Education and training monitor 2013.
Date: 2013-11-27
Institutions: Directorate-General for Education, Youth, Sport and Culture
Subjects: early childhood, education policy, education statistics, learning, schooling, updating of skills, vocational training

Education and Training Monitor 2013 

ec.europa.eu/education/monitor 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
This  publication  is  based  on  document  SWD(2013)434.  The  2013  Education  and  Training  Monitor 
was prepared by the unit ‘Statistics, studies and surveys' with the help of thematic units within the 
Directorate-General of Education and Culture (DG EAC).  DG EAC was assisted by the Eurydice unit 
from  the  Education  and  Culture  Executive  Agency  (EACEA),  the  JRC’s  Centre  for  Research  on 
Lifelong  Learning  (CRELL)  and  Eurostat.  The  members  of  the  Standing  Group  on  Indicators  and 
Benchmarks (SGIB) were consulted during the drafting phase. 

2 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Foreword 

Education  and  training  are  a  source  of  future  growth  and  employment  and  are  becoming  key 
success  factors  for  the  Europe  2020  Strategy.  In  times  of  budget  constraints  it  comes  as  no 
surprise  that  the  spotlight  is  on  spending.  Yet  it  is precisely  in  such  times  that  growth-enhancing 
policies, such as education, should be a top priority: spending on education is an investment, not a 
cost.  As  many  EU  Member  States  are  forced  to  cut  back,  the  need  to  scrutinise  the  effectiveness 
and  efficiency  of  our  education  and  training  systems  becomes  all  the  more  relevant  as  we 
endeavour to do more with less.  

The wealth of data provided by this Education and Training Monitor supports Member States in this 
effort. It enables countries to compare investments in education and training systems against their 
outcomes  and  identifies  ways  of  maximising  efficiency.  It  particularly  enables  countries  to  assess 
their  performance  compared  to  other  countries,  regarding  the  specific  recommendations  they 
received during the last European Semester. 

The  EU  level  benchmarks  set  for  2020  provide  standards  for  comparison,  encouraging  the 
exchange  of  information  and  stimulating  peer  learning.  Cross-country  policy  research  serves  to 
demonstrate how each Member State performs on the basis of the ET 2020 benchmarks and, more 
importantly,  strives  to  bring  to  light  the  most  successful  policy  measures  within  education  and 
training across Europe. 

This  year's  Monitor is  published  on  the  eve  of  the  launch  of  a  new  7-year  programme  supporting 
Europe’s  cooperation  in  education,  training,  youth  and  sports.  Erasmus+  demonstrates  the  EU’s 
commitment  to  education.  Compared  to  its  predecessor,  the  budget  of  the  new  programme  will 
increase by approximately 40%, to more than €14 billion over the 2014-2020 period. 

This publication also comes at the point when Member States  and the Commission are discussing 
the European Structural and Investment Funds 2014-2020. The Commission’s task will be to make 
sure that these funds have real impact on education and training systems in Europe. This will only 
happen if countries design a strategy for education with clear, concrete and measureable targets; 
milestones for each education level and age-group; and time-frames for implementation, with tools 
for monitoring progress. 

I  believe  that  the  Education  and  Training  Monitor  2013  is  a  tool  that  will  prove  invaluable  in 
facilitating  decision-makers  across  Europe  to  reform  their  education  systems,  guaranteeing  high-
quality and equitable education and training for all our citizens.  

Androulla Vassiliou 
European Commissioner for Education, Culture, Multilingualism and Youth 

3 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Contents 

1. 

2. 

Key findings 

Volume I 

Introduction 

Investing in skills and qualifications 

2.1. 

Investing in education and training in a context of economic crisis 

2.2.  Opening up education and training through new technologies 

2.3.  Tools for transparency of skills and qualifications 

3. 

Tackling early school leaving and raising the bar in school education 

3.1.  Reducing the share of early leavers from education and training 

3.2. 

Improving early childhood education and care 

3.3.  Strengthening the teaching profession 

3.4.  Laying the foundations for skills development 

4. 

Emphasising effectiveness and quality in the modernisation of higher 
education 

4.1. 

Increasing tertiary education attainment 

4.2.  Meeting the challenge of effective resource allocation in higher education 

4.3.  Promoting learning mobility in higher education 

5. 

Facilitating the transition from education to work through vocational 
education and training 

5.1.  Reshaping vocational education and training  

5.2.  Enhancing the employability of young people  

5.3.  Fostering entrepreneurship education 

6. 

Upgrading skills through lifelong learning 

6.1.  Taking a closer look at the Survey of Adult Skills 

6.2.  Raising adult participation in lifelong learning 

Annex 

Volume II 

Country reports 
ec.europa.eu/education/monitor 

4 

5 

9 

13 

13 

17 

21 

25 

25 

31 

33 

34 

39 

39 

43 

47 

52 

52 

55 

58 

62 

62 

66 

71 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Key findings 

The European Union's Strategy to boost growth and jobs – Europe 2020 – aims to tackle the crisis 
and  build  a  stronger,  more  competitive  Europe.  To  meet  these  objectives,  people  have  to  be 
equipped with the skills and qualifications they need on today's labour market, and even more so 
on  tomorrow's  global  knowledge-based  economy.  Skills  and  qualifications  are  one  of  the  key 
factors determining Europe's economic success.  

However,  the  difficult  economic  context  casts  its  shadow  on  the  financing  of  education  and 
training.  The  Commission  has  called  on  Member  States  repeatedly  to  give  priority  to  growth-
friendly  expenditure.  In  July  2013,  17  Member  States  were  given  a  country-specific 
recommendation,  urging  them  to  pursue  growth-friendly  fiscal  policies.  In  practice,  however, 
spending  on  education  and  training,  a  growth-enhancing  mechanism  by  design,  is  decreasing  or 
stagnating. This is particularly worrying as it puts at risk Europe's return to smart, sustainable and 
inclusive  growth.  After  all,  world-class  education  and  training  requires  investing  substantial 
resources. 

Education  outcomes  can  be  measured  in  terms  of  skills  or  qualifications.  The  Europe  2020 
Strategy focusses on qualifications by setting out a twofold headline target on early school leaving 
and tertiary education attainment, to be reached by 2020. First, the share of early school leavers 
is  to  be  decreased  to  below  10%.  In  2012,  Europe  stood  at  12.7%,  down  from  13.4%  the 
previous  year.  The  target  seems  to  be  within  reach,  but  about  5  and  half  million  citizens  is  still 
leaving school prematurely, which makes it hard for them to find employment. Second, the EU is 
making  good  progress  towards  the  target  to  increase  tertiary  attainment  to  40%.  The  EU  now 
stands at 35.7%, up from 34.5% the year before. However, it will be a challenge to combine the 
increase in numbers with a solid quality of higher education.  

Another way to measure education outcomes is by looking at skills. New findings from the OECD’s 
Survey of Adult Skills (PIAAC)  expose  a  weakness: the skills of  Europe's working-age population 
are  not  in  line  with  the  needs  and  requirements  of  the  labour  market.  Today  Europe  is  facing  a 
serious skills gap that risks hampering growth and employment in the future; and the least skilled 
workers, who are in the most urgent need of up-skilling to be employable, tend not to take part in 
training.  To  close  this  skills  gap  and  bring  adult  skills  in  line  with  the  general  expectations  and 
needs of our modern economy will require substantial investment over many years. 

To secure the necessary investments for skills and qualifications is not easy. In part, the solution 
will be to scrutinise spending in light of the various education outcomes. Another approach will be 
to  introduce  efficiency  measures  that  have  to  potential  to  transform  investments  into  stronger 
outcomes. Efficiency measures can help to meet the twin challenge of pursuing fiscal consolidation 
and investing in growth-enhancing policies. 

As  an  example  of  such  efficiency  measures,  Europe  would  benefit  from  overcoming  remaining 
barriers that are due to the myriad of existing diplomas, certificates and qualifications. Despite the 
existence of a large number of policies and instruments, there still remain obstacles for individuals 
to move between countries, across different education sub-systems, and from education to work. 
Europe  needs  better  transparency  and  recognition  of  skills  and  qualifications.  Efforts  towards  a 
European Area for Skills and Qualifications will enhance the effective recognition of competences 
and qualifications and support the free movement of learners and workers. 

Another  example  of  efficiency  measures  will  be  to  link  the  worlds  of  work  and  education  more 
closely,  in  order  to  curb  and  even  prevent  youth  unemployment,  which  is  one  of  Europe's  most 
pressing problems. To ensure that education and training systems provide high-quality and labour 
market relevant  skills, they have to be adjusted to respond better  to economic developments; if 
possible,  they  have  to  detect  or  anticipate  emerging  trends  in  order  to  secure  in  time  a  stable 
supply  of  relevant  skills.  This  will  help  to  avoid  shortages  of  qualified  labour  and  skills 
mismatches. 

5 

 
 
 
 
 
 
 
 
 
 
 
 
The  policy  messages set  out in  the analysis above  are supported by  10  key  findings that emerge 
from the second annual Education and Training Monitor.  

The consolidation of public finance and youth unemployment challenge European 
education and training systems … 

1. 

Sixteen  Member  States  decreased  their  education  expenditure  at  some 

stage between 2008 and 2011,  with six  of  them showing further significant  budget 
decreases in 2012 (EL, IT, CY, LV, PT,  UK-WLS). Cutbacks in spending per student across 
Europe  started  to  be  most  prevalent  in  tertiary  education  (12  Member  States)  between 
2008  and  2010.  Whereas  the  majority  of  Member  States  decreased  spending  per  student 
for at least one level of education, BG, ES, HR, IT, LV and RO cut down on all levels from 
primary to tertiary in this period. 

2. 

3. 

The  employment  rate  of  recent  graduates  with  at  least  upper  secondary 

education  stands  at  75.7%,  down  from  82.0%  in  2008.  An  advantage  of 
tertiary  education  attainment  over  upper  secondary  education  attainment  is  still  visible  in 
all Member States. However, across the EU, 21% of people with tertiary qualifications are 
active  in  jobs  that  usually  require  lower  qualifications.  This  suggests  that,  in  spite  of  the 
high levels of unemployment, there is also evidence of skills mismatches. 

The  transition  from  education  to  work  can  be  facilitated  through  quality 

traineeships,  apprenticeships  and  dual  learning  models.  Students  from 
vocational  education  and  training  programmes  have  a  better  transition  from  education  to 
work  in  Member  States  with  developed  work-based  learning  (e.g.  DK,  DE,  NL  and  AT). 
Many  Member  States  are  working  on  reforms  that  build  on  the  experiences  of  these 
countries.  

… while analysis of the twofold Europe 2020 headline target underlines the need 
to link the worlds of work and education more closely, … 

4. 

Early  school  leavers  are  struggling  to  move  between  the  worlds  of  work 

and education. The rate of early leavers from education and training stands at 12.7%. 
However, between 2009 and 2012, IT, DE, FR and CY have been making little progress and 
HU,  RO  and  BE  have  even  shown  an  increase  in  their  early  school  leaving  rates.  The 
biggest  challenge  lies  in  the  transition  from  school  to  work,  with  the  unemployment  rate 
amongst early school leavers at 40.1%, and from work back to learning, with only 0.8% of 
18 to 24 year-olds in non-formal learning after having left formal education. 

5. 

A global race for talent changes the landscape of higher education. With the 
tertiary  attainment  rate  now  at  35.7%,  the  policy  focus  is  shifting  towards  improving 
completion rates (still below 70% in many Member States), further enhancing quality and 
relevance  and  promoting  the  international  mobility  of  students.  International  mobility  in 
higher  education  increases  the  probability  of  mobility  after  graduation  and  can  help  in 
tackling skills mismatches and bottlenecks across the European labour market. 

6 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
… the current skills diagnosis reveals serious underperformance in the basic and 
transversal skills that are crucial on the European labour market, … 

6. 

20% of 16 to 65 year-olds is unable to exceed a basic level of literacy and 

24%  is  unable  to  do  so  in  numeracy.  The  results  from  the  Survey  of  Adult  Skills 
underline  the  need  for  lifelong  learning.  However,  skills  levels  and  participation  in  adult 
learning are strongly connected in many countries, confirming that lifelong learning is still 
not  profited  from  by  those  who  would  benefit  from  it  most.  Adult  participation  in  lifelong 
learning  stands  at  only  9.0%  and  is  most  prevalent  amongst  the  young  and  highly 
educated. 

7. 

Only  half  of  the  EU  population  aged  15  years  and  above  agree  that  their 

school  education  helped  them  to  develop  entrepreneurial  competences. 
Virtually all countries that show an above-average performance in entrepreneurial attitude 
also  have  above-average  percentage  participation,  at  school  or  university,  in  courses  or 
activities concerning entrepreneurship.  Efforts to develop entrepreneurial skills are needed 
to  support  new  business  creation,  employee  innovation  within  existing  companies  and  to 
improve employability levels of the young. Entrepreneurship education is a tool to drive up 
the economic benefits of education. 

…  and  important  cross-sectorial  issues  still  impede  progress  of  Europe’s 
education and training systems. 

8. 

9. 

Inequalities  persist  in  European  education  and  training  systems.  Evidence 
suggests that many education and training systems in Europe are marked by inequalities, 
reflected  by  strong  disadvantages  in  the  skills  and  qualifications  of  social  groups  such  as 
young  people  with  a  migrant  background.  There  is  also  wide  variation  between  different 
Member States in their success at addressing the problem. These inequalities have severe 
consequences for individuals, for economic progress and for social cohesion. 

Rethinking  how  we  attract,  educate  and  support  teachers,  school  leaders 

and  teacher  educators  is  a  pressing  issue,  with  the  teaching  profession  across 
Europe strongly affected by demographic trends. In many Member States, the majority of 
teachers currently in employment are in the highest age brackets. In IT, DE, EE and NL, for 
example, more than 45% of the teaching workforce is in the 50+ category and in IT, BG, 
DE and ES there are very few teachers under the age of 30.  

10.  Europe  is  lagging  behind  in  the  development  of  Open  Educational 
Resources (OER) and Massive Open Online Courses (MOOCs). Although digital 
technologies are fully embedded in the way people interact, work and trade, they are not 
being fully exploited in European education and training systems. While 70% of teachers in 
the  EU  recognise  the  importance  of  training  in  ICT-supported  pedagogies,  only  20%  of 
students are taught by digitally confident and supportive teachers. 

7 

 
 
 
 
 
 
 
 
 
 
 
 
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T

 
 
 
 
 
 
 
   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
   
1.  Introduction 

The challenge of doing more with less 

The on-going crisis challenges European education and training systems from two different angles. 
Firstly,  Member  States  have  to  consolidate  public  finance  while  investing  in  growth-enhancing 
policies1. Secondly, the EU is faced with a youth unemployment rate of 23.2%, representing a huge 
untapped resource and a social crisis that Europe cannot allow to persist2. Education and training, 
with  its  impact  on  productivity  and  innovation,  is  a  growth-enhancing  mechanism  by  design  and 
contributes to the employability of young and old. Yet more than half of the Member States have 
decreased their investments in education and training. 

These two key challenges require Europe to strengthen the outcomes of its various education and 
training systems and to adapt them more flexibly to the changing needs of the labour market. In 
other  words,  European  education  and  training  systems  will  have  to  become  more  relevant  and 
adaptable, while at the same time fighting for sustained investments as the crisis continues. This is 
the main argument for modernising our education and training systems3 and for Member States to 
debate efficiency measures in order to enhance returns to education investments. The 2013 Annual 
Growth  Survey  recalled  the  efficiency  of  education  expenditure  and  pointed  towards  policy  levers 
that, amongst others, link the worlds of work and education more closely4.  

While  the  primary  responsibility  for  the  reform  process  lies  at  national  level,  the  EU  offers 
significant  support.  Starting  in  2014,  a  new  generation  of  programmes  will  be  in  place  to  offer 
financial support to Member States. Erasmus+, the new single programme for EU cooperation and 
mobility  in  education,  training,  youth  and  sports  for  2014-2020,  demonstrates  the  EU’s 
commitment  to  education  even  in  times  of  severe  fiscal  constraint:  the  budget  for  the  new 
programme  will  increase  by  approximately  40%,  to  more  than  14  billion  for  the  seven  years. 
Furthermore, the next generation of European Structural and Investment Funds will assist Member 
States in addressing shortcomings in the field of education and training and to give precedence to 
the priority areas that have been pin-pointed in the country-specific recommendations5. 

These  country-specific  recommendations,  proposed  by  the  Commission  and  adopted  by  the 
Council,  are  based  on  an  assessment  of  each  Member  State's  key  challenges  and  aim  at  offering 
tailor-made  guidance.  Many  of  these  recommendations  call  on  Member  States  to  combat  early 
school  leaving,  increase  tertiary  attainment,  improve  their  school  or  vocational  education  and 
training  system  by  making  their  outcomes  more  relevant  for  the  labour  market,  and  secure  the 
necessary funding for investments in education. The recommendations are the key EU-level policy 
tool  for  driving  reforms  at  the  national  level.  Reporting  on  the  implementation  of  the  country-
specific  recommendations  by  the  Member  States  is  carried  out  in  the  context  of  the  European 
Semester6. The annual Education and Training Monitor, in turn, contributes to the analytical basis. 

