Towards an improved adult learning monitoring framework : revisiting the available data and indicators.
Date: 2020-05-26
Institutions: Joint Research Centre
Subjects: adult education, continuing education, education policy, learning, professional qualifications, research report, vocational training

Towards an improved adult learning 
monitoring framework. 

Revisiting the available data 
and indicators 

Vera-Toscano, E., Urzì Brancati, C. 

2020 

EUR 30069 EN 

 
 
This publication is a Technical report by the Joint Research Centre (JRC), the European Commission’s science and knowledge service. It 
aims to provide evidence-based scientific support to the European policymaking process. The scientific output expressed does not imply a 
policy position of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is 
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of its frontiers or boundaries. 

Contact information  
Name: Maria Cesira Urzì Brancati  
Address: C/ Inca Garcilaso, 3 41092 Seville/Spain 
Email: Cesira.URZI-BRANCATI@ec.europa.eu  
Tel.: +34 9544-88278 

EU Science Hub 
https://ec.europa.eu/jrc 

JRC119018 

EUR 30069 EN 

PDF 

ISBN 978-92-76-10222-9 

ISSN 1831-9424 

doi:10.2760/160673 

Luxembourg: Publications Office of the European Union, 2020 

© European Union, 2020 

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All content © European Union, 2020, except: Figure 1, page 7 taken from: Molyneux et al, 2019; page 104. 

How to cite this report: Vera-Toscano, E., Urzì Brancati, C. Towards an improved adult learning monitoring framework. Revisiting the 
available data and indicators, EUR 30069 EN, Publications Office of the European Union, Luxembourg, 2020, ISBN 978-92-79-10222-9, 
doi:10.2760/160673, JRC119018. 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Contents 

Abstract ....................................................................................................................................................................................................................................................................... 1 

Acknowledgements .......................................................................................................................................................................................................................................... 2 

1 

Introduction..................................................................................................................................................................................................................................................... 3 

1.1  Milestones in EU Adult Education and Training policy ............................................................................................................................. 3 

1.2  A Renewed European Agenda for Adult Learning: Objectives and Actions .......................................................................... 6 

2  An examination of the ET2020 benchmark of adult participation in lifelong learning: Features, caveats and 
challenges .............................................................................................................................................................................................................................................................. 10 

2.1  The European Labour Force Survey as the main data provider for the ET2020 benchmark on adult 
participation in lifelong learning. ............................................................................................................................................................................................ 11 

2.1.1 

Structure and objectives of national LFS surveys .................................................................................................................. 12 

2.1.2 
The impact of using a 12-months or 4-weeks reference period and the type of education and 
training recoded: A short look at the 2003 LFS ad hoc module on lifelong learning. () ........................................... 12 

2.2  The distribution of adult lifelong learning by individual characteristics across the EU. ...................................... 16 

2.2.1 

Adult participation in lifelong learning and age. ...................................................................................................................... 16 

2.2.2 

Adult participation in lifelong learning and level of educational attainment............................................... 17 

2.2.3 

Adult participation in lifelong learning and labour market status. ......................................................................... 18 

2.2.4 

Adult participation in lifelong learning and type of occupation. ............................................................................... 20 

2.3  Discussion on the limitations of the existing ET2020 benchmark on adult participation in lifelong 
learning: Challenges ahead. ().................................................................................................................................................................................................... 21 

3  Towards a better framework for monitoring adult participation in lifelong learning within the EU. .................... 22 

3.1  The Adult Education Survey (AES): A rich source of evidence on adult learning statistics ................................ 22 

3.2  The Continuing Vocational Training Survey (CVTS): An employer’s survey. ..................................................................... 28 

3.3  The OECD Survey on Adult Skills (PIAAC): Skills acquisition beyond formal education ........................................ 31 

3.4  UNESCO-UIS OECD Eurostat (UOE) joint data collection on education, DG EMPLOYMENT’s labour 
market policy database, and other European statistics. .................................................................................................................................. 33 

3.5  Other European Surveys: ECHP, EU-SILC, EWCS and ESJS. .............................................................................................................. 34 

3.6  Considerations for Policy and Practice ................................................................................................................................................................ 36 

4  Summary and Conclusions ........................................................................................................................................................................................................... 38 

References ............................................................................................................................................................................................................................................................. 39 

Annex – A Benchmarking Framework .......................................................................................................................................................................................... 41 

List of figures ..................................................................................................................................................................................................................................................... 44 

List of tables ........................................................................................................................................................................................................................................................ 45 

i 

 
 
 
 
 
 
 
 
Abstract 

Adult  education  is recognised  as an  essential  driver of  economic  growth  and  social  development  within  the 
European Union and has been a political priority for nearly two decades. It is deemed to play a pivotal role to 
create better jobs in Europe, improve quality of life and promote individual development, personal fulfilment 
and active citizenship.  

A number of Commission initiatives in the recent past have underscored the importance of adult learning. In 
particular, the European Pillar of Social Rights, proclaimed and signed by the Council of the EU, the European 
Parliament and the Commission during the Gothenburg Social Summit for fair jobs and growth announced the 
right to quality and inclusive education, training, and life-long learning as its very first principle. In addition, as 
part  of  the  Education  and  Training  2020  (ET2020)  strategy,  EU  Member  States  have  agreed  on  a  common 
target to increase participation in adult learning in the EU.  

Fostering adult learning is now more important than ever because of three concurrent factors: technological 
change, population ageing and global migration flows.  

Technological change, and in particular automation and digitisation, affecting the world of work by altering or 
erasing certain tasks, often the most repetitive and standardised, and creating new ones. Adult and learning is 
essential to ensure that workers, and especially older ones, are equipped with the necessary skills throughout 
their lifetime, so that they can thrive in a constantly changing labour market. 

Similarly, in the context of population ageing, adult learning and continuing education become crucial as they 
can provide older people with the capabilities they need to stay in work well into their sixties and seventies. 

Finally, adult learning has a central role to play in a context of international migration, since it can be a tool to 
support the linguistic, social and cultural integration of immigrants. .  

The "Education and Training 2020" (ET 2020) strategic framework is a crucial tool to monitor participation in 
adult learning; it set the average participation rate in adult learning at 15% of the population aged 25-64 by 
2020. Yet, so far, only a few Member States have reached the benchmark. Furthermore, to underpin the adult 
learning target and support its monitoring within the European Semester, in 2018 Member States approved a 
comprehensive  framework,  developed  by  the  Commission,  for  benchmarking  adult  skills  and  adult  learning 
systems in the EU,.  

This report aims to reflect on the  performance of the existing ET  2020 benchmark on adult  participation in 
learning, by  comparing  cross-country  patterns  of  participation  using  different  sources  of  data.  In  particular, 
this  report  provides  empirical  evidence  on  participation  in  adult  learning,  with  a  specific  focus  on  different 
subgroups, such as older people or others belonging to groups that are traditionally excluded from learning, 
which  are  identified  as a  priority  by  the  European  Council’s  “Renewed  European  Agenda  for  Adult  Learning” 
(EEAL). The report also discusses the strengths and weaknesses of the current data source used to create the 
indicators, i.e. the EU Labour Force Survey (EU-LFS) and extended coverage of adult learning in the EU-LFS as 
of 2022, enabling improved indicators, and further introduces the possibility to create other indicators based 
on  different,  complementary  data  sources,  such  as  the  Adult  Education  Survey  (AES),  the  Continuing 
Vocational Training Survey (CVTS), the OECD Survey on Adult Skills (PIAAC), and others. 

1 

 
Acknowledgements 

The  authors  would  like  to  thank  Mantas  Sekmokas  (DG  EMPL),  Sabine  Gagel  (Eurostat)  and  Elodie  Cayotte 
(Eurostat) for their substantial reviews and comments; we would also like to thank Enrique Fernández-Maciás 
for his support and suggestions.  

Authors 

Esperanza Vera-Toscano 

Cesira Urzí Brancati 

2 

 
1 

Introduction 

Adult  learning  refers  to  the  participation  of  adults  in  learning,  that  is,  all  learning  activities  undertaken 
throughout  the  working  life  with  the  aim  of  improving  knowledge,  skills  and  competences,  within  personal, 
civic, social or employment-related perspectives (i.e. lifelong learning). (1) 

Adult  education  is recognised  as an  essential  driver of  economic  growth  and  social  development  within  the 
European  Union  and  has  been  a  political  priority  for  nearly  two  decades.  The  2006  European  Commission's 
Communication  ‘Adult  learning:  It  is  never  too  late  to  learn’  and  the  subsequent  resolution  by  European 
Parliament underline the importance of adult learning to create ‘better jobs in Europe, improve quality of life 
and promote individual development, personal fulfilment and active citizenship’ (p. 5).  

Fostering adult learning is now more important than ever because of three concurrent factors: technological 
change, population ageing and global migration flows.  

Technological change, and in particular automation and digitisation, affecting the world of work by altering or 
erasing certain tasks, often the most repetitive and standardised, and creating new ones. Adult and learning is 
essential to ensure that workers, and especially older ones, are equipped with the necessary skills throughout 
their lifetime, so that they can thrive in a constantly changing labour market. 

Similarly, in the context of population ageing, adult learning and continuing education become crucial as they 
can provide older people with the capabilities they need to stay in work well into their sixties and seventies. 

The JRC, in collaboration with DG employment, is carrying out a series of studies to build up evidence on adult 
education,  as  well  as  work-based  learning  (Flisi,  2019).  In  addition,  given  the  increasing  complexity  in  the 
types of tasks workers are required to carry out and the parallel upskilling needs, the JRC is working on the 
formulation of a unified framework for tasks, skills and competences (Rodrigues and Fernández-Macías 2020; 
Fernández-Macías and Bisello 2020). This includes a pilot programme on the compilation of data on tasks at 
the  national  level  leading  to  the  development  and  testing  of  a  tasks  questionnaire  (Cirillo  and  Guarascio 
2020).  This  report,  in  particular,  provides  empirical  evidence  and  a  conceptual  discussion  on  monitoring 
participation in adult learning in Europe. So far, the main tool to monitor how Member States have fared in 
terms of participation in adult learning has been the indicator identified for the Education and Training 2020 
(ET 20202), which sets the benchmark at an average of at least 15 % of adults should participate in lifelong 
learning.  However,  this  report  will  present  empirical  evidence  to  show  why  the  current  benchmark  is 
inadequate,  or  at  least  incomplete  to  measure  progress  if  we  are  to  achieve  the  goals  established  by  the 
strategy, such as the need to improve access to high quality learning opportunities for all adults, regardless of 
their gender and family circumstances, with a particular emphasis on less traditional groups of learners, such 
as older people. It should be mentioned that this report is in line with other research in the field, such as the 
OECD study (EC-OECD, 2019) according to which there is significant room for improving the coverage of adult 
learning systems.   

To sum up, the aim of this report is twofold:  

1.  To reflect on the performance of the existing  ET 2020 benchmark on adult participation in lifelong 

learning, by comparing cross-country patterns of participation using different sources of data.  

2.  To  discuss  the  potential  use  of  alternative  data  sources  to  select  a  series  of  complementary 

indicators of adult learning in future monitoring exercises. 

1.1  Milestones in EU Adult Education and Training policy 

The Lisbon European Council in March 2000 was the turning point for the development of adult and lifelong 
learning policy in the EU.  

The  Education  and  Training  2010  programme  was  set  up  in  2002,  when,  in  a  thoughtful  attempt  to 
strengthen  the  European  dimension  of  national  educational  policies,  an  expert  Standing  Group  on 
Indicators and Benchmarks (SGIB) was established.  

(1)   Eurostat Glossary – Statistics Explained: https://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:Lifelong_learning.. 

3 

 
 
 
 
                                           
The SGIB aimed to “give advice on the use of indicators as tools for measuring progress towards the common 
objectives”. By July 2003, the Group  proposed  up to 29 indicators in the  field of education (DG-EAC 2003), 
spread  across  the  8  Lisbon  objectives.  Identifying  and  developing  indicators  proved  both  technically  and 
politically challenging, as the lack of relevant and comparable data caused difficulties in some areas; for this 
reason, the European Council and the European Commission emphasised the need to improve the quality and 
comparability  of  existing  indicators  (Council  of  the  EU  2004,  p32).  As  a  consequence,  long-term 
activities/strategies  were  scheduled  (3  or  more  years)  to  generate  surveys  that  collected  the  information 
required for those indicators which lacked data at national or international level (CEC 2004, p. 4.). 

In May 2003, the European Council agreed: 

to  establish  a  series  of  reference  levels  (benchmarks)  of  European  average  performance,  while  taking  into 
account  the  starting  point  of  the  individual  Member  States (MS)  which  will  be  used  as one  of  the  tools  for 
monitoring  the  implementation  of  the  “Detailed  work  programme  on  the  follow-up  of  the  objectives  of 
education and training systems in Europe”. 

The overall idea was to enable the European Commission and the Member States (MS) to: 

(a)  underpin key policy messages;  

(b)  analyse progress both at the EU and national levels;  

(c)  identify good performance for peer review and exchange; and  

(d)  compare performance with third countries. (CEC 2008, p. 10) 

In 2009, through the strategic framework for education and training (ET 2020),(2) EU countries identified four 
common objectives to be addressed  by  2020: (1) make lifelong learning and  mobility a  reality; (2) Improve 
the quality and efficiency of education and training; (3) promote equity, social cohesion, and active citizenship; 
and (4) enhance creativity and innovation, including entrepreneurship, at all levels of education and training. 

Up  to  eight  targets  -or  benchmarks-  where  identified  with  the  core  indicators  covering  the  whole  learning 
continuum  from  pre-school  to  adult  education,  teachers'  professional  development  and  investment  in 
education and training (the  main six are reported in Table 1).(3)  Since 2004 the Commission has published 
several reports on the progress made by these indicators of education with the visualization tool produced by 
DG JRC and available at https://crell.jrc.ec.europa.eu/ET2020Indicators/  being an important landmark (see also 
DG EAC yearly flagship publication “Education and Training Monitor” and European Commission, 2012).( 4)   

(2)   https://ec.europa.eu/education/policies/european-policy-cooperation/et2020-framework_en 
(3)   The  ET  2020  framework  includes  two  more  benchmarks  on  “learning  mobility  in  higher  education”  and  in  “initial  vocation  and 
educational training” (https://ec.europa.eu/eurostat/web/education-and-training/eu-benchmarks ), but since there are only partial or 
no data available, they are left out of the main table. 

(4)   Flisi, et al., (2014) provides more detailed information on how the different benchmarks are collected when data becomes available, 
as well as information regarding their sub-indicator. For Adult participation in lifelong learning, the only visualization tool available 
is from 2014 at https://crell.jrc.ec.europa.eu/ET2020_2014/index.htm . 

4 

 
 
 
 
 
                                           
Table 1: Targets in education and training (ET 2020 Indicators) 

t
e
g
r
a
t

e
n

i
l
d
a
e
H

s
t
e
g
r
a
t

r
e
h
t
O

1 

2 

3 

4 

5 

6 

Reduce the share of Early 
leavers from education 
and training 

Increase Tertiary 
education attainment 

The share of the population aged 18-24 fulfilling the 
following two conditions: (1) the highest level of 
education or training attained equals International 
Standard Classification of Education (ISCED) level 0, 1, 
or 2; (2) respondents declared not having received any 
education or training in the four weeks preceding the 
survey. Data comes from the EU Labour Force Survey. 
The share of the population aged 30-34 years who 
have successfully completed university or university-
like (tertiary-level) education that equals International 
Standard Classification of Education (ISCED) level 5,6, 
7 or 8. Data comes from the EU Labour Force Survey. 

Current 
EU28(5) 

Target 

10.6 %  
(EU-LFS 2018) 

Below 10 % 
(2020) 

40.7 %  
(EU-LFS 2018) 

At least 40 % 
(2020) 

Increase participation in 
Early childhood education 
and care 

The share of the population aged four to the age 
when the compulsory education starts who are 
participating in early education. Data comes from the 
UOE data collection. 

95.4 %  
(UOE 2017) 

95 %  
(2020) 

Reduce Low achievement 
in reading, maths and 
science 

The share of 15-year-olds failing to reach level 2 in 
reading, mathematics and science as measured by the 
OECD’s Programme for International Student 
Assessment (PISA). 

