Recent participation in formal education is an important factor influencing adults’ participation in additional non-formal learning. Across OECD countries and economies, 61% of young adults who completed their highest qualification in the last five years have participated in non-formal learning, compared to only 46% of those whose highest qualification was earned more than five years ago.
Employment also plays a role in engaging individuals and facilitating access to non-formal learning. Although on average 49% of employed adults participate in non-formal learning across the OECD, the rate drops to about 34% for adults who are unemployed and to 17% of adults who are outside the labour force.
Adults with below upper secondary attainment are over three times more likely to report having never participated in non-formal learning compared to those with a tertiary qualification.
Education at a Glance 2026
In per cent; 25-34 year-olds; Survey of Adult Skills (PIAAC)
For data, see Table A5.1. The data for this figure can be accessed via https://stat.link/ds0m4z.
Context
Adult learning has become a central pillar of education and skills policy across OECD countries, reflecting the recognition that learning can no longer be confined to initial schooling or early adulthood. The rapid adoption of artificial intelligence in the workplace, demographic ageing and labour-market transformation are reshaping the skills individuals need throughout their lives, increasing the need for adults to learn, let go of outdated practices and re-learn best practices. In this context, adult learning is increasingly understood as a critical component of lifelong learning strategies that support healthy economies and societies.
Despite this evolving understanding of the role and importance of adult learning systems, participation in adult education and training remains unequal across OECD countries and population groups. Adults with higher levels of education, stronger literacy skills and stable employment are significantly more likely to participate in further learning, while low-skilled adults, older workers and those in precarious employment participate less frequently (OECD, 2025[1]). Furthermore, even where the gaps between different populations have narrowed, this has mostly been due to declines in participation among advantaged groups rather than increases among historically disadvantaged ones (OECD, 2025[1]). Barriers related to time, cost, motivation, information and access continue to limit participation among those who could benefit most from upskilling and reskilling opportunities.
This chapter focuses on access to adult learning opportunities through examining differences in participation across population groups. Characteristics such as educational attainment, age, labour-force status, gender and how recently people had completed their highest qualification provide insight into how participation in adult learning differs and help identify the groups that remain least connected to lifelong learning opportunities. In addition to examining current participation patterns, the chapter also considers the share of adults who report having never participated in non-formal learning and explores differences in adults’ interest in participation.
Other findings
On average, there is little reported unmet interest in further learning among adults, with over 75% of the population overall reporting they have no interest in participating in non-formal learning beyond any they have already done.
Across all countries with available data, adults whose health problems severely limit their everyday activities are less likely to participate in adult learning than their peers with no such limitations (16% compared to 41%).
There is some overlap between the skills most commonly targeted by employer-provided courses and the skills adults most frequently report they need at work. Employers are most likely to report providing continuing vocational training (CVT) courses targeting technical or job-specific skills, followed by “other” skills, and management and organisational skills. Meanwhile, digital skills, management and organisational skills, interpersonal skills, and “other” skills are the areas where individuals feel they need upskilling.
Note
Different sources are used in this chapter. The Survey of Adult Skills (PIAAC) is used for those countries and economies which participate in it and national sources are used for the other countries. Boxes A5.1 and A5.2 feature data from additional sources. Refer to the Sources section for more detail.
Although education policy has traditionally focused on early childhood to late adolescence, the importance of continued learning has become globally recognised in recent decades. Modern adult learning policies highlight the economic imperative of increasing and maintaining an employable workforce while recognising the impact of lifelong learning on individual learners (Elfert and Rubenson, 2022[2]). OECD and partner countries have implemented a wide array of policies aimed at strengthening the motivation of adult learners, supporting employability and the portability of skills, and expanding sustainable access to learning opportunities (OECD, 2025[3]). Although countries have made efforts to increase coherent and consistent learning opportunities for adults beyond initial education, engagement in such learning is not consistent across subpopulations.
