Adult education and learning

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Database Specific

Database Specific

Abstract

Abstract

This dataset presents internationally comparable data on participation in adult learning activities (formal and non-formal education and training).

Concepts & Classifications

Concepts & Classifications

Classification(s) used

Classification(s) used

For data from the Survey of Adults Skills, educational attainment variables are based on ISCED-97. For other data sources, educational attainment variables are based on ISCED 2011.

Other manipulations

Other manipulations

Data are not diplayed when the sample size for numerator is below 3 and when the sample size for denominator is below 30.

Other Aspects

Other Aspects

Quality comments

Quality comments

When interpreting the results and the differences between groups a special attention should be given to the standard errors and the confidence interval.

Recommended uses and limitations

Recommended uses and limitations

The statistical estimates presented in this table are based on samples of adults, rather than values that could be calculated if every person in the target population in every country had answered every question. Therefore, each estimate has a degree of uncertainty associated with sampling and measurement error, which can be expressed as a standard error. The use of confidence intervals provides a way to make inferences about the population means and proportions in a manner that reflects the uncertainty associated with the sample estimates. In this table, there is one column with the heading “Value”, which indicates the average percentage or mean, and a column with the heading “SE”, which indicates the standard error. Given the survey method, there is a sampling uncertainty in the percentages or means of twice the standard error. For example, for the values: % = 10 and S.E. = 2.6, 10% has an uncertainty zone of twice (1.96) the standard error of 2.6, assuming an error risk of 5%. Thus, the true percentage would probably (error risk of 5%) be somewhere between 5% and 15% (“confidence interval”). The confidence interval is calculated as: % +/– 1.96 * S.E., i.e. for the previous example, 5% = 10% – 1.96 * 2.6 and 15% = 10% + 1.96 * 2.6.

This dataset presents internationally comparable data on participation in adult learning activities (formal and non-formal education and training).

If not otherwise stated in the indicator, data are coming from the Survey of Adult Skills, a product of the OECD Programme for the International Assessment of Adult Competencies (PIAAC).

Markus SCHWABE

Simon NORMANDEAU

For data from the Survey of Adults Skills, educational attainment variables are based on ISCED-97. For other data sources, educational attainment variables are based on ISCED 2011.

Data are not diplayed when the sample size for numerator is below 3 and when the sample size for denominator is below 30.

The statistical estimates presented in this table are based on samples of adults, rather than values that could be calculated if every person in the target population in every country had answered every question. Therefore, each estimate has a degree of uncertainty associated with sampling and measurement error, which can be expressed as a standard error. The use of confidence intervals provides a way to make inferences about the population means and proportions in a manner that reflects the uncertainty associated with the sample estimates. In this table, there is one column with the heading “Value”, which indicates the average percentage or mean, and a column with the heading “SE”, which indicates the standard error. Given the survey method, there is a sampling uncertainty in the percentages or means of twice the standard error. For example, for the values: % = 10 and S.E. = 2.6, 10% has an uncertainty zone of twice (1.96) the standard error of 2.6, assuming an error risk of 5%. Thus, the true percentage would probably (error risk of 5%) be somewhere between 5% and 15% (“confidence interval”). The confidence interval is calculated as: % +/– 1.96 * S.E., i.e. for the previous example, 5% = 10% – 1.96 * 2.6 and 15% = 10% + 1.96 * 2.6.

When interpreting the results and the differences between groups a special attention should be given to the standard errors and the confidence interval.