Cedefop newsletter no 162

Digital skills integration in IVET curricula

This paper analyses how digital skills are embedded in initial vocational education and training (IVET) curricula across eight European countries, drawing on harmonised national reports developed using a shared analytical framework.

Context

This paper forms part of a broader research project on the mapping of digital skills in initial vocational education and training (IVET) curricula using natural language processing (NLP) techniques across eight European countries at ISCED Level 3.
Drawing on comparative evidence, these preliminary findings show that although digital skills are a shared European policy priority, their curricular integration remains uneven in scope, depth, and consistency across countries. These differences are not random. Rather, they reflect structural features of IVET systems, including governance arrangements, curriculum update processes, stakeholder involvement, and implementation capacity. Understanding these structural factors is essential for policy-relevant conclusions.

Facts and findings

Governance arrangements are the main driver of curricular responsiveness: centralised systems ensure consistency but may update more slowly, while decentralised or partnership-based systems adapt faster but can lead to uneven outcomes across sectors and regions.
Three integration models are evident across the eight countries analysed: transversal digital skills for all learners, sector-specific embedding, and elective or pilot-based approaches; each with different implications for coverage, equity, and labour market relevance.
Systems with formal skills anticipation mechanisms and ongoing stakeholder involvement (employers, trade unions, sectoral bodies) integrate emerging digital skills more rapidly and systematically than those relying on periodic policy reform cycles.

Key messages

Digital skills are a shared EU policy priority, but their integration in IVET remains uneven in scope, depth, and consistency, reflecting structural features of national systems rather than differences in policy ambition.
No single governance model solves the trade-off between coherence and adaptability: the most effective approaches combine transversal digital skills requirements with sector-specific embedding, supported by responsive updating mechanisms and strong stakeholder coordination.
Without explicit equity-oriented measures, digitalisation risks increasing inequalities in IVET, as learners in lower-intensity sectors, rural regions, and small institutions may have fewer opportunities to acquire meaningful digital skills.
Teacher and trainer capacity is a cross-cutting constraint in all systems: curriculum reform without parallel investment in digital pedagogy and professional development risks remaining largely symbolic rather than impactful.

Policy pointers

Transversal digital skills could be embedded as a compulsory component across all IVET programmes to help ensure a common baseline for all learners, while still allowing space for sector-specific differentiation.
Flexible curriculum update mechanisms may support incremental, evidence-based revisions between major reform cycles, drawing on skills anticipation and labour market intelligence.
Stakeholder involvement in curriculum governance could be strengthened, alongside coordination mechanisms aimed at preventing advanced sectors from progressing in ways that widen digital disparities across the VET system.
Policy attention could be extended beyond curriculum design to implementation conditions: infrastructure, learning environments, and access to industry partnerships in disadvantaged regions and small providers may require targeted investment to support effective implementation.
Teacher and trainer professional development in digital competences and digital pedagogy is likely to be most effective when treated as a core rather than optional element of curriculum reform.

Policy approaches to tackle VET teacher shortages in the EU

Shortages of vocational education and training (VET) teachers and trainers have become a structural challenge for Europe’s VET systems, hindering progress towards EU priorities of agile, quality-assured, flexible, inclusive, innovative and attractive VET. As shortages are expected to grow, EU Member States, Norway and Icel...

Shortages of vocational education and training (VET) teachers and trainers have become a structural challenge for Europe’s VET systems, hindering progress towards EU priorities of agile, quality-assured, flexible, inclusive, innovative and attractive VET. As shortages are expected to grow, EU Member States, Norway and Iceland have been introducing systemic and project-based measures in national VET reform plans. Cedefop examines these policy responses reported in the Timeline of VET policies in Europe, collects robust evidence through the European Vocational Teacher Survey (EVTS).

Context

The 2020 Council Recommendation on VET, the Osnabrück Declaration and subsequent national reform plans recognised teachers and trainers as key enablers to achieving EU priorities in VET. In 2025, the Union of Skills initiative and the Herning Declaration described them as a strategic resource, calling for stronger action. Further measures are expected from the forthcoming EU Teachers and Trainers Agenda.

Facts and findings

Teacher shortages are among major issues across EU-27+ and affect all VET systems.
More than 300 measures across EU-27+ target VET teachers and trainers in the Timeline of VET policies in Europe.
VET teacher posts account for around 6 % of vacancies advertised through EURES.
In Belgium (Flemish Community), 2022 PISA data indicate that 80.1 % of learners attended schools, including VET, where learning was impacted by teacher shortages, the highest rate in the EU.
In 12 Member States, 44.2% of upper-secondary VET teachers are over 50 years old.
Only 9% of VET teachers feel valued in their countries.

Key messages

VET teacher shortages have been driven by ageing workforce, low numbers of new entrants, and growing replacement needs.
Teacher shortages are likely to grow.
Countries are responding with recruitment measures, continuing professional development, and career progression and retention of VET teachers but policies are often fragmented.
Retaining teachers is not less important that recruiting new ones.
Motivation and wellbeing (working conditions, access to training, support to deal with new challenges) are crucial for teaching remain attractive. Cedefop’s forthcoming Insight will explore it in-depth.
Lack of data makes it hard to know what works.

Policy pointers

Making VET teaching an attractive career for both new and experienced staff by improving pay, working conditions, status and clear career paths beyond classroom teaching, e.g. specialist, mentoring and leadership roles.
Focusing on both hiring and keeping teachers by reducing workload, supporting wellbeing and preventing burnout, especially for beginners
Improving alternative routes into teaching and make them high quality. For side-entry and hybrid teachers, clear standards, induction and mentoring, training and a pathway to a recognised teaching qualification are needed.
Ensuring professional development is practical, relevant and accessible, targeting real teaching needs such as caring for diverse learners, using digital tools and teaching skills for the green transition, with protected CPD time for CPD.
Building a stronger evidence base on VET teachers’ recruitment, working conditions, training, mobility and careers to inform better policies; Cedefop’s European Vocational Teacher Survey will be key.

