upon the release of the Adult Skills and Learning Statistics Publication.
Customer questions and inquiries about the publication and its results are also received through various communication channels, such as:
•    GASTAT official website:   www.stats.gov.sa
•    GASTAT official email address:   info@stats.gov.sa
•    Official visits to GASTAT’s official head office in Riyadh or one of its branches in Saudi Arabia.
•    Official letters.
•    Statistical telephone: (199009).