Strengthening the evidence-base 

The  strategic  framework  for  European  cooperation  in  education  and  training  (ET  2020)  was  re-
vamped  in  2012  to  bring  it  in  line  with  the  EU  Strategy  for  growth  and  jobs,  and  to  support 
Member  States  in  their  reform  efforts7.  One  objective  has  been  to  strengthen  the  evidence-base 
and analytical capacity of ET 2020, on which the next country-specific recommendations can draw. 
This  is  the  aim  of  the  Education  and  Training  Monitor  series,  the  first  edition  of  which  was 
presented in November 20128. 

1  
2  
3  
4  

5  

6  
7  

8  

Moving Europe beyond the crisis (COM(2013) 350 final). The package was adopted by the Council on 19 June 2013. 
Working together for Europe’s young people: A call to action on youth unemployment (COM(2013) 447 final). 
Rethinking Education: Investing in skills for better socio-economic outcomes (COM(2012) 669 final). 
Annual Growth Survey 2013 (COM(2012) 750 final). Priorities were affirmed in the Council Conclusions on investing in 
education and training (OJ 2013/C 64/06). 
The  financial  support  offered  by  the  European  Structural  and  Investment  Funds,  in  particular  the  European  Social 
Fund  and  the  European  Regional  Development  Fund,  will  help  Member  States  to  maintain  an  appropriate  level  of 
growth-friendly investments. 
See http://ec.europa.eu/europe2020/making-it-happen/country-specific-recommendations/index_en.htm. 
 See  the  May  2009  Council  Conclusions  (2009/C  119/02)  and  the  2012  Joint  Report  of  the  Council  and  the 
Commission on the implementation of ET 2020 (2012/C 70/05). 
See http://ec.europa.eu/education/news/rethinking/sw373_en.pdf. 

9 

 
 
 
 
 
 
 
 
 
 
                                               
At  the  request  of  the  Council,  the  Education  and  Training  Monitor  is  an  annual  report  presented 
every autumn by the Commission Services, setting out, in a succinct document, progress on the ET 
2020 benchmarks and core indicators, including the Europe 20209 headline target on education and 
training (see Table 1.1). The Education and Training Monitor illustrates the evolution of education 
and 
focus  on  the  country-specific 
recommendations  adopted  in  the  field  of  education  and  training.  It  contributes  to  the  analytical 
basis for the next European Semester and provides input to national debates. 

training  systems  across  Europe,  with  a  particular 

As  such,  the  annual  Education  and  Training  Monitor  is  an  instrument  to  foster  and  encourage 
evidence-based policy making, implementing the methodology of the Joint Assessment Framework 
(JAF)  –  the  monitoring  tool  for  the  Europe  2020  strategy  –  to  help  ensure  a  consistent  and 
transparent assessment of progress across Member States10. 

The second edition of the annual Education and Training Monitor consists of comparative analyses 
on the basis of the twofold Europe 2020 headline target on education and training and the formally 
adopted  ET  2020  benchmarks.  These  benchmarks  and  indicators,  summarised  in  Table  1.1,  are 
closely inter-related and contribute directly to the policy debate on youth unemployment. Beyond 
these benchmarks and indicators, the 2013 Monitor reflects recent progress in the political agenda, 
linking to the latest policy documents11. 

The Education and Training Monitor 2013 is accompanied by an online visualisation tool12. This tool 
makes it possible to quickly evaluate the performance and progress of Member States in relation to 
the Europe 2020 and ET 2020 targets. The online visualisation tool complements the Education and 
Training  Monitor  and  enables  readers  to  compare,  for  example,  particular  sub-groups,  countries, 
and their performance at a given point in time.   

Outline of the Education and Training Monitor 2013 

Chapter  2  assesses  the  trends  in  public  and  private  expenditure,  and  covers  two  cross-sectorial 
opportunities to increase efficiency in education and training systems. These opportunities are part 
of  the shift  towards open and flexible learning:  opening up education  and  training through  digital 
technologies and implementing tools for transparency of skills and qualifications. 

The  two  subsequent  sector-specific  chapters  cover  school  education  and  higher  education  and 
above  all  prioritise  the  twofold  Europe  2020  headline  target  in  education  and  training.  Chapter  3 
addresses  the  headline  target  on  early  leavers  from  education  and  training,  followed  by  early 
childhood  education  and  care,  the  teaching  profession  and  the  determinants  of  basic  skills  and 
foreign  language  skills.  Chapter  4  examines  the  headline  target  on  tertiary education  attainment, 
followed by a closer look at resource allocation and learning mobility in higher education. 

The final two chapters have a strong labour market orientation, moving from employability and its 
most  prominent  determinants  to  continued  learning.  Chapter  5  covers  vocational  education  and 
training  (VET),  the  transition  from  education  to  work  and  the  contribution  of  entrepreneurship 
education. Chapter 6 highlights the European dimension of the OECD Survey of Adult Skills (PIAAC) 
by analysing the skill levels of the European working-age population. It also shows trends in adult 
learning  and  continuing  vocational  training,  following  the  benchmark  on  adult  participation  in 
lifelong learning.  

9  
10  

11  

12  

Europe 2020: A strategy for smart, sustainable and inclusive growth (COM(2010) 2020 final). 
In this year’s Education and Training Monitor, the cross-national JAF analysis is of a purely descriptive nature, using 
scatterplots to compare Member States’ current performance and recent change, and looking at particular subgroups 
in  the  population.  However,  the  28  country  reports  are  added  as  Volume  II  primarily  to  shed  more  light  on  the 
broader context and the determinants underlying Member States’ current performance and recent change as regards 
particular indicators. Here, the JAF analysis mainly concerns the twofold Europe 2020 headline target, but from next 
year onwards this standardised approach will be applied to other ET 2020 benchmarks as well. Moreover, DG EAC is 
working to extent its quantitative JAF approach to incorporate a more qualitative, system-level assessment, which will 
further strengthen the analytical capacity and deepen the problem analysis in the next edition of the Education and 
Training Monitor.  
In  particular,  the  Commission  Communications  European  higher  education  in  the  world  (COM(2013)  499  final)  and 
Opening  Up  Education:  Innovative  teaching  and  learning  for  all  through  new  technologies  and  open  educational 
resources (COM(2013) 654 final; SWD(2013) 341). 
The  visualisation  tool  is  part  of  the  Online  Education  and  Training  Monitor,  which  can  be  found  here: 
http://ec.europa.eu/education/monitor. 

10 

 
 
 
 
 
 
 
 
 
 
 
                                               
Country reports 

The  28  individual  country  reports  represent  Volume  II  of  the  Monitor  and  summarise  the 
performance  of  each  Member  State  as  regards  the  main  benchmarks  and  indicators  monitored  in 
this  report13.  At  the  same  time,  various  examples  of  key  challenges,  particularly  good  outcomes, 
and reform areas, as mentioned in the country reports, have been taken up in the 2013 Monitor.  

The  country  reports  pinpoint  the  main  challenges  the  different  Member  States  face  in  education 
and  training  and  outline  the  most  significant  measures  adopted  to  respond  to  these  challenges. 
Information  is  provided  on  trends  in  financing  education  and  training,  with  a  special  focus  on 
investing  in  skills  and  qualifications.  Furthermore,  each  country  report  features  a  detailed 
assessment  on  school  education  and  higher  education  in  line  with  the  twofold  Europe  2020 
headline target in education and training. The last part of each country report has a strong labour 
market orientation, as it discusses the transition from education to work, the employment rate of 
recent  graduates,  reforms  in  vocational  education  and  training  and  trends  in  adult  learning  and 
continuing vocational training. 

The  specific  information  used  in  the  country  reports  provides  both  quantitative  and  qualitative 
evidence,  based  on  a  broad  range  of  data  sources.  The  monitoring  methodology  builds  on 
indicators of the Joint Assessment Framework (JAF). The 28 country reports contribute both to the 
monitoring  of  the  implementation  of  country-specific  recommendations  resulting  from  the  2013 
European  Semester  and  to  the  strengthening  of  the  analytical  basis  for  the  next  European 
Semester.           

13  

The  28  country  reports  are  part  of  the  Online  Education  and  Training  Monitor,  which  can  be  found  here: 
http://ec.europa.eu/education/monitor. 

11 

 
 
 
 
 
                                               
Table 1.1. Performance summary benchmarks and indicators 

Europe 2020 headline targets 

Early leavers from education and training 
Europe 2020 headline target: less than 10% 

Tertiary education attainment 
Europe 2020 headline target: at least 40% 

ET 2020 benchmarks 

Early childhood education and care 
ET 2020 target: 95% 

Low achievers in basic skills 
ET 2020 target: 15% 

Reading 
Maths 
Science 

Learning mobility 

IVET 

Leonardo da Vinci 
outbound 

Higher education  Erasmus inbound 

Inbound degree 
mobile students 

Employment rate of recent graduates 
ET 2020 target: 82% 

Adult participation in lifelong learning 
ET 2020 target: 15% 

Proposed ET 2020 benchmark14 

EU average 

HIGHEST 
performer 

LOWEST 
performer 

2009 

2012 

2012 

2012 

14.2% 

12.7% 

4.2% 

24.9% 

32.1% 

35.7% 

51.1% 

21.7% 

91.7% 

93.2%11 

100%11 

70.6%11 

19.6% 
22.2% 
17.7% 

0.6% 

: 

: 

: 
: 
: 

0.7%11 

1.1%11 

7.0%11 

8.1%09 
7.8%09 
6.0%09 

7.1%11 

8.4%11 

40.6%11 

41.0%09 
47.1%09 
41.4%09 

0.1%11 

0.0%11 

0.5%11 

78.3% 

75.7% 

91.9% 

42.9% 

9.2% 

9.0% 

31.6% 

1.4% 

Foreign language skills 

ISCED 2 students at proficiency 
level B1 or higher in first foreign 
language1 
ISCED 2 students learning a 
second foreign language 

: 

43.5%11 

82.7%11 

9.3%11 

58.6% 

60.8%10 

100%11 

0.0%11 

Other ET 2020 indicators 

Investment  in 
education  and 
training 

General government expenditure on education  
(% of GDP) 
Expenditure on educational 
institutions per student in € PPS  

ISCED 1-2 
ISCED 3-4 
ISCED 5-6 

5.5% 

5.3%11 

7.8%11 

3.6%11 

5,732 €08 
6,964 €08 
9,309 €08 

6,021 €10 
7,123 €10 
9,168 €10 

15,262 €10 
13,203 €10 
15,068 €10 

1,674 €10 
1,680 €10 
2,956 €10 

Digital competences 

Pupils  in  grade  4  (ISCED  1)  using 
computers at school 
Individuals  aged  16-74  with  high 
computer skills2 

60.7%07 

: 

85.8%07 

21.9%07 

25.0% 

26.0% 

42.0% 

8.0% 

Entrepreneurial competences  
Individuals  aged  18-64  who  believe  to  have  the  required  skills  and 
knowledge to start a business 

42.3%a 

42.0%a 

54.0% 

30.0% 

Vocational education and training 
Share of vocational students at ISCED 3 

Skills for future labour markets 
Projected change in employment 2010-2020 

High qualification 
Medium qualification 
Low qualification 

Adult skills 
Low achievers in basic skills 

Literacy 
Numeracy 
Problem  solving  in  technology-
rich environments 

49.6% 

50.3%11 

76.1%11 

12.7%11 

: 
: 
: 

: 
: 

: 

19.1% 
4.6% 
-20.2% 

19.9% 
23.6% 

26.9% 

38.0% 
39.3% 
26.4% 

10.6% 
12.8% 

19.1% 

-8.8% 
-18.7% 
-42.9% 

27.7% 
31.7% 

38.0% 

Source:  CEDEFOP,  EAC,  European  Survey  on  Language  Competences  (ESLC),  Eurostat  (LFS-ISS-UOE),  IEA  TIMSS,  Global 
Entrepreneurship  Monitor,  OECD  (PISA).  Notes:  07=2007;  08=2008;  09=2009;  10=2010;  11=2011;  e=estimate;  a=unweighted 
average;  b=break;  p=provisional;  1=average  of  skills  tested  in  reading,  listening,  writing;  2=  having  carried  out  5-6  specific 
computer related activities. See the corresponding sections in the Monitor for the number of countries incorporated in each EU 
average presented in this table. 

14  

SWD(2012) 372 final. 

12 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
                                               
2.  Investing in skills and qualifications  

Sustaining  public  investment  in  education  is  a  challenging  task  within  the  current  economic 
context.  Public  spending  on  education  is  essential  for  growth  and  employment  as  a  more  skilled 
and educated workforce will support further productivity gains, innovation and wealth. Low-skilled 
workers, conversely, run an increasing risk of becoming unemployed in the face of labour markets 
that  are  ever  more  demanding  in  terms  of  skills  and  qualifications.  Member  States  face  different 
demographic15,  economic  and  social  challenges  to  improve  the  returns  to  their  investments  in 
education  and  training.  Regardless,  combining  fiscal  consolidation  and  growth-enhancing 
investment by definition requires improving the efficiency of public expenditure. 

This  edition  of  the  Education  and  Training  Monitor  looks  at  the  trends  in  public  and  private 
expenditure  on  education  and  training  (section  2.1)  and  subsequently  provides  insights  into  the 
main outcomes of education and training in terms of skills and qualifications. Rather than defining 
efficiency by simply relating these investments and outcomes16, the Education and Training Monitor 
sheds  light  on  various  efficiency  measures  that  have  the  potential  to  transform  investments  into 
stronger  outcomes.  Two  examples  are  opening  up  education  through  new  technologies  and 
removing obstacles to have skills and qualifications recognised across borders. 

Section  2.2  evaluates  whether  Europe  is  sufficiently  reaping  the  benefits  of  new  technologies  in 
order  to  open  up  education  to  new  groups  of  learners  and  to  make  teaching  and  learning  more 
engaging, innovative and effective. Digital technologies can improve efficiency through economies 
of scale, expanding access to a wider number of people at lower costs. Section 2.3 addresses how 
transparency  and  recognition  of  skills  and  qualifications  acquired  through  different  learning 
pathways can be fostered through the implementation and further coordination of European policy 
instruments  such  as  qualification  frameworks,  quality  assurance  frameworks,  credit  systems  and 
tools for validation on non-formal and informal learning, paving the way for a future European Area 
of Skills and Qualifications.     

2.1.   Investing in education and training in a context of economic crisis 

Spending  on  education  is  an  investment  in  the  future.  EU  Member  States  need  to  continue 
investing in education, research and innovation while pursuing the consolidation of public budgets. 
Underinvestment  in  human  capital  risks  undermining  Europe's  prospect  for  smart,  inclusive  and 
sustainable  growth  in  the  future  as  underlined  by  the  European  Commission  in  the  last  three 
Annual  Growth  Surveys  and  the  country-specific  recommendations  issued  in  the  context  of  the 
European Semester17. The empirical evidence shows that Member States are tackling this challenge 
in different ways. Growth-friendly public expenditure is a key concern under Europe 202018 but the 
situation of public finance across the EU requires differentiated approaches. 

A key question is how Member States have adapted their public education spending to respond to 
the  crisis.  Two  kinds  of  indicators  are  considered  for  this  purpose:  (1)  education  expenditure  in 
absolute values and as a percentage of GDP as a proxy for the commitment of Member States to 
invest in human capital and (2) education expenditure per student as a measure of the actual level 
of spending on educational institutions per study level. The comparison covers three to four years 
to encompass the 2009 drop in GDP growth and the delays in national processes to adjust public 
expenditure on education to recent economic trends. 

15  

16  

17  

18  

See Table A.1 in the Annex and chapter 2 of the 2012 Education and Training Monitor on demographic change and 
education spending (http://ec.europa.eu/education/lifelong-learning-policy/monitor12_en.htm). 
There  is  a  considerable  time  lag  between  a  change in investment  and  its  first likely  effect  on  a particular  cohort  of 
students;  and  multiple  measures  to  be  considered  for  such  an  effect,  whether  skills,  qualifications,  or  given 
benchmarks  and  indicators.  In  2014,  the  JRC’s  Centre  for  Research  on  Lifelong  Learning  (CRELL)  Joint  Research 
Centre will, on behalf of DG EAC, investigate whether more sophisticated econometric models can bring to light the 
relationship between investment and outcomes in a more reliable and meaningful way. 
  The 2013 country-specific recommendations, approved by the Council, can be found at: 
  http://ec.europa.eu/europe2020/making-it-happen/country-specific-recommendations/index_en.htm.  The  package 
was  adopted  by  the  Council  on  19  June  2013.  Significant  amounts  were  earmarked  in  the  2014-2020  European 
Programme  Erasmus+,  the  European  Social  Fund  (ESF)  and  the  European  Regional  Development  Fund  (ERDF)  to 
support investments in education and training and measures to improve efficiency of education spending. 
  Key areas for comparing Member States' performance are fiscal policy, long-term sustainability and taxation. 