Skill development and employment pathways for adults with low skill levels

This publication examines the characteristics, skills development, employment patterns and challenges of low-qualified and low-skilled adults in the European labour market. Low-qualified adults are defined as those with International Standard Classification of Education levels 0-2, while low-skilled adults are identified b...

This publication examines the characteristics, skills development, employment patterns and challenges of low-qualified and low-skilled adults in the European labour market. Low-qualified adults are defined as those with International Standard Classification of Education levels 0-2, while low-skilled adults are identified based on job skill requirements from the European skills and jobs survey.
Nearly half of European workers are employed in low-skilled jobs. Educational mismatches are widespread, but graduates in STEM, ICT, engineering and health fields face lower risks of low-skilled employment. Participation in education and training is significantly lower among low-qualified and low-skilled adults, making improved access to training a key policy priority.
Digitalisation and automation are reducing job opportunities for low-qualified and low-skilled workers. They face higher unemployment, lower income, greater poverty risk and lower job satisfaction. The publication concludes that targeted upskilling and reskilling, supported by coordinated stakeholder action, are essential for inclusion and long-term employability.

Context

The publication addresses the growing vulnerability of adults with low qualifications and skill levels within the EU labour market, in the context of the green and digital transitions, demographic ageing, and rising competitiveness pressures. As automation, digitalisation and structural shifts increase demand for higher-level skills, adults in low-skilled jobs face declining job opportunities, poorer working conditions and higher risks of unemployment and social exclusion. This issue is central to EU priorities such as the European Skills Agenda, the Digital Decade targets and inclusive growth objectives. The research examines the characteristics of this group, demonstrating how skill gaps, limited training participation, and job quality challenges affect them across Member States. With nearly half of EU workers in low-skilled jobs and potentially in need of reskilling or upskilling, this issue is a key concern for policymakers, VET systems, employers, and social partners.

Facts and findings

Around 50% of EU employment is in jobs with low skill requirements, extending far beyond the low qualification boundary.
Employment opportunities for low-qualified workers are projected to decline sharply, with up to one-third of such jobs expected to disappear by 2035.
Workers in low-skilled jobs have significantly lower participation in education and training, with only about one-third of training participants coming from this group and markedly lower engagement across all learning types.
Digital skill gaps are substantial, with nearly 40% of workers performing only basic digital tasks concentrated in low-skilled jobs, and limited involvement in higher-value digital activities such as problem-solving.
Workers in low-skilled jobs experience poorer labour market outcomes, including lower wages, lower job satisfaction and higher exposure to precarious employment conditions.

Key messages

The persistence of low-skilled jobs across sectors shows that low skills needs are not confined to low education, requiring broader policy responses than focusing on qualification levels increase.
Limited participation in adult learning and low awareness of upskilling needs indicate that structural barriers and motivational gaps must be addressed simultaneously.
Digital skill deficits among low-skilled adults risk deepening inequalities during the digital transition, undermining EU productivity and inclusion goals.
Poor job quality and limited career progression opportunities highlight that employment policies must focus not only on access to jobs but also on job quality.
The findings are particularly relevant for policymakers, VET providers and social partners, as coordinated action is needed to align skills systems with labour market transformations.

Policy pointers

EU and national level: Prioritise targeted upskilling and reskilling initiatives, especially in digital, technical and numerical skills, aligned with the European Skills Agenda and Digital Decade targets.
National and regional level: Improve alignment between VET systems and labour market needs to reduce persistent qualification mismatches, particularly among VET graduates.
VET providers and employers: Expand flexible, work-based and modular learning opportunities, combined with guidance and financial support, to increase participation among adults with low skill levels.
Sectoral and social partner level: Address job quality issues (wages, working conditions, career progression) in low-skilled occupations to reduce labour shortages and improve their attractiveness.
Cross-level action: Develop targeted outreach strategies for vulnerable groups (e.g. older workers, women) and strengthen coordination between policymakers, employers and learning providers to ensure inclusive transitions.

Adult education and training: Statistics overview

Adult learning has lately gained centrality as a focus topic in EU education policies because of its key role in tackling several ongoing demographic, societal, technological, digital, environmental and economic challenges. This article aims to monitor the current situation of adult education and training through available...

Adult learning has lately gained centrality as a focus topic in EU education policies because of its key role in tackling several ongoing demographic, societal, technological, digital, environmental and economic challenges. This article aims to monitor the current situation of adult education and training through available statistics from two sources of information: the Adult Education Survey and the European Labour Force Survey. Recent years’ participation rates are checked and contrasted with existing EU quantitative targets where possible, providing an overview of ongoing trends and relevant variables of interest.
First, the article outlines a brief social and policy context for adult education and training in the EU. It then sets out the differences between the two data sources and the reasons behind them, so that the participation rate targets can be adequately contrasted with the existing data in the following section. After that, it introduces other variables of interest to qualify the analysis of participation rates, and highlights the main reasons for non-participation. The article ends with a section wrapping up the key findings and pointing to some possible conclusions.

