TOP 10 Countries by Adult Participation in Lifelong Learning (2025)
Adult learning is a practical signal of workforce resilience: it shows how easily adults can update skills while staying in work. This ranking focuses on adults aged 25–64 who took part in organised education or training (formal or non-formal) within a defined reference period.
Comparability note (why rates differ by source)
- “Last 4 weeks” captures recent participation (short-window engagement).
- “Last 12 months” captures whether adults had at least one learning episode over a year.
- The same country can be “high” in one series and “moderate” in the other because the windows measure different behaviours.
Leaders typically combine employer co-funding, flexible delivery (short courses, modular credentials), and adult-education infrastructure that makes learning episodes routine during working life.
Top 10 snapshot
Training is embedded in workplaces and public adult education, supported by modular pathways that fit working schedules.
Reskilling is closely linked to labour-market transitions, with strong incentives to train during sector shifts.
Broad access to training and continued emphasis on digital and green skills, supported by strong institutions.
Sustained mid-career upskilling supported by strong foundational skills and modular adult learning options.
Flexible work arrangements and a dense training ecosystem support frequent short learning episodes.
Strong vocational pathways and employer incentives keep job-relevant training participation high.
Upskilling stays closely aligned with employer needs in a compact labour market.
Consistently strong participation across OECD-style measures, supported by broad provision and flexible formats.
A fast climber: participation rose alongside digital transformation and expanding access to adult training.
Strong by international comparison, with wider variation by region, sector, and education level than Nordic leaders.
Table 1. Adult participation in education and training (25–64), Top 10 (2025 snapshot)
| Rank | Country | Adults 25–64 participating, % | Reference window |
|---|---|---|---|
| 1 | Sweden | ≈ 35 | 4 weeks / 12 months (varies by source) |
| 2 | Denmark | ≈ 32 | 4 weeks / 12 months (varies by source) |
| 3 | Norway | ≈ 30 | 4 weeks / 12 months (varies by source) |
| 4 | Finland | ≈ 29 | 4 weeks / 12 months (varies by source) |
| 5 | Netherlands | ≈ 27 | 4 weeks / 12 months (varies by source) |
| 6 | Switzerland | ≈ 26 | 4 weeks / 12 months (varies by source) |
| 7 | Iceland | ≈ 25 | 4 weeks / 12 months (varies by source) |
| 8 | New Zealand | ≈ 24 | 4 weeks / 12 months (varies by source) |
| 9 | Estonia | ≈ 23 | 4 weeks / 12 months (varies by source) |
| 10 | United Kingdom | ≈ 22 | 4 weeks / 12 months (varies by source) |
Values are rounded “snapshot” levels commonly observed in Eurostat/OECD-style reporting around 2023–2025. Use the original databases for exact metadata and country figures.
Chart 1. Adults 25–64 participating in education and training, Top 10 (2025 snapshot)
Fallback view (if the chart does not load)
- Sweden — ≈ 35%
- Denmark — ≈ 32%
- Norway — ≈ 30%
- Finland — ≈ 29%
- Netherlands — ≈ 27%
- Switzerland — ≈ 26%
- Iceland — ≈ 25%
- New Zealand — ≈ 24%
- Estonia — ≈ 23%
- United Kingdom — ≈ 22%
Small percentage-point differences can translate into large differences in the absolute number of adult learners, depending on country population size.
Methodology (how the snapshot is constructed)
Indicator: adult participation in organised education and training (ages 25–64), including formal programmes and non-formal training. The headline indicator typically excludes informal self-study unless explicitly measured in a separate series.
Windows: official reporting commonly uses either “last 4 weeks” (recent participation) or “last 12 months” (at least one learning episode over the year). The “2025” label reflects the most recent comparable observations available around 2023–2025, presented as a current-state snapshot.
Interpretation: treat participation as a behavioural measure of engagement, not a direct measure of hours trained, course quality, or skills gained. The most actionable comparisons usually focus on patterns: age gradients, likely participation gaps by education level, and the sensitivity of rankings to the chosen window.
What this means for readers
High participation typically signals a dense training ecosystem and stronger employer involvement, which can matter for mid-career transitions and sector restructuring. The most policy-sensitive margin is often the 55–64 group: where participation holds up better, older workers are less exposed to skill obsolescence.
FAQ
Why do some sources use “last 4 weeks” while others use “last 12 months”?
They measure different behaviours: recent participation versus any learning episode within a year. This can change a country’s apparent level without implying a contradiction.
Does a high participation rate mean people are constantly studying?
No. In high-performing systems, participation often reflects frequent short courses, workplace training, and modular credentials.
Is informal learning included (self-study, videos, reading)?
Usually not in the headline participation rate. Informal learning is often measured separately and may not be comparable across surveys.
Why does participation often fall after age 55?
Perceived payoff declines as retirement nears, time constraints rise, and training offers are less tailored. Strong systems reduce the drop with flexible formats and guidance.
Can countries improve quickly?
Yes, but sustained gains usually require coordinated changes on both the supply side (access, modular options) and demand side (employer incentives, time flexibility).
Where participation drops: the age profile behind the headline rate
The headline participation rate often reflects short, frequent learning episodes. The key stress test is older working age: participation typically declines after 55, which can increase vulnerability to skill obsolescence during technology and job-task change. The table and chart below illustrate a common age gradient using four cases: three high performers and one mid-level comparator.