13 

 
 
 
 
  
 
 
 
 
 
                                               
 
 14 Sixteen Member States decreased their education expenditure at some stage between 2008 and 2011  Firstly, looking at public education expenditure in real terms or as a percentage of GDP19 shows that investment in education tended to shrink overall in many European countries. Evidence shows that budgets decreased further from 2011. BG, IT and RO already had decreasing values over the period 2008-2011; this was also the case for EL and SK from 2009 or 2010 (albeit not yet down to 2008 values). RO reinvested in education in 2011 although keeping to low levels.  While eleven countries have managed to keep their spending on education at a higher or comparable level in absolute terms from 2008 to 2011 (BE, CZ, DE, FR, LU, MT, NL, AT, SI, FI and SE – see table 2.1), cuts in education expenditure were significant during this period in EE, IE, LV and HU as well as in BG, EL, IT and RO where spending levels in relation to the GDP were already low and have been cut further. DK, ES, CY, LT, PL, PT, SK and UK made cuts at some stage between 2008 and 2011 which is reflected in a reduction of education spending as a percentage of GDP in 2011. ES, PT, SK and UK had significant cuts in 2011.  The fall in education spending in recent years in these sixteen Member States represents a worrying trend and calls for strengthening the efficiency of education investment and supporting innovation and competitiveness20. This is of particular relevance in the context of limited GDP growth forecasts for 2014.   Figure 2.1. Public expenditure on education as a percentage of GDP (2010- 2011)21    Source: Eurostat (Government finance statistics; online data code: gov_a_exp). Notes: No comparable data for HR. Countries are ranked in ascending order according to public expenditure on education in % of GDP in 2010.  More recent figures available at national level22 show that the budget continued to decrease by more than 5% between 2011 and 2012 in six of the sixteen Member States mentioned above for all education levels (EL, IT, CY, LV, PT, UK-WLS) as well as in HR and for tertiary education in two other Member States (CZ, IE). Education spending increased by 5% or more only in BE (German speaking Community), LU and MT. These trends, as well as changes in 2013 national budgets, explain why, in the context of the 2013 European Semester, it was recommended pursuing or implementing growth-friendly policies in BG, EE, HU, LT, IT, RO, FI, SE and UK; improving the efficiency of public spending in DE, FR, and SK; and protecting growth-enhancing expenditure in future budgets in MT, NL, PL and SI.                                                 19   Eleven Member States had a level of public education spending below the EU average of 5.3% of GDP in 2011 (BG, CZ, DE, IE, EL, ES, IT, LU, HU, RO and SK). On the other hand, in some Member States public expenditure on education exceeded the average by a considerable margin. It was between 6% and 7% of GDP in BE, EE, FR, PT, SI, SE, FI and UK. In CY, expenditure even amounted to 7.2% and in DK to 7.8% of GDP. 20   COM(2013) 350 final. 21   Based on breakdowns of expenditure data according to the Classification of the Functions of Government (COFOG). According to the COFOG, education expenditure covers pre-primary, primary, secondary and tertiary education, education not definable by level, subsidiary services to education and R&D in education. 22   Eurydice (2013), Funding of Education in Europe, 2000-2012 (changes in budgets in constant prices).  -1,00,01,02,03,04,05,06,07,08,0-1,00,01,02,03,04,05,06,07,08,0ROBGELDESKITCZESLUIEEUHUPLATMTNLLVLTFRBEFISIEEUKSEPTCYDKDecrease between 2010 and 2011 in percentage pointsIncrease between 2010 and 2011 in percentage points % of GDP  15 BG, ES, HR, IT, LV and RO cut down on all levels from primary to tertiary education Secondly, when looking at public education expenditure per student and by education level23, data availability allows only for a 2008-2010 analysis. Nevertheless, the concerns expressed above were already visible before the real impact of the crisis on education and training budgets. On average, Member States spent about 6,900 € per student in 2010 (about 9,600 € per student in tertiary education compared to about 5,100 € for primary and 6,100 € for secondary education). Education spending per student was down in seven Member States between 2008 and 2010 when considering averages for all educational levels (Figure 2.2). This was the case in countries with existing low levels like BG, HR, IT, LV and RO as well as in ES for primary, secondary and tertiary education.  Overall education spending per student was also down in EE although the decrease concerned primary education. In nine other Member States, spending per student decreased for certain educational levels only. This was the case in BE, CZ, CY, NL, AT and SE for tertiary education (see Table 2.1), in CY, LT, LU and AT for upper secondary education, and in SI for primary and lower secondary education.   Table 2.1. Government expenditure on education (2008-2011) and annual expenditure per student in € PPS (2010-2008)   Government expenditure on education  in absolute terms Expenditure on educational institutions  Primary and lower secondary Upper secondary and post-secondary non tertiary education Tertiary  change 2008-2010 % change 2010-2011 % in € PPS / student 2010 change 2008-2010 % in € PPS / student 2010 change 2008-2010 % in € PPS / student 2010 change 2008-2010 % European Union 4.5 0.4 6,131 6.9 7,128 3.0 9,638 3.5 Belgium 6.4 5.1 6,818 2.2 8,476 3.1 11,691 -0.5 Bulgaria -6.3 2.1 2,190 -6.2 2,148 -4.8 3,763 -22.1 Czech Republic 4.8 5.6 4,136 9.9 4,464 6.2 5,881 -5.8 Denmark 16.2 -1.0 8,598 8.2 9,177 5.0 14,617 5.8 Germany  8.9 3.1 6,240 15.6 8,373 4.3 12,357 2.6 Estonia -10.3 5.7 4,108 -7.3 5,355 9.9 5,038 11.9 Ireland -9.7 -3.6 : : : : : : Greece -7.3 -4.4 : : : : : : Spain 3.0 -2.3 6,207 -0.3 7,938 -8.5 10,301 -1.3 France 8.7 2.1 6,039 4.0 9,825 4.1 11,606 4.8 Croatia : : 3,285 -3.8 3,485 -3.8 5,233 -28.4 Italy -0.2 -3.2 6,467 -8.4 6,660 -6.5 7,379 -1.1 Cyprus 11.2 -0.5 9,260 9.1 10,849 -0.4 9,933 -4.0 Latvia -27.1 5.5 3,533 -15.1 3,365 -19.2 4,315 -12.0 Lithuania -10.0 6.3 3,295 4.1 3,291 -7.0 5,066 6.9 Luxembourg 19.0 5.1 15,262 19.6 13,203 -15.5 : : Hungary -2.1 -4.7 : : : : : : Malta 16.5 5.1 7,713 23.3 5,444 1.3 11,719 21.0 Netherlands 5.9 1.2 7,279 7.1 9,048 2.2 13,219 -4.9 Austria 7.5 2.4 8,774 7.6 9,136 -1.9 11,895 -3.1 Poland -3.9 2.6 4,279 20.2 3,735 15.9 5,951 28.5 Portugal 13.9 -11.3 4,684 10.9 6,258 8.6 7,742 6.9 Romania -33.5 30.5 1,674 -24.6 1,680 -20.2 2,956 -19.5 Slovenia 3.6 2.4 6,971 -2.3 5,670 3.1 7,296 14.0 Slovakia 31.4 -5.2 4,168 35.8 3,466 5.6 5,318 3.7 Finland 7.2 3.0 6,997 5.2 6,094 4.3 12,874 6.7 Sweden 5.8 9.1 7,634 4.4 7,945 1.7 15,068 -4.0 United Kingdom 2.1 -3.6 7,585 8.6 7,642 6.1 12,781 7.1 Source: Eurostat (Government finance statistics; online data code: gov_a_exp and UOE; online data code: educ_fitotin). Notes: See Eurostat on line metadata for a precise definition of education  expenditure in each source. No comparable data for HR on Government expenditure on education. PT 2009 data are used for expenditure on educational institutions in primary and secondary education. For IT, data on expenditure on educational institutions cover public institutions only (except in tertiary education) and data excludes post-secondary non-tertiary education. EU aggregate are calculated without IE, EL, LU and HU.                                                 23   Expenditure on educational institutions per student provides complementary information on trends across education levels and Member States considering demographic factors and enrolment in educational programmes. The indicator adopted here is the annual expenditure on public and private educational institutions per pupil/student in Purchasing Power Standards, based on full-time equivalents. In 2009, 77% of this expenditure was devoted to personnel expenditure at EU level (see also Section 3.3).  16 Tuition fees and enterprise sponsorship accounted for 14% of total spending on educational institutions There is a need for national debates on the funding of education and training In the other Member States, education expenditure per student increased or remained stable between 2008 and 201024. However, the cuts in education spending in 2011 and 2012 are likely to impact expenditure per student particularly in tertiary education in the view of upward enrolment trends across Europe (+4.3% in the period 2008-2010, with more than 10% in BE, CZ, DE, CY, MT and AT). In 2013, efficiency gains are expected in a number of Member States as national budget priorities focussed on e.g. improving the efficiency of education administration in BG, CZ, AT, SI and UK-NIR and the employability of graduates and/or the provision of apprenticeship in BG, CZ, ES and UK-SCT25. Nevertheless, there is still a need for national debates on the funding of education and training.   Figure 2.2. Annual expenditure per student, all levels of education, in € PPS (2008-2010)   Source: Eurostat (UOE; online data code: educ_fitotin). Notes: For the EU28, DE and PT 2009 data are used instead of 2010 data. EU aggregate calculated without IE, EL, LU, HR and HU. Countries are ranked in ascending order according to the growth in annual expenditure per student between 2008 and 2010.  Private spending on educational institutions  Financing educational institutions has always been largely the role of public actors across the EU. For all educational levels, public funding accounted for about 86% of investments in educational institutions in 2010. Over the last decade, the share of private funding (tuition fees paid by households/students, sponsorship by enterprises) of educational institutions increased from 11.5% of total spending on institutions in 2000 to close to 14% in 2009 for the EU as a whole.   In 2010, private spending on educational institutions accounted for less than 5% of total spending in FI, SE and RO as well as in NO, but between 15% and 20% in BG, CY, MT, NL and SK. The share of private spending was as high as 31.4% in UK, close to values reached in non EU countries like the United States and Japan, which reflects the specific UK-ENG funding model for higher education. Tuition fees paid by households/students for tertiary education largely reflect the diversity and evolution of education financing models across Europe26 (see chapter 4).                                                24  See also a forthcoming JRC-CRELL report on public financing of education in EU countries (to be published at: https://crell.jrc.ec.europa.eu). 25   Eurydice (2013), Funding of Education in Europe, 2000-2012. 26   See also Eurydice (2013), Funding of Education in Europe, 2000-2012 (chapter 5 on financial support to students). The figures do not take into account private spending of households on non-formal education to supplement formal education with a private tutor. See NESSE (2011), The challenge of shadow education for further information at http://www.nesse.fr/nesse. Furthermore, when examining the differences in funding of educational systems across Member States, this chapter does not address local and regional disparities. See NESSE (2012),Mind the Gap for -2 00002 0004 0006 0008 00010 000-20000200040006000800010000LVROITHRBGESEESISELTBECZNLFIFRATPTCYEUUKSKDKPLDEMTDecrease between 2008 and 2010 in € PPS Increase between 2008 and 2010 in € PPS  in € PPS per student  17 A more advanced use of computers during lessons is still not commonplace in many countries Figure 2.3. Share of private expenditure on educational institutions (2010)    Source: Eurostat (UOE). Notes: Private expenditure corresponds to transfers from private sources to educational institutions. This includes private fees for educational services as well as public funding via subsidies to households.   In relation to further use of a mix of private and public sources, the European Commission underlined the need for strengthening the knowledge triangle between education, research and business in the European Union in its Communication on European Higher Education in the World27. This was already the aim of recommendations made to BG, EE and SK within the context of the 2013 European Semester in order to foster effective knowledge transfer.   Private spending on educational institutions stands to face significant changes in coming years with the development of new relationships between educational institutions, households and enterprises. Significant efficiency gains can be expected with the increasing role of ICT in education and training and Open Educational Resources (see section 2.2) and with a better transferability between educational institutions, companies and sectors of skills acquired across different learning platforms and pathways (see section 2.3).   2.2. Opening up education and training through new technologies   Today new technologies offer unprecedented opportunities to make learning more effective, inclusive and engaging. Digital technologies can improve effectiveness of resources through economies of scale, expanding access to a wider number of people (e.g. through MOOCs28 and other Open Educational Resources (OER)) at lower costs or allowing teachers to focus on what they do best by automating or offloading more routine tasks. ICT can be used to foster more creative and innovative methods of learning (including personalised and collaborative learning)29, and it has the potential to facilitate collaboration, exchange and access to learning resources.  A huge potential for the modernisation of education and training  As highlighted in the Communication on Opening Up Education30, Europe is not fully exploiting the potential offered by new technologies and the upsurge across the globe of digital content in order to better fulfil learners' needs, cater for more individualised learning paths and offer high quality education.  Even if data from TIMSS 201131 show that the use of computers at school (in grade 4) has increased, the differences across countries remain significant. In UK-ENG nearly all grade 4 students use ICT at school, whereas in AT, LT, SI and RO less than half of the students do so. To fully benefit from the                                                                                                                                                 further information at http://www.nesse.fr/nesse. 27   European higher education in the world (COM(2013) 499 final). 28   Massive Online Open Courses. 29   See e.g. JRC-IPTS (2012) Innovating Learning: Key Elements for Developing Creative Classrooms in Europe (http://ftp.jrc.es/EURdoc/JRC72278.pdf). 30   Opening Up Education: Innovative teaching and learning for all through new technologies and open educational resources (COM(2013) 654 final). 31   Trends in International Mathematics and Science Study by the IEA (http://timss.bc.edu/). See also Section 3.4. 0%5%10%15%20%25%30%35%UKCYMTNLSKBGESDEPLCZLTSILVFRITATIEPTEEHRDKBEROSEFIISCHNOEU28  18 Only 1 in 5 are taught by digitally confident and supportive teachers potential of new technology, the question of how ICT is used in learning is even more pertinent than asking if ICT is used. With respect to science teaching, data from TIMSS 2011 show certain limitations to the level of integration of new technologies in lessons. More advanced use of computers to conduct experiments or simulations of natural phenomena is far less commonplace than other types of use during lessons32.  Results from the 2011-12 Survey of Schools: ICT in Education33 show that students’ frequency of ICT-based activities for learning in the classroom increase when schools have specific formal policies to use ICT in their teaching and learning and, even more importantly, implement concrete support measures at school level (such as facilitating teachers' participation in training, availability of an ICT coordinator, etc.). However, in the EU only around 30% of students at grade 4 and around 25% at the other grades (grade 8 and 11) are in such digitally supportive schools and as much as 35% of students are in schools characterised by both weak policy and weak support.    As mentioned in relation to the results from TIMSS 2011, the key issue is to really integrate ICT as a teaching and learning tool in mainstream practices, which does not simply mean more electronic devices or more broadband connections. The combination of innovative pedagogies with an effective use of digital tools and content can boost education and training in terms of quality, equity and efficiency.    Table 2.2. Use of computers in school and during science lessons (%)   % of grade 4 students who use computers at school % of grade 4 students using computers at least monthly during science lessons (TIMSS 2011) TIMSS 2007 TIMSS 2011 To Look Up Ideas and Information To Do Scientific Procedures or Experiments To Study Natural Phenomena Through Simulations To Practice Skills and Procedures Belgium (Flemish) : 68.8 78 (3.3) 21 (3.3) 26 (3.4) 56 (3.8) Czech Republic 51.1 69.6 45 (4.1) 22 (3.4) 16 (3.0) 37 (4.2) Denmark 78.8 79.8 71 (3.4) 25 (3.7) 37 (4.5) 45 (3.9) Germany 37.5 51.0 54 (3.2) 14 (2.4) 15 (2.4) 23 (2.9) Ireland : 69.8 55 (3.9) 29 (3.5) 35 (3.4) 30 (3.5) Spain : 60.7 33 (3.5) 21 (3.2) 20 (3.3) 29 (3.5) Croatia : 26.8 13 (2.2) 7 (1.5) 5 (1.4) 12 (2.3) Italy 63.2 60.0 28 (3.1) 21 (2.8) 18 (2.7) 23 (2.9) Lithuania 21.9 37.9 45 (4.1) 30 (3.3) 21 (2.8) 41 (3.8) Hungary 42.9 78.1 34 (3.5) 14 (2.5) 15 (2.6) 27 (3.2) Malta : 80.3 65 (0.1) 50 (0.1) 39 (0.1) 59 (0.1) Netherlands 83.2 85.6 58 (5.0) 13 (3.4) 16 (3.4) 27 (4.5) Austria 37.4 42.8 60 (3.5) 20 (2.6) 20 (2.8) 32 (3.3) Poland : 56.9 16 (2.8) 7 (2.0) 11 (2.5) 13 (2.8) Portugal : 59.9 46 (5.3) 29 (3.9) 30 (4.2) 39 (4.3) Romania : 37.8 23 (3.5) 21 (3.2) 21 (3.3) 23 (3.5) Slovenia 33.3 45.3 37 (3.6) 12 (2.1) 20 (2.7) 21 (3.0) Slovakia 46.7 70.0 42 (3.2) 17 (2.3) 24 (2.7) 43 (3.2) Finland : 80.6 59 (3.7) 17 (2.7) 15 (2.2) 42 (3.5) Sweden 58.5 66.8 49 (4.6) 11 (3.1) 10 (2.5) 21 (3.5) UK (England) 85.8 96.6 68 (5.0) 40 (4.8) 51 (5.1) 43 (4.8) UK (Northern Ireland) : 97.3 73 (3.9) 47 (4.0) 42 (4.3) 53 (4.4) Source: IEA (TIMMS 2007 and 2011).   The Communication on Opening Up Education stresses the role of teachers as key agents for such change. The results from the 2011-12 Survey of Schools underpin this. While 70% of teachers in the EU recognise the importance of training in ICT-supported pedagogies, only around 20% of students are taught by digitally confident and supportive teachers having high access to ICT and facing low obstacles to their use at school. However, the survey also shows that teachers who are highly confident and positive about the use of ICT can overcome low access to equipment and other obstacles affecting the provision of ICT use in teaching and learning.                                                 32   Similar findings from TIMSS (2007) are analysed in Eurydice report (2011), Key data on Learning and Innovation through ICT at School in Europe 2011. 33   European Commission (2013), Survey of Schools: ICT in Education. Benchmarking Access, Use and Attitudes to Technology in Europe’s Schools (Study carried out for the Commission by the European Schoolnet and the University of Liège).   19 Teacher training on the pedagogical use of ICT is rarely compulsory Current experiences show that sharing and collaborating are proven to be successful in changing attitudes and introducing new innovate ways of teaching and learning34. This is demonstrated by the strong engagement of teachers in the communities of practices of the e-Learning Portal35 or of the e-Twinning36, with more than 200,000 registered users and 100,000 schools. An Electronic Platform for Adult Learning in Europe is also in development. The 2011-12 Survey of Schools found that around 30% of students at grade 4, 8 and 11 are taught by teachers having participated in online communities for professional exchange amongst other teachers, there is thus scope for further strengthening teachers’ participation in these collaborative practices.   The 2011-12 Survey of Schools shows that teacher training on the pedagogical use of ICT is rarely compulsory (only for 25-30% of teachers depending on the grade). Teachers’ participation in courses on the pedagogical use of ICT in teaching and learning also varies considerably between countries. In LT, around 70% of students or more across all grades are taught by teachers who have undertaken such courses (with similarly high figures for one or more grades in ES, EE, SI and LV). By contrast, only around one third of students across all grades in BE are taught by teachers who have participated in these types of courses (figures of less than 30% can also be found for one or more grade in AT, LU, FR, EL and IT).   The impact and new possibilities offered by technological advances is also felt in higher education and in adult learning. As underlined in the two Communications on European Higher Education in the World and Opening Up Education, the appearance of phenomena like MOOCs is pushing for a globalisation of educational markets. In the US, the three main MOOC providers offer around 400 courses, with 3 million users worldwide, and Europe is currently lagging behind. Few European universities are providing MOOCs (e.g. only 9 are involved in Coursera37) and a recent EUA survey38 shows that many European universities are not even aware of what a MOOC is. To strengthen the evidence-base in the area of technological advances in higher education and adult learning, the Commission is launching various studies this year to strengthen the evidence-base in the area of technological advances in higher education and adult learning. In order for society and individuals to make full use of the competences acquired through online learning and OER, recognition of such learning will be considered in the development of the European policy instruments (see chapter 2.3).  Digital competences  If learners of all ages are to benefit fully from the opportunities for more engaging, effective and inclusive learning offered by new technologies, digital competences are a prerequisite. The 2012 Communication on Rethinking Education39 emphasised the importance of building the right skills for the 21st century, and developing digital competence is part and parcel of this set of skills, knowledge and attitudes.   Recent results on 8th and 11th grade pupils' confidence in their ICT skills are available from the 2011-12 Survey of Schools: ICT in Education40. As can be seen in Figure 2.4, the results show that pupils express higher confidence in their ability to use the internet safely and lower confidence in their social media skills than in the other ICT skills they were asked about.   The analysis of the survey results finds a positive link between confidence in these ICT skills and the use of ICT at home and at school. Students with high access/use of ICT both at home and at school are more confident in their ICT skills than those who only report high access/use at home and not at school, or low access/use both at home and at school. These students are not only                                                34   See e.g. chapter 4 of European Commission (2013): Study of the impact of eTwinning on participating pupils, teachers and schools. 35  See http://www.elearningeuropa.info. 36  See http://www.etwinning.net. 37 http://www.eua.be/news/13-02-25/Massive_Open_Online_Courses_MOOCs_EUA_to_look_at_development_of_MOOCs_and_trends_in_innovative_learning.aspx. 38  Ibid. 39   COM (2012) 669 final. 40   European Commission (2013), Survey of Schools: ICT in Education. Benchmarking Access, Use and Attitudes to Technology in Europe’s Schools (Study carried out for the Commission by the European Schoolnet and the University of Liège).  20 Digitally supportive schools can help foster digitally confident and supportive students confident in their digital competences, but are also positive about the impact of using ICT in teaching and learning, i.e. they are digitally confident and supportive students.   Figure 2.4. Average pupil confidence in using ICT skills (Grade 8, 2011-12)     Source: European Commission (2013): “Survey of Schools: ICT in Education. Benchmarking Access, Use and Attitudes to Technology in Europe’s Schools”. Note: All EU28 countries are included except DE, HR, NL and UK.  Across EU countries, on average 30–35% of students are digitally confident and supportive students (Figure 2.5). The highest percentage of such students is observed in grade 11 general education (36% compared with 29% at grade 11 vocational and 31% at grade 8). Yet there are important variations between countries. The highest percentage is found in DK at all grades, whereas AT, BE, FI and IE are amongst the lower five countries for both grade 8 and grade 11 (general education). The results from the survey also demonstrate that educational systems with a high percentage of digitally supportive schools include a large percentage of digitally confident and supportive students. This is particularly clear for grade 11 general education, as shown in Figure 2.5.    Figure 2.5. Mapping of countries according to their percentage of students in digitally supportive schools and percentage of digitally confident and supportive students       Source: European Commission (2013): “Survey of Schools: ICT in Education. Benchmarking Access, Use and Attitudes to Technology in Europe’s Schools”. Note: The plot covers grade 11 of general education, 2011-12. All EU28 countries are included except DE, HR, NL and UK.  The Commission proposes in the Communication on Opening up Education to develop – in close cooperation with stakeholders and Member States – digital competency frameworks, including a 3,16 3,05 2,55 2,88 2,58 2,13 2,93 2,64 2,17 2,78 2,42 1,83 1,001,502,002,503,003,504,00Pupils with high access/use at school& homePupils with low access/use at school& high access/use at homePupils with low access/use at school& homeScale 1-4  (from "not at all" to "a lot") Safe internet useResponsible internet useOperational skillsSocial media skillsAT BE BG HR CY CZ DK EE FI FR EL HU IE IT LV LT MT NO PL PT RO SK SI ES SE TR EU 01020304050607080901000102030405060708090100% digitally supportive schools  (grade 11 general education) % digitally confident and supportive students  (grade 11 general education) self-assessment  citizens’  tool41.  Such  instruments  would  further  support  policy  development  to 
foster competences and to facilitate documentation of digital competences, e.g. for validation and 
recognition  purposes.  The  importance  of  transparency  and  recognition  of  what  individuals  know 
and can do is discussed more widely in the subsequent section.  