Increase Employment rate 
of recent graduates 

Increase Adult 
participation in lifelong 
learning 

The share of employed people aged 20-34 having 
successfully completed upper secondary or tertiary 
education 1 to 3 years before the reference year of 
the survey and who are no longer in education or 
training. Data comes from the EU Labour Force 
Survey. 
The share of the population aged 25-64 who stated 
that they received formal or non-formal education or 
training in the four weeks preceding the survey. Data 
comes from the EU Labour Force Survey. 

Reading: 19.7% 
(PISA 2015) 
Maths: 22.2% 
(PISA 2015) 
Science: 20.6 % 
(PISA 2015) 
81.6%  
(EU-LFS 2018) 

15 % (2020) 

82 %  
(2020) 

11.1 %  
(EU-LFS 2018) 

15 %  
(2020) 

Source: Authors’ re-elaboration of data from the Education and training Monitor, 2019. 

As  shown  in  Table  1,  the  ET  2020  gave  special  attention  to  adult  participation  in  lifelong  learning  with  the 
approval  of  an  indicator  that  collected  information  on  the  share  of  participants  in  adult  learning  using  the 
annual EU Labour Force Survey (EU-LFS) as their main data provider.  

The ET 2020 framework is implemented through a variety of tools and instruments, including working groups, 
peer learning activities, peer counselling, and above all the Annual Education and Training Monitor reports on 
Member States’ progress towards achieving the ET2020 objectives and benchmarks. The analysis carried out 
in these reports feeds into the evaluation of broader socio-economic progress by Member States within the 
framework of the European Semester. 

Moreover, in order to go beyond the first snapshot provided by the six operational ET 2020 benchmarks, each 
indicator  is  broken  down  by  standard  JAF  sub-groups:  sex  (male/female)  and  country  of  birth  (foreign-
born/native-born) and a standard set of about five quantitative sub-indicators per benchmark to shed light on 
the overall country  performance, in order to better explain the picture provided by the main indicator.  More 
specifically,  the  selection  of  the  sub-indicators  has  been  carried  out  with  the  purpose  of:  (a)  Hinting  at 
possible policy levers to be identified with additional, country-specific information; (b) Assessing the broader 
context (socio-demographic characteristics, labour market and economic conditions, etc.), in order to evaluate 
to  what  extent  the  country-specific  situation  affects  the  performance  in  terms  of  the  benchmarks;  (c) 
Shedding  light  on  closely  related  domains  of  interest  and;  (d)  Explaining  the  behaviour  of  the  benchmark 
performance  in  the  medium  and  long  term.  It  is  also  worth  pointing  out  that  data  availability  and 
comparability  across  countries,  was  another  key  factor  driving  the  selection  of  the  sub-indicators.  More 
information on the sub-indicators chosen for each benchmark can be found at Flisi, et al., (2014) 

(5)   The UK is still included in average figures. 

5 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
                                           
To  emphasise  the  importance  of  adult  learning,  in  2011,  the  European  Council  adopted  the  “Renewed 
European Agenda for Adult Learning” (EAAL).(6) The EAAL defines the focus for European cooperation in adult 
education policies for the period to 2020 and highlights the need to significantly increase adult participation 
in  formal,  non-formal  and  informal  learning  whether  to  acquire  work  skills,  for  active  citizenship,  or  for 
personal  development  and  fulfilment.  The  adoption  of  the  New  Agenda  was  partly  motivated  by  the 
acknowledgement  that  adult  learning  was  “the  weakest  link  in  national  lifelong-learning  systems”  and  that 
participation had failed to increase, mainly due to low motivation and a lack of care facilities to help women 
and  men  combine  family  and  work  responsibilities (Council  resolution  2011/C  372/01,  page  2).  Overall, the 
objective of the EAAL is to improve access to high quality learning opportunities for all adults, regardless of 
their gender and family circumstances; a particular emphasis is also put on less traditional groups of learners, 
such as older people, and on the importance of involving employers and promoting workplace learning.  

After  taking  stock  of  the  findings  of  the  2015  Education  and  Training  Monitor,  the  European  Council  and 
Commission  produced  a  report  highlighting  the  crucial  role  of  adult  learning  in  up-skilling, re-skilling, active 
citizenship and social cohesion. Given the persistent low levels of basic skills in adults, the report stressed the 
importance  of  implementing  the  Renewed  European  Agenda  for  adult  learning  (EAAL)  and  stated  that 
priorities should include more effective governance, significant increases in supply and take-up, more flexible 
provision, broader access, closer monitoring and better quality assurance. (7)   

Furthermore,  to  support  the  analysis of  adult  learning  systems  across  the  Member  States,  the  Commission 
developed and in 2018  Member States endorsed a comprehensive framework for benchmarking adult  skills 
and learning systems across EU Member States, This benchmarking framework belongs to the broader work 
on benchmarking in the labour market and social domain that was initiated in 2015 following the 2015 Five 
Presidents'  Report,  the  Commission  Communication  of  October  2015  "On  steps  towards  completing  EMU"  8, 
and the 2017 Commission Communication on "Establishing a European Pillar of Social Rights"  9. It support the 
monitoring of the performance of adult learning systems as well as the measures taken by Member States to 
increase participation in adult learning in line with the agreed target (see more details in the Annex). 

The  ET  2020  adult  learning  benchmark  is  a  crucial  indicator  to  monitor  participation  in  adult  learning; 
however, it may not be sufficient to assess the achievement of most of the objectives set out by the agenda, 
as the remainder of this report is going to show.   

Given that it is now 2020, the time to  critically  assess the  current  benchmark  has come, so this report will 
provide empirical evidence on participation in adult learning, with a specific focus on different subgroups, such 
as  older  people  or  others  belonging  to  groups  that  are  traditionally  excluded  from  learning,  which  are 
identified as a priority by the EAAL. The report also  discusses the  strengths and  weaknesses of the current 
data source used to create the indicators, i.e. the EU-LFS, and further introduces the possibility to create other 
indicators  based  on  different,  complementary  data  sources,  such  as  the  Adult  Education  Survey  (AES),  the 
Continuing Vocational Training Survey (CVTS), the OECD Survey on Adult Skills (PIAAC), and other. 

1.2  A Renewed European Agenda for Adult Learning: Objectives and Actions 

It is widely accepted that the accumulation of human capital is not something that takes place only during the 
early years of an individual’s life, but in a process of lifelong learning and that adult participation in lifelong 
learning  must  be  monitored  with  adequate  indicators.  So  far,  only  a  few  member  states  have  reached  the 
15% participation rate benchmark, as can  be  concluded from the low overall EU average shown in table  1. 
Key to monitoring is to properly identify meaningful indicators which are easily understood by those who seek 
to  use  the  information  they  provide.  More  importantly,  it  is  necessary  that  indicators  are  linked  to  specific 
objectives and/or actions.  

Regarding  this  matter,  the  Council’s  Resolution  on  a  Renewed  European  Agenda  for  Adult  Learning  and  the 
Commission’s  Communication,  Rethinking  Education(10)  adopted  in  2012  emphasised  the  role  of  adult 
learning to respond to economic challenges facing Member States and the need for an active Adult Learning 
Policy.  The  Council  resolution  recognises  the  “substantial  contribution  which  adult  learning  can  make  to 
economic  development  —  by  strengthening  productivity,  competitiveness,  creativity,  innovation  and 
entrepreneurship” and urges Member States to take action to support it.  

(6)   https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32011G1220(01)&from=EN.  . 
(7) 
https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52015XG1215(02)&from=EN.  . 
(8)     COM(2015) 600 final, https://ec.europa.eu/transparency/regdoc/rep/1/2015/EN/1-2015-600-EN-F1-1.PDF 
(9)  COM(2017) 250 final, https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=COM:2017 :250:FIN 
(10)  Commission Communication Rethinking education: investing in skills for better socio-economic outcomes 

http://ec.europa.eu/education/news/rethinking/com669_en.pdf   . 

6 

 
                                           
Investment in education and training beyond initial/compulsory education is critical to increase participation in 
adult learning so as to: (1) upgrade the skills of working age individuals and increase the economy’s overall 
skill  level;  but  also  (2)  contribute  to  non-economic  objectives  such  as  personal  fulfilment,  improved  health, 
civic participation and social inclusion.  

By  re-elaborating  some  of  the  key  concepts  expressed  in  the  most  recent  European  Commission  report  on 
adult learning (Molyneux et al, 2019), this report suggests that policy goals should aim at:  

1.  Enhancing public/private investment in adult learning. Participation in adult learning is strongly 
linked  to  the  availability  of  government  funded  learning  opportunities,  and  the  amount  of 
government  investment  in  learning.  Nonetheless,  industries  and  individuals  should  also  be 
encouraged to invest. Still public intervention is needed to ensure an adequate supply of trainers and 
instructors; 

2.  Facilitating  Access:  in  particular,  Member  States  should  offer  adults  with  a  low  level  of  skills 
access to education and training so that they can acquire minimum level of literacy, numeracy and 
digital competence; and/or acquire a wider set of skills, knowledge and competences, relevant for the 
labour market and active participation in society; 

3.  Effectively updating knowledge and raising skills. Provision of employment- and  work-related 
training  so  that  individuals  can  acquire  the  necessary  skills  and  key  competences  to  succeed  in 
economic and social life (non-economic rewards).   

4.  Reducing  inequalities:  Member  states  should  identify  priority  target  groups  by  taking  also  into 
account gender, diversity and various sub-groups in the targeted population. Greater investment on 
under-represented groups is important since not only it reduces inequalities in accessing learning, but 
also increases overall adult participation in learning. This objective may request a proper account of 
adult learning needs, as well as barriers to participation of those under-represented; 

5.  Deliver  high quality adult learning. Recognising competencies and skills through an appropriate 
certification  system.  Moreover,  in  the  face  of  increasing  informal  learning,  mechanisms need  to  be 
put  in  place  to  foster  self-directed  and  other  informal  ways  of  learning  with  the  appropriate 
recognition systems.  

Previous work undertaken by the Directorate General for Employment, Social Affairs and Inclusion (European 
Union, 2015) identified six key factors for successful adult learning policies, related to these policy goals: 1. 
Improve  learners’  disposition  towards  learning;  2.  Increase  employers’  investment  in  learning;  3.  Improve 
equality of access for all; 4. Deliver learning that meets the needs of employers and learners; 5. Deliver high 
quality  adult  learning;  6.  Co-ordinate  an  effective  lifelong  learning  policy.  Based  on  a  policy  model  which 
presents each policy goal (‘key success factor’), as well as the key elements that would ensure its successful 
implementation  (‘building  blocks  for  success’)  and  then  the  resultant  output  and  outcome  they  built  up  a 
conceptual framework for effective adult learning (see Figure 1) (11)  .  

(11)   For  a  detailed description  how  the  framework was  devised  and  the evidence underpinning  it,  please  see “An  in-depth  analysis of 

adult learning policies and their effectiveness in Europe” European Union, 2015.   . 

7 

 
 
                                           
Figure 1: Conceptual framework for the analysis of effectiveness of adult learning policies 

Source: Molyneux et al, 2019; page 104..  

8 

 
 
The policy goals (objectives) to be monitored and the theoretical framework constitute then a solid basis for 
the definition and selection of a list of indicators for monitoring adult learning. Similar exercises have been 
undertaken by Borkowsky (2013) for the OECD and by the World Bank (2013). Despite the differences in how 
they  have  been  shaped,  these  frameworks  agreed  upon  the  complexity  of  collecting  satisfactory, 
comprehensive information on participation on adult learning.  

In terms of data collection, several European initiatives coordinated by Eurostat and aimed at improving the 
coverage  of  lifelong  education  and  learning  activities  by  the  European  Statistical  System  have  been 
implemented  in  the  last  15  years.  The  primary  source  for monitoring  adult  learning  is the  European  labour 
Force Survey (EU-LFS); to appreciate its potential limitations, cross country comparisons will be presented in 
the next section along with a discussion on the strengths and weaknesses of this data source. In addition, we 
will  present  descriptive  statistics  based  on  the  EU-LFS  ad  hoc  module  on  adult  participation  in  lifelong 
learning carried out in 2003. 

Section three looks at other data sources for monitoring adult learning, with a specific focus on the objectives 
mentioned above, and suggests some useful indicators. The other data sources include: The Adult Education 
Survey,  a  European  Union  harmonised  survey  on  adult  participation  in  learning  activities;  the  Continuing 
Vocational  Training  Survey  (CVTS),  European  Union  harmonised  survey  on  continuing  vocational  training  in 
enterprises; and the Survey on Adult Skills part of the OECD’s Programme for the International Assessment of 
Adult Competencies (PIAAC). Statistics(12) from different, but comparable, education and training systems and 
other  European  surveys  such  as  the  European  Community  Household  Panel  (ECHP)  and  its  successor  the 
European Survey on Income and Labour Conditions (EU-SILC), but also the European Working Condition Survey 
(EWCS) and the European Skills and Jobs Survey (ESJS) will also be introduced and briefly analysed.  

This  exercise  will  serve  as  an  additional  piece  of  empirical  evidence  towards  future  developments  in 
monitoring (and benchmarking) adult learning across the European Union. 

(12)   These are all international statistics collected nationally in national languages. They are aggregated according to common standards 

and definitions to ensure comparability across Member States.   . 

9 

 
 
                                           
2  An examination of the ET2020 benchmark of adult participation in 

lifelong learning: Features, caveats and challenges   

Adult  learning  was  already  a  key  component  of  the  Lisbon  Strategy.  Reviews  of  available  data  on  adult 
learning carried out in early 2000s revealed a lack of harmonisation and conceptual unity across Europe. In 
parallel with the  Lisbon Strategy issued by the Council, Eurostat set out to create two task forces: the task 
force on measuring lifelong learning (2000-2001) and the task force on the Adult Education Survey (2002-
2004).  The  task  forces  benefited  from  the  active  involvement  of  EU  member  states,  as  well  as  non-EU 
countries  (Switzerland,  Canada)  and  international  organisations  (OECD,  Unesco  Institute  for  Statistics, 
International  Labour Office)  having  experience  and  interest  in  the  field.  (EC,  2005).  The  joint  efforts  by  the 
Council  and  the  task  forces  culminated  in  the  adoption,  among  others,  of  the  EU2010  benchmark  of 
increasing  by  2010  adult  participation  in  lifelong  learning  to  an  average  of  at  least  12.5  %  of  the  adult 
working age population (25-64 years-old) across EU MS (CEC 2003, p.6). In May 2009, the Council raised this 
benchmark: “By 2020, an average of at least 15% of adults should participate in lifelong learning”. Eurostat’s 
European  Union  Labour  Force  Survey  (EU-LFS)  includes  a  section  on  participation  in  lifelong  learning;  the 
information collected relates to all education or training received (formal and non-formal) in the four weeks 
preceding  the  survey,  whether  relevant  or  not  to  the  respondent’s  current  or  possible  future  job.  Estimates 
starting in 2009 are summarised in Figure 2(13).  

Figure 2: Participation rate of adults (aged 25-64) in education and training (last 4 weeks) 

Western Europe (Incl. British Isles)

Northern Europe 

35%

30%

25%

20%

15%

10%

5%

0%

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Netherlands
Luxembourg
United Kingdom
EU28

France
Austria
Ireland
Belgium

35%

30%

25%

20%

15%

10%

5%

0%

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Sweden
Denmark
EU28

Finland
Estonia

Central/Eastern Europe 

Southern Europe 

35%

30%

25%

20%

15%

10%

5%

0%

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Czechia
Hungary
Croatia
EU28

Slovenia
Lithuania
Slovakia
Romania

Latvia
Poland
Bulgaria

35%

30%

25%

20%

15%

10%

5%

0%

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Malta

Italy

EU28

Spain

Cyprus

Portugal

Greece

Source: Eurostat [trng_lfse_01]. Since 2006, the indicator on adult participation in learning is calculated as annual average of quarterly 
data. Note that the questionnaire design was substantially changed in France in 2013, hence the jump in values. Other significant breaks 
in time series occurred in 2011 for Czechia and Portugal, in 2015 for Luxembourg and Hungary, in 2016 for Denmark and in 2017 for 
Malta. 