Key insights

What is adult learning and why is it important? Adult learning is the activity resulting from formal or non-formal education and training – of a general or vocational nature – undertaken after initial education and training, with different possible aims such as improving or updating knowledge and skills (upskilling) or acquiring new skills for a career move (reskilling). In the EU, recent demographic, societal, technological, digital, environmental and economic challenges are affecting the demand for skills and competences as well as career situations and transitions, intensifying the need for continuous skills development and therefore for adult education and training. Acknowledging that, the post-2020 European vocational education and training policy includes several quantitative targets related to adult learning.
How widespread is participation in adult education and training in the EU? In 2022, around 4 out of 10 adults in the EU-27 participated in formal or non-formal education and training in the previous 12 months, as measured by the Adult Education Survey excluding guided on-the-job training. Although this reflects some progress over recent years, it is still well below the EU participation rate targets of 47% in 2025 and 60% in 2030. Indicator levels vary considerably across countries and, at the current pace of progress, EU targets are unlikely to be met.
How common is low-qualified adults’ participation in education and training? Measured by the same standards, the participation rate of low-qualified adults continues to be well below the average. In 2022, almost 2 out of 10 low-qualified adults participated in the 12 months prior to the survey, still short of the 30% target set for 2025. At the current pace of progress, this target is unlikely to be met.
How common is unemployed adults’ participation in education and training? In 2024, as an EU average, fewer than 1 out of 6 unemployed adults participated in formal or non-formal education and training in the previous 4 weeks, as measured by the EU Labour Force Survey, which was used to define a target of a 20% unemployed adults’ participation rate to be met by 2025. Despite a 2 percentage point increase since 2022, the 2024 participation rate remains well below the target and, at the current pace of progress, is unlikely to reach it on time.
Who else tends to participate less in adult education and training? Among the EU’s adult population, participation rates vary considerably by age group, highest level of education attained, main labour market status, occupation group and the degree of urbanisation of the area of usual residence. Older, lower-qualified, inactive and unemployed adults, as well as those in elementary occupations and those living in rural areas, continue to have lower levels of participation.
Do adults in the EU want to participate (more) in education and training? In 2022, around 1 out of 4 adults said they wanted to participate, or participate more, in education and training. Among those, Adult Education Survey data show that adults who had already participated in the past 12 months and wanted to participate more were more numerous than those who had not participated in the same period but wanted to do so.
What are the main reasons for not participating and/or not wanting to participate? Almost 8 out of 10 adults not participating in education and training said that the main reason was that they ‘did not want’ to. At the same time, among adults not wanting to participate, around 3 out of 4 said that this was because they did not perceive the need for it.
What are the main situational obstacles to participation faced by adults wanting to participate? Adult Education Survey results indicate that time- and cost-related obstacles are the most common main reasons for not participating in adult education and training: ‘schedule’ is cited as the main reason by more than 20% of respondents wanting to participate, and around 14% point to ‘family reasons’ and to ‘costs’.
Are the obstacles to participation in education and training evenly distributed across the adult population? The findings of this article suggest that sex, age and educational attainment can account for important differences in the obstacles perceived as the main reasons for not participating in adult education and training. For example, women tend to cite ‘family reasons’ as the main obstacle more than men, while ‘schedule’ works the other way around.

Social and policy context for adult education and training.

The demographic, societal, technological, digital, environmental and economic challenges that have recently emerged across the EU affect the way adults live and work. This includes the distribution of jobs, the demand for skills and competences, and life and career situations and transitions. According to Cedefop’s Skills Forecast, the highest labour force growth in the following years is expected in the 55+ age groups. This naturally increases the need for continuous skills development, so that people can more easily adapt by updating, upgrading and acquiring relevant skills. As a result, adult learning remains a crucial aspect of social and economic policies and the EU has further stressed its promotion as a focus topic for the period 2021-2030.

Several quantitative targets have been set to guide and measure progress in European adult learning policies across Member States. The Council Resolution on the European Education Area established that, by 2025, 47% of adults aged 25-64 should have participated in learning during the last 12 months. The European Pillar of Social Rights Action Plan set a target of at least 60% by 2030. Further, the European Skills Agenda set other relevant targets to promote adult learning participation specifically among low-qualified and unemployed adults: by 2025, 30% of low-qualified adults should have participated in learning during the last 12 months, and 20% of unemployed adults should have done so during the last 4 weeks. In addition, several adjacent targets aim to guide desired progress in the coming years and concern adult education and training, for example, with the increasing of the rates of exposure of VET graduates to work-based learning and the rates of adults with at least basic digital skills.

This article aims to provide a concise and updated statistical picture of the status and progress of adult learning participation in the EU. First, it offers a brief explanation of the different data sources on adult education in the EU. It then contrasts the main participation rate targets with the data over recent years, first for the whole adult population and then specifically for low-qualified and unemployed adults. In the next two sections, it introduces other variables of interest to better understand participation, non-participation and the reasons for it. Finally, the article ends with some conclusions.

Adult education and training statistics: concepts, data and sources.

Main statistics and indicators on adult learning refer to participation of persons aged 25-64 years in formal and non-formal education and training. Information comes from survey data, now usually using a reference period of 12 months prior to the interview. This is considered to provide a more appropriate measure of participation in adult learning than indicators based on participation in education and training in the last 4 weeks used for monitoring earlier in the 2002-2010 and 2010-2020 policy cycles.

Adult participation in education and training in the EU is measured by two main surveys: the European Labour Force Survey (LFS) and the Adult Education Survey (AES). The LFS traditionally measured participation in the previous 4 weeks, and only since 2022 has it also collected biennial data on participation in the last 12 months. Before that, the AES was the only source providing data for the more comprehensive ‘12 months prior to the survey’ approach, but it is carried out only once every six years. Several methodological differences exist between the two surveys. They are summarised in a previous Cedefop web article and extensively described in more detail in a 2024 Eurostat information note. The most important difference to consider for the purposes of this article is that the AES covers guided on-the-job training as a key part of non-formal learning, while the LFS does not. This accounts for an important difference in the results of both surveys, but even when GOJT is analytically excluded from the production of AES estimates, a significant difference persists due to further methodological differences (Figure 1).

Figure 1: Adults with a learning experience in the last 12 months, LFS and AES data (%). EU-27, 2016, 2022 and 2024

Source:;Eurostat, LFS (trng_lfs_17,access date: 12/03/2026) and AES (trng_aes_100, access date: 12/03/2026) (data excluding guided on the job training supplied at Cedefop request).

AES with the inclusion of guided on-the-job training is considered by Eurostat as the best measure of participation in adult learning in the last 12 months, but EU-level targets were defined using baseline levels derived from the AES data excluding guided on-the-job training. The biennial data from the LFS on participation in the last 12 months also exclude it and can provide additional indication on trends since 2022, but given their recent introduction and the ongoing quality analysis, these data should be interpreted with more caution.

Given this policy and technical context, Cedefop now gives priority to AES data (excluding GOJT) in the European VET policy dashboard and uses a multi-source, multi-indicator approach in the key indicators on VET. In line with this approach, this article checks the status of the policy targets with AES 2022 (excluding GOJT) data when available. At the same time, to enrich the analysis, some LFS data as well as AES data including GOJT are also used.