Participation in non-formal learning by time since completing formal education
Access can be analysed through both system- and individual-level characteristics, as their interaction shapes participation in adult learning. Across OECD countries and economies, 61% of adults who completed their highest formal qualification within the last five years had participated in additional non-formal learning within the previous 12 months, compared to 43% of adults whose highest qualification was obtained more than five years ago (Table A5.1). A formal qualification refers to an educational qualification recognised by a national entity, while non-formal learning refers to organised education or training that does not lead to a formal qualification. For more information on the difference between formal and non-formal learning, please see the Definitions section.
Some of this difference in participation is likely to be associated with age, as older adults are both less likely to participate in adult learning (Figure A5.2) and more likely to have completed their highest qualification more than five years ago. However, Figure A5.1 shows that the pattern persists even among 25-34 year-olds, suggesting that the association between recent formal education and participation in adult learning is not explained by age alone.
This finding is strongly supported in the lifelong learning literature. Foundational OECD work on adult learning describes this dynamic as “learning begets learning” – prior educational participation strongly predicts continued engagement in adult education (OECD, 2014[4]). Research further suggests that participation in education builds confidence, motivation and social capital, while active learning networks and supportive social environments reinforce continued participation in lifelong learning (Cocquyt et al., 2019[5]).
Participation in non-formal learning by age and labour force status
Figure A5.2 shows that participation in non-formal learning among employed adults varies considerably across OECD member and accession countries and age groups. Among employed adults aged 25-44, participation rates range from 16% in Korea and 28% in Croatia and Poland to over 70% in Finland, Norway and the United States. Participation is also relatively high in Canada, Denmark, Estonia and Ireland, where more than 65% of employed younger adults report having participated in non-formal learning during the previous 12 months.
In per cent; 25-64 year-olds; participation in the last 12 months; Survey of Adult Skills (PIAAC) or national survey
1. Source for Australia is Australia's Work-Related Training and Adult Learning Survey. The reference year is the 2020/2021 financial year.
For data, see Table A5.2. The data for this figure can be accessed via https://stat.link/ds0m4z.
Participation rates tend to decline with age in OECD countries and economies, although the difference is relatively small compared to those associated with educational attainment (see Figure A5.5). On average across the OECD, 52% of employed 25-44 year-olds participated in non-formal learning in 2023, compared to 45% of employed 45-64 year-olds. The gaps are particularly wide in Canada, Chile, Estonia and Latvia, where participation rates among younger workers exceed those of older workers by at least 10 percentage points. In contrast, the differences are smaller in Italy, Korea and New Zealand (Figure A5.2). Differences between age groups may reflect differences in labour-market incentives and access to training. Younger employed adults are often more likely to participate in training because they are earlier in their careers, more exposed to technological change and more likely to anticipate greater financial returns from continued training (OECD, 2025[6]). Additionally, younger adults may need to participate in adult learning to acquire practical, company- or job-specific skills that were not covered in their initial education or training. Older workers, on the other hand, may face barriers due to time constraints or lower employer support, or simply perceive fewer benefits to participating in training (OECD, 2021[7]).
Overall, cross-country differences in participation in adult learning among employed adults are linked to a range of factors, including labour-market structures, employers’ demand for skills, access to training opportunities and national lifelong learning policies. Countries with high participation rates often have strong labour-market demand for advanced skills with well-developed adult learning systems and broad employer support for training (OECD, 2023[8]). Box A5.1 examines the overlap between the skills targeted by employers in the training they provide, and the areas where adults feel they need skills most.
Aside from age and systemic factors, employers play a role in facilitating access to learning opportunities. Although on average 49% of employed adults participate in non-formal learning across the OECD, the rate drops to about 34% for adults who are unemployed and to 17% of adults who are outside the labour force (Table A5.2). This pattern highlights a potential policy challenge, as opportunities for learning are often less accessible to adults who have weaker connections to the labour market.