(13)   Please note that participation in adult education and training (last 4 weeks) is available in Eurostat since 1992 though not for all 

current EU Member States. For more information see online table [trng_lfse_01].  . 

10 

 
 
 
 
 
 
 
                                           
2.1  The European Labour Force Survey as the main data provider for the ET2020 

benchmark on adult participation in lifelong learning. 

The  EU-LFS,  administered  by  the  different  EU  MS  but  coordinated  by  Eurostat,  seems to  fulfil  three  of  the 
main  requirements  for  monitoring  any  benchmark  performance  across  EU  MS,  namely  a  high  degree  of 
comparability, country coverage of data and, most important, frequency of data availability. This means that 
there must be data on adult participation in lifelong learning across the EU for practically all EU countries to 
almost the same standards on a regular basis (e.g. yearly). EU-LFS measures are reported in Table 2.(14) 

Table 2: Variables related to adult participation in lifelong learning as posed in the EU-LFS (4-weeks reference period) 
from 2003 onwards. 

Variable 
name 

EDUCSTAT 

COURATT 

Formal 
education 
and training 

Non-formal 
education 
and training 

Question 

Additional information 

Student or apprentice in regular education during 
the last 4 weeks. Prior to 2003, formal and non-
formal education were collected through the 
variable EUDC4WN. 
Did you attend any courses, seminars, conferences 
or received private lessons or instructions outside 
the regular education system (hereafter mentioned 
as taught learning activities) within the last 4 
weeks.  Prior to 2003, formal and non-formal 
education were collected through the variable 
EUDC4WN. 

Mandatory: asked to everybody 
aged 15 years and more; 
information on the level and 
the field also provided. 
Mandatory; asked to everybody 
aged 15 years or more 
Information on the length, 
purpose, field and whether it 
took place during working 
hours is also provided. 

None 

Informal 
learning 
Source: EU Labour Force Survey Database user guide, page 28 and 29 ; 
https://ec.europa.eu/eurostat/documents/1978984/6037342/EULFS-Database-UserGuide.pdf 

While Eurostat supervises the comparability of data, each country conducts its own national LFS which retains 
–  to  a  greater  or  lesser  extent  –  some  national  characteristics.  An  annual  report  outlines  the  “main 
characteristics  of  the  national  practices”  (Eurostat  2010)  showing  some  national  distinctive  histories.  The 
French LFS has functioned for several decades. It started in 1950 and was organised in 1954 as an annual 
survey. An extensive revision of the questionnaire of the French  LFS (in use from 1 January 2013 onwards) 
explains the level shift break for France, which had an impact also on the EU aggregates. (15) The Finnish and 
Swedish LFS started in 1959. The Spanish LFS was launched for the first time in 1964, referencing to some 
quarters in each year until 1968. Between 1969 and 1974 it was biannual, but quarterly from 1975. In 1999 
the survey was redesigned as a continuous survey providing quarterly results. The UK LFS survey started in 
1973 as a biennial survey (not using the ILO definition of unemployment) and was redesigned in 1984 as an 
annual  survey  and  from  1992  as  a  continuous,  quarterly  survey.  The  Belgian  LFS  started  in  1983  as  an 
annual survey but has been continuous since January 1999 providing quarterly and yearly results. The Greek 
LFS survey began in 1981 as an annual survey covering all weeks of the second quarter. It was redesigned as 
a continuous survey providing quarterly results in 1998.  

The LFS was introduced in Eastern Europe in the 1990s. In the  Czechia, Hungary and Poland was introduced 
since 1992, in Bulgaria, Romania, Slovakia and Slovenia in 1993, in Latvia in 1995, in Estonia in 1997, and in 
Lithuania  in  1998  (Eurostat,  2010).  In  summary,  each  country’s  LFS  is  regularly  revised  to  improve 
methodologies  at  country  level,  but  also  a  EU  level  methodological  adjustment  are  undertaken,  which 
generates multiple breaks in time series and impacts comparability over time. 

Moreover, the LFS questionnaire follows a different approach from country to country. In  fourteen countries 
participation  is  compulsory,  while  it  is  voluntary  in  twenty-one  countries  (Eurostat  2019,  Annex  p.  80).  The 
response  rate  varies  from  48.9  per  cent  in  the  UK  to  100  per  cent  in  Iceland,  even  though  participation  is 
voluntary  in  both.  The  average  quarterly  sample  achieved  in  2008  varied  from  2,700  (Luxembourg)  to 
131,400 (Germany).  

(14)   For more details see: https://ec.europa.eu/eurostat/web/microdata/european-union-labour-force-survey . 
(15)   https://ec.europa.eu/eurostat/cache/metadata/en/trng_lfs_4w0_esms.htm . 

11 

 
 
 
 
 
                                           
The  extent  of  this  heterogeneity  and  variation  has  sparked  a  long  debate  among  practitioners  on  the 
appropriateness of the existing measure of adult participation in lifelong learning. In particular, in relation to: 
(i)  the  way  the  different  national  LFS  surveys  are  structured  and  their  main  objective,  which  affects  the 
attention  dedicated  to  the  specific  issue  of  adult  participation  in  lifelong  learning, and therefore  its  quality, 
scope and reliability; (ii) the reference period used for the question (the 4-weeks vs. 12-months); and (iii) the 
types of learning that are included (e.g. formal and non-formal learning). These  have been the three major 
concerns among users. We will devote the remaining of this section to bring further insights into these three 
issues. 

2.1.1  Structure and objectives of national LFS surveys 

Holdford  and  Mleczko  (2011)  provide  an  interesting  insight  on  the  potential  association  between  high 
participation  rates  and  the  extent  of  apparent  national  contextualization  of  interview  questions.  One  may 
assume  that  a  common  questionnaire  is  applied  in  all  countries  but  this  is  not  the  case.  Questions  are 
administered in national language(s) and some adaptation to the national character of educational systems 
also  takes  place.  Starting  from  the  2009  English  versions  (published  on  the  Eurostat  website  for  most 
countries),  the  authors  reflect  on  the  association  between  phrasing  and  reported  participation  rate.  They 
identify  a  set  of  countries  which  poses  questions  on  education  other  than  formal  education  in  the  most 
comprehensive and inclusive way, giving  detailed examples. These  countries report the highest participation 
rates  (see  Figure  2):  Sweden,  Finland,  Denmark,  The  Netherlands,  United  Kingdom,  Slovenia,  Austria  and 
Estonia. 

By contrast, as the degree of inclusiveness decreases and questions become brief or general, reported adult 
participation rates in lifelong learning significantly drop, and it is difficult to say to what extent the definition 
used is clear to the participants and accurately describes their educational experiences.  

Moreover,  in  France  some  specificities  of  the  questionnaire  design  may  produce  non-comparable  results. 
There was (in 2007) no question relating specifically to education taken in a four-week period. In the French 
LFS,  two  questions  strongly  related  to  participation  in  adult  learning  were  posed  (“During  the  last  three 
months, have you attended classes or a training course, however short?” and “Are you attending training as 
part  of  your  work  contract?”).  From  these,  and  supplementary  questions  related  to  the  starting  and  ending 
dates  of  these  courses,  the  participation  rate  for  the  four  weeks  preceding  the  interview  is  presumably 
calculated. Therefore, data always need to be interpreted with caution, especially when revisions/updates of 
the  national  questionnaires  (aimed  at  improving  the  way  adult  learning  is  capture  in  the  survey)  can 
significantly affect EU averages. 

2.1.2  The  impact  of  using  a  12-months  or  4-weeks  reference  period  and  the  type  of 
education  and  training  recoded:  A  short  look  at  the  2003  LFS  ad  hoc  module  on 
lifelong learning. (16) 

On the one hand, the 4-weeks reference period may be considered appropriate for monitoring the level 
and  characteristics  of  participation  in  education  and  training  –  even  thought  it  was  clearly  thought-out  to 
measure current participation in formal/long programmes or traditional courses and may not be as suited to 
measure adult learning, given the characteristics of the learning activities. However, the measure is consistent 
with the reference periods used most frequently for other variables in the LFS. Second, it reduces problems 
associated  to  recall  bias,  because  it  focuses  on  a  very  recent  period.  Finally,  it  corresponds  to  the  most 
appropriate reference period to cover different degrees of participation in all Member States (a way between 
generally high levels in the Northern countries and low levels in the Southern countries) while time series are 
in  2003  see  https://ec.europa.eu/eurostat 
available  on 
/cache/metadata/en/trng_lfs_4w0_esms.htm    for  further  details  about  how  this  variable  has  been  collected 
since 1992). 

(with  a  break 

from  1992 

this  basis 

On the other hand, there are a number of reasons to question its appropriateness: 

(16)   For more information on this matter, access: https://circabc.europa.eu/sd/d/32d8e3e2-d91b-4178-a0d0-

0893141b570f/AL_Metadata_Section4_Dissemination_Coherence_AllSources.htm  . 

12 

 
 
 
                                           
The  4-weeks  reference  period  can  be  seen  as a  measure  of  “training  events”  dividing  the  year in  blocks  of 
four weeks. Since the calculation is an annual average of quarterly data, it may provide the same value for 
two different situations: for example, in country A 10% annual adult participation rate might correspond to 
the  same  individuals  all  over  the  year,  but  in  country  B  this 10%  annual  adult  participation  rate  per  each 
quarter may correspond to up to 4 times the population of country A all over the year if different individuals 
are involved.  

1.  The  4-weeks  reference  period  is  a  sort  of  snapshot  of  the  situation  in  a  given  country  at  that 
moment in time. The risk of misinterpretation is high: since the variable does not measure individual 
paths  along  the  year,  if  an  individual  has  completed  an  educational  program  but  the  question  is 
asked  just  a  little  later  than  4  weeks  after  the  completion,  he/she  figures  as  not  involved  in  any 
education or training. However, if we are interested in observing the number of people participating in 
education and training at a particular moment, this 4-weeks reference period should work as a good 
tool.  In  other  words,  the  4-week  reference  period  is  an  adequate  measure  of  what  could  be 
considered as “recent exposure to adult learning”.  

2. 

If policy interests lie in the number of persons participating in education and training in a particular 
moment,  the  indicator  on  adult  participation  in  learning  based  on  the  LFS  measures  well  the 
phenomenon. However if the interest is in the number of people who were involved in any education 
and  training  in  a  given  year,  an  indicator  covering  participation  over  the  full  year  (i.e.  the  past  12 
month) might capture this better.17 . 

3.  Finally,  a  short  reference  period  limits  the  possibilities  of  cross  tabulations  and  analysis  of  the 
individual's  paths,  for  instance,  the  impact  of  education  and  training  on  the  duration  of 
unemployment.  One  could  argue  that  a  short  and  incidentally  captured  activity  might  not  increase 
employability  of  the  individual.  Moreover,  as  it  concerns  flexicurity  and  employability,  the  indicator 
based on a 4-week reference period does not fully reflect the individual perspective of accumulating 
relevant  knowledge  and  competencies  through  education  and  training,  and  it  is  more  difficult  to 
assess the performance of countries on the basis of data referring to such a short reference period. 

Clearly, considering a time span of 12 months is much more inclusive and tends to provide higher proportions 
since the likelihood of finding an individual who participated in lifelong learning in the previous 12 months is 
higher  than  the  likelihood  of  finding  an  individual  who  only  received  training  in  the  previous  4  weeks.  In 
addition,  including  more  individuals  results  in  a  larger  sample  size  which  also  allows  for  the  analysis  of 
smaller  population  sub-groups.  Overall,  if  we  are  interested  in  looking  at  general  access  to  education  and 
training, the 12-month reference period is a better option. In light of this, the Regulation 2019/1700 of the 
European Parliament and Council18 established that from 2022 onwards, the LFS will include information on 
participation in formal and non formal education and training in the last 12 months19.  

The new indicators will be collected biennially (every two years) on even years, so in 2022, 2024 and so on. 
The  target  population  will  be  all  individuals  aged  15  to  74,  which  will  guarantee  that  the  new  measure  is 
inclusive and representative of the overall population. The stated purpose is to collect a more comprehensive 
measure of participation in education and training for the calculation of an indicator on 'adult participation in 
(lifelong) learning' (AL). The 12 months time-frame will capture more activities and avoid seasonal effects.  

The first instrument to deal with this limitation of the time span was the ad hoc module on lifelong learning 
(now adult learning) included in the LFS questionnaire in the spring 2003 EU-LFS(20). The initial outline for the 
ad hoc module on lifelong learning was developed by the task force on measuring lifelong learning in 2000. 
This ad hoc module consists of a series of questions (participation in lifelong learning, time spent in learning, 
etc.)  prepared  by  Eurostat  and  representatives  from  the  MS  and  adopted  by  the  Employment  Statistics 
working group. It was implemented in the  EU member states (excluding Croatia) and in UK, Norway, Iceland 
and Switzerland. 

(17)  For the 2016 AES, there had been a discussion “reference period = calendar year” vs “12 months prior to the interview”. There was 
agreement that calendar year would be methodologically better but this can only be asked if the survey is done early in the year 
after the reference period. In the majority of countries, AES can only be conducted in Q3 or Q4, therefore this was not an option for 
AES.  For  the  quarterly  LFS,  the  calendar  year  as  reference  year  does  also  not  make  sense  as  interviews  are  conducted  in  all 
quarters. 

(18)  https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32019R1700&from=EN 
(19)  Please note that “guided on-the-job training” remains excluded from non-formal education and training in the EU-LFS. 
(20)   The legal basis for the module is the Commission Regulation (EC) No 1313/2002 of 19 July 2002 implementing Council Regulation 
(EC) No 577/98 on the organisation of a labour force sample survey in the Community concerning the specification of the 2003 ad 
hoc module on lifelong learning. 

13 

 
                                           
Figure 3: Adult participation ‘Formal and non-formal learning activities LFS – 4 weeks (2003)’  

%

100
90
80
70
60
50
40
30
20
10
0

AT SI LU DK FI SE SK MT FR IE IT LV PT BE DE NL CY UK EE PL CZ LI ES EL BG HU RO
Any learning activities ad hoc LFS - 12 months (2003)

Formal and Non-formal LFS - 4 weeks (2003)

Source: Eurostat [trng_any1]; [trng_lfse_01]. A detailed description of the variables is available in Table 3.  

Results reported in Figure 1 show a much greater participation in adult learning if captured from the ad hoc 
module  than  from  the  general  LFS.  As  already  discussed,  the  12  months  reference  period  increases  the 
possibilities for an individual to participate in adult learning activities and highlights one of key differences in 
institutional setting and course duration across countries. For example, the prevalence of non-formal learning 
in  certain  countries  (e.g.  FI)  significantly  increases  the  participation  in  adult  learning  if  a  longer  window  is 
considered.  Conversely, those  countries with  a  more  formally  structured  system of  adult  education  (greater 
occurrence of formal learning) will display less discrepancy between the 4 weeks and 12 months periods.  

Moreover, as reported in Table 3, the ad hoc module of the LFS collected information on the different types of 
learning activities as developed by Eurostat (2003), namely: 

—  Formal (intentional, institutional learning of at least 6 months, with official recognition and other specific 

features); 

—  Non-formal (intentional, institutional learning of any duration, that does not lead to official recognition); 

and 

—  Informal (intentional but non-institutional learning). 

Table 3: The variables related to participation in education and training of the 2003 ad-hoc module on lifelong learning 
of the EU-LFS 

Variable 

Description 

LLLSTAT 
LLLCOURATT 

LLLINFORATT 

During the last 12 months has been a student or an apprentice in regular education (FORMAL) 
Did you attend any courses, seminars, conferences or receive any private lessons or instructions 
outside the regular education system (hereafter mentioned as taught activities) within the last 12 
months? (NON-FORMAL) 
Did you use any of the following Methods for non-taught learning including self-learning with the 
purpose to improve your skills during the previous 12 months, which wasn’t part of a taught activity 
or program of studies? (INFORMAL) 

Source: Explanatory notes for the Labour Force Survey Specification of the 2003 ad hoc module on lifelong learning; available at: 
https://ec.europa.eu/eurostat/documents/1978984/6037334/Explanatory-notes-AHM-2003.pdf  

Given  the  importance  of  the  type  of  learning  provided,  Figure  4a  and  4b  below  present  the  share  of  adult 
population (aged 25-64) attending  formal and non-formal training as reported by the  2003  ad  hoc EU-LFS 
module, using the 12 months reference period and, by the 2004 EU-LFS, using the 4 weeks reference as in 
the ET2020 benchmark(21).  