Participation in adult education and training: rates and trends.

Figure 2 shows European and country-level percentages of adults participating in education and training in the last 12 months in 2016 and 2022. It uses AES data, available every six years, with estimates derived excluding guided on-the-job training, the same type of data used to obtain baselines and define the main targets for the current policy cycle.

Figure 2: Adults with a learning experience in the last 12 months, AES data excluding GOJT (%). EU-27 and countries, 2016 and 2022

Figure 2. Adults with a learning experience in the last 12 months, AES data excl. GOJT (%). EU27 and countries, 2016 and 2022.

Source: Eurostat, AES (data excluding guided on the job training supplied at Cedefop request). 2022 data for FR, IT and RO are accompanied by a 'b' flag: break in time series, and their values cannot be compared over time with previous ones. 2022 data for FR is also accompanied by a 'p' flag: provisional.

Using this metric, the adult participation rate in education and training for the EU-27 in 2022 was 39.5%. Despite the 2.1 percentage points increase since 2016, this is still 7.5% below the 2025 target (47%). This means that the annual increase derived from the six years between 2016 and 2022 (+0.35 percentage points per year) is not enough to meet the targets when applying a simple linear interpolation into the target years, which results in an expected participation rate of 40.6% in 2025 and of 42.3% in 2030. Here and in following interpolations, this is done by first subtracting the 2016 value to the 2022 value and dividing the result by the number of years between both (six years). Then, this annual percentage points increase is applied to the last value as many times as the years between the year it was taken and the target year.

Great variability exists at country level. Some countries such as Sweden or Hungary have already met and even surpassed the European objectives for 2030. In contrast, some other countries such as Bulgaria and Greece have very low rates and have even seen decreases compared with 2016.

A closer inspection of adult participation in education and training in recent years can be achieved by turning now to the LFS data using a ‘12 months prior to the interview’ reference period. In Figure 3, 2022 and 2024 data from this source are displayed.

Figure 3: Adults with a learning experience in the last 12 months, LFS data (%). EU-27 and countries, 2022 and 2024

Figure 3. Adults with a learning experience in the last 12 months, LFS data (%). EU27 and countries, 2022 and 2024.
Source: Eurostat, LFS (trng_lfs_17, access date: 12/03/2026). 2024 data for HU. BE, IE, DE and EL are accompanied by a 'b' flag: break in time series, and their values cannot be compared over time with previous ones. 2024 data for MT is accompanied by a 'u' flag: low reliability.

Different methodologies between AES and LFS account for different levels in the participation rates measured by both surveys. The EU average tends to be lower in the latter, which accounts for participation rates of 25.1% in 2022 and 28.5% in 2024 (meaning a 14.4% difference for 2022 EU-27 data). The 2024 LFS data confirm the persistence of considerable cross-country differences and indicate a modest average upward trend in recent years for the EU as a whole. For the EU average, between 2022 and 2024 it is possible to estimate an absolute increase of 3.4 percentage points (as the difference between the 2024 and 2022 values). Among countries for which reliable comparisons can be carried out over time, most of the changes are also positive.

For a broader view of trends in adult participation in education and training over the years, it is also possible to rely on the LFS ‘4 weeks prior to the interview’ variable. Although it is now considered a less precise indicator, it can still provide some information regarding progress over a longer period

Figure 4: Adults with a learning experience in the last 4 weeks, LFS data (%). EU-27, 2015 2024.

Source: Eurostat, LFS (trng_lfse_01, access date: 12/03/2026). 2021 data for EU27 is accompanied by a 'b' flag: break in time series, and its value cannot be compared over time with previous ones.

IIn the previous policy cycle, this indicator was used to monitor progress towards a target of 15% of adults participating in education and training in the last 4 weeks by 2020 agreed under the European agenda for adult learning. Figure 4 shows that, following years of minor improvements and a drop in 2020 (most probably due to COVID-19 pandemic effects), EU average values for this indicator are now increasing at a more sustained pace towards the 15%. By 2024, the participation rate documented by this approach for the EU-27 was 13.5%. Caution is advised when comparing the pre- and post-2021 data due to a break in time series derived mainly from the introduction of a new IESS Framework Regulation, on which the LFS is based.

Status of the new targets: low qualified and unemployed adults.

The European Skills Agenda introduced two new targets regarding adult education and training with the aims to reach, by 2025, 30% of low-qualified adults participating in adult education and training during the last 12 months and 20% of unemployed adults doing so during the last 4 weeks.

As in the previous section, Figure 5 below prioritises and focuses on 2016 and 2022 AES data excluding GOJT.

Figure 5: Low-qualified adults with a learning experience in the last 12 months, AES data excl. GOJT (%). EU-27 and countries, 2016 and 2022

Source: Eurostat, AES (data excluding guided on‑the‑job training supplied at Cedefop request). 2022 data for FR, IT and RO are accompanied by a 'b' flag: break in time series, and their values cannot be compared over time with previous ones. 2016 data for CZ, EL and HR and 2022 data for DK, SK, LV, SI, CZ, PL and EL are accompanied by a 'u' flag: low reliability. 2016 data for BG, LT, SK and RO and 2022 data for BG, LT and HR are not available.

CCompared with the already discussed participation rates for the whole EU-27 adult population, Figure 5 shows lower values for the group of low-qualified adults (with at most a qualification at ISCED levels 0-2). Using AES data excluding guided on-the-job training for 2022, it is observed that while 39.5% of the whole adult population claimed to have participated in the last 12 months, only 18.4% of low-qualified adults did so. The 2025 target is still 11.6 percentage points away from being reached, and the increase achieved since the previous round of AES six years before is minimal (+0.5 percentage points). At this rate, simple linear interpolation returns an 18.7% participation rate for low-qualified adults in 2025, still 11.4 percentage points below the target.

As with participation rates for the whole adult population, great country-level variability persists in participation rates among low-qualified adults. Country-specific data tend, however, to be more affected by low reliability and breaks in time series.