Adult learning systems are shaped both by employers’ decisions about what training to provide and workers’ perceptions of the skills they need. Enterprise-based and household surveys offer complementary evidence from both these perspectives into how continuing vocational training (CVT) is addressing labour-market skill requirements and filling individual skill gaps. This box compares the type of skills targeted by employer-provided training courses with individuals’ assessments of the skills they need, in order to understand the relationship between employer and employee perspectives. Data from the EU Continuing Vocational Training Survey (EU-CVTS) provide information about the types of skills targeted by employer-financed CVT courses. On average across the surveyed countries, the skills most frequently covered are technical or job-specific skills, “other” skills, and management and organisational skills (Figure A5.3).
Although this pattern is broadly consistent regardless of firm size, some differences do emerge. Smaller enterprises (10-49 employees) are more likely to provide CVT courses related to interpersonal skills, such as handling customers, while these are replaced by management skills among medium-sized (50-249 employees) and large firms (250 employees and over). The change in emphasis may reflect differences in job roles and organisational complexity. Smaller firms often rely on direct customer interaction, while larger firms require stronger management and co-ordination capacities, differences that may also shape how workers experience and address skill shortfalls (OECD, 2024[9]). Larger firms are more likely to report skills gaps overall, perhaps because their organisational complexity makes it harder for them to react quickly to close skill gaps (OECD, 2024[9]).
In per cent of firms surveyed; EU Continuing Vocational Training Survey (EU-CVTS)
Note: Skills domains are descriptive composite indicators constructed by grouping related skill categories across PIAAC and EU-CVTS. Please see the Methodologies section for more information. The data for this figure can be accessed via https://stat.link/ds0m4z.
The Survey of Adult Skills (PIAAC) household survey offers a complementary perspective by asking individuals to identify areas where their skills are not sufficient for their job. Across OECD countries and economies, adults cite digital skills, management and organisational skills, interpersonal skills, and “other” skills as areas where they feel the need for upskilling (Figure A5.4). These areas are a fairly good match for those targeted by employers in their CVT provision, except that employers place greater emphasis on technical or job-specific skills. The absence of these skills from individuals’ reported skill shortfalls does not necessarily indicate a mismatch in employee and employer perspectives. Instead, it may reflect that training in these areas is effective, well-targeted or tightly matched to their job requirements.
In both surveys, “other” skills are cited frequently, and this prominence of the “other” category is notable, as it suggests that a substantial portion of skills relevant to employees and employers alike do not fall neatly into the predetermined survey categories. This highlights the diverse nature of skills in today’s labour market, which often requires individuals to master interdisciplinary or context-specific competencies if they are to perform well in their jobs and be able to pivot at their roles change.
This combined analysis underlines the importance of aligning training programmes with actual skill needs, including emerging and cross-cutting competencies such as digital literacy, problem solving and interpersonal communication. Policies could focus on ensuring equitable access to relevant training across firms of all sizes, supporting initiatives that respond to evolving and interdisciplinary skill demands, and promoting lifelong learning strategies that help workers keep adapting to the labour market.
In per cent; 25-64 year-olds; Survey of Adult Skills (PIAAC)
Note: Skills domains are descriptive composite indicators constructed by grouping related skill categories across PIAAC and EU-CVTS. Please see the Methodologies section for more information. The data for this figure can be accessed via https://stat.link/ds0m4z.
Adults who have never participated in non-formal learning
A notable share of adults report never having participated in non-formal learning. Across all levels of educational attainment, around one in five adults report not having participated at all in such training during their lifetime. Non-participation is particularly prevalent among adults with lower levels of educational attainment, with twice as many adults with below upper secondary attainment reporting never participating in such learning than among the total adult population. In contrast, the share is substantially lower among tertiary-educated adults, often below 15% in many countries. On average there is a 30 percentage-point difference between adults with below upper secondary attainment and adults with tertiary attainment, highlighting the cumulative nature of inequalities in adult learning participation (Table A5.3).