(21)   Information on formal and non-formal education using the general LFS is only available from 2004. 

14 

 
 
 
 
 
                                           
In  2004,  using  the  four-week  reference  period,  10.6  %  of  adults  participated  in  some  formal  and/or  non-
formal learning (EU-25), while only 3.3% participated in formal learning. Similarly, in 2003, using a 12-month 
reference period of the ad hoc LFS, 20.5 % of adults stated that they have undertaken some formal or non-
formal  learning,  but  only  4.5  %  stated  that  they  have  done  any  formal  adult  learning  during  the  year. 
Participation  in  non-formal  learning  is  larger  if  the  12-month  window  is  considered.  Great  heterogeneity  is 
observed among MS with those countries reporting higher level of adult participation in lifelong learning also 
reporting  higher  involvement  in  the  non-formal  learning  type,  namely:  Sweden,  Denmark,  Finland,  UK  and 
Austria.  

Figure 4a. Adult participation in formal learning: ET2020 benchmark (4-weeks) and EU-LFS ad hoc module indicators  
(12 months) 

15.0

13.0

11.0

9.0

7.0

5.0

3.0

1.0

-1.0

Formal ad hoc LFS - 12 months (2003)

Formal LFS - 4 weeks (2004)

Figure 4b. Adult participation in non-formal learning: ET2020 benchmark (4 weeks) and EU-LFS ad hoc module indicators 
(12 months) 

50

45

40

35

30

25

20

15

10

5

0

Non-formal ad hoc LFS - 12 months (2003)

Non-formal LFS - 4 weeks (2004)

Source: Eurostat [trng_fed1]; [trng_nfe1]; [trng_lfs_09] 
Note: MT Formal and non-formal learning LFS 4 weeks: definition differs; MT Formal learning LFS 4 weeks: low reliability. 

15 

 
 
 
Informal learning (collected in the ad hoc module of the LFS) is arguably the most prevalent mode, as shown 
in  Figure  5.  On  average,  nearly  one  in  three  Europeans  claimed  that  they  had  been  involved  in  informal 
learning, more specifically self-learning, by using different methods like books, computers, learning centres or 
educational broadcasting. However, this type of learning is not part of either formal or non-formal education 
and  training  and,  therefore,  not  collected  in  the  regular  cycles  of  the  EU-LFS.  Given  the  importance  of 
upgrading  human  capital  as  a  lifelong  learning  process,  these  results  show  that  a  great  deal  of  valuable 
learning  also  takes  place  informally.  Policy  makers  need  to  be  aware  of  it  and  find  a  structured  way  to 
classify it and report it on a regular basis.  

Figure 5: Adult participation in informal learning: EU-LFS ad hoc module indicator (2003) 

%

100
90
80
70
60
50
40
30
20
10
0

AT LU SI

FI DK SK SE MT IT

FR IE

LV PT DE EU-25 BE NL CY PL

EE

LT CZ ES BG EL RO HU

Source: Eurostat [trng_inf1] 
Note: Information of the UK is not available 

2.2  The  distribution  of  adult  lifelong  learning  by  individual  characteristics 

across the EU. 

The  purpose  of  this  section  is  to  examine  more  in  depth  the  level  and  distribution  of  adult  participation  in  
education  as  reported  by  the  ET  2020  benchmark.  More  specifically,  observed  cross-country  patterns  are 
considered  in  relation  to  a  set  of  individual  characteristics  that  drive  unequal  chances  to  participate  both 
between  and  within  countries.  As  reported  in  the  previous  section,  one  of  the  main  goals  of  adult  learning 
policies is to improve access for groups that are traditionally less likely to participate, but stand to benefit the 
most, for instance older individuals, those with low skills or people who are not part of the labour market. The 
following  charts  show  a  detailed  breakdown  of  participation  in  adult  learning,  by  age  groups,  level  of 
educational attainment (which can be considered as a proxy for skill), occupation and employment status. The 
underlying idea is to understand whether the average participation rate reported for the benchmark is in fact 
hiding substantial heterogeneity.  

Results in this section are reported for the most recent year available, that is, 2018. 

2.2.1  Adult participation in lifelong learning and age. 

The human capital theory suggests that investment in skills is likely to be concentrated in the early years of 
an individual’s life and career so as to ensure higher rates of return (Becker, 1962). Indeed, basic schooling 
and initial vocational training are generally concentrated in the pre- or early-career years. However, there may 
be significant differences in the way in which workers continue to receive education and training later in their 
working lives. Nowadays, it is widely accepted that inappropriate training (especially if not properly updated) 
may lead to skill obsolescence, which in turns may generate employment difficulties for some older workers, 
while also reducing the adaptive capacity of the economy as the workforce ages in coming decades (Callahan, 
et al. 2003; Desjardins and Warnke, 2012; Picchio and van Ours, 2013). 

The policy indicator for ‘adult participation in  learning’ is defined for 25-64; Figure 6 differentiates between 
younger and older adult learners by reporting rates of participation separately for  adults aged 25 to 34 and 
those 55 to 64, and comparing the two. In 2018, the EU28 participation rate in adult learning activities  was 
17.8% for younger adults (aged 25-34) and 6.4% for older adults (aged 55-64). However, the cross-country 
heterogeneity is huge: from 2.7% in Romania to 39.1% in Sweden among the young, and from 1.2 in Greece 
to 22.4% in Sweden for the older adults. In general, there is a very strong correlation between participation 

16 

 
 
rates  of  the  young  and  of  the  older  age  groups  (about  0.93),  but  again  there  are  some  differences  across 
countries. While on average younger adults show a participation rate that is 2.8 times the rate of the older 
adults, this ratio varies from a minimum of 1.7 times in Sweden  and France to a maximum of 9.3 times in 
Greece.  These  findings  strongly  suggest  not  only  that  adult  education  opportunities  vary  greatly  across 
Europe, but also that several states may be failing to engage older age groups. It should also be mentioned 
that while the current indicator only covers a portion of the population, excluding the very young (under 25) 
and the elderly (over 65). 

Figure 6: Percentage of adults aged 25 to 34 and 55 to 64 who participated in  education and training in the 4 weeks 
preceding the survey – LFS 2018.  

Romania
Slovakia
Bulgaria
Croatia
Poland
Hungary
Lithuania
Greece
Latvia
Cyprus
Czechia
Belgium
Italy
Portugal
Malta
EU - 28
Ireland
Slovenia
United Kingdom
Germany
Spain
France
Austria
Luxembourg
Estonia
Netherlands
Denmark
Sweden
Finland

2.7

6.4
8.2
9.0
9.6
10.1
10.4
11.1
11.8
12.2
13.3
14.4
15.3
16.5
16.5
17.8
18.0
18.2
18.4
18.7
19.5

1.9

0.4

1.9
2.6
4.3

1.2

3.0
2.9
4.1
4.4
5.0
5.0
4.0

6.4
8.3

5.9

9.9

3.2
4.7

23.6
24.8
25.5

28.2
29.3

33.5

36.0
37.2

25-34

55-64

13.6

8.5
8.2
10.5
11.7

16.3

21.0

18.8

Source: Eurostat [trng_lfse_01] 
Note: Croatia 55-64: low reliability. 

Research done by CRELL (2011) based on LFS data confirms that participation in formal training programmes 
at  a  later  career  stage  is  among  the  factors  that  reduce  early  retirement.  Enrolling  in  a  learning  activity, 
especially  for  women,  increases  the  expected  time  in  the  labour  market  and  is  strongly  correlated  with  the 
belief that more opportunities for skills upgrading would keep one longer at work. 

2.2.2  Adult participation in lifelong learning and level of educational attainment 

The  demand  for  a  highly  qualified  and  adaptable  workforce  is  projected  to  increase  in  the  near  future: 
European labour market projections indicate that around  35% of all jobs  will require tertiary graduate-level 
qualifications by 2020, however only 31% of the EU’s labour force (aged 25-64) was qualified at this level in 
2017 (https://ec.europa.eu/eurostat/web/products-eurostat-news/-/EDN-20181008-1)..  

Figure 7 provides participation rates in education and training for adults aged 25-64 who at most completed 
lower secondary education (ISCED 0-2) and those who completed tertiary education (ISCED 5-8). Once again, 

17 

 
 
inequality in participation (in this case between the more and less educated) is present in all countries; Nordic 
countries, as well as the Netherlands are much more successful at extending adult learning opportunities to 
both  those  who  initially  had  low  levels  of  educational  attainment  and  those  who  already  attained  tertiary 
education.  

This  goes  completely  against  the  stated  objectives  of  adult  learning  policies  according  to  the  Council  and 
Commission,  given  that  adult  with  low  skills  should  be  the  primary  target  and  access  should  be  facilitated 
above all for this group.  

 Figure 7: Percentage of adults aged 25 to 64 who participated in education in the 4 weeks preceding the survey by low 
and high level of educational attainment – LFS 2018.  

Croatia
Bulgaria
Greece
Slovakia
Poland
Cyprus
Italy
Lithuania
Czechia
Latvia
Slovenia
Hungary
Belgium
Spain
Malta
Germany
EU - 28
Ireland
Portugal
Austria
United Kingdom
France
Luxembourg
Estonia
Netherlands
Denmark
Finland
Sweden

0.5

0.7
0.8

0.9
1.0
1.5
2.0
2.4
2.4
2.5

2.8
2.9
3.2
3.7
4.1
4.3
4.3
4.4
4.7
5.6
5.8
7.1
7.3
7.4

9.9

14.9
15.6

20.7

6.1

4.3

7.5
7.8

12.6

10.9

18.7

11.4

16.1

11.3

19.5

11.1

13.7

17.6

22.6

12.4

19.0
18.1

20.7

25.7

20.6

29.3

26.3

28.8

25.5

29.6

36.4
37.0

Less than primary, primary and lower secondary education (ISCED 0-2)

Tertiary education (ISCED 5-8)

Source: Eurostat [trng_lfse_03] 
Note: Information for Romania is only reliable for tertiary education (ISCED 5-8) with 2.2% of adults aged 25-64 participating in adult 
education (4 weeks window); Less than primary, primary and lower secondary (ISCED 0-2): low reliability for Bulgaria, Cyprus, Croatia, 
Latvia, Slovenia and Slovakia.  

2.2.3  Adult participation in lifelong learning and labour market status. 

According to the literature, employment status is greatly correlated with participation in adult learning (OECD, 
2011, 2012). According to the estimates reported in figure 8, having a job (being employed) seems to have a 
small positive effect on participation in adult learning, since 11.8% of the employed individuals participate in 
education  and  training  vs.  10.7%  of  their  unemployed  peers.  However,  there  are  substantial  cross-country 
differences:  in  a  few  countries  it  seems  that  participation  in  adult  learning  is  significantly  more  frequent 
among the unemployed that the employed, as for instance in Sweden, Luxembourg or Denmark; whereas in 
other  countries,  such  as  Malta,  France  or  Finland,  the  proportion  of  participants  in  adult  learning  is 
significantly higher among those who have a job.  

18 

 
 
 
 
This association could be related to the need to improve one’s knowledge and skills in order not to lose one’s 
job or, in the case of unemployed people, to enter the labour market (initial entry or re-entry).  

Figure  8:  Percentage  of  adults  aged  25  to  64  who  participated  in  education  in  the  4  weeks  preceding  the 
survey by labour status – LFS 2018. 

Romania
Bulgaria
Croatia
Slovakia
Greece
Cyprus
Hungary
Poland
Latvia
Lithuania
Germany
Belgium
Italy
Czechia
Spain
Portugal
EU-28
Slovenia
Malta
Ireland
Austria
United Kingdom
Luxembourg
France
Netherlands
Estonia
Denmark
Sweden
Finland

0.8

1.9

2.4

1.5
1.6

4.3
4.3

6.5
6.6
6.7
6.9
7.2
7.8
8.5
8.7
9.2
10.3
10.4
11.8
12.4
12.6
12.6

15.8
16.0

19.7
20.4
20.6
21.5
23.1

27.8

30.0

3.9
5.7

2.7

4.9

6.8

2.9

8.4

12.3

5.0
5.1

12.8
13.2

10.7
12.0

6.0

16.0
16.3

13.1

14.3

18.6
20.1

29.7

28.5

24.7

45.5

Source: Eurostat [trng_lfse_02] 
Note: Croatia, Hungary, Lithuania and Malta: low reliability for unemployed. 

Employed

Unemployed

Active  Labour  Market  Policies  (ALMP)  —  including  measures  such  as  job  assistance,  labour  market  training, 
wage subsidies to the private sector, and direct job creation in the public sector  — are a central element of 
Europe’s strategy to combat unemployment. According to DG employment, training absorbs the largest share 
of the amount spent on ALMP. (22) Empirical work undertaken by Card, Kluve, & Weber (2009) between 1995 
and 2007 found that formal and non-formal training programmes exhibited insignificant or negative impacts 
on the reduction of unemployment in the short-term (after one year from completion) but have significantly 
positive  effects  in  the  medium-term  (after  two  or  three  years).  One  possible  explanation  of  the  short-term 
negative  effect  of  training  programmes  could  be  that  these  programmes  are  typically  used  to  renew  the 
eligibility to unemployment benefits; thus, discouraging unemployed to look for possible occupation (Sianesi, 
2008). 

Likewise,  Newton,  Hurstfield,  Miller,  Akroyd,  &  Gifford  (2005)  studied  more  closely  the  determinants  of  the 
participation  in  training  programmes  among  unemployed  and  inactive  people  in  the  UK  and  identified  four 
factors  affecting  the  decision  to  participate  in  training.  They  found  a  negative  correlation  between  age  and 
the  likelihood  of  engaging  in  training  and  greater  engagement  in  training  among  people  with  higher 
qualifications. Moreover, recent training is a predictor for training participation; that is, the likelihood to receive 
training is higher for the unemployed that have attained their higher qualification(s) more recently (two years 
before the survey).  

(22)   https://ec.europa.eu/eurostat/statistics-

explained/index.php?title=Archive:Labour_market_policy_interventions&direction=next&oldid=159378 .. 

19 

 
 
 
 
                                           
Overall, the literature suggests that the institutional setting of the  different EU  MS  plays a substantial role 
when it comes to adult education. For this reason, it is important to identify the role of national governments 
in putting in place publicly financed education programs to support unemployed individuals in their transition 
to full employment, but also the relevance, scope and quality of job-related training provided  by employers 
concerned  with  competitiveness.  Similarly,  to  understand  what  explains  differences  in  participation  rates 
between  employed  and  unemployed  it  is  necessary  to  assess  which  learning  activities  are  job-related  and 
likely  subsidized  by  the  employer,  and which  ones are  publicly  financed  through, for example, active  labour 
market policy programmes. 

2.2.4  Adult participation in lifelong learning and type of occupation. 

Figure 9 presents participation rates of adults in formal and non-formal education activities among different 
types  of  occupations  classified  according  to  the  level  of  skills  demanded,  from  high  skills  (Managers, 
professionals,  technicians  and  associate  professionals)  to  medium  and  low  skills  (Plant  and  machine 
operators and assemblers, elementary occupations).  Overall, participation in adult learning  is more frequent 
among highly skilled occupations than elementary  ones.  Clearly, we cannot infer any  sort of causality from 
this chart, given that people in high skill occupations are more likely to be offered training opportunities, and 
at  the  same  time  people  who  receive  training  can  potentially  access  better  jobs;  however,  it  is  still  worth 
mentioning  how  adult  educational  opportunities  are  distributed  in  light  of  the  policy  priorities  already 
discussed. Once again, adult learning appears to be most evenly distributed across occupational profiles in the 
Nordic  countries  (Finland,  Sweden  and  Denmark),  the  Netherlands,  Austria  or  the  UK.  Eastern  and  Southern 
European countries stand out as the most unequal ones in providing learning.  

Figure 9: Percentage of employed adults aged 25 to 64 who participated in  education in the 4 weeks preceding the 
survey by type of occupation – LFS 2018. 