For a closer inspection of more recent progress, results from LFS can be considered.

Figure 6: Low-qualified adults with a learning experience in the last 12 months, LFS data (%). EU-27 and countries, 2022 and 2024

Source: Eurostat, LFS (trng_lfs_18, access date: 12/03/2026). 2024 data for HU. BE, IE, DE and EL are accompanied by a 'b' flag: break in time series, and their values cannot be compared over time with previous ones. 2016 data for FI, SI and HR and 2022 data for FI, MT and HR are accompanied by a 'u' flag: low reliability. 2022 data for LV and BG and 2024 data for BG are not available.

Figure 6 confirms that LFS-based EU estimates tend to be lower than those from AES (even when guided on-the-job training is excluded from the latter), reflecting other methodological differences: in 2022, the EU-27 participation rate for low-qualified adults was 18.4% in AES and 11.2% in LFS. Figure 6 is nonetheless helpful in that it shows progress in the very last years.

Most countries have recently experienced increases in the participation rates of low-qualified adults. The average EU-27 value has gone up to 12.7% in 2024, corresponding to an increase of 1.5 percentage points since 2022.

When monitoring unemployed adults’ participation in education and training, the reference period of ‘4 weeks prior to the interview’ is considered more in line with the labour market concept of unemployment status. LFS is consequently the preferred reference source to consider.

Figure 7. Unemployed adults with a learning experience in the last 4 weeks, LFS data (%). EU-27 and countries, 2022 and 2024.

Source: Eurostat, LFS (trng_lfse_02, access date: 12/03/2026). 2024 data for IE, BE, DE and EL are accompanied by a 'b' flag: break in time series, and their values cannot be compared over time with previous ones. 2022 and 2024 data for ES and FR are accompanied by a 'd' flag: definition differs. 2022 data for LU and HR and 2024 data for MT, HR and RO are accompanied by a 'u' flag: low reliability. 2022 data for RO, BG and SK and 2024 data for BG and SK are not available

Figure 7 shows 2022 and 2024 participation rates of unemployed adults in the EU-27 and at country level. The participation rate for EU-27’s unemployed adults was 13.3% in 2022 and 15.3% in 2024, accounting for a 2 percentage points increase in two years.

Even though the 2025 EU target is unlikely to be met at the current pace, these results indicate that, following years of modest improvements, EU average values for this indicator are increasing at a more sustained pace and show better progress. This is clear when looking at the longer period trend for both low-qualified and unemployed adults as shown in Figure 8.

Figure 8. Recent (last 4 weeks) adult learning participation among low qualified and unemployed adults, LFS data (%). EU-27, 2015 2024.

Source: Eurostat, LFS (trng_lfse_03, access date: 12/03/2026 & trng_lfse_02, access date: 12/03/2026). 2021 data for EU27 are accompanied by a 'b' flag: break in time series, and their values cannot be compared over time with previous ones.

Here, the most promising evolution is depicted in the participation rates of unemployed adults. Although there is an important break in the time series in 2021, there is still a visible change of pace in the latest rate increases, with a 2.6 percentage points increase from 2021 to 2024. Recent increases in participation rates of low-qualified adults have been overall smaller, with a difference of +1.2 percentage points between 2021 and 2024.

LFS data show that, regardless of the possible overlaps of both sub-groups of the adult population in EU-27, unemployed adults were in 2024 almost three times more likely to participate in education and training in the 4 weeks prior to the survey than low-qualified adults, with participation rates of 15.3% and 5.5% respectively.

Other important aspects of participation rates.

These last findings point to the importance of a deeper understanding of the dynamics involved in the participation of adults in education and training. To this end, it is worth looking into participation rates for other relevant sub-groups of adults, even when no target is set for them. This section is dedicated to the analysis of different aspects that can account for crucial differences in the way participation rates vary among the population. This can not only point at pertinent categories for understanding the topic of interest but suggest leverage points for a more informed tackling of the challenges ahead.

Since the monitoring of targets is not the main goal now, it is possible to use AES including GOJT data as the main reference. This allows users to take advantage of the full potential of the survey. Guided on-the-job training is an essential part of adult education and training and including it can result in a more precise picture, which might be useful for policy design and implementation.

This section turns the attention to participation rates in the AES including GOJT data when disaggregated by sex, age, educational attainment, labour status, occupation and degree of urbanisation of the area of usual residence of the respondents. Apart from showing differences across socio-demographic groups and checking their absolute changes between the two last AES rounds (as the difference between 2022 and 2016 values), it includes relative changes (as absolute changes divided by the value of the baseline year, 2016) as an additional point of reference using a secondary axis in the charts.

Figure 9. Participation rate in adult education and training by sex, AES data incl. GOJT (%). EU-27, 2016 and 2022.

Source: Eurostat, AES (trng_aes_100, access date: 12/03/2026).

Figure 9 shows the participation rates of adults and adults by sex in 2016 and 2022, as well as their relative change percentage over those six years. As it is clear from the chart, no major differences are found in the participation between men and women based on EU-27 average estimates from the last two AES rounds. Men and women had very similar participation rates in adult education and training in 2016 (43.6% and 43.8% respectively). Compared with 2016, in 2022 participation rates went up for both genders, the increase for women being slightly larger than the one for their male counterparts, resulting in rates of 46% for men and 47.2% for women. However, the gender dimension does relate to some differences in the perceived obstacles to participation (see next section).

Figure 10. Participation rate in adult education and training by age groups, AES data incl. GOJT (%). EU-27, 2016 and 2022.

Source: Eurostat, AES (trng_aes_101, access date: 12/03/2026).

Figure 10 presents the same kind of analysis with participation rates disaggregated by age. In this case, there is a visible relation in which participation in education and training becomes less common among older groups. AES data show that in the six years between the last two surveys (2016-2022) every age group has experienced an increase in its participation in adult education and training. The 25-34 years old group is the one with the greatest absolute increase (+4.3 percentage points) and the 55-64 years old group the one with the greatest relative increase (+12%). Still, major differences by age persist, with the 55-64 year-olds participating the least. Statistically speaking, for every adult in the 55-64 age range participating in education and training in 2022 there were almost 1.6 adults in the 25-34 age range doing the same. This leads to concern because, as already mentioned, workers aged over 55 are increasing in number faster than other age groups and need to adapt more to new technological advances.