Table 2. Adult participation in education and training by age group (2025 snapshot)
| Country | Age group | Participation, % | Interpretation |
|---|---|---|---|
| Sweden | 25–34 | ≈ 42 | High early-career training intensity. |
| Sweden | 35–54 | ≈ 36 | Sustained learning while employed. |
| Sweden | 55–64 | ≈ 24 | Drop exists, but remains comparatively moderate. |
| Denmark | 25–34 | ≈ 39 | High participation at career-building ages. |
| Denmark | 35–54 | ≈ 33 | Training integrated with labour-market transitions. |
| Denmark | 55–64 | ≈ 22 | Older-worker participation remains a bottleneck. |
| Estonia | 25–34 | ≈ 30 | Catching-up profile with rising engagement. |
| Estonia | 35–54 | ≈ 24 | Meaningful participation in mid-career. |
| Estonia | 55–64 | ≈ 15 | Steeper drop; flexible formats and guidance matter. |
| Italy | 25–34 | ≈ 15 | Lower baseline participation. |
| Italy | 35–54 | ≈ 11 | Learning episodes are less common in mid-career. |
| Italy | 55–64 | ≈ 6 | Very low participation increases risk of skills becoming outdated. |
Snapshot values are rounded and illustrate the age gradient commonly seen in adult-learning statistics; consult official databases for exact country figures and metadata.
Chart 2. Participation by age group (selected countries, 2025 snapshot)
Fallback view (if the chart does not load)
The 55–64 group is often the most policy-sensitive margin: raising participation here can reduce skill obsolescence risk and support longer working lives.
How to interpret participation without over-reading it
Participation rates describe how common organised learning is among adults, not how many hours people train or what they learn. A higher rate can reflect widespread short courses, while a lower rate can coexist with intensive training concentrated in a smaller group.
For practical comparison, profiles usually matter more than single-point rankings: the age gradient, likely gaps by education level, and sensitivity to the reference window (“4 weeks” vs “12 months”).
Interpretation: what adult-learning participation reveals (and what it does not)
Differences in adult participation are best read as differences in how “normal” organised learning is during working life. High-performing systems usually combine employer co-investment, flexible delivery, and adult-education infrastructure that lowers time and administrative barriers. Lower-performing systems can still have strong providers, but weaker demand-side incentives and fewer options that fit around full-time work.
This indicator has clear limits. It does not measure learning quality, hours trained, or whether skills improved. It is also sensitive to the reference window (“last 4 weeks” vs “last 12 months”) and survey design. For decision-making, the most useful comparisons focus on patterns: the age cliff after 55, likely gaps by education level, and whether participation is broadly distributed or concentrated in already-advantaged groups.
Policy takeaways (what tends to raise participation)
Participation rises when learning fits working life. The strongest results typically come from aligning incentives, time, and delivery formats.
- Make time feasible: paid learning time, predictable schedules, and short stackable modules.
- Strengthen employer engagement: co-funding, sector training arrangements, and recognition of micro-credentials.
- Target older workers (55–64): tailored programmes, guidance, and flexible formats to reduce the age cliff.
- Reduce access gaps: subsidies and outreach so participation does not concentrate only among high-skilled adults.
- Recognise prior learning: pathways that convert experience into credentials increase perceived payoff.
For readers comparing labour markets, high participation often signals a denser ecosystem of training providers and employer programmes, which can make mid-career transitions smoother. For governments and employers, the most actionable margin is frequently older working age, where modest improvements can deliver outsized benefits.
Sources (official and primary references)
These references provide definitions, metadata, and datasets commonly used for international comparisons of adult participation in education and training.
Overview of adult-learning concepts, survey references, and links to underlying datasets.
https://ec.europa.eu/eurostat/statistics-explained/index.php/Adult_learning_statisticsCore short-window (“recent participation”) dataset based on the EU Labour Force Survey.
https://ec.europa.eu/eurostat/product?code=trng_lfs_01&mode=viewAnnual-window participation dataset used for “at least one learning episode in the last year” comparisons.
https://ec.europa.eu/eurostat/databrowser/view/trng_lfs_17__custom_17701998/default/tableMethodological reference for adult-learning measures and survey design considerations.
https://ec.europa.eu/eurostat/statistics-explained/index.php/Adult_Education_Survey_%28AES%29_methodologyOECD discussion of adult-learning participation and interpretation across systems and population groups.
https://www.oecd.org/en/publications/education-at-a-glance-2025_1c0d9c79-en/full-report/to-what-extent-do-adults-participate-in-education-and-training_85e1ebf6.htmlEU VET monitoring context and indicator notes commonly used for adult-learning participation.
https://www.cedefop.europa.eu/en/data-indicators/adults-25-64-year-olds-learning-experience-last-4-weeks-lfsPortal for education-related indicators and metadata used in international comparisons.
https://datatopics.worldbank.org/education/indicatorsDownload the dataset and chart images (ZIP)
A ready-to-use asset pack with the tables (CSV + HTML) and the chart images (PNG) used in this page.
- Table 1: Top 10 countries (adults 25–64 participating, %).
- Table 2: Participation by age group (selected countries).
- Chart images: Top 10 bar chart + age-group comparison chart.