One  in  four  adults  in  the  17  EU  Member  States  that  participated  in  the  Survey  of  Adult  Skills 
(PIAAC)  showed  very  low  to  no  skills  in  problem  solving  in  technology-rich  environments.  This 
consists of 14% that could only perform very simple tasks (below proficiency level 1) and another 
13% that lacked any computer experience or had such low levels of proficiency that they could not 
take the computer based test.   

The Survey of Adult Skills also showed that the use of ICT both at work and at home is one of the 
strongest  determinants  of  reading  literacy  skills,  just  after  education  attainment.  The  more 
individuals  tend  to  engage  in  the  use  of  information  communication  technology,  the  higher  their 
literacy  skills  and  vice  versa.  Good  literacy  skills  ease  the  use  of  ICT  for  retrieving  and  using 
information,  while  frequent  ICT  use  may  contribute  to  improving  or  at  least  maintaining  literacy 
abilities. Further results from the Survey of Adult Skills are discussed in section 6.1. 

2.3.  Tools for transparency of skills and qualifications 

In the last decade, several European policies and instruments have been developed and are being 
implemented in the context of the ET 2020 strategic framework and the Bologna process that aim 
to support the mobility of learners and workers through better transparency and easier recognition 
of what they know and can do. Providing individuals with the opportunity to develop their skills in a 
flexible way and have those skills clearly understood and recognised across borders (both sectorial 
and  geographical)  will  reduce  skills  mismatches  and  increase  the  efficiency  in  education  and 
training systems. 

European qualifications frameworks (EQF42 and QF EHEA43) based on a learning outcome approach 
provide  a  reference  point  for  the  comparison  of  individual  qualifications  and  qualification  systems 
across countries. European credit systems (ECTS44 and ECVET45) support learners in shaping their 
own learning pathway through accumulation of credits – whether within a certain institution, from 
institution  to  institution,  from  country  to  country,  or  between  different  contexts  of  learning  (i.e. 
formal,  non-formal  and  informal  learning).  Common  European  quality  assurance  arrangements 
(ESG46, EQAR47 and EQAVET48) contribute to improving mutual trust in education and qualifications 
systems,  thus  facilitating  recognition  across  borders.  The  Europass  framework,  including  the 
Europass  CV  and  the  European  Skills  Passport49,  provides  important  documentation  tools  for 
citizens  to  describe  their  acquired  knowledge,  skills,  competences  and  qualifications  in  a  more 
transparent and structured way. 

Important progress in  the implementation and use of  the above mentioned policies and tools can 
be  identified.  However,  the  analysis  below  also  depicts  certain  remaining  challenges  and  lends 
support to closer coherence and coordination between the different tools and services, as called for 
in  the  “Rethinking  Education”  Communication,  which  announced  the  creation  of  a  European  Area 
for Skills and Qualifications. The European Area for Skills and Qualifications is to support the drive 
to  achieve  transparency  and  recognition  of  skills  and  qualifications  within  and  across  national 
borders, in all sub-systems of education and training as well as on the labour market. 

41  

42  

43  

44  

45  

46  

47  
48  

49  

  See also the report JRC-IPTS (2013) DIGCOMP: A Framework for Developing and Understanding Digital Competence 

in Europe (http://ftp.jrc.es/EURdoc/JRC83167.pdf). 

  European  Qualifications  Framework  for  lifelong  learning,  launched  by  the  Recommendation  of  the  European 

Parliament and the Council of 23 April 2008. 

  Qualifications  Framework  for  the  European  Higher  Education  Area  agreed  by  ministers  responsible  for  higher 

education within the Bologna Process in 2005.  
European  Credit  Transfer  and  Accumulation  System  -  the  credit  system  for  higher  education  used  in  the  European 
Higher Education Area, involving all countries engaged in the Bologna Process. 

  European  Credit  System  for  Vocational  Education  and  Training  adopted  by  the  Recommendation  of  the  European 

Parliament and the Council of 19 June 2009.  

  European Standards and Guidelines for Quality Assurance in Higher Education developed by ENQA (European Quality 
Assurance  Network  in  higher  education)  and  endorsed  by  ministers  of  higher  education  in  the  Bologna  Process  in 
2009. 

  European Quality Assurance Register for Higher Education – which was established in March 2008.  
  European Quality Assurance for Vocational Education and Training adopted by the Recommendation of the European 

Parliament and Council of 18 June 2009. 
Decision  no  2241/2004/EC  of  the  European  Parliament  and  of  the  Council  of  15  December  2004  on  a  single 
community framework for the transparency of qualifications and competences (Europass). 

21 

 
 
 
 
 
 
 
 