Figure 11. Participation rate in adult education and training by highest level of education attained, AES data incl. GOJT (%). EU-27, 2016 and 2022.

Source: Eurostat, AES (trng_aes_102, access date: 12/03/2026).

The biggest differences among the analysed categories of adults can be found when grouping by highest level of educational attainment (Figure 11). Low-qualified adults (that is, adults with at most a qualification at ISCED levels 0-2 as their highest) had a participation rate of 25.1% in 2022, considerably lower than the 41.5% average for adults with a medium level of education (that is, those with at most a qualification at ISCED levels 3-4) and the 65.7% for adults with a qualification at tertiary level (that is, ISCED levels 5 to 8). This means that highly-qualified adults were, in 2022, more than twice as likely to participate in education and training as low-qualified adults. However, low-qualified adults were also the group that experienced the largest increase since 2016, both in absolute (+2.2 percentage points) and in relative terms (+9.6%).

In the second group (ISCED levels 3-4), which clusters adults with upper secondary and post-secondary non-tertiary education, 2022 AES data allow a distinction between those with general and vocational orientation. In 2022, in the EU-27, adults with medium-level vocational qualifications as their highest had a participation rate in adult education and training slightly lower than their counterparts with general education at the same ISCED level, with a negative difference of 3.4 percentage points (40.7% and 44.1% respectively).

Figure 12. Participation rate in adult education and training by main labour market status, AES data incl. GOJT (%). EU-27, 2016 and 2022.

Figure 12. Participation rate in adult education and training by main labour market status, AES data incl. GOJT (%). EU27, 2016 and 2022.
Source: Eurostat, AES (trng_aes_103, access date: 12/03/2026).

Figure 12 displays participation rates by main labour market status according to AES data including GOJT. Employed adults clearly emerge as those with higher participation rates in adult education and training. In 2022 the rates were 53.9% for employed adults compared with 29.2% for unemployed adults and 24.4% for inactive ones. In this case, the chances that an employed adult had participated in education and training in the 12 months prior to the interview were more than double with respect to inactive adults but not with respect to unemployed ones. Still, it could be said that every unemployed participant accounted for 1.85 employed participants. To an extent, this also relates to the importance of GOJT, which is easier for employed adults to access. Unemployed adults had a 27.8% participation rate in 2016 and experienced an increase of 1.4 percentage points between 2016 and 2022 as measured by AES data including GOJT. This corresponds to a 5% relative increase in six years, still below the 10.4% relative change experienced by the otherwise less participative inactive adult population.

Figure 13. Participation rate in adult education and training by occupation groups, AES data incl. GOJT (%). EU-27, 2016 and 2022.

Source: Eurostat, AES (trng_aes_104, access date: 12/03/2026).

Participation rates can seem overall higher when dividing the adult population by occupation groups, probably due to the absence of some adults who were part of the less participative groups of inactive and unemployed adults (those not previously employed who could not be classified in a specific category). However, there are still important differences to consider between groups of occupations (Figure 13). The group of managers, professionals, technicians and associate professionals had a participation rate of 68.7% in 2022 and clearly clusters the adults who participate the most in education and training.

Adults with such occupations were more than twice as likely to participate than adults with elementary occupations, who reached a participation rate of 31.5% in the same year. Skilled manual workers and clerical support workers, service and sales workers occupied a middle-ground position between the other two groups and had participation rates of 36.7% and 48.1% respectively. Absolute and relative increases since 2016 were generally small.

Figure 14. Participation rate in adult education and training by degree of urbanisation of the area of usual residence, AES data incl. GOJT (%). EU-27, 2016 and 2022.

Source: Eurostat, AES (trng_aes_105, access date: 12/03/2026).

The degree of urbanisation of the area where adults usually live is the last dimension considered in this section. Figure 14 shows that adults living in more urbanised areas tend to participate more than those living in less urbanised areas. Adults living in cities are both those participating more and those whose participation increased more in the six years between the last two AES, both in absolute and in relative terms. In 2022, rural areas had a participation rate in adult education and training of 40.5% and cities one of 51%, which means that adults living in cities were around 25% more likely to participate than adults living in rural areas.

Obstacles, barriers and reasons for not participating.

This last section focuses on data for a better understanding of the reasons for participating or not participating in education and training.

Figure 15. Adult population by participation in education and training in the last 12 months and by desire to participate/participate more, AES data incl. GOJT (%). EU-27, 2022.

Source: Eurostat, AES (trng_aes_175, access date: 12/03/2026).

AES allows the clustering of the European adult population into four different groups according to their participation and desire to participate in education and training (Figure 15). In 2022, the largest group was adults who did not participate and did not want to participate in education and training, accounting for 42.4% of the whole adult population. The second-largest group consisted of adults who participated and did not want to participate more in education and training (30.4%). Only 10.2% did not participate but wanted to do so and 15.7% participated and wanted to participate more. This may be due to a selection bias by which the group of adults who participate tends to include those more inclined to participate again, but it may also indicate that taking part in education and training, even in short programmes, drives greater interest in continuing that involvement.

One reason behind the prominence of adults who do not participate and state that they do not want to do so could be that they perceive education and training as involving certain obstacles or inconveniences. Further exploration of the data is needed here, including to understand the obstacles faced by adults who state that they want to participate but still refrain from doing so.

Figure 16. Adult population not participating in education and training by main reason, AES data incl. GOJT (%). EU-27 and countries, 2022.

igure 16. Adult population not participating in education and training by main reason, AES data incl. GOJT (%). EU27 and countries, 2022.