45.0

40.0

35.0

30.0

25.0

20.0

15.0

10.0

5.0

0.0

FI SE EE FR DK NL LU AT UK MT SI PT ES EU -
28

IE IT CZ LT PL LV BE HU DE CY EL SK BG RO

Managers, professionals, technicians and associate professionals
Clerical support workers, service and sales workers
Skilled agricultural, forestry and fishery workers, craft and related trades workers
Plant and machine operators and assemblers, elementary occupations

Source: Eurostat [trng_lfs_04] 
Note: Clerical support workers, service and sales workers: low reliability for HR; Skilled agricultural, forestry and fishery workers, craft and 
related trades workers: low reliability for BG, CY, HR and MT; Plant and machine operators and assemblers, elementary occupations: low 
reliability for BG, CY, HR and LT. 

20 

 
 
2.3  Discussion  on  the  limitations  of  the  existing  ET2020  benchmark  on  adult 

participation in lifelong learning: Challenges ahead. (23)  

The  purpose  of  this  Section  has  been  to  thoroughly  revise  the  existing  ET2020  benchmark  on  adult 
participation  in  lifelong  learning.  A  number  of  drawbacks  and  limitations  have  been  identified,  including 
limitations that depend on the data source, namely the LFS, and limitations that go beyond it: 

—  Limitations related to the current variables in the EU-LFS: 

o  The  4  weeks  window  appears  too  narrow  for  the  analysis  of  adult  participation  in  lifelong 
learning, since most of it is of non-formal type with short duration. Having a short time reference 
limits the probability of capturing any of these activities and it is sensitive to significant changes. 
The LFS from 2022 will have variables for both 4 weeks and 12  months (biannually) reference 
periods. 

o  The EU-LFS does not provide information on informal learning, even though data from the 2003 
the  ad-hoc  module  shows  that  potentially  it  is  also  very  frequent  as  shown  in  Figure  5;  this 
makes the current benchmark incomplete. While it is true that informal learning may not be the 
most appropriate indicator to convey information on upskilling needs of the workforce, it would 
still provide useful generic information on a person’s human capital.   

—  More generic limitations related to the definition of the benchmark:  

o  The  benchmark is an  average  participation  rate  among  all  adults  aged  25  to  64  and  does not 
specifically  give  higher  weight  to  participation  rates  among  older  groups  and  low-qualified 
adults,  even  though  they  are  the  main  target  groups  (according  to  the  Council  resolution);  if 
average  participation  rates  keep  increasing,  but  these  individuals  rarely  take  part  in  any  adult 
learning, it cannot be inferred that adult learning policies have been successfully implemented. 
Efforts are needed to better monitor those more disadvantaged which should be at the core of 
any lifelong learning policies for upskilling and re-skilling. Disaggregating by key sub-group could 
be already a significant improvement. (24)  

o  Given that participation in adult learning is higher among people in work, and especially among 
those who are in better occupations (see Figure 8 and Figure 9), a useful indicator should give 
information on private, employer provided or personally sought training, as well as and publicly 
funded adult learning.  

To summarise, core indicators, as the one used for the ET 2020 benchmark, generally provide headline figures 
for  summary  overviews,  without  assessing  national  systems  or  policies;  however,  in  doing  so,  they  risk 
oversimplifying the complexity of the measured phenomenon resulting less useful. More detailed breakdowns 
of  adult  participation  in  lifelong  learning  would  result  in  more  efficient  monitoring  and  could  adequately 
inform policy makers. 

(23)   Additional analysis on the measurement of adult learning and its weaknesses has also been done in Education and Training Monitor 
(page  64-65)  https://ec.europa.eu/education/sites/education/files/document-library-docs/volume-1-2018-education-and-
2018 
training-monitor-country-analysis.pdf 
skills: 
https://ec.europa.eu/eurostat/documents/3888793/7753369/KS-TC-16-023-EN-N.pdf/438b69b5-2fcb-4923-b9e2-fa7b59906438 . 
the  Education  and  Training  Monitor  2018: 

(24)   Some  attempts  have  already  been  done  as 

in  pp.  72-73  of 

methodological 

measuring 

ESTAT 

guide 

and 

on 

; 

https://ec.europa.eu/education/sites/education/files/document-library-docs/volume-1-2019-education-and-training-monitor.pdf . 

21 

 
 
 
                                           
3  Towards a better framework for monitoring adult participation in 

lifelong learning within the EU. 

The  previous  section  discussed  the  main  strengths  and  weaknesses  of  the  current  benchmark  as  a  tool  to 
monitor the success of adult learning; it also pointed out some limitations concerning the data source used to 
build  the  main  indicator  for  participation  in  adult  learning,  namely  the  EU-LFS.  This  section  discusses  the 
appropriateness of other available sources for monitoring participation in adult lifelong learning highlighting 
their  uniqueness  and  appropriateness  in  light  of  the  policy  goals  and  theoretical  framework  mentioned  in 
section 1.2.  

The data sources described in this section include: The Adult Education Survey, a European Union harmonised 
survey  on  adult  participation  in  learning  activities;  the  Continuing  Vocational  Training  Survey  (CVTS),  a 
European Union harmonised survey on continuing vocational training in enterprises, both carried out according 
to European legislation, with results published by Eurostat; and the Survey on Adult Skills part of the OECD’s 
Programme  for  the  International  Assessment  of  Adult  Competencies  (PIAAC).  The  UNESCO-UIS  –  OECD  - 
Eurostat  (UOE)  joint  data  collection  on  education  and  other  statistics  collected  at  the  national  level;  and 
finally,  this  section  discusses  what  information  could  be  drawn  from  national  statistics  from  different 
education  and  training  systems  and  other  European  surveys  such  as  the  European  Survey  on  Income  and 
Labour  Conditions  (EU-SILC),  as  well  as  the  European  Working  Condition  Survey  (EWCS)  and  the  European 
Skills and Jobs Survey (ESJS). 

3.1  The  Adult  Education  Survey  (AES):  A  rich  source  of  evidence  on  adult 

learning statistics 

The AES provides an overview of the participation of individuals in education and training including formal and 
non-formal  education  and  training  as well  as informal  learning.  It  collects  information  beyond the  limits  of 
publicly offered educational opportunities for adults. The reference period for the participation in the learning 
activities is the twelve months prior to the interview. The survey focuses on people aged 25-64. Apart from 
participation in formal, non-formal and informal learning, the following information is also available:  

—  Access to information on learning possibilities  

—  Time spent on education and training  

—  Characteristics of the learning activities  

—  Reasons for (not) participating  

—  Obstacles to participation  

—  Employer financing and costs of learning 

—  Self-reported language skills(25) 

Three  waves  of  the  AES  have  been  implemented  so  far.  The  first  AES  (2007  AES)  was  a  pilot  survey 
conducted  in  26  EU  Member  States  (Ireland  and  Luxembourg  did  not  participate),  as  well  as  in  Norway, 
Switzerland and Tukey. The second wave (2011 AES) was conducted in 27 EU Member States (Croatia did not 
participate), Norway, Switzerland as well as in Serbia and Turkey. The third wave (2016 AES) was conducted in 
28 EU Member States, Norway, Switzerland as well as in Serbia, Turkey, Albania, Bosnia and Herzegovina and 
the Former Yugoslav Republic of Macedonia. The next AES is planned for 2022. 

See  Table  3  to  find  out  how  the  questions  related  to  adult  participation  in  lifelong  learning  (formal,  non-
formal and informal) are presented in the survey. 

(25)   For more detailed information visit: https://ec.europa.eu/eurostat/web/microdata/adult-education-survey . 

22 

 
 
 
 
 
                                           
Table 3: Questions related to adult participation in lifelong learning as posed in the 2016 AES. (12-month reference 
period) 

Variable 
name 
FED 

Formal 
education 

Non-formal 
education 

NFE  

Informal 
learning 

INF 

Question 

Additional information 

Number of formal education 
activities, start year and month, 
level, completion,  field, 
orientation, method of learning, 
reasons for participation, whether 
learning took place during 
working hours, number of 
instruction hours, who paid and , 
outcomes and use of skills or 
knowledge. 
Information on number of 
activities, type, purpose (job-
related or not), whether they took 
place during working hours and 
whether the employer paid partly 
or fully. For two randomly 
selected activities information are 
provided also on: field, method, 
reason for participation,  number 
of hours, providers, whether the 
activity lead to certificate, who 
paid, personal cost, use of skills 
or knowledge and outcomes. 

“During the last 12 months, that is since <<month, year>> 
have you been a student or apprentice in formal 
education or training?” 

The AES includes the following note: The question(s) for 
this variable should be phrased by countries in a way that 
the concept of education designed to lead to achievement 
included in the National Framework of Qualifications is 
described as fully as possible.  

Activities in which the respondent participated during the 
last 12 months with the intention to improve knowledge 
or skills in any area (including hobbies) either in leisure 
time or in working time.  
This includes completed and ongoing activities. 
a. During the last 12 months have you participated in 
courses at the workplace or in your free time? 
(NFECOURSE)    
Examples: language, computer, driving, management, 
cooking, gardening or painting courses. 
b. During the last 12 months have you participated in 
workshops or seminars at the workplace or in your free 
time?  (NEFWORKSHOP)              
Examples: Data workshop, inspiration day, study day, 
inspirational workshop, work information seminar, health 
seminar. 
c. During the last 12 months have you participated in 
guided-on-the-job training, which means planned periods 
of education, instruction or training directly at the 
workplace, organised by the employer with the aid of a 
designated teacher/instructor? (NFEGUIDEDJT)   
Examples: Training to operate a new machine or to learn 
new software (for one or two people).  
d. During the last 12 months have you participated in 
private lessons with the aid of a teacher or tutor for 
whom this is a paid activity? (NEFLESSON)         
Examples: mathematics or piano lessons. A lesson should 
be included if provided by a professional teacher and 
excluded if provided by a friend, family member or 
colleague. 
During the last 12 months, apart from the activities 
mentioned earlier, have you deliberately tried to learn 
anything at work or during your free time to improve your 
knowledge or skills through any of the following means?  
a. Learning from a family member, a friend or colleague 
(INFFAMILY) 
b. Learning by using printed material (books, professional 
magazines, etc.) (INFMATERIAL) 
c. Learning by using computers (online or offline) 
(INFCOMPUTER) 
d. Learning through television/radio/video (INFMEDIA) 
e. Learning by guided tours in museums, historical or 
natural or industrial sites (INFMUSEUM) 
f. Learning by visiting learning centres (including libraries) 
(INFLIBRARIES)  

23 

 
 
 
 
 
The 2016 Adult Education Survey provides a  detailed view on who is most or least likely to be learning, the 
type and intensity of learning, what their motivations are and the barriers adults experience when seeking to 
take  up  learning.  A  brief  statistical  analysis  of  some  of  the  key  variables  is  provided  here  to  highlight  the 
potential of this survey to explore what the policy levers might be to engage more people. 

To  begin  with,  Figure  10  compares  the  results  of  participation  in  formal  and  non-formal  learning  obtained 
using  the  AES  (12-month  reference  period)  with  those  provided  by  the  4  weeks  reference  period  of  the  EU 
LFS. We use the same year to compare them, 2016.  

First, as expected, there is a greater probability of reporting adult learning if the timeframe is longer: in 2016, 
for  the  EU-28  average  45.2%  of  the  individuals  reported  participation  in  adult  learning  (formal  and  non-
formal) using the 12-month reference period (AES) while only 10.8% was the share of participants if the EU-
LFS  (4  weeks  periods)  was  used.  It  has  to  be  noted  that  the  coverage  of  non-formal  learning  is  different 
between the two sources as AES covers guided-on-the-job training while the EU-LFS excludes them. 

Second, Figure 10 shows that adult learning is mostly non-formal;  

Finally,  as  we  already  observed  with  the  ad  hoc  module  of  the  EU  LFS  in  2003  (Figure  5),  participation  in 
informal learning as reported in the AES for 2016 is overall high with 60.5% of adults reporting some type of 
informal  learning  at  EU-28  level  and  going  as  high  as  96.1%  for  Cyprus  to  22.4%  for  Lithuania  [for  full 
detailed statistics from the AES informal learning see: Eurostat, trng_aes_200]. 

Figure 10: Participation in formal and non-formal learning: The AES and the LFS compared – 2016 

80

70

60

50

40

30

20

10

0

NL AT SE HU DE FR IE

FI UK CY LV LU SK CZ PT DK SI EU-28BE EE IT ES MT HR LT PL BG EL RO

2016 AES Formal

2016 LFS Formal

2016 AES Non-formal

2016 LFS Non-formal

Source: [trng_lfs_09] and [trng_aes_100]. 
Note: 2016 AES Formal: low reliability for SK. 

These  results  in  Figure  11  further  show  that  adult  learning  takes  place  in  different  forms.  While  some 
individuals learn in a formal education institution (formal learning), a big majority participates in work-related 
learning  (non-formal),  while  overall,  there  is  an  increasing  prevalence  of  informal  learning.  In  fact,  as 
identified in the 2018 E&T Monitor (DG EAC, 2018) for most adults, the learning activities are job-related and 
sponsored by the employing organisation.  

24 

 
 
 
 
Figure 11: Participation in job-related non-formal adult learning over 12 months, by type of sponsor – 2016 AES 

60

50

40

30

20

10

0

L
N

E
S

T
A

E
I

E
D

I

K F
S

K
U

T
P

Z
C

R
F

U
H

L
D

I

V S
L

U
L

E
E

E
B

T
I

Y
C

S
E

T
M

T
L

R
H

G
B

L
P

L
E

O
R

8
2
-
U
E

Sponsored by the employer

Not sponsored by employer

Source: [trng_aes_120]. 
Note: Not sponsored by the employer: low reliability for SE,  

It is important to estimate not only participation in adult learning but also the intensity of training, measured 
as  number  of  hours  of  instruction,  as  it  seems  to  increase  inequality  among  potential  recipients  of  adult 
learning.  For  instance,  not  only  do  younger  people  report  higher  participation  rates,  they  also  devote 
significantly  more  hours  to  learning  than  their  older  counterparts,  therefore  widening  the  gap  already 
mentioned in section 2. 

Further, Figure 12 shows that at EU-28 level, during the 12 months prior to the interview in 2016, individuals 
aged  25-34,  spent  202  hours  on  average  in  education  and  training  whereas  those  aged  55-64  spent  an 
average of 65 hours. .  

Figure 12: Mean instruction hours in formal and non-formal learning by age group – 2016 AES. 

Slovakia
Cyprus
Lithuania
Czechia
Netherlands
Ireland
Malta
Hungary
Romania
France
Latvia
Croatia
United Kingdom
Belgium
Bulgaria
Estonia
Italy
EU - 28
Austria
Poland
Switzerland
Albania
Luxembourg
Spain
Portugal
Finland
Sweden
Greece
Slovenia
Germany
Denmark

72
79
89
92

35
40
46

29

63

45

56

32

45

65

80

82

67

51
51

76
65
57
56

75

51

66

72
61
58

76

52

81

90

130

126

129
129
132
135
144

160
168
169
177
180
183
185

202
202

219
222
227
228
228
232
234
235
236
248
252

279

303

Source: [trng_aes_147] 
Note: 55-64: low reliability for RO. 

25-34

55-64

25 

 
 
 
Just  like  the  EU-LFS,  the  AES  provides  the  necessary  tools  to  analyse  participation  in  adult  learning  by 
different socio-economic characteristics. For brevity, estimates are not described in detail here, however, they 
suggest  the  same  conclusion:  outreach  and  interventions  should  seek  to  target  adults  in  lower  occupations 
(Figure  13);  adults  who  live  outside  urban  areas  (see  Figure  14  that  compares  participation  between 
individuals living in cities and rural areas); but also older adults, and those with lower education. In addition, 
the AES provides very  useful information on the  willingness to  participate in adult learning, the reasons for 
not participating and the barriers identified. 