                                               
 22 ECTS is not yet fully in line with the learning outcomes approach Among 36 countries50 that participate in the EQF, 20 countries have already adapted their national qualification levels to the EQF and 7 countries are planning to follow them by the end of 2013. By the end of 2014, it is foreseen that 32 countries will have referenced to the EQF, including all Member States. Half of the 20 countries that have already referenced the EQF have also self-certified to the QF EHEA in a single process relating their qualifications levels to both the EQF and the QF EHEA51.  There are important subsequent steps required to make the qualifications frameworks function in practice. So far, 7 countries have started to indicate EQF levels in their new certificates, diplomas and Europass documents issued, and in national qualifications databases.    Table 2.3. Status of the implementation of the European Qualifications Framework  National Qualification Frameworks referenced to the EQF? Countries Completed 20 countries: AT, BE-fl, BG, CZ, DE, DK, EE, FR, HR, IE, IT, LT, LU, LV, MT, NL, PL, PT, SI, UK To be completed by end 2013 7 countries: BE-fr, CY, EL, ES, FI, RO + IS, NO To be completed in 2014 5 countries: HU, SE, SK + MK, TK Implementation of EQF in documents and national qualifications databases  Countries EQF level in new certificates, diplomas 3 countries: CZ, DK, LT EQF level in Europass supplements (Certificate Supplements and Diploma Supplements) 5 countries: CZ (cs), DK (ds), EE (ds),  FR (cs), IE (ds)  EQF level in national qualifications databases 4 countries: CZ, DK, FR, UK  Complementing the EQF recommendation, the Council Recommendation on the validation of non-formal and informal learning52 invites Member States to develop new arrangements by 2018 and to allow citizens to obtain qualifications on the basis of validated learning outcomes. The Member States with the most advanced arrangements  include FR, PT, NL, FI and LU. Several other countries are also making significant progress, but some are still at a starting point and there is often still a lack of transparency around the rules and procedures of recognition of skills and qualifications. The state-of-play of validation practices in Europe will continue to be mapped through regular reviews and updates of the European Inventory on the validation of non-formal and informal learning53, in cooperation with the Member States.   The extensive use of the tools in the Europass framework is instrumental in providing citizens with relevant and recognised documentation tools. The Europass portal has been visited by almost 60 million people since its launch in February 2005 and the Europass CV is the most iconic document:  it has been used by more than 24 million people since its launch in 2005. However, it remains a challenge that Europass is not sufficiently well-known by employers. Part of the Europass framework, the European Skills Passport was implemented in 2012. As of early July 2013, more than 800 000 passports have been created by citizens.   The implementation of the European credit transfer systems in higher education (ECTS) and VET (ECVET) are at different stages. The 2012 Bologna Process Implementation Report concludes that “a look at the implementation of ECTS as a transfer and accumulation system shows that it is almost completed. Yet, linking credits with learning outcomes is not completed […]”. The report found that there were nine systems – amongst them AT, BE fr, BE nl, CZ, DE and PT – where all parts of programmes are linked with learning outcomes in less than 50 % of programmes, and three countries – amongst them HU and SK – where no links were made to learning outcomes54.  As regards ECVET, the preparatory phase of implementation has started in all European countries (ECVET coordination points are being set up, and detailed roadmaps for ECVET implementation are emerging)55. The ECVET Recommendation invites the Commission to evaluate the implementation                                                50   28 Member States, 5 candidate countries, CH, LI and NO. 51   See also pp. 45-46 of the 2012 Bologna Process Implementation Report at:   http://www.ehea.info/Uploads/(1)/Bologna%20Process%20Implementation%20Report.pdf. 52   OJ 2012/C 398/01. 53    http://www.cedefop.europa.eu/en/about-cedefop/projects/validation-of-non-formal-and-informal-learning/european-inventory.aspx. 54   See also Figure 2.16 and 2.17 on p. 48 of the same report. 55   Cedefop (2012), The development of ECVET in Europe (see: http://www.cedefop.europa.eu/EN/Files/6114_en.pdf).  23 of ECVET five years after its launch. The Commission will launch the evaluation on ECVET in mid-2013 and report in 2014. The parallel implementation of the two credit systems does however leave room for improved consolidation and coherence in order to strengthen permeability across sub-systems.   The importance of a holistic vision also applies to the European quality assurance instruments (ESG, EQAR and EQAVET). External evaluations of EQAVET and quality assurance arrangements in higher education are on-going. For these instruments to fulfil their purpose of contributing to mutual trust in education and qualification systems, the principles they enshrine should be applied evenly and understood in the same way across education systems, while also respecting the autonomy of national governments in this area.   The exchange of information and debate between the world of education and training and the world of the labour market is still occasional and under–developed in many countries. To facilitate such exchange it is important to have a common language (on knowledge, skills and competences) and easily accessible and up-to-date information on skills supply and skills needs for the near and medium-term future. The various instruments above, and in particular the qualifications frameworks and the learning outcomes approach, have indeed promoted communication on skills need and skills supply in the labour market. However, further action is taken to address this challenge, most notably the European Skills Panorama56 and the European Skills, Competences, Qualifications and Occupations taxonomy (ESCO)57.  The European Skills Panorama was launched in December 2012 and gathers comprehensive intelligence on skills supply and skills needs in various sectors and occupations of the labour market. It is used by a wide range of actors including bodies responsible for education and employment policies, job and career guidance centres and education and training institutions. Since the launch the European Skills Panorama website has had on average around 600 daily visitors.  ESCO aims to describe the most relevant skills, competences and qualifications needed for several thousand occupations and provide a common language bridging education and the labour market. ESCO has the potential to bring benefits to both jobseekers, employers and education and training institutions, for example by allowing a more precise description of skills sets held by individuals or required by employers or a better adaptation of training initiatives and career guidance services to the needs of the labour market. A first version of ESCO will become available in October 2013. A full ESCO covering all economic sectors is planned to be completed in 25 languages in 2017.                                                 56  See http://euskillspanorama.ec.europa.eu/. 57  See http://ec.europa.eu/social/main.jsp?langId=en&catId=89&newsId=852.  Policy lessons  With public debt in the EU expected to reach 90.6% of GDP in 2014 and economic growth to remain moderate (1.4%), all Member States are confronted with the double challenge of consolidation public finance while investing in growth-enhancing policies. Education and training, on average, is granted 5.3% of GDP (2011). As the crisis persists, many Member States consider reducing education expenditure as an option to reduce budget deficits, running the risk of compromising sustained growth in the years to come.  Sixteen Member States decreased their education expenditure at some stage between 2008 and 2011, with six of them showing further significant budget decreases in 2012 (EL, IT, CY, LV, PT, UK-WLS). Cutbacks in spending per student across Europe started to be most prevalent in tertiary education (12 Member States) between 2008 and 2010. Whereas the majority of Member States decreased spending per student for at least one level of education, BG, ES, HR, IT, LV and RO cut down on all levels from primary to tertiary in this period.  Europe is lagging behind in the development of Open Educational Resources (OER) and Massive Open Online Courses (MOOCs). Although digital technologies are fully embedded in the way people interact, work and trade, they are not being fully exploited in European education and training systems. While 70% of teachers in the EU recognise the importance of training in ICT-supported pedagogies, only 20% of students are taught by digitally confident and supportive teachers.    24   Policy lessons (continued)  Despite the existence of a large number of tools for the transparency and recognition of skills and qualifications there still exist obstacles for individuals to move between countries, across different education sub-systems and from education to work. In a fully developed European Area for Skills and Qualifications anybody should be able to move freely and have their competences and qualifications quickly recognised for further learning and adequately understood and assessed by employers, supported through European transparency and recognition tools for skills and qualifications.    25 3. Tackling early school leaving and raising the bar in school education   This chapter looks at the main challenge in school education; raising the bar for a strong start for everyone. The cornerstone – and starting point in section 3.1 – is the performance of Member States in relation to the Europe 2020 headline target and national targets on early leavers from education and training. Section 3.2 examines the provision of early childhood education and care, which has been identified as one of the most effective measures to give children a good start in education. Moving from prevention to intervention, section 3.3 takes a look at the teaching workforce. Lastly, section 3.4 looks at how these various determinants of low attainment also affect the development of foundation skills at a young age.   3.1. Reducing the rate of early leavers from education and training  Completing upper secondary education is recommended as the minimum entrance qualification when making the crucial transition from education to the labour market (chapter 5). There is ample evidence that early leavers from education and training58 are more at risk of unemployment and social exclusion, resulting in monetary and non-monetary costs to themselves and, in the longer run, to society59. This is why an early school leaving rate of less than 10.0% is one of the Europe 2020 headline targets.  In 2012, nearly 5.5 million young people across the EU between 18 and 24 years old had not finished upper secondary education and were no longer in formal or non-formal education and training. The EU average rate of early leavers from education and training was 12.7% in 2012; down 0.7 percentage points from 2011. This improvement is mainly due to progress in some larger Member States and hides negative trends in a number of other countries.   Figure 3.1. Early school leaving (2012)   Source: Eurostat (LFS).  Since 2009, the EU has on average decreased its early school leaving rate by 1.5 percentage points, which is an average annual progress of 3.7%. Knowing that the EU early school leaving rate needs to be below 10.0% by 2020, it is possible to calculate the minimum annual progress that the EU as a whole will have to make on average between 2009 and 2020. Figure 3.2 plots the recent change in early school leaving rates (2009-2012) against the current performance (2012) of each country. This enables a more comprehensive comparison between current performance and recent change, keeping in mind the headline target and the minimum annual progress necessary to reach it by 2020.                                                58   The terms early school leavers and early leavers from education and training are used interchangeably. 59   Reducing Early School Leaving in the EU, authored in 2011 by GHK at the request of the European Parliament. 051015202530ESMTPTITROUKEUBGBEFRHUELCYDEEELVIEDKFINLLUATSELTPLCZSKSIHR2012National targetHeadline target5.5 million young people have left school without finishing upper secondary education  26 Figure 3.2. Early school leaving: current performance and recent change       Source: JRC-CRELL and DG EAC calculations based on Eurostat (LFS) data. Member States having already achieved their national targets are marked in green. Countries are shown according to their 18-24 cohort size, with five categories. Further notes: the average annual change rate is artificial for countries with a break in series, i.e. NL (2010) and LV (2011).  In terms of current performance and recent change regarding the rates of early leavers from education and training, four groups of Member States can be distinguished. Firstly, Member States with early school leaving rates above 10% in 2012 in addition to little progress or even stagnation in recent years. Amongst these countries, IT, DE, FR and CY are falling behind the minimum progress necessary for the EU as a whole to reach the headline target by 2020. Of these four Member States, the early school leaving rate in IT is by far the highest, resulting in a 2013 country-specific recommendation60 to step up efforts to prevent early school leaving.  In this same group, BE, RO and HU are faring even worse; early school leaving rates in these countries have actually been increasing in recent years. In the 2013 country-specific recommendations, RO and HU have been urged to implement a national strategy on early school leaving. BE, in the meantime, has been taking steps towards a comprehensive strategy61.  Secondly, Member States with early school leaving rates above 10% but nevertheless significant progress in recent years. This group, found in the upper left quadrant of Figure 3.2, can be divided into two parts.  Despite considerable progress in recent years, ES (24.9%), MT62 (22.6%) and PT (20.8%) still have rates above 20%. ES and MT display the highest early school leaving rates amongst all Member States and have been asked in the 2013 country-specific recommendations to stregthen their efforts to tackle the problem, notably by setting up more comprehensive monitoring systems. PT has achieved the strongest improvement of all countries since 2009.  Early school leaving rates in UK, BG, EL, EE and LV are above 10% but have decreased significantly in recent years. In these countries, the average annual change rate between 2009 and 2012 has been higher than the minimum progress required for the EU as a whole to meet the headline target.                                                 60   The 2013 country-specific recommendations, approved by the Council, can be found at:   http://ec.europa.eu/europe2020/making-it-happen/country-specific-recommendations/index_en.htm. The package was adopted by the Council on 19 June 2013.    61   See the country report on BE that accompanies this Education and Training Monitor at:   http://ec.europa.eu/education/monitor. 62   The Maltese series on early leavers from education and training have been revised. The revision concerns the classification of certain qualifications at secondary level. No new national target has been set as of yet. BG CZ DK DE EE IE EL ES FR IT LV LT LU HU MT NL AT PL PT RO SI SK FI SE UK BE HR EU CY 0510152025-14,0-12,0-10,0-8,0-6,0-4,0-2,00,02,04,0Average annual change in early school leaving rate (%) over the period 2009-2012 Early school leaving rate 2012 Headline target Minimum progress needed Improving   |   Getting worse In Belgium, Romania and Hungary, early school leaving rates have been increasing  Thirdly,  Member  States  that  show  early  school  leaving  rates  below  10%  but  stagnation  in  recent 
years. In CZ, LU, SE, PL, HR and SK, the rate of early school leaving has even increased. Amongst 
these countries, PL is still to reach its national target of 4.5%. 

Table 3.1. Early leavers from education and training (%) 

2009 

Total 

Total 

Males 

Females 

EU28 
Belgium 
Bulgaria 
Czech Republic 
Denmark 
Germany 
Estonia 
Ireland 
Greece 
Spain 
France 
Croatia 
Italy 
Cyprus 
Latvia 
Lithuania 
Luxembourg 
Hungary 
Malta 
Netherlands 
Austria 
Poland 
Portugal 
Romania 
Slovenia 
Slovakia 
Finland 
Sweden 
United Kingdom 
Montenegro 
Iceland 
MK 
Serbia 
Turkey 
Norway 
Switzerland 

14.2 
11.1 
14.7 
5.4 
11.3 
11.1 
13.9 
11.6 
14.5 
31.2 
12.2 
3.9 
19.2 
11.7 
13.9 
8.7 
7.7b 
11.2 
27.1n 
10.9 
8.7 
5.3 
31.2 
16.6 
5.3 
4.9 
9.9 
7.0 
15.7 
: 
21.3 
16.2 
: 
44.3 
17.6 
9.1d 

12.7p 
12.0 
12.5 
5.5 
9.1 
10.5p 
10.5 
9.7 
11.4 
24.9 
11.6 
4.2 
17.6 
11.4 
10.5 
6.5 
8.1p 
11.5 
22.6 
8.8p 
7.6 
5.7p 
20.8 
17.4 
4.4 
5.3 
8.9 
7.5 
13.5 
: 
20.1 
11.7 
: 
39.6 
14.8 
5.5 

14.4p 
14.4 
12.1 
6.1 
10.8 
11.1p 
14.0 
11.2 
13.7 
28.8 
13.4 
(4.6) 
20.5 
16.5 
14.5 
8.2 
10.7p 
12.2 
27.5 
10.2p 
7.9 
7.8p 
27.1 
18.0 
5.4 
6.0 
9.8 
8.5 
14.6 
: 
23.6 
11.1 
: 
36.1 
17.6 
5.7 

10.9p 
9.5 
13.0 
4.9 
7.4 
9.8p 
7.1 
8.2 
9.1 
20.8 
9.8 
(3.6) 
14.5 
7.0 
6.2 
(4.6) 
5.5p 
10.7 
17.6 
7.3p 
7.3 
3.5p 
14.3 
16.7 
(3.2) 
4.6 
8.1 
6.3 
12.4 
: 
16.5 
12.3 
: 
43.0 
11.9 
5.3 

2012 

Native-
born 

11.5p 
10.6 
12.6 
5.5 
9.0 
9.1p 
10.6 
9.2 
8.3 
21.4 
10.8 
4.2 
14.8 
8.1 
10.6 
6.4 
7.1p 
11.4 
22.7 
8.6p 
6.0 
5.7p 
20.9 
17.4 
4.2 
5.3 
8.7 
6.7 
13.7 
: 
19.3 
: 
: 
: 
14.6 
3.7 

Foreign-born 

EU 

Non EU 

22.8p 
17.4 
: 
(10.0) 
: 
: 
: 
15.1 
(24.7) 
39.1 
23.5 
: 
35.4 
21.6 
: 
: 
(11.1) 
: 
: 
13.0p 
(10.2) 
: 
: 
: 
: 
: 
: 
(10.3) 
16.1 
: 
32.6 
: 
: 
: 
20.1 
8.9 

26.5p 
26.0 
: 
(8.5) 
(11.7) 
: 
: 
: 
45.8 
41.1 
22.7 
: 
40.5 
19.5 
: 
: 
: 
: 
: 
11.9p 
21.5 
: 
19.4 
: 
(10.3) 
: 
: 
13.1 
9.9 
: 
: 
: 
: 
: 
15.3 
17.1 

2020 

Target 

< 10.0 
9.5 
11.0 
5.5 
< 10.0 
< 10.0 
9.5 
8.0 
9.7 
15.0 
9.5 
4.0 
15.0-16.0 
10.0 
13.4 
< 9.0 
< 10.0 
10.0 
- 
< 8.0 
9.5 
4.5 
10.0 
11.3 
5.0 
6.0 
8.0 
< 10.0 
- 
- 
- 
- 
- 
- 
- 
- 

Sub- 
total 
25.4p 
22.6 
: 
(9.3) 
10.1 
: 
: 
12.3 
42.0 
40.7 
22.9 
: 
39.1 
20.7 
: 
: 
10.6p 
: 
: 
12.2p 
17.7 
: 
20.3 
: 
(10.1) 
: 
(14.9) 
12.8 
12.2 
: 
28.1 
: 
: 
: 
17.1 
14.1 

Source: Eurostat (LFS). Intermediate breaks in time series for NL (2010) and LV (2011). Notes: "b" = break in time series; "p" 
= provisional; "()" = Data lack reliability due to small sample size; ":" = data either not available or not reliable due to  very 
small sample size; “d” = definition differs; “n” = national data. 

Fourthly,  Member  States  that  have  early  school  leaving  rates  below  10%  and  have  also  made 
significant further progress in recent years. In this group, LT, NL, DK, AT, FI, IE and SI all show a 
decreasing trend while already having reached the headline target. Amongst these countries, IE, FI 
and NL have not yet met their national target, which is set at, or below, 8% for all three. 

In terms of policy development, the above mentioned groups of countries face different challenges 
depending on their education and training systems, economic situation and structure of local labour 
markets.  Although  there  is  an  overall  tendency  to  address  early  school  leaving  in  a  more 
comprehensive  manner,  few  Member  States  have  developed  and  implemented  comprehensive 
strategies  to  tackle  the  problem63.  NL  and  IE  have  had  comprehensive  approaches  to  reducing 
early  school  leaving  rates  for  some  years.  AT  has  recently  adopted  a  new  strategy  to  tackle  the 
problem  and  BG  and  MT  are  about  to  do  so.  FR  has  significantly  increased  its  commitment, 

63  

  As  suggested  in  the  Council  Recommendation  on  policies  to  reduce  early  school  leaving  (2011/C  191/01),  the 
Commission  Communication  "Tackling  early  school  leaving:  A  key  contribution  to  the  Europe  2020  Agenda" 
(COM(2011)18), and the Commission working document "Reducing early school leaving" (SEC(2011)96). 

27 

 
 
 
 
 
 
 
 