Source: Eurostat, AES (trng_aes_195, access date: 12/03/2026). Some data points are accompanied by a ‘u’ flag: low reliability. The following categories and countries are concerned: 'Wanted but encountered difficulties which were not due to personal reasons' data for DK and SK, 'Wanted but encountered difficulties for personal reasons' data for BG, DK and SK and 'No response' data for SE, LU, FR, ES and BG. Data on every category for CZ are accompanied by a 'd' flag: definition differs. 'No response' data for EE, DE, CY, IT, MT, HU, RO, SI, HR, LV, BE, LT, DK, PL, SK and CZ are not available.

Figure 16 shows that among adults not participating in education and training in the EU-27 in 2022 the vast majority claimed that the main reason was that they ‘did not want’ to (79.5%). In all countries, this is the category with the highest share of answers (55% or more). On average, apart from the small percentage of no response (1.3%), adults not participating who opted for a different answer are divided between those who indicated difficulties not related to personal reasons (that is, external factors) (11%) and those who pointed to difficulties related to personal reasons (6.8%).

Figure 17. Adult population not wanting to participate in education and training by main reason, AES data incl. GOJT (%). EU-27 and countries, 2022.

Figure 17. Adult population not wanting to participate in education and training by main reason, AES data incl. GOJT (%). EU27 and countries, 2022.
Source: Eurostat AES (tng_aes_192, access date: 12/03/2026). 'Other reason' data for BG and 'No response' data for IE and DK are accompanied by a 'u' flag: low reliability. Data on every category for CZ are accompanied by a 'd' flag: definition differs. 'Personal reasons' for BG and 'No response' data for RO, MT, HR, LV, BE, CY, AT, HU, SI, IT, SK, CZ, EE, LT and BG are not available.

Figure 17 shows that the great majority of adults not wanting to participate in education and training in the EU-27 indicate that they feel ‘no need’ to do so (75.9%). This perception relates to the awareness of one’s needs and the ability to assess them, both in relation to individual objectives and in the wider context affecting the perspectives of adults, workers, organisations, societies and economies at large. It also relates to the experience of guidance, which is far from widespread and universal in the EU, with considerable variability across countries and demographic and socio-economic groups (Guidance for adult learning, evidence from the 2022 AES, Cedefop forthcoming).

This is also part of a broader picture of obstacles typically framed as dispositional barriers or attitudes towards learning in major frameworks proposed in the scientific literature (Cross, 1981; Rubenson & Desjardins, 2009), which should be examined: i) alongside institutional and situational barriers, ii) together with financial, time- and information-related barriers, and iii) with reference to all non-participants. The AES survey has some limitations in this sense but allows some indications to be derived.

Figures 18 and 19 focus on adults wanting to participate in education and training but not participating, by main reason for not participating.

Figure 18: Adult population wanting to participate in education and training but not participating by main reason, AES data incl. GOJT (%). EU-27, 2022.

Source: Eurostat, AES (trng_aes_179, access date: 12/03/2026).

Although there is a wide variety of obstacles preventing adults who want to participate in education and training from doing so, in the EU as a whole in 2022 the most common ones were time- or cost-related. Schedule incompatibilities were the main obstacle for adults not participating but wanting to (22.8%), followed by family reasons (14.4%) and costs (13.7%) (Figure 18). Together, these three account for 50.9% of the total.

Figure 19. Adult population wanting to participate in education and training but not participating by main reason, AES data incl. GOJT (%). EU-27 and countries, 2022.

Source: Eurostat, AES (trng_aes_179, access date: 12/03/2026). Some data points are accompanied by a ‘u’ flag: low reliability. The following categories and countries are concerned: 'Schedule' data for DK and NL, 'Family reasons' data for BG, LT and DK, 'Costs' data for BG, SK, CZ and DK, 'No response' data for MT, IE, CZ and NL, 'Other personal reasons' data for MT, SK, HR, IE, FI and DK, 'Lack of support from employer or public services' data for MT, HU, SI, LT, HR, EE, IE, CZ and NL and 'No suitable offer for education or training' data for MT, HU, SK, LT, HR, IE and DK. Data on every category for CZ are accompanied by a 'd' flag: definition differs. Some data points are not available. The following categories and countries are concerned: ‘No response’ data for LV, BG, IT, SI, AT, SK and EL, ‘Other personal reasons’ data for HU, BG, EL and DK, ‘Lack of support from employer or public services’ data for LV, BG, SK and EL and ‘No suitable offer for education or training’ data for BG and EL. ‘Other reasons (combined)’ category is the ad hoc grouping of the ‘Health or age reasons’, ‘Other reason’, ‘Course booked out’, ‘Distance’ and 'Too few registration’ categories. These usually have high proportions of low reliability flags which can be directly consulted in the Eurostat table. In the chart, several countries show a gap at the end of their columns and do not reach the 100% with the sum of every category. This is due to the unavailability of various data points in some of these categories

The distribution and even the order of prominence of the main obstacles that stop adults who want to participate in adult education and training from doing so can vary considerably from country to country (Figure 19).

Costs were the third most common obstacle faced by that subgroup of the population at EU-27 level in 2022 (13.7%), but they reached much higher levels in some countries, such as Romania, where costs were the most common obstacle (31.2%), or Lithuania (24.6%). By contrast, in some other countries fewer than 5% of adults not participating though wanting to did so for cost-related reasons, such as France (4.3%) and the Czech Republic (4.1%).

Time-related obstacles also vary between countries. Cyprus is a visible outlier for the ‘family reasons’ obstacle, being the only country where more than 30% of adults wanting to participate in adult education and training but not doing so reported this as the main reason (44%). As for the schedule obstacle, there is no such outlier, but eight countries exceed the 30% threshold: Malta (41.3%), Latvia (40.1%), Hungary (38.1%), Bulgaria (37.1%), Italy (33.1%), Belgium (32.3%), Slovenia (31.4%) and Austria (30.1%).

In any case, these two last obstacles are involved in another noteworthy pattern when analysed separately by gender.

Figure 20. Adult population wanting to participate in education and training but not participating by main reason and sex, and percentage gap by sex (Women - Men), AES data incl. GOJT (%). EU-27, 2022.