Figure 13: Participation of employed adult in formal or non-formal learning by low and high skills occupations – 2016 
AES 

90.0

80.0

70.0

60.0

50.0

40.0

30.0

20.0

10.0

0.0

L
N

T
A

I

E S
S

E
I

R
F

U
H

Y
C

I

U F
L

V
L

E
D

S
E

T
P

Z
C

L
D

K
S

T
I

K
U

E
B

E
E

R
H

T
M

L
P

T
L

G
B

L
E

O
R

8
2
-
U
E

Managers, professionals, technicians and associate professionals

Elementary occupations

Source: [trng_aes_104] 
Note: Elementary occupations: low reliability for DK, EE, HR, LU, MT, NL, SK, FI and SE. 

Figure 14: Participation rate in formal and non formal education and training by degree of urbanisation  – 2016 AES 

70

60

50

40

30

20

10

0

E
S

L
N

I
F

U
L

K
D

E
I

T
A

K
U

I

U S
H

R
F

E
D

S
E

V
L

Z
C

E
E

K
S

T
P

Y
C

T
I

E
B

R
H

L
P

T
M

T
L

G
B

L
E

O
R

8
2
U
E

Source: [trng_aes_105];  
Note: data for participation in rural areas in Slovakia, Cyprus, Belgium, Malta and Lithuania are not available. 

Cities

Rural Areas

26 

 
 
 
 
 
The  results  of  the  search  for  information  on  learning  possibilities  summarised  in  Figure  15  are  rather 
disappointing:  in  2011,  for  the  EU-28  average:  72.9%  of  the  individuals  aged  25-64  did  not  look  for 
information  on  possible  courses  available.  Interestingly,  the  UK,  Luxembourg,  Denmark,  Finland  and  the 
Netherlands have the highest rates of successful search for information of learning possibilities (looked and 
found information on learning possibilities in  Figure 15). This is a good indication of educational institutions 
efficiency in reaching the target audience. 

Figure 15: Result of the search for information on learning possibilities – 2011 AES 

UK
LU
DK
FI
NL
SE
PT
EU-28
FR
ES
SK
MT
LV
DE
AT
EE
IE
SI
CZ
BE
CY
IT
PL
HU
LT
EL
BG
RO

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Did not look for information on learning possibilities
Looked for and found information on learning possibilities
Looked for but did not find any information on learning possibilities

Source: [trng_aes_186] 
Note: Looked for but did not find any information on learning possibilities: low reliability for BG, CY, LT and MT. 

AES  also  provides  more  specific  information  on  the  most  frequent  barriers  to  learning.  More  specifically, 
adults who say that they wish to participate in education and training are given are asked to provide reasons 
for not doing so.  At EU-28 level, in 2016, the most  common obstacle to participate in adult learning  was a 
conflicting schedule, selected by 44.2 per cent of respondents  (see Figure 16); the second most frequently 
mentioned tem was costs selected by 35.3% of respondents, followed by family reasons (32.7%). The least 
frequently mentioned obstacle was age or health related reasons. 

27 

 
 
 
Figure 16: Population wanting to participate in education and training, by reason for not participating EU-28 

0%

5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

Schedule

Costs

Family reasons

Lack of support from employer or public services

Distance

Other personal reasons

No suitable offer for education or training

Health or age reasons

Other

Source: [trng_aes_176] 

3.2  The Continuing Vocational Training Survey (CVTS): An employer’s survey. 

Continuing Vocational Training (CVT) are training measures or activities which have as their primary objectives 
the acquisition of new competences or the development and improvement of existing ones and which must be 
financed at least partly by the enterprises for their persons employed who either have a working contract or 
who benefit directly from their work for the enterprise such as unpaid family workers and casual workers. Part 
financing  could  include  the  use  of  work-time  for  the  training  activity  as  well  as  financing  of  training 
equipment..(26) 

The CVTS is a European Union harmonised survey on continuing vocational training (CVT) in enterprises and is 
part of the EU statistics on lifelong learning(27).  

The survey aims to gather comparable statistical information on continuing vocational training in enterprises 
and covers the following topics: 

—  Continuing vocational training, skills supply and demand and training needs 

—  Measurement of the forms, contents and volume of continuing training 

—  The enterprises own training resources and the use of external training providers 

—  The costs of continuing training 

—  Initial vocational training 

CVTS covers enterprises  with 10 or more persons employed in the  business economy  (mainly). The detailed 
coverage  according  to  NACE  Rev  2  categories  is:  B,  C10-C12,  C13-C15,  C17-C18,  C19-C23,  C24-C25,  C26-
C28+C33, C29-C30, C16+C31-C32, D-E, F, G45, G46, G47, H, I, J, K64-K65, K66, L+M+N+R+S. Data from the 
CVTS are available for 1993, 1999, 2005, 2010 and 2015. The next CVTS is planned for the reference year 
2020. 

Some  important  differences  are  found  between  the  CVTS  and  the  EU-LFS  or  the  AES  for  monitoring  adult 
learning.  

(26)   For more information visit: https://ec.europa.eu/eurostat/web/microdata/continuing-vocational-training-survey. 
(27)   Information 

at https://circabc.europa.eu/sd/a/43cebda2-6b09-4298-b9b9-

available 

CVTS  manual 
in 
ba57d1f42301/1_CVTS5manual_V1-2_20161201.pdf  

available 

the 

28 

 
 
 
 
 
                                           
Table 4: Type of training included in the CVTS manual 

CVT courses are typically separated from the active workplace (learning takes place in locations specially assigned for 
learning like a class room or training centre).  
They are organised (time, space and content) by a trainer or a training institution. The content is designed for a group of 
learners (e.g. a curriculum exists).  

—  Two distinct types of CVT courses are identified Internal CVT courses (designed and managed by the 

enterprise itself, and the responsibility for the content of the course lies within the enterprise ) 

—  External  CVT  courses  (designed  and  managed  by  organizations  which  are  not  part  of  the  enterprise  itself,  e.g. 

third-party organizations. The course is then selected and ordered/ purchased by the enterprise)  

Other forms of CVT: 
—  Guided on-the job-training (planned periods of training, instruction or practical experience in the work place using 

the normal tools of work, either at the immediate place of work or in the work situation) 

—  Job-rotation,  exchanges,  secondments  or  study  visits  (these  are  considered  as  “other”  forms  of  CVT  only  if 
these measures are planned in advance with the primary intention of developing the skills of the workers involved. 
Transfers  of  workers  from  one  job  to  another  which  are  not  part  of  a  planned  developmental  program  should  be 
excluded) 

—  Learning or quality circles (groups of persons employed who come together on a regular basis with the primary 
aim  of  learning  more  about  the  requirements  of  the  work  organization,  solving  production  and  work  place-based 
problems, through discussion) 

—  Self-directed learning/e-learning (when an individual engages in a planned learning initiative where he or she 
manages the settings of the learning initiative/activity in terms of time schedule and location, using one or 
more  learning  media.  Learning  can  take  place  in  private,  public  or  job-related  settings.  It  might  be  arranged  using 
open and distance learning methods, video/audio tapes, correspondence, computer-based methods (including internet, 
e-learning) or by means of a Learning Resources Centre.  

—  Participation in conferences, workshops, trade fairs and lectures (considered as training actions only when 
they are planned in advance and if the primary intention of the person employed for participating is training/learning) 

Source: Eurostat 

First, CVTS poses the training questions to employers (at enterprise level) and not workers; there are likely to 
be  systematic  differences  in  how  these  two  groups  report  training  activities.  Little  is  known  about  the 
differences in reported training activities between employer and employees. An exception is a study by Barron 
(1997) which uses data from a matched employer-employee survey to see to what extent their responses are 
consistent. They find that correlations between the employee and the employer measures are less than 0.5 
and  that  employers  report  25  percent  more  hours  of  training  on  average  than  workers  do,  suggesting  a 
substantial differences in data as reported by employees compared to data reported by employers.  

Second, while all surveys mentioned here provide measures of the level of continuing education and training 
among  the  adult  workforce,  there  are  important  differences in  how  the  training  questions  are  phrased.  The 
AES and the EU-LFS use definitions based on ISCED where learning is understood to be ‘any improvement in 
behaviour, information, knowledge, understanding, attitude, value or skills’; and while the AES covers all types 
of learning opportunities and education and learning pathways including formal, non-formal and informal, the 
EU-LFS focus on formal and non-formal education only. However, the CVTS collects participation in continuing 
vocational training (see table 4 to learn about the type of training included in the CVTS questionnaire) defined 
as  training  measures  and  activities  which  the  enterprise  finances,  partially  or  entirely,  for  their  employees 
who  have  a  working  contract.  The  CVTS  distinguishes  between  initial  and  continuing  training,  so  that  the 
former  can  be  explicitly  omitted  from  the  training  estimates.  It  should  be  mentioned  that  CVTS  does  not 
distinguish  between  formal  and  non  formal  education,  even  though  we  can  safely  assume  that  it  is  non 
formal, and it only asks the number or participants in CVT courses, and not about other forms of training. 

Third,  CVTS  excludes  workers  in  enterprises  with  fewer  than  10  persons  employed  and  all  enterprises  in 
certain  sectors  of  activity  (see  Figure  17  for  participation  rates  by  enterprise  size).  Because  of  these 
exclusions the CVTS cannot  be used to infer participation rates in the total economy, since the exclusion of 
small  firms  could  bias  the  training  participation  rates  upwards  given  that  these  rates  tend  to  rise  with 
enterprise  size  over  the  observed  range  (Eurostat,  2002).  More  specifically,  participation  in  training  among 
smaller firms is likely to be lower because: i) training involves fixed costs and scale economies; ii) small firms 

29 

 
 
 
might  find  more  difficult  to  replace  a  worker  who  goes  training;  and  iii)  small  firms  might  have  fewer 
opportunities to fully obtain the benefits of training through internal reallocation of workers. 

Figure 17: Participants in CVT courses by sex and size class - % of persons employed in all enterprises (2015 CVTS) 

90

80

70

60

50

40

30

20

10

0

Z
C

I

U S
L

S
E

K
S

T
I

E
I

R
F

T
P

E
B

L
P

E
S

T
A

T
M

Y
C

I
F

8
2
-
U
E

E
E

L
N

K
D

E
D

V
L

R
H

G
B

T
L

L
E

O
R

K
U

U
H

250 persons employed or more

From 10 to 49 persons employed

From 50 to 249 persons employed

Source: [trng_cvt_12s] 

Bearing  in  mind  all  highlighted  concerns,  Figure  18  compares  the  share  of  participants  in  job-related  non-
formal training as reported by the 2016 AES (aged 25-64, employed or not) with its ‘quasi’ equivalent share 
from  the  2015  CVTS  (any  working  age,  only  persons  employed  in  enterprise  with  10  and  more  persons 
employed in specific sectors of activity). The difference between both surveys is shown in yellow. It is worth 
repeating that the comparison is purely indicative, since the reference populations are different. (28) 

Figure 18: Share of participants in adult learning: 2016 AES and 2015 CVTS 

100

80

60

40

20

0

-20

-40

-60

2015 CVTS (employers)

2016 AES (participants)

Difference p.p.

Source: [trng_cvt_12s]; [trng_aes_120] 

(28)   A presentation given at the 22nd meeting of the INES Network on Labour Market, Economic and Social Outcomes of Learning (INES-
LS) in Riga (14-16 October 2019), Statistics Sweden provided some comparable data between AES and CVTS. In essence, results do 
not vary enormously from those provided in Figure 18. 

30 

 
 
 
 
 
 
                                           
First, we observe that, in general, employers’ reported figures from CVTS are higher than those reported by 
individuals  (employed  or  not)  in  AES  (except  for  Lithuania,  Estonia,  Latvia,  Denmark,  Hungary,  the  UK, 
Germany, Austria and the Netherlands), as we expected. Second, despite all the differences between surveys, 
countries like Romania, Greece, Bulgaria, Croatia or Lithuania report low shares of participants in both surveys, 
while  top  performers  in  adult  learning  (Nordic  countries,  Austria,  the  Netherlands  and  the  UK)  also  behave 
similarly in both surveys. Considering the unique features of the CVTS, and the fact that a large share of non-
formal training is job-related and funded by the employer as reported in figure 18. Earlier on, we argue that 
this data source could be used to provide additional indicators and for better understanding the demand and 
supply of non-formal adult learning. 

3.3  The  OECD  Survey  on  Adult  Skills  (PIAAC):  Skills  acquisition  beyond  formal 

education 

The  OECD  has  carried  out  a  comprehensive  thematic  review  of  adult  learning  to  improve  the  quality  and 
effectiveness  of  its  activities  in  member  countries.  The  DeSeCo  Project  (Definition  and  Selection  of 
Competencies project at http://deseco.ch/ ) was initiated by the OECD at the end of 1997 and was carried out 
under  the  leadership  of  Switzerland.  It  was  embedded  in  the  OECD's  long-term  programme  on  education 
indicators  (INES),  which  aimed  to  provide  measurements  on  the  functioning,  development  and  impact  of 
education and lifelong learning. The DeSeCo project claims that adult learning can play an important role in 
helping  people  to  develop  and  maintain  key  information-processing  skills  and  acquire  knowledge  and  other 
skills throughout their lives (beyond educational attainment). Indeed, workers need to adapt to changes during 
their careers as the skills demanded by the labour market change. It is thus crucial for adults to have access 
to organised learning opportunities beyond their initial formal education. 

The OECD and Statistics Canada implemented cross-national surveys such as the International Adult Literacy 
Survey (IALS) in 1994 to assess people's literacy scales on top of educational attainment (a final report was 
produced in 2000, see OECD/STATCAN, 2000), and the Adult Literacy and Life Skills (ALL) conducted between 
2003 and 2008 (https://nces.ed.gov/surveys/all/index.asp ), also sought to profile the skills of adults and their 
participation in lifelong learning among the contributing countries. 

The introduction in 2008 of the OECD’s Survey of Adult Skills (PIAAC), which measures literacy, numeracy and 
problem-solving in technology-rich environments and specifically looks into participation in adult learning, has 
placed greater attention to this topic across Europe. Seventeen EU countries participated in the first round in 
2011/2012 (Austria, Belgium-Flanders, Cyprus, Czechia, Denmark, Estonia, Finland, France, Germany, Ireland, 
Italy,  Netherlands,  Poland,  Slovak  Republic,  Spain,  Sweden  and  UK-England  and  Northern  Ireland)  while 
Greece, Lithuania and Slovenia participated in the second round (2014/2015) and Hungary in the third round 
(2017/2018)..  

PIAAC  collects  information  on  formal  and  non-formal  education.  It  uses  a  list  of  possible  non-formal 
education  activities,  including  open  or distance  learning  courses, private  lessons,  organized  sessions  for  on-
the-job training, and workshops or seminars to prompt respondents to list all their learning activities during 
the  previous  12  months.  Some  of  these  learning  activities  might  be  of  short  duration.  Formal  education  is 
defined  as  planned  education  provided  in  the  system  of  schools,  colleges,  universities  and  other  formal 
educational  institutions,  and  which  normally  constitutes  a  continuous  “ladder”  of  full-time  education  for 
children and young people. The providers may be public or private. 

As reported in Figure 19, there seems to be a clear relationship between participation in adult lifelong learning 
programmes  and  literacy  and  numeracy  scores,  with  those  reporting  higher  participation  in  adult  learning 
(Nordic countries and the Netherlands) also scoring higher in literacy and numeracy skills. 

31 

 
 
Figure 19: Participation in adult learning and literacy and numeracy scores (PIAAC) 

Source: Survey of Adult Skills; PIAAC 2011-12 (round 1) and 2013-14 (round 2).  

However, participation in adult learning is not evenly distributed. Figure 20 compares rates of participation in 
education  activities  between  adults  who  display  very  low  levels  literacy  (Level  1  or  below)  and  adults  who 
display the highest levels of literacy (Level 4/5). The Nordic countries as well as the Netherlands appear to be 
the  most  successful  in  ensuring  that  adults  with  low  literacy  take  up  adult  education  opportunities.  On  the 
contrary, in some Eastern and Southern European countries, the most literate can have over four to five times 
the probability of participating than adults with the lowest levels of literacy. 