                                               
 28 improving the evidence-base for identifying young people at risk and ensuring a broad range of measures in the area of prevention, intervention and compensation.  Other policies adopted across Europe that can help tackle early school leaving include measures addressing the specific needs of children with a migrant background (BE fr, FI, CZ, FR, UK); measures to reduce early tracking (MT, AT) and grade retention (BE fr, LT); and measures to improve vocational education and training (VET) systems. The latter includes improving guidance systems (LV, LT); facilitating the transition to the labour market (FI, NL); and strengthening the permeability between general and vocational education (MT, PL). PT and ES have increased access to VET especially for students struggling in general education.  The gender pattern in the early school leaving rate  Taking a closer look at the early leavers from education and training, a striking disparity remains between male and female early school leaving rates, with boys clearly at higher risk of leaving school before finishing upper secondary education than girls (Table 3.1). The male/female difference has slowly decreased over time (from 3.8 percentage points in 2009 to 3.5 percentage points in 2012), but is still prominent in all Member States except BG. The disparity is greatest in CY, LV and PL, with male early school leaving risks more than twice as high as those for females. Between 2009 and 2012, the gender divide has increased most in LV, CY and LU and decreased most in SI, IE and DK. These gender patterns coincide with overall differences between boys and girls in education attainment and needs further reflection.  The disadvantage for foreign-born students  It is found that across the EU, early school leaving rates amongst the foreign-born population are more than twice as high as the early school leaving rates for the native-born population, hinting at worrysome socioeconomic discrepancies between the two groups. The native-born/foreign-born disparity has slightly decreased (from 14.7 percentage points in 2009 to 13.9 percentage points in 2012), but is still astounding in a number of Member States64. The difference is by far worst in EL, followed by AT, IT and CY. Calculations show that the EU as a whole would be 30% closer to reaching its Europe 2020 target of reducing the early school leaving to below 10% if the gap between foreign-born and native-born were closed, and some countries would even meet their national targets65. Identifying ways of tackling the problem, a recent study on newly arrived migrant children demonstrated that inclusive education systems are better equipped to integrate migrant children successfully and to support them effectively in school education66.  The increasing age effect in early school leaving rates  When looking at the early school leaving rates by age, the analysis shows that (1) early school leaving rates increase with age and that (2) every birth cohort yields on average lower risks of leaving school early when compared to the previous birth cohort. However, the data also suggests that the decrease in early school leaving rates between 2009 and 2012 has not been the same across the 18 to 24 year old age group. As Figure 3.3 illustrates, Europe has on average been most successful in tackling early school leaving amongst 18- and 19-year-olds (a decrease of 17.6% and 16.1% respectively). Amongst 23- and 24-year-olds, on the other hand, progress has been much more difficult (a decrease of 6.1% and 8.4% respectively).  These results imply that schools manage to keep students in education longer, whether because of policies against early school leaving or because of the on-going crisis. But the limited change for 23- and 24-year olds implies that Europe on average has not found a way to attract individuals back into education and training, be it                                                64   It has to be noted that across Europe, the foreign-born sub-group is very diverse, affected by historical migration patterns that are often incomparable between Member States. Some of the foreign-born early school leavers (age group 18 to 24) did not even go to school in the host country. Moreover, the categorisation of foreign-born early school leavers confounds related issues, such as language spoken at home, socioeconomic status and access to learning support. 65   Based on a report prepared for the Directorate-General for Home Affairs, Using EU Indicators of Immigrant Integration (http://ec.europa.eu/ewsi/UDRW/images/items/docl_37216_243039941.pdf). 66   Authored in 2013 by the Public Policy and Management Institute (PPMI) on behalf of the European Commission (http://ec.europa.eu/education/more-information/doc/migrants/report_en.pdf). Vocational pathways are being explored in order to reduce early school leaving rates  Schools increasingly manage to keep students in education longer...  29 formal or non-formal. Otherwise the progress in the older age groups would have been much stronger.   Figure 3.3. Early school leaving trends by age (2009-2012)  Source: Eurostat (LFS). Note: the dashed bars on top of the 2012 early school leaving rates denote the respective rates for 2009, 2010 and 2011 (from top to bottom).  Non-formal learning amongst early school leavers  Early school leavers are by definition no longer in formal education or in non-formal education. Some of the 18 to 24 year-olds with lower secondary education attainment at most, however, are not in formal education anymore but do follow some kind of non-formal training (see Figure 3.4). These individuals are not counted toward a country’s early school leaving rate. Non-formal learning, however, can function as a second chance for individuals leaving formal education early67. Figure 3.4 shows that non-formal learning is not prevalent amongst 18 to 24 year olds. There is untapped potential here that could help low-schooled individuals improve their chances on the labour market.   Figure 3.4. Early school leaving: breakdown by employment status (2012)   Source: Eurostat (LFS). Notes: Countries are ranked in ascending order of early school leaving rates. **Not counted towards the early school leaving rate.                                                  67   See the report Learning from second chance education: making use of good practices in second chance education to prevent early school leaving, authored for the European Commission by the Ecorys consortium. 02468101214161818192021222324Early school leaving rate (%) Age 0,05,010,015,020,025,030,035,040,045,0ESMTPTITROUKEUBGBEFRHUELCYEELVDEIEDKFINLLUATSELTPLCZSKSIHRTRISNOMKCHUnemployedInactiveEmployedNon-formal learning (including second-chance programmes)**… But second chance education remains under-exploited  17.6% decrease since 2009 16.1% decrease since 2009 12.3% decrease since 2009 10.5% decrease since 2009 11.5% decrease since 2009 6.1% decrease since 2009 8.4% decrease since 2009  30 Unemployment amongst early school leavers  Figure 3.4 also shows the employment status of early leavers from education and training. Across the EU, the unemployment rate amongst early school leavers was 40.1% in 2012, against an overall youth unemployment rate of 22.8%68. Studies show that these heightened unemployment risks are part of a cascade of events that often starts long before an individual leaves the education and training system and continues long thereafter with lengthier and more frequent unemployment spells, more unattractive working conditions, and higher risks of social exclusion69.   The road to 2020  Analysis using a new econometric model developed by the European Commission's Joint Research Centre (JRC)70 shows that the development of early school leaving over time and across Europe is strongly affected by parental education and the risk of subsequent unemployment. Assuming that these effects remain the same in the near future, and taking into account the projected changes in education of the parental cohort and the unemployment risks, it is possible to forecast the rate of early school leavers up to 2020 in a way that is more meaningful than a rudimentary linear trend (see Figure 3.5).   Figure 3.5. Early school leaving: forecast and linear trend  Source: JRC-CRELL. Notes: the fan chart depicts a 30% confidence interval, with light blue shading added for the 60% confidence interval. The dashed line denotes the linear trend.  Based on the model set-up described above, the current forecasting exercise paints a relatively optimistic picture for the majority of Member States as regards their likelihood of reaching the national targets listed in table 3.1. The results show that 15 Member States have a high probability (AT, LU, SE, SI) or quite high probability (BG, CY, DK, FR, EL, IE, IT, LT, LV, NL SK) of reaching the national targets. 7 other Member States (BE, CZ, DE, EE, FI, HU, PL) have 2020 forecasts which draw close to the targets, meaning that the chances of reaching the targets could be labelled only as “fair”. The remaining countries (ES, PT and RO) have a low (<35%) probability of reaching their national targets for early school leaving. Evaluating Member States against the EU-wide target of “below 10%” provides more or less the same distribution of probabilities.  Of course, these forecasts merely provide us with a simulation of the probable development in early school leaving rates if policy does not change in the meantime. For the strong performers this means that current efforts will have to be sustained until 2020 and for the weak performers this means there is still the opportunity to strengthen efforts and introduce comprehensive policy measures. This section points towards the need for flexible pathways that increase access to work-                                               68   Individuals below the age of 25. 69   Reducing Early School Leaving in the EU (2011). 70   The econometric model is the result of a first exercise undertaken by the JRC’s Centre for Research on Lifelong Learning (CRELL), based on a methodology that is to be further refined in the future. For the full technical report, see https://crell.jrc.ec.europa.eu. 051015202520002005201020152020Future success in tackling early school leaving hinges on the awareness of unemployment risks  The unemployment rate amongst early school leavers is almost twice the overall youth unemployment rate   31 based learning or enable individuals to re-enter formal and non-formal education and training. It also suggests that the very real medium-term and long-term labour market disadvantage needs to be better understood by individuals at risk of leaving school early71.   3.2. Improving early childhood education and care  The different benefits of early childhood education and care (ECEC) on both an individual and societal level is increasingly acknowledged across Europe. Firstly, for today’s young children, ECEC can considerably help to provide a strong start in education attainment and achievement and an indispensable preventative measure against early school leaving. By guaranteeing a solid foundation in a child's formative years, ECEC paves the way for successful lifelong learning, social integration and personal development. It increases the equity of educational outcomes and thus helps to break a cumulative cycle of disadvantage. Secondly, on today’s labour market, countless second earners are helped by the provision and affordability of ECEC. Parental labour market participation is facilitated by ECEC, providing a large cohort of young parents a more flexible working arrangement.  The 2013 country-specific recommendations on ECEC approach the topic from two different angles. Some Member States (AT, CZ, RO, SK, UK) are urged to widen ECEC access to low-income households and other disadvantaged groups, thereby tackling inequities in the education and training systems early on. Other Member States (DE, HU, IT, MT, PL) received a country-specific recommendation in the context of parental labour market participation and are asked to remove disincentives for second earners.   The corresponding ET 202072 benchmark is to ensure that at least 95% of children between the age of four and the age for starting compulsory primary education73 participate in ECEC74. The latest available data show that in 2011, the EU average ECEC participation was already 93.2%; 0.8 percentage points up from the previous year. Some Member States have ECEC participation rates at or close to 100% (ES, FR, MT, IE, NL). Others show lower rates (FI, EL, SK, PL), but this is partly due to the availability of alternative types of provision such as family day care. This asks for a more qualitative, system-level look at ECEC arrangements.  Comparing the 2011 ECEC rates with their recent development (2008-2011) reveals the particularities of this ET 2020 benchmark and enables us to distinguish between four groups of Member States (see figure 3.6). Firstly, a number of countries in the lower left quadrant have ECEC rates below the 95% target and on top of that an average decrease in their ECEC rates between 2008 and 2011 (SK, RO, CY, CZ, EE).  A second group of Member States is formed by EL, FI and HR, which are making progress, but not enough to have a reasonable chance of reaching the 95% target by 2020. These countries are on the positive side of the minimum progress required, but this threshold applies to the EU as a whole, which is already very close to its target. Thirdly, there are Member States with relatively low ECEC rates in 2011 while recording a 2008-2011 progress that is indeed likely to be sufficient for them to reach the 95% target by 2020 (LT, BG, PL).  The fourth and final group is made up of countries that are close to or beyond the 95% target. This includes a number of Member States that are hardly improving for the simple reason that they are approaching an ECEC rate of 100% (FR, ES, BE, UK, DE, IT, LU, SE and HU), but also Member States that are close to or beyond the 95% target while still making progress (DK, PT, AT, LV and –                                                71  A large scale FP7 research project called RESL.eu – reducing early school leaving in the EU – is currently collecting and comparing data in 9 EU countries (see: resl-eu.org). 72   ET 2020: A strategic framework for European cooperation in education and training (2009/C 119/02). 73   As of the school year 2012/2013, the age for starting compulsory primary education is: 4 years in CY, LU, UK-NIR; 5 years in EL, LV, HU, MT, NL, PL, UK-ENG/WLS, UK-SCT; 6 years in BE, CZ, DE, DK, IE, ES, FR, IT, AT, PT, RO, SI, SK, HR; and 7 years in BG, EE, LT, FI, SE. More details can be found at:   http://eacea.ec.europa.eu/education/eurydice/documents/facts_and_figures/compulsory_education_EN.pdf. 74   An alternative indicator is used for the Barcelona objectives set by the European Council in 2002, which aims to provide by 2010 childcare to at least 90% of children between 3 years old and the mandatory school age and to at least 33% of children under the age of 3. For a recent report on the Barcelona objectives, see: http://ec.europa.eu/justice/gender-equality/files/documents/130531_barcelona_en.pdf. Romania, Slovakia, the Czech Republic, Cyprus and Estonia are making no progress in ECEC participation   32 to a lesser extent – SI). Since some of the larger Member States are part of this group, the weighted EU average is also very close to it.   Figure 3.6. Early childhood education and care: current performance and recent change     Source: JRC-CRELL and DG EAC calculations based on Eurostat (UOE) data. Notes: Countries are shown according to their 5-6 cohort size, with five categories. MT has been excluded from this scatterplot as its 2011 ECEC rate is – due to a break in series – unrelated to its 2008-2010 percentage change. IE is excluded because of methodological revisions in 2010 and 2011. EL is included only with its 2010-2011 percentage change.  The road to 2020  Even a simple linear trend is enough to see that the ET 2020 target of 95% should be reached before 2020. After all, the 2011 ECEC rate was only 1.8 percentage points away from the target. With universal ECEC as a plausible scenario for the not too distant future, it becomes all the more important to focus not on the participation of ECEC but rather the quality of ECEC provision. As will be emphasised in section 3.4, many of the benefits of ECEC participation is conditional on the quality of provision and the early learning activities children are engaged in. Recent developments in the field of ECEC have indeed been focusing on factors affecting quality75. Here, the evidence-base needs to be strengthened by providing internationally comparable data closely examining the question of quality; what is the nature of activities in which children are engaged and who is providing the support?  In this context, various projects are currently underway76. A forthcoming Eurydice report, Key Data on ECEC 2014, draws on existing research in order to provide insights into what constitutes high quality ECEC. Based on the data collected for the report and the reforms captured through                                                75   The thematic working group on ECEC working within the Open Method of Coordination is addressing quality issues set out in the latest policy documents (COM(2011)66 final and OJ 2011/C 175/03). The group is currently developing a European Quality Framework that will cover areas such as access, workforce, curriculum, evaluation and monitoring, and funding.  76   Apart from the Eurydice work mentioned here, the OECD and the International Association for the Evaluation of Educational Achievement (IEA) are also conducting research on the quality of ECEC provision. In order to collect more data on ECEC for international comparison and consolidate information on how countries measure quality and assess their progress in improving it, the OECD Review of Policies and Practices for Monitoring and Evaluating Quality in Early Learning and Development is being carried out from 2013-14. Parallel to this, the IEA cross-national Early Childhood Education Study will collect information on the systems, contexts, and results of early childhood education from a range of sources enabling the development of indicators in three key dimensions: availability, reach, and inclusion; quality; and outcomes. BG CZ DK DE EE EL ES FR IT LV LT LU HU NL AT PL PT RO SI SK FI SE UK BE HR EU CY 707580859095100-3,0-2,0-1,00,01,02,03,04,05,06,0Average annual change in ECEC rate (%) over the period 2008-2011 The quality of ECEC provision should be prioritised by strengthening the evidence-base and following up with annual monitoring  ET 2020 benchmark Early childhood education and care rate 2011 Getting worse   |   Improving Minimum progress needed  33 Eurypedia77, it is clear that steps are being taken in an effort to improve the quality of provision provided for young children including reviewing central guidelines, revising child/staff ratios, increasing the number of specialised staff and reforming governance aspects. Finally, most European countries have implemented measures to support disadvantaged children in ECEC, varying from language training through to the provision of additional staff or funds.    3.3. Strengthening the teaching profession  Teaching staff are arguably the most important in-school factor affecting the learning outcomes of students. They have an indispensable role to play in any intervention measure tackling early school leaving, whether related to school climate, supportive and individualised learning environments, early warning systems, or cooperation with parents. Moreover, the salaries of teachers account for around 70% of current spending on education. Within the context of increased pressure on public budgets and the irrefutable role of teaching staff in the performance of education and training systems, the investment in the teaching profession should be made in the most effective and efficient way, fostering a high quality, well-educated and well-led teaching workforce78.  Member States need to establish or indeed reinforce mechanisms not only to attract, select and recruit the best candidates, but also to educate them well and ensure they are supported in their professional development throughout their careers. In 2013, three Member States received country-specific recommendations on the teaching profession, urging them to improve the quality of teaching (PL), reform teachers’ professional and career development (IT) and to attract young people into the profession (SK).  Structured induction programme  A structured induction programme, providing professional, social and personal support in the early years, is one mechanism that can help newcomers adjust to the profession, improve overall quality, and tackle the issue of teacher retention faced by several countries. In only 16 Member States (DE, EE, IE, FR, IT, HR, CY, LU, MT, AT, PT, RO, SI, SK, SE, and UK) do teachers beginning their career have access to a structured induction programme, usually directly after gaining their qualification. In FR, IT, LU, MT, PT and UK induction is also considered a probationary period and thus linked to obtaining a permanent contract. In most countries, with the exception of MT and AT, induction applies to all beginning teachers at all levels of education.   Continuing professional development  On-going, individualised professional learning is fundamental and while it has gained considerable importance over the years it warrants further action79. It is now considered a professional duty in 28 education systems. In 8 European education systems, teacher participation in continued learning is clearly linked to promotion or a system of advancement for a higher grade. However, in only six Member States (LU, HU, MT, PT, RO and FI) are the exact minimum number of hours each teacher is expected to attend courses specified and in just three Member States (NL, SI and UK-SCT), a minimum number of hours for continued learning is considered a right.   Quality leadership  The quality of leadership has been shown to affect both the motivation and quality of teaching. Student achievement on PISA tests was higher when teaching staff were held accountable through the involvement of school leaders and external inspectors in monitoring lessons. It is therefore vital that countries ensure that adequate systems are in place to induct school leaders and support them in their role, but the picture across Europe is extremely diverse and these systems are currently few and far between. Furthermore, continuing professional development for school                                                77   European encyclopaedia on national education systems; see:   https://webgate.ec.europa.eu/fpfis/mwikis/eurydice/index.php/Main_Page. 78   Findings in this section are taken from Eurydice (2011/12), Teachers' and School Heads' Salaries and Allowances in Europe and Eurydice (2013), Key data on Teachers and School Leaders in Europe. 79   The results of the OECD Teaching and Learning International Survey 2013 (TALIS) will be released in June 2014 and will provide key data on the professional development of teachers.  Only in the Netherlands, Slovenia and Scotland, teacher’s continued learning is considered a right   34 leaders is key to enabling them to cope with a changing leadership profile and increased responsibilities.   Teacher educators  Those responsible for educating teachers should themselves have attained a high academic standard and possess solid practical experience of teaching, as well as the competences that good teaching requires. However, in most Member States there is little explicit policy provision either to define what quality means in the work of a teacher educator, or what are the necessary recruitment and selection requirements. Few Member States have set standards for teacher educators or defined the competences required to be allowed to work as a teacher educator. Almost no Member States collect data about this key profession.  Demographic change  Rethinking how we attract, educate and support teachers, school leaders and teacher educators is a hugely pressing issue, with the teaching profession across Europe strongly affected by demographic trends. As can be seen in Figure 3.7, in many Member States, the majority of teachers currently in employment are in the highest age brackets (40-49 and older than 50). In IT, DE, EE and NL, for example, more than 45% of the teaching workforce is in the 50+ category and in IT, BG, DE and ES there are very few teachers under the age of 30.    Figure 3.7. Age distribution of teachers in lower and upper secondary education (2011)  Source: Eurostat (UOE). Online data code: educ_thpertch. Note: Teachers in public and private institutions at ISCED level 2-3.  The current demographic profile of teachers in Europe means that some Member States will shortly have to recruit large numbers of new teaching staff – in all subjects – to fill the gap left by a wave of teacher retirement. This pending wave of retirements, coupled with the relatively low status of the teaching profession in many countries, and a declining number of applicants for teacher education, could lead to serious teacher shortages80 and risks accentuating the lack of adequately trained staff in subjects such as science, maths, ICT and foreign languages.   3.4. Laying the foundations for skills development  This final section assesses the determinants of education achievement, represented by basic skills – reading, mathematics and science – and foreign language skills. Ensuring that these foundation skills are achieved by all will serve to level the playing field and is a gateway to employment and social inclusion.                                                  80   See Eurydice (2013), Key Data on Teachers and School Leaders    (http://eacea.ec.europa.eu/education/eurydice/documents/key_data_series/151EN.pdf). 0%10%20%30%40%50%60%70%80%90%100%MTPTCYPLUKLUROESSIIEFRBEHUFISKCZSELTLVBGATNLEEDEITCHNOISTeachers aged below 30Teachers aged 30-39Teachers aged 40-49Teachers aged 50 and overIn Italy, Germany, Estonia and the Netherlands, more than 45% of the teaching workforce is aged 50 years or more The determinants of basic skills 

Achievement  in  reading,  maths  and  science  has  been  the  cornerstone  for  comparative  surveys  in 
the  field  for  many  years.  The  next  results  from  the  OECD’s  Programme  for  International  Student 
Assessment  (PISA)  are  expected  by  the  end  of  2013  and  will  provide  an  update  on  the 
performance of Member States in relation to the ET 2020 benchmark on basic skills, which states 
that by 2020, the share of 15 year-olds with low achievement in reading, mathematics and science 
should be less than 15%81. The IEA82’s PIRLS83 and TIMSS84 focus on comparable skills of younger 
pupils85.  Across  the  EU  Member  States  participating  in  these  surveys,  19.8%  fails  to  reach  a 
minimum  threshold  of  literacy  skills,  versus  28.5%  in  mathematics  and  25.2%  in  science  (see 
Table 3.2)86. 