In per cent; 25-64 year-olds; Survey of Adult Skills (PIAAC)
For data, see Table A5.3. The data for this figure can be accessed via https://stat.link/ds0m4z.
There are also differences in participation by gender, although they are smaller than those related to educational attainment. Gender disparities in participation may relate to differences in labour-market participation, caring responsibilities and access to training opportunities (OECD, 2023[8]). Women with below upper secondary attainment are generally more likely than their male peers to report never having participated in non-formal learning. The gender differences among tertiary-educated adults are smaller and, in several countries and economies, women are only slightly less likely than men to report never having participated in non-formal learning activities (Figure A5.5).
Figure A5.5 shows that, on average across the OECD, 40% of men and 44% of women with below upper secondary attainment report never having participated in non-formal learning, compared to 13% of tertiary-educated men and 12% of tertiary-educated women. Across all countries and economies, a far larger share of men and women with lower educational attainment report never having participated in non-formal education or training than their tertiary-educated peers. In Korea, the share reaches 90% of men and 74% of women with below upper secondary attainment. This may partially be explained by the common practice of working long hours in Korea, which may inhibit individuals from participating in additional learning (Hijzen and Thewissen, 2020[10]), but long working hours are also seen in other OECD countries, suggesting that there are additional factors behind the high level of non-participants (OECD, 2023[11]).
These patterns suggest that participation in adult learning remains associated with prior educational attainment and that some groups remain persistently disconnected from adult learning systems over their life course. Adults with lower levels of education may face multiple barriers to participation, including limited access to training opportunities, financial constraints, weaker foundational skills and lower employer support for training. OECD analysis also shows that adults who are already highly skilled and highly educated are more likely to continue engaging in learning throughout adulthood, potentially reinforcing existing inequalities in skills development and labour-market outcomes (OECD, 2021[12]). Regardless of educational attainment, health problems can also be a barrier to adult learning (Box A5.2).
Interest in participating in non-formal learning
Figure A5.6 shows that a substantial share of adults neither participated in non-formal learning nor wanted to do so during the previous 12 months. This pattern is particularly common among adults with lower levels of educational attainment. On average across OECD countries and economies, 69% of adults with below upper secondary attainment reported not participating and not wanting to participate in non-formal learning in 2023, compared to 53% of those with upper secondary or post-secondary non-tertiary attainment and 33% of tertiary-educated adults.
In per cent; 25-64 year-olds; participation in the last 12 months; Survey of Adult Skills (PIAAC) or national survey
1. Source for Australia is Australia's Work-Related Training and Adult Learning Survey. The reference year is the 2020/2021 financial year.
For data, see Table A5.4 (available online). The data for this figure can be accessed via https://stat.link/ds0m4z.
In most countries and economies, adults with below upper secondary attainment are considerably more likely to report having no interest in participating in non-formal learning than tertiary-educated adults. The shares are particularly high among this group in Croatia (93%), Poland (90%) and the Slovak Republic (86%), whereas the lowest shares are found in Estonia (46%), Norway (52%) and Sweden (51%). Among tertiary-educated adults, the share reporting that they have neither participated nor wanted to participate was relatively high in Croatia (48%), Korea (67%) and Poland (56%) (Figure A5.6).
Out of adults of all educational attainment levels who had participated in non-formal learning the past 12 months, 30% reported that they have no desire for any further training. This means that together with the population of adults who did not participate in non-formal learning in the past 12 months, over 75% of adults report no interest in a primary or additional non-formal learning activity, suggesting that there is very little latent interest among the population (Table A5.4, available online).
Such a lack of latent interest is concerning from a policy perspective, and understanding what underlies it is difficult as it can be multifaceted. Lack of interest could reflect weaker perceived benefits, negative prior educational experiences, limited information about available opportunities or low expected labour-market returns (Ampofo et al., 2026[13]). Hindrances to adult learning, however, may extend beyond such structural or experiential barriers to include motivational ones. Although it is difficult to disentangle structural and motivational factors, research shows that motivation is not only a predicator of participation in adult learning – albeit smaller in effect than educational attainment or employment status – but also something that is malleable (Gorges, 2025[14]). In addition to addressing structural or resource constraints, policymakers should begin to assess whether interventions targeting motivation could be effective in increasing and sustaining participation.