Source: Eurostat, AES (trng_aes_179, access date: 12/03/2026).
Figure 20 shows 2022 EU-27 values for four selected items indicated as main obstacles to participation in education and training by adult men and women who did not participate but wanted to, along with their differences in response by gender. As is evident, reasons for not participating are not equally distributed across the adult population wanting to participate. Some obstacles seem to affect women more than men and vice versa.

The biggest difference is found in the ‘family reasons’ obstacle, stated as the main one by 18.7% of women and 9.3% of men (9.4 percentage points difference). On the other hand, the ‘schedule’ obstacle works the other way around (with a 7.6 percentage points difference in favour of men). This points to an important imbalance in the gender distribution of obstacles to education and training that deserves its own consideration, but also again highlights the overall importance of time-related conflicts and difficulties when wanting to participate in education and training. Other relevant variables are ‘costs’, which also affect women’s participation more, and ‘lack of support from employer or public services’, which men find more impeding.

Figure 21. Adult population wanting to participate in education and training but not participating by main reason and age groups (25¬ 34 years old and 55 64 years old), and percentage gap (oldest - youngest), AES data incl. GOJT (%). EU-27, 2022.

Source: Eurostat, AES (trng_aes_180, access date: 12/03/2026).

The same kind of analysis can be done with the age variable, now focusing on the youngest and oldest groups of adults considered for this article (Figure 21). As could have been expected, ‘health or age reasons’ are the main point of divergence between these two groups: for adults aged 55-64 this is the main reason in 12.2% of cases, while the same happens only in 3.6% of cases when the respondents are 25-34 years old (8.6 percentage points difference). By contrast, younger adults are more likely to consider ‘costs’ as the main reason for not participating, with a difference of 7.7 percentage points compared with the older group. Other, smaller differences are found in the more time-related reasons of ‘schedule’ and ‘family reasons’, the first being more commonly pointed out by the younger group of adults and the latter by the older one.ns’, the first being more commonly pointed out by the younger group of adults and the latter by the older one.

Figure 22. Adult population wanting to participate in education and training but not participating by main reason and highest level of educational attainment (ISCED levels 0 2 and ISCED levels 5 8), and percentage gap (highest – lowest qualified), AES data incl. GOJT (%). EU-27, 2022.

Source: Eurostat, AES (trng_aes_181, access date: 12/03/2026).

Finally, Figure 22 compares the main reasons given by adults not participating in education and training by highest level of educational attainment, focusing on the groups of adults with the lowest and the highest qualifications. The greatest difference found in this last section regarding main reasons for not participating is between these two groups of adults. The higher-qualified group of adults has a much stronger tendency to consider ‘schedule’ as the main reason, which is chosen in 28% of cases, than the lower-qualified group, for whom it is the main reason in 14.6% of cases (a 13.4 percentage points difference). By contrast, lower-qualified adults tend to point out ‘health or age reasons’ more, with a 7.5 percentage points difference compared with higher-qualified adults. It should also be noted that, for the first time in the last three charts, ‘costs’ instead of ‘schedule’ is the most common main reason for a subgroup of adults: low-qualified adults, who consider it the main reason for not participating in 15.2% of cases, 0.6 percentage points more than their own rate for ‘schedule’ and 3.3 percentage points more than the rate for the same reason for the high-qualified group of adults.

Conclusions.

Considering the four EU-level quantitative targets currently in play for adult education and training (47% participation rate by 2025, 60% participation rate by 2030, 30% participation rate for low-qualified adults by 2025 and 20% recent participation rate for unemployed adults by 2025), progress is ongoing. However, at the current pace, increases are not sufficient to meet the targets in their proposed years.

Considerable differences persist across countries as well as demographic and socio-economic groups, namely by age, highest level of education attained, main labour market status, occupation and degree of urbanisation of the area of usual residence. Among these, the variable with the highest difference in participation in 2022 between its least and most participative groups is educational attainment. By contrast, participation rates turn out to be very similar by gender. Instead, gender appears to be more relevant when analysing the distribution of obstacles to participation, which are also unevenly distributed across age and educational attainment groups.

The most pressing concerns for people wanting to participate in adult education and training but not able to do so continue to relate to time (family reasons being the main obstacle for 14.4% of these adults in the EU-27 and schedule being so for 22.8%) and costs (the main obstacle for 13.7% of adults wanting to participate). Time-related issues could be alleviated by promoting flexibility of education and training, including workplace and on-the-job training, so that it is not an additional burden for the people enrolled.

However, the vast majority of the adult population not participating in education and training indicate unwillingness to do so. Moreover, there is a high proportion of adults not perceiving a need to participate in adult education and training (75.9% of those not wanting to participate). This perception relates to the awareness of one’s needs and the ability to assess them with respect to individual objectives and in the wider context affecting the perspectives of adults, workers, organisations, societies and economies at large. Cedefop’s Skills Forecast projections support the idea of a changing labour market that will likely keep reinforcing the importance of adult learning across the EU in the coming years, potentially deepening the discrepancy between real and perceived needs. One way to tackle this at an aggregate level is through the promotion and strengthening of guidance services and systems.

11:00 - 11:10	Welcome and introduction	Cedefop and the European Commission, DG Employment
11:10 - 11:30	Setting-the-scene	Quality in apprenticeship schemes in Europe - findings from Cedefop’s comparative analysis based on the European Framework for Quality and Effective Apprenticeships
11:30 - 12:10	Panel discussion	Representatives of governments, employers, trade unions, providers and apprentices
12:10 - 12:20	Q&As
12:20 -12:30	Key take-aways and closing	Cedefop

Cedefop newsletter

Context

Facts and findings

Key messages

Policy pointers

Context

Facts and findings

Key messages

Policy pointers

Context

Facts and findings

Key messages

Policy pointers

Key insights

Social and policy context for adult education and training.

Adult education and training statistics: concepts, data and sources.

Participation in adult education and training: rates and trends.

Status of the new targets: low qualified and unemployed adults.

Other important aspects of participation rates.

Obstacles, barriers and reasons for not participating.

Conclusions.

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