Table 3.2. Pupil achievement in reading, maths and science (2009, 2011) 

Reading 

Mathematics 

Science 

FAILING IIB* in 
PIRLS 2011 
19.9 
- 
29.6 
- 
22.9 
12.7 
11.7 
15.4 
14.9 
27.6 
24.8 
10.2 
15.0 
20.1 
18.9 
44.8 
9.9 
19.6 
23.2 
16.0 
34.8 
20.5 
17.8 
7.9 
14.7 
- 
17.3 
13.4 

FAILING LEVEL 2 
IN PISA 2009 
19.6 
17.7 
23.3 
13.4 
41.0 
23.1 
15.2 
18.5 
17.2 
19.6 
19.8 
22.5 
21.0 
24.3 
17.7 
36.3 
14.3 
27.5 
15.0 
17.6 
40.4 
21.2 
22.3 
8.1 
17.4 
18.4 
18.4 
17.5 

FAILING IIB* in 
TIMSS 2011 
28.5 
- 
- 
10.8 
- 
28.2 
18.1 
19.3 
23.4 
43.8 
- 
39.6 
31.3 
20.9 
29.6 
36.9 
11.6 
29.6 
44.4 
19.5 
43.0 
28.0 
31.2 
15.3 
31.5 
- 
22.4 
15.0 

FAILING LEVEL 2 
in PISA 2009 
22.2 
19.1 
26.0 
13.5 
47.1 
22.3 
17.1 
18.6 
20.8 
23.7 
22.5 
33.2 
24.9 
26.2 
22.3 
33.7 
13.4 
23.2 
20.5 
23.7 
47.0 
20.3 
21.0 
7.8 
21.1 
20.2 
19.8 
21.4 

FAILING IIB* in 
TIMSS 2011 
25.2 
- 
- 
27.3 
- 
19.0 
22.0 
22.0 
28.3 
32.5 
- 
24.8 
24.2 
26.7 
22.1 
59.4 
14.1 
21.0 
33.2 
24.8 
34.0 
25.6 
21.1 
7.9 
21.0 
- 
24.5 
25.7 

FAILING LEVEL 2 
in PISA 2009 
17.7 
18.0 
24.7 
12.9 
38.8 
17.3 
16.6 
14.8 
15.2 
18.2 
19.3 
18.5 
20.6 
17.0 
14.1 
32.5 
13.2 
21.0 
13.1 
16.5 
41.4 
14.8 
19.3 
6.0 
19.1 
15.0 
14.8 
16.7 

EU** 
BE 
  BE fr 
  BE nl 
BG 
CZ 
DK 
DE 
IE 
ES 
FR 
HR 
IT 
LT 
HU 
MT 
NL 
AT 
PL 
PT 
RO 
SI 
SK 
FI 
SE 
UK 
  UK-ENG 
  UK-NIR 

Source: OECD (PISA 2009), ACER (PISA 2009+) and IEA (PIRLS 2011 and TIMSS 2011). Notes: * Intermediate International 
Benchmark. ** Weighted EU average is based on 25 Member States for PISA, 23 for PIRLS and 21 for TIMSS. 

In  terms  of  low  achievement  in  reading,  MT  and  RO  show  the  most  unfavourable  results,  with  FI 
and  NL  at  the  other  extreme.  Underperformance  in  mathematics  is  most  common  in  PL,  ES,  RO 
and  HR  (the  latter  showing  a  stark  contrast  with  its  favourable  reading  results)  and  least 
pronounced in BE nl and NL. When it comes to science there is a strong diversity between Member 
States,  with  MT  showing  by  far  the  highest  rate  of  underperformance  and  FI  showing  by  far  the 
lowest rate of underperformance. 

81  

82  
83  
84  
85  

86  

  For the latest available PISA data (2009) see the summary table in chapter 1 and the country reports that accompany 

this Education and Training Monitor (http://ec.europa.eu/education/monitor). 

  International Association for the Evaluation of Educational Achievement. 
  Progress in International Reading Literacy Study. 
  Trends in International Mathematics and Science Study. 
  Both  TIMSS  and  PIRLS  focus  on  the  foundation  skills  of  pupils  in  fourth  grade  (not  below  9.5  years  old).  Although 
PISA adopts a different assessment framework and has a different performance scale than TIMSS and PIRLS, the two 
approaches aim to rest the same underlying theoretical constructs, and both include certain benchmark performance 
levels.  

  Arguably most comparable to PISA Level 2 – used as the achievement threshold for the ET 2020 benchmark on basic 
skills  –  is  the  Intermediate  International  Benchmark  in  TIMSS  and  PIRLS.  Reaching  this  level  means  students  can 
retrieve  information,  make  straightforward  inferences,  use  some  presentational  features  and  begin  to  recognize 
language  features.  For  maths  and  science  it  means  students  can  apply  basic  mathematical  knowledge  in 
straightforward situations and have a basic knowledge and understanding of practical situations in the sciences.  

35 

 
 
 
 
 
 
 
 
                                               
 36 More importantly for the purposes of this section, TIMSS 2011 and PIRLS 2011 feature an extensive background questionnaire that provides a wealth of information on the various underlying drivers of student achievement in reading, maths and science87. As regards student background, attending ECEC and – more specifically – engaging in early literacy and numeracy exercises before starting primary school prove to be crucial in raising later achievement. This strengthens the argument not only for universal participation in early childhood education and care, but also for a closer look at the quality of its provision (section 3.2).  Household resources for learning, covering parental education, parental occupation, books in the home and study supports, are also strongly related to the development of these foundation skills. The equity dimension that transpires through this finding emphasises the need to level the playing field as early as possible. This again has implications for quality ECEC provision, specifically targeted towards low-income families and other disadvantaged groups.  When it comes to schools, resource shortages clearly affect reading, maths and science achievement. The TIMSS 2011 data show that the percentage of grade 4 students attending a school in which the head indicated that they are sometimes affected by a shortage or inadequacy of teachers with a specialisation in science was greater than 15% in the majority of participating countries. In IT, MT, NL and PT, these percentages were highest, between 30% and 40%88. School heads themselves, meanwhile, positively affect overall achievement outcomes with a commitment to academic success, lending credence to the importance of leadership as emphasised in the previous section.  But it is also the school climate that influences overall achievement scores. Problems with school discipline and safety are strongly related to low achievement. Across all participating countries in TIMSS and PIRLS, students reported that bullying – one of the school problems with a negative impact on student achievement – occurred either about monthly (32%) or about weekly (20%). Unlike school resources, school climate has been given little attention in comparative studies, even though its effect on overall achievement is at least as strong.  The determinants of foreign language skills  Poor language skills constitute a fundamental obstacle to learning mobility and domestic and international employability, preventing individuals from seizing professional opportunities abroad and in enterprises or organisations active at an international level. With this in mind, the Commission has proposed to monitor student proficiency in the first foreign language and the uptake of a second foreign language at lower secondary level89. One of the key objectives of the twofold language benchmark will not be to compare between Member States, but rather to monitor the progress of each education system over time in a comparable and transparent way.  Member States must ensure that quantity and quality of foreign language learning is scrutinised and that teaching and learning is geared towards practical, real life application90. Foreign language skills should be taken into account in the effort to equip young people with the competences needed to meet labour market demands, as reflected in the recent Communication on youth unemployment91 and a number of 2013 country-specific recommendations92.  Despite the widely acknowledged benefits of language skills, data show a strong variation with regards to foreign language teaching and learning across Member States. The results from the first European Survey on Language Competences (ESLC), published in June 2012, show that the share of pupils reaching the level 'independent user' in the first foreign language ranged from 9% in UK-                                               87   See PIRLS 2011: International Results in Reading (http://timssandpirls.bc.edu/pirls2011/international-results-pirls.html), TIMSS 2011: International Results in Mathematics (http://timssandpirls.bc.edu/timss2011/international-results-mathematics.html) and TIMSS 2011: International Results in Science.   (http://timssandpirls.bc.edu/timss2011/international-results-science.html).  88   The possible responses being: not affected; somewhat affected; affected a lot.  89   For more information on the proposal see the Commission working document Language Competence for employability, mobility and growth (SWD(2012) 327). 90   Rethinking Education: Investing in skills for better socio-economic outcomes (COM(2012) 669 final). 91   COM(2013) 447 final. 92   The 2013 country-specific recommendations, approved by the Council, can be found at:   http://ec.europa.eu/europe2020/making-it-happen/country-specific-recommendations/index_en.htm. The package was adopted by the Council on 19 June 2013. Early learning activities before primary school are crucial in the development of basic skills  37 ENG and 14% in FR to 82% in both MT and SE93. As for the second foreign language, the percentage of students learning two or more foreign languages in lower secondary education is extremely diverse across Member States (see Figure 3.8). In 2011, this was over 90% of students in CY, EL, FI, IT, LU, and RO whereas countries such as AT, HU, IE fell at the other end of the spectrum with numbers barely reaching 10%.  Secondary analysis of the ESLC data conducted by the JRC’s Centre for Research on Lifelong Learning (CRELL)94 confirms that, amongst other factors, achievement in the target language is positively influenced by: an early start to language learning; positive student perception in relation to the quality of the lessons; greater exposure to media in the target language; perceived usefulness of the target language in particular for entertainment; and parents' knowledge of the target language.   Figure 3.8. Percentage of pupils at ISCED 2 learning 2 or more foreign languages (2008, 2011)   Source: Eurostat (UOE). Online data code: educ_thfrlan. EU and EL: 2010 instead of 2011 data. AT, HR, PL and PT: 2009 instead 2008 data. No data for EE and DE available. Only languages regarded as foreign languages in the curriculum drawn up by the central education authorities are included. Languages taught outside the curriculum as optional subjects are not included.  Furthermore, the analysis reveals the strong impact of socio-economic status on language attainment. In only one participating country (NL) did socio-economic background not present any influence on students' achievement in their first foreign language. This stands to support previous research demonstrating that socio-economic status is strongly associated with a rise in proficiency levels. The equity dimension is comparable to the one found for basic skills, stressing the need for targeted support to lower-income families and other disadvantaged groups.  Within this context, Member States should step up efforts to ensure that both students and parents have a clear vision of the value of language proficiency not only to enhance, but rather to enable future development, whether educational, professional, cultural, or social. Language learning, more than any other competence, does not lend itself to a 'one size fits all' solution and national and local peculiarities will require tailored solutions taking into account historical, geopolitical and linguistic factors amongst others. Nevertheless, in addition to the basic skills discussed above, language competence should be considered part and parcel of the foundations all students should acquire to enable further learning and future development.                                                 93   See figure 6.4 in the 2012 Education and Training Monitor (SWD(2012) 373 final). The ESLC Final Report in addition to national reports for the majority of participating education systems can be found at: http://ec.europa.eu/languages/eslc/.  94   The report can be found at https://crell.jrc.ec.europa.eu. The analysis was carried out on 13 adjudicated entities that participated in the ESLC survey and have English as their first foreign language: BE fr, BG, EE, EL, ES, FR, HR, MT, NL, PL, PT, SI, SE. 0102030405060708090100BEfrUKHUATIEBGCZESBEnlHRSLSKFREULVPTSENLPLLTDKMTCYROELFIITLU20082011Foreign language proficiency is helped by early exercises before primary school  38 Policy lessons  The rate of early leavers from education and training stands at 12.7%. Schools manage to keep students in education and training longer, but an on-going problem lies in the transition from school to work – with 40.1% of early school leavers unemployed – and in second chance education – with only 0.8% of 18 to 24 year-olds in non-formal learning after having left formal education. This calls for stronger links between the worlds of work and education.  Participation in early childhood education and care (ECEC) stands at 93.2% and is close to its 2020 target of 95%. However, the evidence-base needs to be strengthened on the quality of ECEC provision and the criteria that make ECEC a strong start for individuals. New evidence shows that engaging in learning exercises prior to starting primary school proves to be crucial in raising later skills levels, in terms of both basic skills and foreign language skills.  Rethinking how we attract, educate and support teachers, school leaders and teacher educators is a hugely pressing issue, with the teaching profession across Europe strongly affected by demographic trends. In many Member States, the majority of teachers currently in employment are in the highest age brackets. In IT, DE, EE and NL, for example, more than 45% of the teaching workforce is in the 50+ category and in IT, BG, DE and ES, there are very few teachers under the age of 30.   4.  Emphasising  effectiveness  and  quality  in 
the modernisation of higher education 

Globalisation  and  technological  development  are  radically  changing  the  landscape  of  higher 
education.  Demand  for  higher  education  is  expected  to  continue  to  grow  rapidly  world-wide, 
putting  the  emphasis  on  Europe's  ability  to  keep  pace  in  modernising  higher  education  within 
Europe and vis-à-vis the competition with emerging educational powers. Higher education provides 
a  key  contribution  to  the  Europe  2020  strategy  with  Europe's  ambition  to  become  a  smart, 
sustainable  and  inclusive  economy.  The  EU  seeks  to  support  this  contribution  by  building 
partnerships  within  Europe  and  world-wide,  by  promoting  international  student  mobility,  and  by 
providing tools for ensuring compatibility and comparability for higher education institutions when 
they cross borders to co-operate with institutions in other countries95. 

The  first  part  of  this  chapter  focuses  on  the  performance  of  Member  States  in  relation  to  the 
Europe  2020  and  national  targets  for  tertiary  education  attainment  (section  4.1).  Subsequently, 
section 4.2 examines the challenge of ensuring adequate and efficient funding of higher education 
against  the  backdrop  of  the  economic  crisis.  Finally,  in  section  4.3,  attention  is  drawn  to  recent 
developments in the area of learning mobility, and in particular the pull factors attracting students 
to  study  in  EU  Member  States  including  evidence  on  students  coming  from  countries  outside  the 
EU. 

4.1. 

Increasing tertiary education attainment 

The  EU  average  employment  rate  of  recent  graduates  from  tertiary  education  is  12.1  percentage 
points  higher  than  that  of  recent  graduates  from  upper  secondary  education  (see  chapter  5)  and 
the rate of continued learning amongst adults with tertiary education attainment is double the rate 
for individuals with only upper secondary education attainment (see chapter 6). These are just two 
illustrations of the positive economic and social impacts of higher education, which, in turn, explain 
why  a  tertiary  education  attainment  rate  of  at  least  40%  is  one  of  the  Europe  2020  headline 
targets. 

Figure 4.1. Tertiary education attainment levels or equivalent, aged 30-34 (%) 

60,0

50,0

40,0

30,0

20,0

10,0

0,0

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

ISCED 5a

ISCED 5b

ISCED 6

ISCED 4 *

Headline target

National target

Source:  Eurostat  (Labour  Force  Survey).  *  The  dashed  additional  bars  for  AT  and  DE  denote  the  postsecondary  attainment 
qualifications included in the definition of their respective national targets (ISCED 4 for DE and ISCED 4/4a for AT, both national 
data).  For  FR,  the  50%  national  target  refers  to  the  age  group  17-33  years  old.  For  FI,  the  national  target  is  defined  more 
narrowly than the EU headline target and excludes technological institutes. 

The 2012 figures show that tertiary education attainment among 30-34 year olds exceeds the 40% 
benchmark  in  nearly  half  of  all  EU  Member  States.  Overall,  the  EU  average  reached  35.7%  (see 

95  

  The Communications Rethinking Education (COM (2012)) 669 final), Modernising Europe's Higher Education Systems 
(COM (2011) 567 final) and European higher education in the world (COM(2013) 499 final) underline these aspects. 
See also OECD (2012), Education Indicators in Focus #5. It highlights the remarkable expansion of higher education, 
notably in G20 countries such as Argentina, Brazil, China, India, Indonesia, the Russian Federation, Saudi Arabia and 
South Africa. 