Figure 20: Percentage of adults aged 16-65 (youth 16-24 in initial cycle of formal studies excluded) who participated in  
education in the 12 months preceding the survey, by high low levels of literacy proficiency - PIAAC  

Cyprus

Slovakia

Italy

France

Poland

Czechia

Belgium

Ireland

Austria

United Kingdom

Estonia

Spain

Netherlands

Germany

Sweden

Finland

Denmark

24

7

10

17

12

21

23

28

21

26

22

17

17

40

42

37

39

51

57

57

59

65

66

69

75

75

75

77

79

80

81

84

85

86

Source: Survey of Adult Skills 

Literacy below 1

Literacy at level 4/5

32 

 
 
 
 
 
 
The  PIAAC  dataset  contains  also  questions  on  barriers  to  further  participation  in  adult  education.  However, 
they are only asked to those who have stated that they would like to participate in adult learning while those 
who  answered  that  they  have  no  interest  in  participating  in  adult  learning  have  not  received  any  questions 
about barriers. 

The  uniqueness  of  PIAAC  data  for  studying  adult  learning  (formal  and  non-formal)  resides  in  its  link  to 
literacy,  numeracy  and  problem solving,  functional  skills  very  much  needed  to  accommodate  to  a  changing 
labour market and society. While it would be a very useful tool for research purposes, low frequency, changes 
over time and the limited coverage of EU Member States reduce its appeal for monitoring purposes. 

3.4  UNESCO-UIS  OECD  Eurostat  (UOE)  joint  data  collection  on  education,  DG 
labour  market  policy  database,  and  other  European 

EMPLOYMENT’s 
statistics. 

The objective of the UOE data collection on education statistics is to provide internationally comparable data 
on key aspects of formal education systems (participation, completion, cost and type of resources).  

Under  UOE  data,  ‘adult  education’  or  ‘continuing  education’  are  included  only  if  they  are  part  of  regular 
educational  programmes;  that  is,  data  is  available  only  for  formal  education.  The  different  indicators 
(downloadable  at:  https://ec.europa.eu/eurostat/web/education-and-training/data/database)  provide  useful 
figures for summary overviews and cross-country comparisons; in particular data is available by age allowing 
to focus analysis on different age groups. However, as discussed in this report, a thorough monitoring would 
require also the coverage of non-formal adult learning, which is outside of the scope of UOE data collection. 

The timeliness of data depends on national accounting procedures and in some cases, there is a significant 
delay before the annual data are finalized, particularly those  related to expenditure. As a result, data for all 
countries  are  only  available  18-20  months  after  the  reference  period.  However,  its  usefulness  is  not 
negligible,  as,  for  example,  one  of  the  sub-indicators  in  the  ET2020  benchmark  of  adult  participation  in 
lifelong learning relies on these statistics. This sub-indicator focuses on the expenditure on training as part of 
active  labour  market  policy  interventions.  It  covers  (at  least  partially)  the  supply  side  for  training  and 
measures  how  many  individuals  who  want  to  work  participate  in  training  paid  by  the  government  (through 
active labour market policies). Results in Figure 20 show that Finland, a country with a high participation rate 
in adult learning, spends 0.47% of its GDP in publicly financing training aimed to increasing employability. By 
contrast, countries with the lowest participation rate in adult learning (Romania, Bulgaria, Slovakia, Poland or 
Greece) spend below 0.05% of their GDP for this type of initiatives. 

Figure 21: Public expenditure on labour market policy (LMP) interventions: Training – 2016 

0.47

0.44

0.33

0.30

P
D
G

f
o
%

0.50

0.45

0.40

0.35

0.30

0.25

0.20

0.15

0.10

0.05

0.00

0.22

0.20

0.19 0.19 0.19

0.15

0.13

0.11

0.08 0.08 0.07 0.07 0.07

0.04

0.02 0.02 0.01 0.01 0.01 0.01 0.01 0.00

FI AT DK FR HR PT DE LU IE BE SE ES LV EE LT NL CY BG HU EL MT PL SI CZ SK RO

Source: https://webgate.ec.europa.eu/empl/redisstat/databrowser/view/LMP_EXPSUMM/default/table 

33 

 
 
 
 
 
UOE data and national statistics have their limitations including that to be understood properly they must be 
read in the context of the national education systems they represent; and they are subject to inevitable time 
lags. However, they are undoubtedly the most appropriate when it comes to monitor the policy goal of greater 
public investment in adult education. 

In  relation  to  adult  learning,  information  is also  collected  on  labour market  interventions,  including  training, 
from  administrative  sources 
labour  market  policy  database: 
‘lmp_ind_actsup’) (29) 

in  all  MS  (see  DG  EMPLOYMENT’s 

On this topic, it's worth mentioning the work coordinated by the Conference of European Statistician (CES) to 
develop a more comprehensive measure of human capital in a way that is aligned with the principles of the 
national accounts and comparable among countries. In particular, the CES and its Bureau have established a 
task  force  aimed  at  developing  a  framework  for  constructing  satellite  account  for  education  and  training 
including the breakdowns of the various expenditures on training and education, including the identification of 
the financing arrangements for these expenditures. (30) 

3.5  Other European Surveys: ECHP, EU-SILC, EWCS and ESJS. 

Other  European  Surveys  have  also  been  used  to  study  adult  learning.  While  they  might  not  be  the  most 
appropriate ones for monitoring trends, either because the concept of adult learning is not properly measured 
or there is not enough information over time on the variable we want to measure, they might be extremely 
useful  to  investigate  different  aspects  adult  participation  in  lifelong  learning.  For  example,  through 
multivariate analysis we could identify some socio-economic determinants that may encourage/prevent adult 
participation in lifelong learning. These EU Surveys include: 

The  European  Community  Household  Panel(31)  (ECHP),  which  delivers  comparable  data  on  training 
participation  for  13  EU  countries  (Belgium,  Denmark,  Ireland,  Greece,  Spain,  France,  Italy,  the  Netherlands, 
Austria,  Portugal,  Sweden  and  the  United  Kingdom.  Germany  is  excluded  due  to  short  training  spells  and 
Luxembourg due to sample size).  The total duration of the ECHP was 8 years, running from 1994 to 2001 (8 
waves). The key question on education and work-related training in the survey is: “Have you at any time since 
January  in  the  previous  year  been  in  vocational  education  or  training,  including  any  part-time  or  short-
courses?”.  While  this  question  is  informative  on  training  incidence  among  workers  (informal  on-the-job 
training is not included), it is silent on the duration of training spells as well as their source of financing. The 
duration of the last training spell is reported in classes (less than 2 weeks, 2-9 weeks, more than 9 weeks). 
Unfortunately,  the  information  on  the  duration  of  training  in  the  ECHP  is  completely  missing  for  the 
Netherlands and Sweden, and largely  missing  for the UK. The  disadvantage of the ECHP is primarily on the 
fact that additional training information (financing, duration, etc.) is of less good quality (since it is provided 
only for the last course taken and training refers to a time interval the length of which can vary from country 
to  country  and  even  from  one  interviewee  to  another).  In  a  separate  question,  the  respondent  is  asked 
whether  the  last  training  spell  was  paid  or  provided  by  the  employer.  This  information  is,  however,  not 
available for Sweden. Interestingly, results show that on average 72.0% (17.25/23.97) of the training courses 
on which we have information on the source of financing (for the last course only) is employer-sponsored (see 
Table 5). 

(29)   https://webgate.ec.europa.eu/empl/redisstat/databrowser/view/LMP_IND_ACTSUP/default/table . 
(30)   https://www.unece.org/fileadmin/DAM/stats/documents/ece/ces/bur/2017/February/06-

ToR_TF_on_Satellite_Accounts_for_Education_and_Training_final.pdf.  

(31)   https://ec.europa.eu/eurostat/web/microdata/european-community-household-panel . 

34 

 
 
 
 
                                           
Table 5. Training participation rates by source of financing in the ECHP - 1997 

Country 

Total training 

Employer-sponsored training are 

Austria 
Belgium 
Denmark 
Finland 
France 
Greece 
Ireland 
Italy 
Netherlands 
Portugal 
Spain 
UK 
Average 
Source: ECHP, taken from Bassanini, et al., (2005) 

25.33 
18.76 
53.21 
43.50 
15.56 
6.96 
13.72 
8.79 
11.75 
5.11 
19.98 
39.67 
23.97 

20.78 
15.23 
48.55 
39.20 
14.20 
6.14 
11.30 
7.31 
7.63 
4.10 
14.09 
39.40 
17.25 

The  main  advantage  of  the  ECHP  lies  in  its  large  set  of  individual  socio-economic  and  demographic 
characteristics  and  its  longitudinal  dimension,  covering  a  significant  number  of  European  countries  with  a 
commonly designed questionnaire. Furthermore, while using ECHP systematically underestimates the relative 
training effort (given the way it is measured), Bassanini et al. (2005) argue that the  ranking of countries is 
approximately the same if OECD data are used, showing that certain cross-country differences are persistent 
across surveys and reassuring about the comparability of large cross-country micro datasets.  

Since 2005 the European Union Statistics of Income and Living Conditions(32)(EU-SILC) has succeeded 
the ECHP covering a larger number of countries. The information for adult participation in learning activities 
among  workers is collected from the  question  where the  individual reports if  he/she is currently involved in 
some learning (education or training) programme defined under ISCED-11 as “a coherent set or sequence of 
educational activities or communication designed and organized to achieve pre-determined learning objectives 
or accomplish a specific set of educational tasks over a sustained period.” (UNESCO, 2012, p. 9. Again, adult 
learning  is  measured  as  whether  an  adult  participates  in  any  formal  learning  process,  over  his/her  own 
working-life cycle, leaving aside any type of non-formal or informal learning and limiting the potential use of 
this survey.  

Finally, the European Working Conditions Survey(33)  (EWCS) managed by Eurofound and the European Skills 
and Job Survey  (34) (ESJS) from Cedefop also collect information on participation on education and training.  
In the EWCS the question asks: “Have you had training paid by your employer (or self if self-employed) in the 
last  12  months?”  and  thus  only  includes  employer  sponsored  training.  This  survey  is  a  cross-sectional  one 
running since  1990 every five years. Starting with only  12 countries in  1990, it covers all EU  MS in its last 
release from 2015. Understandably, lower estimates of adult learning are obtained when using this dataset. 
However, the EWCS indicates that the percentage of EU workers receiving training paid for by their employers 
is relatively low at 38% in 2012, even though it has increased from 26% in 2005, and is mainly targeted at 
high-skilled and highly educated workers (information retrieved from European Working Conditions Survey  – 
Data 
https://www.eurofound.europa.eu/data/european-working-conditions-
survey?locale=EN&dataSource=EWCS2017NW&media=png&width=740&question=y15_Q65c&plot=euBars&c
ountryGroup=linear&subset=agecat_3&subsetValue=All).). 

visualisation 

tool: 

Similarly, the ESJS launched in 2014 across all 28 MS with a greater focus on skill mismatch over time, also 
collects information on employer sponsored training. Results indicate that training is needed for employees to 
keep up-to-date but is not supported by all employers. In fact, they found that more than 30% of European 
adult  workers  experienced  changes  (e.g.  new  technologies)  in  the  workplace  and  were  not  supported  by 
training activities paid for by the employer (European Union, 2018). 

(32)   https://ec.europa.eu/eurostat/web/microdata/european-union-statistics-on-income-and-living-conditions . 
(33)   https://www.eurofound.europa.eu/surveys/european-working-conditions-surveys. 
(34)   https://www.cedefop.europa.eu/en/events-and-projects/projects/european-skills-and-jobs-esj-survey. 

35 

 
 
 
                                           
Interestingly, 2010 EWCS allowed collection of self-reported information on the quality/appropriateness of the 
training  when  individuals  were  asked  to  answer to  the  following  statement:  “I  feel  my  prospects  for  future 
employment are better because of my training.” This information could be useful, for example, for monitoring 
quality of adult learning, an ideal policy goal. Results in Figure 22 show that Belgium was the country with the 
lowest share of respondent (workers) who think their prospects for future employment are better due to their 
training (54%), while Malta had the highest share with 87% of the respondents. 

Figure 22: Percentage of respondents who agree to the statement: “I feel my prospects for future employment are better 
because of my training” 

100

90

80

70

60

50

40

30

20

10

0

BE NL FR HU LU CZ DE SI AT LT EU PL DK SE IT UK FI HR RO SK EE IE PT LV CY ES BG EL MT

Source: EWCS, 2010. 

Despite the limitations of these surveys in relation to the definition of adult learning, their country coverage 
and their time span, the additional information they provide in relation to socio-economic and demographic 
characteristics  of  their  respondents  make  them  certainly  a  rich  and  useful  source  of  information  to  better 
understand the incidence and determinants of adult learning in its various forms.  

3.6  Considerations for Policy and Practice 

This section has reviewed, as comprehensively as possible, alternative available datasets (beyond the EU-LFS 
needed  for  producing  the  existing  ET2020  benchmark  on  adult  participation  in  lifelong  learning)  that  could 
potentially be used to learn more and to properly monitor adult learning as it evolves nowadays.  

Different  surveys  are  presently  used  to  study  the  importance  of  adult  learning  (i.e.  Eurostat’s  AES,  CVTS,  , 
ECHP, and EU-SILC; OECD’s PIAAC; Eurofound’s EWCS and Cedefop’s ESJS). All these surveys evaluate human 
capital accumulation from different point of views (e.g. through vocational or general training); and consider 
different definitions and concepts of adult education (e.g. formal, non-formal or informal learning). They also 
cover different populations, a different range of countries and have been in place during various periods apart 
from  their  cross-sectional  or  longitudinal  features.  These  are  some  of  the  reasons  why  it  is  often  rather 
difficult  to  compare  their  empirical  results.  Likewise,  the  System  of  National  Accounts  (SNA)  and  other 
international  statistics  such  as  UOE  data  have  proven  very  useful  for  cross-country  comparisons,  however, 
more  detailed  breakdown  by  different  socio-economic  characteristics  may  be  needed  for  a  thorough 
understanding.   

Having  said  this,  a  few  more  considerations  about  the  usefulness  of  some  of  these  surveys  are  presented 
here to suggest how a successful, more inclusive adult learning policy (and monitoring) can be achieved: 

—  Adults  engage  with  different  types  of  learning,  some  of  which  is  non-formal  or  informal  and  some  of 
which is formal (and leads to a qualification). (35) A broad learning offer needs to be available to adults 
and  should  be  delivered  flexibly,  including  at  the  workplace  as  well  as  remotely  (for  example  through 
online learning), as well as through formal education institutions. The AES is a better option than the EU-
LFS to monitor non-formal and especially informal learning. 

(35)   Non-formal education can also lead to formal qualifications (including through recognition and validation of prior learning; this is 

already included in some countries in UOE data). 

36 

 
 
 
                                           
—  The  AES  could  be  used  to  gather  information  on  the  disengaged,  i.e.  adults  who  are  not  interested  in 

furthering their learning.  

—  Identifying  and  potentially  removing  the  obstacles  to  participation  is  also  important  to  engage  adults.  
The  AES  can  help  us identify  them  and  making  the  case  of  the  value  and  relevance  of  learning  to  the 
potential learners.  

—  Overall, outreach and interventions should seek to target adults in low skill occupations, adults who are 
furthest  from  core  labour  markets (remote  areas  where  labour  market  opportunities  are  limited),  older 
adults, and those with lower level of education.  

—  Adults look for information about learning from a wide range of sources. In order to engage adults who 
are  less  likely  to  learn,  relevant  information  should  be  made  available  in  public  places  and  through 
individuals and services that people come in contact with.. 

—  Employers  are  likely  to  be  more  precise  about  enterprises/firms’  choices  and  characteristics  of  training 
than  employees.  For  this  reason,  CVTS  can  provide  rich  and  useful  information  regarding  main  skills 
targeted by CVT courses, intensity (hours) and cost. The benefits obtained from the training can also be 
analysed.  However,  we  must  be  aware  that  the  survey  provides  a  large  set  of  characteristics  for  the 
enterprises, but only sex, training participation and total training hours in CVT courses for the employed 
people. 

—  Further, the need for individuals to remain employed at older ages has been widely recognized, as well as 
the importance of lifelong learning to uphold a skilled workforce to ensure a competitive labour force and 
economic  growth.  PIAAC  data  permit  more  in-depth  analyses  of  the  general  and  workplace  skills  of 
individuals,  particularly  those  among  the  lower  income  groups  and  the  unemployed,  who  are  likely  the 
most in need of skill upgrades and most at risk for economic insecurity. 