Adults whose health severely limits their everyday activities are consistently less likely to participate in adult learning than those without such limitations across countries with available data. Data from the EU Labour Force Survey (EU-LFS), collected through the Global Activity Limitation Indicator (GALI), show substantial participation gaps in education and training between those with severe activity limitations and those with none.
The GALI indicator measures self-reported long-standing limitations on activities one may “usually do” caused by physical, mental or emotional health problems lasting at least six months (Eurostat, 2026[15]). As of 2024, almost one-quarter of those aged 16 and older reported either some or severe activity limitations (Eurostat, 2025[16]), although the share is likely to be smaller among the 25-64 year-old population discussed here. While such measures cannot fully capture the role of individuals’ environments or wider social barriers, they provide important insight into inequalities in participation associated with activity limitations (Geiger and Prinz, 2025[17]).
In per cent; 25-64 year-olds; participation in formal or non-formal learning in the last 12 months; EU Labour Force Survey (EU-LFS) or national survey
Note: The average includes only countries participating in the 2024 EU Labour Force Survey (EU-LFS), not all OECD countries.
1. Source for Mexico is the INEGI National Time Use Survey (ENUT) 2024.
For data, see Table A5.5 (available online). The data for this figure can be accessed via https://stat.link/ds0m4z.
In all countries with available data, 16% of adults with severe activity limitations participated in adult learning in the last 12 months, compared to 41% of adults with no limitations. Participation rates among adults with severe activity limitations vary substantially across countries. Denmark, Finland, Norway and Sweden report comparatively high participation rates among adults both with and without severe limitations (Table A5.5, available online). These countries are characterised by well-developed lifelong learning systems, including comparatively high public investment in adult education, flexible learning opportunities and established systems of guidance and support for adult learners (OECD, 2025[1]). Participation in formal education after the age of 25 is also more common in these countries, which may contribute to higher participation overall (see Part B).
However, high overall participation rates do not necessarily correspond to smaller participation gaps between adults with and without severe activity limitations. The participation gap between adults with severe limitations and those with no limitations reaches 30 percentage points in Denmark, 35 percentage points in the Netherlands, and 35 percentage points in Norway. This suggests that broad investment in lifelong learning systems alone may not be sufficient to ensure equitable participation among adults with activity limitations.
Gender differences in participation among adults with severe activity limitations also differ from wider adult learning patterns. In most countries with available data, women with severe activity limitations participate in adult learning at slightly higher rates than men with severe limitations (18% compared to 14%) (Figure A5.7). This contrasts with overall adult learning participation patterns, where gender parity has been virtually reached across OECD countries (OECD, 2025[1]).
Adults refer to 25-64 year-olds.
Adult learning means the participation of adults in lifelong learning. In this chapter, the term “learning” is used interchangeably with the term “education and training” and adult learning refers to both formal and/or non-formal education and training, usually taking place after the end of initial education. Formal and non-formal education and training are defined in the Classification of Learning Activities (Eurostat, 2016[18]) as follows:
Formal education or training is defined as “education that is institutionalised, intentional and planned through public organisations and recognised private bodies, and - in their totality - constitute the formal education system of a country. Formal education programmes are thus recognised as such by the relevant national education or equivalent authorities, e.g. any other institution in cooperation with the national or sub-national education authorities. Formal education consists mostly of initial education [...]. Vocational education, special needs education and some parts of adult education are often recognised as being part of the formal education system. Qualifications from formal education are by definition recognised and, therefore, are within the scope of ISCED. Institutionalised education occurs when an organisation provides structured educational arrangements, such as student-teacher relationships and/or interactions, that are specially designed for education and learning”.
Non-formal education or training is defined as “education that is institutionalised, intentional and planned by an education provider. The defining characteristic of non-formal education is that it is an addition, alternative and/or complement to formal education within the process of lifelong learning of individuals. It is often provided in order to guarantee the right of access to education for all. It caters to people of all ages but does not necessarily apply a continuous pathway structure; it may be short in duration and/or low-intensity; and it is typically provided in the form of short courses, workshops or seminars. Non-formal education mostly leads to qualifications that are not recognised as formal or equivalent to formal qualifications by the relevant national or sub-national education authorities or to no qualifications at all. Nevertheless, formal, recognised qualifications may be obtained through exclusive participation in specific non-formal education programmes; this often happens when the non-formal programme completes the competencies obtained in another context”. For example, an individual without an upper secondary degree may attend an evening course for adults run by a community organisation. After completing the programme, they may pass an officially recognised assessment that leads to a formal qualification, while the learning itself happened in a non-formal programme.
For methodological information, please see the Survey of Adult Skills 2023 – Reader’s Companion (OECD, 2024[19]).
The tables in this chapter present data derived from samples and are subject to statistical error. The corresponding standard errors are available in the online version of the tables, accessible via the StatLinks provided in the Tables and Notes section. Readers are encouraged to consult these online tables, as the precision of the estimates varies, and in some cases, the standard errors are relatively large.
To support meaningful cross-survey comparison, individual skill items from the Survey of Adult Skills (2023) and the EU Continuing Vocational Training Survey (EU-CVTS) have been grouped into broader analytical domains reflecting common areas of competence, such as digital, technical, managerial and transversal skills. This approach does not imply direct equivalence between indicators but facilitates comparison by highlighting differences in emphasis between employer training priorities and workers’ perceived skill development needs. Table A5.1.a. shows how the skill items used in these surveys have been grouped into broader domains for comparison purposes.
Source: Survey of Adult Skills (PIAAC) Cycle 2 (2023) and EU Continuing Vocational Training Survey (2020).
For more information, please refer to Education at a Glance 2026 Sources, Methodologies and Technical Notes (https://doi.org/10.1787/dcf64a14-en).
Survey of Adult Skills (PIAAC) Cycle 2 (2023).
EU Labour Force Survey (EU-LFS) (2024).
EU Continuing Vocational Training Survey (2020).
References
[13] Ampofo, J. et al. (2026), “Inclusive lifelong learning for adults: Institutional obligations under UNESCO’s education for sustainable development framework”, International Journal of Educational Development, Vol. 122, p. 103562, https://doi.org/10.1016/j.ijedudev.2026.103562.
[5] Cocquyt, C. et al. (2019), “Examining the role of learning support in blended learning for adults’ social inclusion and social capital”, Computers & Education, Vol. 142, https://doi.org/10.1016/j.compedu.2019.103610.
[2] Elfert, M. and K. Rubenson (2022), “Lifelong learning: Researching a contested concept in the Twenty-First Century”, in Third International Handbook of Lifelong Learning, Springer International Publishing, Cham, https://doi.org/10.1007/978-3-030-67930-9_48-1.
[15] Eurostat (2026), EU Labour Force Survey: Explanatory Notes, European Commission, https://ec.europa.eu/eurostat/documents/1978984/6037342/EU-LFS+Explanatory+notes+from+Q1+2021+onwards.pdf.
[16] Eurostat (2025), Statistics explained: Population with disability, European Union, https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Population_with_disability.
[18] Eurostat (2016), Classification of Learning Activities (CLA): Manual: 2016 Edition, Publications Office of the European Union, https://doi.org/10.2785/874604.
[17] Geiger, B. and C. Prinz (2025), “Measuring disability employment gaps: How to get robust comparisons across countries and over time”, OECD Social, Employment and Migration Working Papers, No. 314, OECD Publishing, Paris, https://doi.org/10.1787/2d0be829-en.