37 

 
4  Summary and Conclusions 

This  report  aimed  at  shedding  some  light  on  the  current  state  of  the  evidence  about  the  existing  ET  2020 
indicator on adult participation in lifelong learning, and its effectiveness in monitoring adult learning as it is 
evolving  in  the  21st  century.  Arguably,  the  present  ET  2020  indicator  may  work  as  a  headline  figure  for 
summary overviews and country ranking, nevertheless an efficient monitoring of adult learning requires more 
detailed breakdowns.  

In particular, it  has been argued that  monitoring of adult learning should go beyond  mere measurement of 
participation of adults in lifelong learning programmes and include indicators of other policy goals such as: (1) 
Enhancing  public/private  investment  in  adult  learning;  (2)  Facilitating  access;  (3)  Effectively  increasing 
knowledge and skills; (4) Improving quality of adult training; or (5) Reducing inequalities. To comprehensively 
cover  these  objectives  a  richer  set  of  indicators  (as  opposed  to  mere  sub-indicators)  may  be  a  better 
approach.  

This  technical  report  did  not  attempt  to  comprehensively  provide  the  set  of  indicators  for  efficient  adult 
learning  monitoring,  but  to  reflect  on  the  existing  information  and  how  to  move  forward.  Thus,  an 
identification and review of comparable data sources across member states has been undertaken and their 
appropriateness to monitor the defined policy goals has been discussed.  The LFS is a good tool to measure 
participation in adult learning for a number of reasons: it is a regular, established survey, with high degree of 
participation and collects the relevant information in a simple and parsimonious way.  

In addition, from 2022, the LFS will include information on participation during the 12 months preceding the 
interview. A time span of 12 months is more inclusive and tends to provide higher level of participation; this is 
due  to  the  fact  that  participation  in  adult  learning  is  a  rather  rare  occurrence  –  the  absolute  majority  of 
individuals declare only one or two learning activities per year. Also, unlike formal learning which is often of a 
relatively  long  duration  (6  months  or  more),  non-formal  learning  is  often  of  a  short  duration,  sometimes 
taking place for only a couple of hours. Therefore, for a more representative coverage of non-formal learning, 
a longer reference period than 4 weeks is preferred. Overall, if there is an interest to monitor general access 
to education and training, the 12-month reference period is a better option.  

A  specific  focus  should  also  be  put  towards  monitoring  the  participation  of  disadvantaged  groups,  such  as 
low-qualified or unemployed adults, given that an overall increase in participation does not automatically lead 
to  an  increase  for  all  population  groups.  In  practice  it  may  even  happen,  that  participation  among 
disadvantaged groups decline at the same time when the participation rate of the total populations increases.  

This  notwithstanding,  the  main  aim  of  the  LFS  is  to  collect  information  on  employment,  and  cannot  be 
burdened with a large number of questions related to adult learning in the same way that the AES could be. 
For this reason, and to collect more in depth information, such as the type and form of adult learning, who is 
in charge of financing, and so on, other sources can be used as a complement. For instance, the AES provides 
essential information on informal learning, which is not captured by the LFS. The OECD Survey of Adult Skills 
(PIAAC)  is the  appropriate  tool  for  monitoring  skills acquisition  beyond formal  education;  the  CVTS  provides 
information  on  employers’  sponsored  type  of  training  (i.e.  demand  side  of  adult  learning  programs);  finally, 
National Statistics for precise monitoring of adult learning public investment.  

Having  said  this,  the  empirical  evidence  provided  shows  that  with  the  enumerated  datasets there  is no  full 
coverage  of  the  policy  goals  identified.  While  the  goals  of  monitoring  “skills  acquisition”  and  “reducing 
inequalities”  can  be  reasonably  covered  using  AES  and  PIAAC  data,  information  on  “investment  in  adult 
learning” is more heterogeneous relying on surveys for employer’s sponsored activities and National Statistics 
(with  some  lags  in  availability  and  missing  data)  for  public  investment.  Moreover,  significant  efforts  are 
needed to collect information on the “quality of training” and “facilitating access”. 

The list of indicators may be long and the AES is produced every five years up to 2016 and every six years 
from  2016  onwards.  These  are  two  important  problems.  Strategic  decisions  may  be  needed  from  the 
statistical offices regarding future development of surveys. While yearly information may not be needed for 
each indicator (associated to a policy goal) a five-year or six-year period may be too long for indicators calling 
for action. The forthcoming introduction of three biennial indicators on  participation in adult learning  during 
the past 12 months in the EU-LFS is a good step forward towards the monitoring of those policy goals that 
may require more frequent attention. 

38 

 
 
 
 
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40 

 
 
Annex – A Benchmarking Framework 

Benchmarking  is  intended  to  strengthen  the  European  Semester  by  supporting  mutual  learning  and 
promoting upward socio-economic convergence, with a primary focus on specific policy parameters that 
can  lead  to  better  outcomes.  The  process  should  also  contribute  to  the  sharing  of  best  practices 
implemented in Member States, while taking into account the insights and experience accumulated within 
the European Semester since 2011. Benchmarking can be used to underpin the analysis in the European 
Semester  by  bringing  better  insights  to  country-specific  analysis  and  more  comparability  to  country 
performance  and  progress  over  time,  thereby  also  supporting  the  formulation  of  Country-Specific 
Recommendations.  

Indicator-based  monitoring  frameworks  have  already  been  developed.  Examples  are  the  Europe  2020 
headline targets, the ET2020 benchmark indicators and the Employment Performance Monitor (see Box 
1). Work on benchmarking should be consistent with these and other existing frameworks. 

Box 1: Existing monitoring frameworks in the field of education and training 

The Commission's Education and Training Monitor monitors several dimensions which have been agreed in the context of 
the Education and Training 2020 (ET 2020) cooperation framework.  
Two of the  ET2020 benchmarks  have also been recognized as Europe 2020 headline targets in the field of education: 
early  leavers  from  education  and  training  (the  share  of  early  leavers  from  education  and  training  should  be  less 
than  10%)  and  tertiary  education  attainment  (the  share  of  30  to  34  year-olds  with  tertiary  education  attainment 
should be at least 40%). 

The four other ET2020 benchmark indicators that are monitored are early childhood education and care (at least 95% 
of  children  between  the  age  of  four  and  the  age  for  starting  ISCED  1  should  participate  in  education); 
underachievement  in  reading,  mathematics  and  science  (the  share  of  15-year-olds  with  underachievement  in 
reading, mathematics and science should be less than 15%); employment rates of recent graduates (82% of recent 
graduates  from  upper  secondary  to  tertiary  education  (age  group  20-34)  who  are  no  longer  in  education  or  training 
should be in employment); participation in adult learning (an average of at least 15% of adults (age group 25-64) 
should  participate  in  formal  or  non-formal  learning).  The  Commission  has  identified,  in  collaboration  with  Eurydice36, 
several structural policy lever indicators in most of these areas (except for adult learning, which is covered in more detail 
in the Joint Assessment Framework (JAF)). The ET2020 indicators and benchmarks are reviewed in the annual Education 
and Training Monitor; this analysis is supported by the structural indicators provided by Eurydice. 

Adult  skills,  employment  and  training  policies  are  also  a  part  of  the  ten  employment  areas  of  the  Joint  Assessment 
Framework  (JAF),  an  analytical  tool  which  was  adopted  at  the  request  of  the  Belgian  Presidency  in  July  2010,  and 
mandated by the EPSCO Council, EMCO and SPC. The ten employment policy areas (PA) monitored under the JAF are: (1) 
labour  market  participation;  (2)  labour  market  functioning,  combating  segmentation;  (3)  ALMPs;  (4)  adequate  and 
employment  oriented  social  security  systems;  (5)  work-life  balance;  (6)  job  creation;  (7)  gender  equality;  (8)  improving 
skills supply and productivity, adult learning; (9) improving education and training systems; (10) wage setting mechanism 
and labour cost development.  

The Employment Policy Monitor (EPM), a joint Commission-EMCO report that is adopted twice a year by the Council, 
provides an overview of Member States' performance with respect to selected JAF indicators, and identifies  "particularly 
good labour market outcomes" and “key employment challenges". Similarly, the Social Protection Performance Monitor 
(SPPM)  identifies  "Member  States  with  significant  improvements"  as  well  as  “Social  trends  to  watch”.  The  Social 
Scoreboard, put forward by the Commission in 2017 to monitor progress with the implementation of the European Pillar 
of Social Rights, comprises several indicators in the area of education, skills and adult learning: early school leaving, adult 
learning,  underachievement  in  education,  tertiary  attainment,  digital  skills,  as  well  as  an  indicator  for  the  impact  of 
parental background on education performance. 37 

(36)   Eurydice is an information network on education established by the Commission and Member States in 1980 to offer policy-makers 

and all those involved in the provision of education in Europe with information and analyses in this area. 

(37)  The  Social  Scoreboard  replaced  the  Scoreboard  of  Key  Employment  and  Social  Indicators  (KESI).  The  latter  identified  different 
categories of performance (very low, low, average, high and very high) based on the levels and trends by Member State of six major 
indicators (unemployment  rate,  youth  unemployment  rate  and  NEETs  rate,  gross  household  disposable  income, at-risk  of  poverty 
and inequality rate). 

41 

 
                                           
However, there is still a gap that needs to be filled. In particular, headline targets and outcome indicators 
are  difficult  to  translate  into  policy  action,  since  they  are  very  general  and  can  result  from  different 
factors, only some under the remit of employment policies. Also,  the ET2020 benchmarks  or the Joint 
Assessment Framework (JAF) and the Employment Policy Monitor (EPM) lead to the identification of Key 
Employment Challenges (KECs) and good outcomes which are not immediately transferable  into policy 
action.  

The  benchmarking  framework  would  contribute  to  filling  this  gap,  based  on  the  three-step  approach 
endorsed by EMCO and SPC in June 2017 (Figure 23).  

Figure 23: A three step approach 

In a first step, based on broad key challenges in the field of adult skills and learning a set of high-level 
outcome indicators is identified. These high-level outcome indicators include indicators which have been 
identified  in  the  Commission's  growth  and  jobs  agenda  and  show  a  positive  relationship  with  the 
performance of education systems, although they can also be influenced by many other (economic and 
institutional) variables.  

In a second step, a set of performance indicators are identified. These performance indicators allow for 
cross-country  comparisons  of  performance  in  the  area  of  adult  skills  and  learning  based  on  the 
scoreboard  methodology  previously  agreed  with  EMCO.  This  methodology  accounts  for  significant 
deviations from the EU average, taking into account levels as well as changes in performance indicators.  

For  the  third  step,  a  thematic  approach  is  followed  to  identify  key  policy  levers  that  are  effective  in 
improving performance of adult skills and learning systems. The analysis is focused on the area of adult 
learning given its strong link with labour market outcomes and its relevance for the implementation of 
the Social Pillar.  

42 

 
 
 
 
 
 
Benchmarking framework indicators on adult skills and learning: 

-  Employment rates by education level (age group 20-64)  
-  Macroeconomic skills mismatch (age group 20-64) 
-  Labour  productivity:  GDP  at  2010  reference  levels  per  person  employed  (in 

euros, at 2010 exchange rates), as compared to the EU average 

Main performance indicators on skills policies (from benchmarking): 

-  Supply  of  medium  and  high  skills:  the  share  of  adults  with  at  least  upper 

secondary education attainment (age group 25-64)  

-  Adult learning: participation of adults in learning (age group 25-64)  
-  Digital  skills:  the  share  of  the  population  with  basic  or  above  basic  overall 

digital skills (age group 16-74)  

-  Demand  for  medium  and  high  skills:  the  share  of  occupations  requiring  at 
least  upper  secondary  education  attainment  (share  of  employment  in 
occupations classified under ISCO categories 1-8) (age group 15-64). 

Secondary (outcome) indicators: 

-  Labour  shortages:  the  share  of  employers  in  manufacturing  reporting  that 

labour shortages are a major factor limiting their production (EU-BCS) 

-  On-the-job skills mismatch: over-qualification rate (the share of people aged 
20-64  with  tertiary  education  working  in  ISCO  4-9  sectors  not  requiring 
tertiary education).  

Policy lever indicators: 

-  Access to guidance: The share of adult population, aged 25-64, who have 

received free of charge information or advice/help on learning opportunities 
from institutions/organisations during the last 12 months (AES) 

-  Participation of unemployed in adult learning: the share of unemployed adults 
25-64 who participated in learning activity during the last four weeks, as part 
of all unemployed adults (LFS) 

-  Participation of low-qualified in adult learning: the share of low-qualified 

adults 25-64 who participated in learning activity during the last four weeks, 
as part of all low-qualified adults (LFS) 

-  Financial  incentives  for  companies  to  provide  training:  the  share  of 
companies  that  report  to  have  received  any  type  of  public  co-financing  for 
training activities in the reference year (CVTS) 

43 

 
 
 
 
 
 
List of figures 

Figure 1: Conceptual framework for the analysis of effectiveness of adult learning policies ................... 8 

Figure 2: Participation rate in adult education and training (last 4 weeks) ......................................10 

Figure 3: Participation in any type of education and training as collected in the general LFS and the ad hoc 
module of  the LFS (2003) ............................................................................................14 

Figure 4a.Adult participation in formal learning: ET2020 benchmark (4-weeks) and EU-LFS ad hoc module 
indicators  (12 months) ...............................................................................................15 

Figure 4b. Adult participation in non-formal learning: ET2020 benchmark (4 weeks) and EU-LFS ad hoc 
module indicators (12 months) .......................................................................................15 

Figure 5: Adult participation in informal learning: EU-LFS ad hoc module indicator (2003) ....................16 

Figure 6: Percentage of adults aged 25 to 34 and 55 to 64 who participated in adult education in the 4 
weeks preceding the survey – LFS 2018. ............................................................................17 

Figure 7: Percentage of adults aged 25 to 64 who participated in adult education in the 4 weeks preceding 
the survey by low and high level of education – LFS 2018. ........................................................18 

Figure 8: Percentage of adults aged 25 to 64 who participated in adult education in the 4 weeks preceding 
the survey by type of occupation – LFS 2018. ......................................................................20 

Figure 10: Participation in formal and non-formal learning: The AES and the LFS compared – 2016 ........24 

Figure 11: Participation in job-related non-formal adult learning over 12 months, by type of sponsor: AES 
2016 ....................................................................................................................25 

Figure 12: Mean instruction hours in formal and non-formal learning by age group. ..........................25 

Figure 13: Participation in adult learning by low and high skills occupations ...................................26 

Figure 14: Participation in adult learning by place of residence ..................................................26 

Figure 15: Result of the search for information on learning possibilities ........................................27 

Figure 16: Obstacles to participation EU-28 .......................................................................28 

Figure 17: Share of participants in adult learning by size of the enterprise (2015 CVTS) ......................30 

Figure 18: Share of participants in adult learning: 2016 AES and 2015 CVTS ..................................30 

Figure 19: Participation in adult learning and literacy and numeracy scores (PIAAC) ...........................32 

Figure 20: Percentage of adults aged 16-65 (youth 16-24 in initial cycle of formal studies excluded) who 
participated in adult education in the 12 months preceding the survey, by high low levels of literacy 
proficiency) - PIAAC ...................................................................................................32 

Figure 21: Public expenditure on labour market policy (LMP) interventions: Training – 2016 ..................33 

Figure 22: Percentage of respondents who agree to the statement: “I feel my prospects for future 
employment are better because of my training” ....................................................................36 

44 

 
 
List of tables 

Table 1: Targets in education and training (ET 2020 Indicators) .................................................. 5 

Table 2: Questions related to adult participation in lifelong learning as posed in the EU-LFS (4-weeks 
reference period) ......................................................................................................11 

Table 3: The variables related to participation in education and training of the 2003 ad-hoc module on 
lifelong learning of the EU-LFS .......................................................................................14 

Table 3: Questions related to adult participation in lifelong learning as posed in the AES. (12-month reference 
period) ..................................................................................................................23 

Table 5. Training participation rates by source of financing in the ECHP - 1997 ................................35 

45 

 
 
 
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doi:10.2760/160673 

ISBN 978-92-76-10222-9