[14] Gorges, J. (2025), “Global motivation to learn and adult learning: A nomological network analysis and a four-year longitudinal study”, Learning and Individual Differences, Vol. 123, https://doi.org/10.1016/j.lindif.2025.102763.
[10] Hijzen, A. and S. Thewissen (2020), “The 2018-2021 working time reform in Korea: A preliminary assessment”, OECD Social, Employment and Migration Working Papers, No. 248, OECD Publishing, Paris, https://doi.org/10.1787/0e828066-en.
[3] OECD (2025), Education Policy Outlook 2025: Nurturing Engaged and Resilient Lifelong Learners in a World of Digital Transformation, OECD Publishing, Paris, https://doi.org/10.1787/c3f402ba-en.
[6] OECD (2025), OECD Employment Outlook 2025: Can We Get Through the Demographic Crunch?, OECD Publishing, Paris, https://doi.org/10.1787/194a947b-en.
[1] OECD (2025), Trends in Adult Learning: New Data from the 2023 Survey of Adult Skills, Getting Skills Right, OECD Publishing, Paris, https://doi.org/10.1787/ec0624a6-en.
[19] OECD (2024), Survey of Adult Skills – Reader’s Companion: 2023, OECD Skills Studies, OECD Publishing, Paris, https://doi.org/10.1787/3639d1e2-en.
[9] OECD (2024), Understanding Skill Gaps in Firms: Results of the PIAAC Employer Module, OECD Skills Studies, OECD Publishing, Paris, https://doi.org/10.1787/b388d1da-en.
[11] OECD (2023), Hours worked, https://www.oecd.org/en/data/indicators/hours-worked.html.
[8] OECD (2023), OECD Skills Outlook 2023: Skills for a Resilient Green and Digital Transition, OECD Publishing, Paris, https://doi.org/10.1787/27452f29-en.
[7] OECD (2021), Career Guidance for Adults in a Changing World of Work, Getting Skills Right, OECD Publishing, Paris, https://doi.org/10.1787/9a94bfad-en.
[12] OECD (2021), OECD Skills Outlook 2021: Learning for Life, OECD Publishing, Paris, https://doi.org/10.1787/0ae365b4-en.
[4] OECD (2014), “Learning begets learning: Adult participation in lifelong education”, Education Indicators in Focus, No. 26, OECD Publishing, Paris, https://doi.org/10.1787/5jxsvvmr9z8n-en.
The data for the figures and tables in this chapter can be downloaded via https://stat.link/ds0m4z.
Data cut-off for the print publication 17 June 2026. Please note that the Data Explorer, http://data-explorer.oecd.org/s/4s , contains the most recent data.
a – category not applicable; b – break in series; d – contains data from another column; m – missing data; x – contained in another column (indicated in brackets). For further control codes, see the Reader’s Guide.
For further methodological information, see Education at a Glance 2026: Sources, Methodologies and Technical Notes (https://doi.org/10.1787/dcf64a14-en).
Survey of adult skills (PIAAC)
Note: Columns showing data on all levels of education, and participation in the last five years are available for consultation online. The data for this Table can be accessed via https://stat.link/ds0m4z.
Participation in the last 12 months
Note: Columns showing the combined data for 25-64 year-olds are available for consultation online.
1. Source for Australia is Australia's Work-Related Training and Adult Learning Survey. The reference year is the 2020/2021 financial year.
2. Source for Brazil is the Continuous National Household Sample Survey (PNAD). The source year is 2024. Results for Brazil are not directly comparable with results from PIAAC. See Education at a Glance 2026: Sources, Methodologies and Technical Notes (https://doi.org/10.1787/dcf64a14-en). The data for this Table can be accessed via https://stat.link/ds0m4z.
25–64-year-olds; Survey of adult skills (PIAAC)
Note: Columns showing the combined data for men and women are available for consultation online.
The data for this Table can be accessed via https://stat.link/ds0m4z.