39 

 
 
 
 
 
 
 
 
 
 
 
                                               
 40 Table 4.1), compared to 32.1% in 2009 and 23.5% in 2002. Moreover, 10 Member States have already reached their national target in this area (AT, CY, DE, DK, FI, LT, LU, LV, NL, and SE).  Figure 4.2 illustrates the current performance (2012) of Member States as regards their tertiary education attainment rate as well as recent change (2009-2012). The dashed vertical line illustrates the minimum average annual progress that would be necessary for the EU as a whole to reach the 40% target by 2020 (2.0%). While the average annual progress between 2009 and 2012 was higher (3.6%) than this minimum progress required, it should be noted that the current EU average tertiary education attainment rate is still 4.2 percentage points below target. More importantly, as illustrated towards the end of this section, a linear trend – simply extrapolating the recent pace of improvement into the future – is likely to overestimate the future development of the tertiary attainment rate across Europe.    Figure 4.2. Tertiary education attainment: current performance and recent change      Source: DG EAC and JRC/CRELL calculations based on Eurostat data. Member States having already achieved their national targets are marked in green. Countries are shown according to their 30-34 cohort size, with five categories. Further notes: the average annual change rate is artificial for countries with a break in series, i.e. MT (2010), NL (2010) and LV (2011). AT and DE are included in this chart without taking into account ISCED level 4A (AT and DE) or ISCED level 4B (DE).  On the basis of current performance and recent change, four groups of Member States can be distinguished. Firstly, Member States which are underperforming in terms of current tertiary attainment rates and in addition have not made much progress in recent years. This group contains only BG, with a current tertiary attainment rate of 26.9% and an average annual change between 2009 and 2012 of -1.2%.  Secondly, Member States that are still underperforming in terms of current tertiary attainment rates while nevertheless showing significant progress in recent years. This group is quite diverse in regard to current performance and recent change, with increases between 2009 and 2012 ranging from 2.1% (MT) to 13.5% (CZ) and current performance from 21.7% (IT) to 39.1% (PL). EE actually reached its national target in 2011 but fell slightly below the rate of 40% again in 2012.  Thirdly, Member States with high current attainment rates at, or above, the 40% level but which have lost momentum in recent years. This group includes countries like IE and FR, which have set highly ambitious national targets (IE, for instance, is the best-performing country in 2012 but is yet to reach its 60% target). Against this background, only about half of the countries in the group have reached their national targets.  BE BG CY CZ DE DK EE EL ES EU FI FR HR HU IE IT LT LU LV MT NL PL PT RO SE SI SK AT UK 15,020,025,030,035,040,045,050,055,0-2,00,02,04,06,08,010,012,014,0Further increasing tertiary attainment rates have positive returns for individuals and societies  Headline target Minimum progress needed Tertiary attainment rate 2012 Average annual change in tertiary attainment rate (%) over the period 2009-2012  41 Finally, Member States that have reached the level of the headline target of 40% and are still making significant progress (LU, SE, CY, UK, LT). These countries have also reached their national targets when set96.   Table 4.1. Tertiary education attainment (%)   2009 2012 2020 Total Total Males Females Native-born Foreign-born Target EU Non EU Sub-total EU 28 32.1 35.7 31.5 39.9 36.4 36.4 31.5 33.1 40 Belgium  42.0 43.9 37.1 50.7 46.5 49.5 24.8 33.6 47 Bulgaria  27.9 26.9 20.5 33.6 26.8 : : : 36 Czech Republic 17.5 25.6 22.4 29.1 25.5 28.3 28.0 28.1 32 Denmark  40.7 43.0 33.7 52.6 43.5 57.4 34.9 39.3 40 Germany  29.4 31.9 31.0 32.9 33.2 : : : 42 Estonia  35.9 39.1 28.1 50.4 39.2 : (34.4) (36.6) 40 Ireland  48.9 51.1 44.0 57.9 49.7 48.4 68.7 55.0 60 Greece  26.5 30.9 27.6 34.2 33.9 (19.0) 8.4 10.3 32 Spain  39.4 40.1 35.0 45.3 45.4 27.3 20.9 22.6 44 France 43.2 43.6 38.5 48.6 44.6 38.9 37.1 37.4 50 Croatia 20.6 23.7 19.4 28.8 23.9 (52.8) (14.7) (22.2) 35 Italy  19.0 21.7 17.2 26.3 24.2 12.1 10.6 11.1 26 Cyprus 45.0 49.9 43.6 55.5 56.5 40.4 39.3 39.8 46 Latvia  30.1 37.0 26.0 48.1 37.3 : : (31.8) 34 Lithuania  40.6 48.7 40.7 56.4 48.3 : : : 40 Luxembourg  46.6b 49.6 50.4 48.9 41.7 57.3 47.4 55.4 40 Hungary  23.9 29.9 24.7 35.5 29.8 (35.8) : 36.7 30.3 Malta 21.0p 22.4 20.7 24.0 21.4 : (38.2) (38.0) 33 Netherlands  40.5 42.3p 39.9 44.8 44.3 46.0 29.0 32.9 40 Austria  23.5 26.3 26.0 26.6 26.8 35.3 17.1 24.8 38 Poland  32.8 39.1p 31.9 46.5 39.1 : : : 45 Portugal  21.1 27.2 24.3 30.1 27.7 31.8 19.6 23.6 40 Romania  16.8 21.8 20.5 23.2 21.8 : : : 26.7 Slovenia  31.6 39.2 29.5 49.6 41.2 : (9.4) (12.6) 40 Slovakia  17.6 23.7 19.4 28.2 23.7 : : : 40 Finland  45.9 45.8 36.7 55.4 47.0 35.1 31.4 33.0 42 Sweden  43.9 47.9 42.4 53.7 49.1 60.9 40.3 44.8 40 United Kingdom 41.5 47.1 44.0 50.2 44.3 49.9 58.9 55.2 : Montenegro : : : : : : : : : Iceland 41.7 42.8 34.5 51.2 45.5 26.0 40.8 30.8 : MK 14.3 21.7 20.8 22.6 : : : : : Serbia : : : : : : : : : Turkey 14.7 18.0 19.8 16.2 : : : : : Norway  47.0 47.6 39.9 55.9 48.6 49.6 39.8 43.8 : Switzerland 43.4 43.8 47.2 40.5 45.1 52.0 31.6 42.1 : Source: Eurostat (LFS). Intermediate breaks in time series for MT (2010), NL (2010) and LV (2011). Notes: "b" = break in time series; "p" = provisional; "()" = Data lack reliability due to small sample size; ":" = data either not available or not reliable due to very small sample size. For AT, DE, FI and FR, see the notes below Figure 4.1.  A gender pattern in tertiary education attainment  Of the 12.4 million 30 to 34 year-olds with a tertiary education qualification, 6.8 million are women, highlighting a significant gender difference in relation to obtaining a high-level education. Moreover, this difference is increasing, up by 0.7 percentage points from 2011. In fact, women, taken as a separate group, achieved the 40% benchmark in 2012, 8 years ahead of the 2020 target date. The biggest gender differences in attainment are in EE, LV, DK, SI and FI, where the gap is approaching a 20 percentage point difference. The female tertiary attainment rate is higher in all countries with the exception of LU, CH and TR.                                                  96   UK has not defined a national target.  Gender differences in tertiary education spill over in labour market segregations Figure 4.3. Attainment by field of education (2012) 

35%

30%

25%

20%

15%

10%

5%

0%

Social
sciences;
business and
law

Engineering;
manufacturing
and
construction

Health and
welfare

Humanities;
languages and
arts

Science;
mathematics
and
computing

Teacher
training and
education
science

Services

Agriculture
and veterinary

Source: Eurostat (LFS). 

Females

Males

There are also very significant gender discrepancies in different fields of study, which inevitably has 
an  impact  on  students'  future  occupational  possibilities  (see  figure  4.3).  As  such,  segregation  or 
segmentation  in  education  paths  spills  over  into  segregation  in  the  labour  market,  with 
engineering,  scientific  fields  and  related  occupations  being  male  dominated  whereas  professions 
related  to  the  social  sciences,  education,  health  and  welfare  subjects  are  overwhelmingly  female 
dominated. 

A disadvantage for foreign-born students 

At  an  aggregate  EU  level,  there  is  also  a  significant  difference  in  tertiary  education  attainment 
levels between native-born and foreign-born individuals; the latter have a particular disadvantage 
when born in countries outside the EU (see Table 4.1). While the overall gap is shrinking (from a 
4.5 percentage point difference in 2011 to 3.5 in 2012), there is still a long way to go. The tertiary 
attainment  level  of  the  foreign-born  population  compared  to  the  native-born  population  is  higher 
only in CZ, IE, HU, LU and the UK, and the tertiary attainment rates for the native-born are double 
of those of the foreign-born population in Member States such as EL, ES and IT. 

This  points  to  some  very  visible  differences  in  the  migration  patterns  within  Europe  with  some 
countries as CZ, IE, HU, LU and UK attracting people with high skill levels, whereas other Member 
States (notably IT) attract a lower skilled work force. 

The road to 2020 

Using a simple linear trend when predicting future tertiary attainment levels can be misleading and, 
in this case, might prove overly optimistic. In reality, development of tertiary education attainment 
is driven by various underlying factors. Analysis using a new econometric model developed by the 
European  Commission's  Joint  Research  Centre  (JRC)97  has  shown  that  two  of  the  most  important 
factors affecting the development of tertiary attainment rates over time are the level of education 
of  the  parental  cohort  and  the  expected  wage  premium  gained  from  obtaining  tertiary  education 
(which  can  be  measured  using  labour  productivity  as  a  proxy).  Assuming  that  the  relationship 
between the variables remains the same in the near future, and taking into account the projected 
changes  in  education  of  the  adult  population  and  of  the  labour  productivity,  we  can  forecast  the 
rate of tertiary education attainment up to 2020 and beyond in a more meaningful way. 

The  econometric  projection  (see  Figure  4.4)  is  more  pessimistic  than  the  linear  trend  for  two 
reasons. Firstly, over the last decade, younger cohorts have not improved their level of education 
as  fast  as  older  cohorts.  As  a  consequence  of  ageing,  we  will  see  a  slower  improvement  in  the 
parental  cohort’s  average  level  of  education  in  the  years  to  come.  Secondly,  the  increase  in 
productivity (and thus the wage premium that tertiary education graduates are likely to command) 
is  slightly  lower  for  the  forecast  period  than  for  the  past,  mainly  due  to  the  on-going  economic 
crisis. This is likely to reduce the comparative advantage of completing higher education and thus 

97  

  The  econometric  model  is  the  result  of  a  first  exercise  undertaken  by  the  JRC’s  Centre  for  Research  on  Lifelong 
Learning (CRELL), based on a methodology that is to be further refined in the future. For the full technical report, see 
https://crell.jrc.ec.europa.eu/. 

42 

 
 
 
 
 
 
 
 
 
 
                                               
 43 impact on young people's study decisions. Taken together, these two underlying drivers lead to a slower improvement in the tertiary education attainment rate in the period up to 2020 than has been the case in the last decade.  At the same time, the JRC econometric model paints a relatively optimistic picture for the majority of Member States as regards their likelihood of reaching the national targets listed in table 4.1. According to the model, 15 Member States have a high probability (EE, FI, LT, LU, LV and SE) or quite high probability (CY, DK, ES, EL, HU, NL, PL, RO and SI) of reaching their national targets by 2020. 6 Member States have a fair probability (BE, BG, CZ, FR, IE and IT) and only 3 Member States have a quite low probability (MT, PT and SK) of reaching their national targets98.  This forecast only provides an illustration of the probable development in tertiary attainment rates taking into account the driving variables discussed. Moreover, it assumes policy does not change in the meantime. For the stronger performers this means that current efforts will have to be sustained and for the weaker performers there is still the opportunity to strengthen efforts and introduce comprehensive policy measures, in particular to ensure current and future student cohorts successfully complete their studies.   Figure 4.4. Tertiary education attainment: projection and linear trend   Source: JRC-CRELL. Notes: the fan chart depicts a 30% confidence interval, with light blue shading added for the 60% confidence interval. The dashed line denotes the linear trend.  Indeed, from the specific perspective of achieving the Europe 2020 headline target, the policy debate has shifted from widening access to higher education (which remains absolutely crucial with a longer term perspective) to the effectiveness of the education systems in ensuring that students who enter successfully obtain their final qualification. After all, many of 2020’s 30-34 year olds – now 23-27 - have already started or completed their tertiary education.    4.2. Meeting the challenge of effective resource allocation in higher education  For many years the number of enrolments (and graduates) in tertiary education has been rising significantly, in Europe but also elsewhere in the world. Particularly within the context of the current economic crisis, the crucial questions are whether overall levels of resources have kept pace with this increase in student numbers (to help ensure quality) and how limited resources can be spent most efficiently. We consider these issues from three perspectives: (1) the absolute level of higher education financing over time, including the latest data since the onset of the economic crisis (2) trends in the level of private resources in higher education institutions and (3) completion rates for students finishing their higher education degree as a proxy for process efficiency.                                                  98   AT and DE are not included in this summary assessment. Their inclusion of postsecondary attainment means that these forecasts would underestimate their ability to reach the national targets on tertiary education attainment. 1020304050607020002005201020152020A relatively optimistic picture for reaching the 2020 target should not hide the fact that sustained efforts are necessary  44 Level of spending on higher education  On average in the EU the expenditure per student on tertiary education (see Figure 4.5) has remained broadly stable since the economic crisis hit in 2008. The country figures, however, show somewhat divergent trends. Cuts have been made in 6 out of 11 countries below the level of EU spending (HR, BG, RO, LV, CZ, IT) whereas higher spending countries such as AT, CY, ES, NL and SE have also cut expenditure per student for tertiary education. The longer term trend since 2000 shows significant increases in absolute spending levels (in PPS per student) in most countries with the notable exception of IT and to a lesser extent NL.   Figure 4.5. Expenditure per student on tertiary education institutions in € PPS (2008-2010)   Source: Eurostat (UOE). Online data code: educ_fitotin. The expenditure includes public and private expenditure on both public and private tertiary education institutions. Countries are ranked in ascending order according to development between 2008 and 2010.  The 2013 country-specific recommendations emphasise strategic planning and effective spending in higher education for a number of countries, including measures regarding improved planning (AT); better alignment of supply and demand with regards to the labour market (BG, RO, SK); and funding and cost-effectiveness of funding (CZ, DK, LV). For other countries, the country-specific recommendations emphasise the equity aspects of higher education, such as more support for disadvantaged students (HU) and to improve career and counselling services for students (IT).  The composition of higher education spending  Examining expenditure structures within tertiary education in terms of how much is paid by public resources compared to private sources adds another interesting dimension (Table 4.2). In Europe, finance for tertiary education is largely public (82.7% of overall expenditures), in contrast to the US where private sources are the main contributors to the budgets of tertiary education institutions (70.4%). In the US, the financial burden lies mainly with individual beneficiaries of tertiary education and their families (and to a lesser extent on other private funders) whereas in Europe it is a collective burden borne primarily by tax payers.   There are, however, noticeable differences within Europe, with the UK resembling the US more than continental Europe. The share of public sources in total expenditure on educational institutions is particularly high in the Nordic countries (DK, FI, SE, IS and NO) and RO (90% or more).  The public-private split in higher education funding has remained stable since 2000 in a majority of countries, although a few have changed towards a larger share of private spending on tertiary education. This is particularly noticeable in UK-ENG, but also in some Eastern European countries such as LT, PL, SK and to a lesser extent DE, AT, IE and IT. A few countries have moved in the opposite direction as is the case for RO and CY (in the latter case due to the state also spending on places for CY students to study abroad).  -3 000-1 0001 0003 0005 0007 0009 00011 00013 00015 000-3000-100010003000500070009000110001300015000HRBGRONLSELVCYATCZESITBESKDELTEUPTFREEDKFIUKSIPLMTDecrease between 2008 and 2010 in € PPS Increase between 2008 and 2010 in € PPS  in € PPS per student  45 Table 4.2. Relative proportions of public and private expenditure on educational institutions as a percentage, for tertiary education (2000, 2010)   2010 2000  Public sources Private sources Public sources Private sources  Household expenditure Other private expenditure All private sources EU*  82.7 : : 17.3 : : Belgium 89.8 4.7 5.6 10.2 85.1 14.9 Bulgaria 51.7 46.8 1.4 48.3 58.7 41.3 Czech Republic 78.8 9.4 11.8 21.2 85.4 14.6 Denmark 95.0 5.0 0.0 5.0 97.6 2.4 Germany 84.4 : : 15.6 91.8 8.2 Estonia 75.4 17.9 6.7 24.6 : : Ireland 81.2 16.3 2.5 18.8 86.2 13.8 Greece : : : : 99.7 0.3 Spain 78.2 17.6 4.2 21.8 74.4 25.6 France 81.9 10.1 8.0 18.1 84.4 15.6 Croatia 76.0 24.0 0.0 24.0 : : Italy 67.6 24.4 8.0 32.4 77.5 22.5 Cyprus 52.1 46.7 1.1 47.9 20.1 79.9 Latvia 60.2 37.7 2.1 39.8 59.4 40.6 Lithuania 68.7 26.1 5.2 31.3 100.0 0.0 Luxembourg : : : : : : Hungary : : : : 76.6 23.4 Malta : : : : 98.6 1.4 Netherlands 71.8 14.7 13.5 28.2 75.0 25.0 Austria 87.8 2.6 9.5 12.2 96.3 3.7 Poland 70.6 22.5 6.9 29.4 100.0 0.0 Portugal 69.0 23.4 7.6 31.0 92.5 7.5 Romania 90.0 9.5 0.5 10.0 70.0 30.0 Slovenia 84.7 10.6 4.7 15.3 : : Slovakia 70.2 11.8 18.0 29.8 91.3 8.7 Finland 95.9 0.0 0.0 4.1 97.2 2.8 Sweden 90.6 0.0 9.4 9.4 88.1 11.9 United Kingdom 25.2 56.1 18.7 74.8 67.7 32.3 Montenegro : : : : : : Iceland 91.2 8.2 0.6 8.8 94.9 5.1 MK : : : : : : Serbia : : : : : : Turkey : : : : 95.4 4.6 Norway 96.0 3.3 0.7 4.0 96.2 3.8 Switzerland : : : : : : US 29.6 58.1 12.3 70.4 : : Source: Eurostat (UOE). Note: *EU average based on available country data. CY: includes private funding for students living abroad. USA: 2009 data.  In addition to spending on institutions, public authorities provide direct support to students in the form of student grants and loans. Since 2000, at EU level there has been a slight increase in the financial aid for students as a percentage of total public expenditure on education. However, the proportions spent differ significantly between EU countries, with relatively high levels in the Nordic countries, NL and UK (as well as in CY) and noticeably lower levels in countries such as BG, CZ, EE, EL, ES, FR, IE, and RO.  Increases in private expenditure for tertiary education institutions are not associated with decreases in public expenditure across Europe99. Moreover, the limited evidence currently available suggests that higher shares of private expenditure (including tuition fees) do not seem to be associated with more limited access amongst disadvantaged groups. The latter is possibly related to the availability of public loans, scholarships and grants100. There is, however, a need for strengthening the evidence-                                               99   See OECD (2012), Education Indicators in Focus #8. 100   See OECD (2012), Education at a Glance 2012 (Indicator B5). The evidence-base needs to be strengthened on equitable opportunities and outcomes in relation to private spending, tuition fees and public loans base,  particularly  on  the  effects  of  the  crisis  and  on  the  longer-term  effects  for  disadvantaged 
students (e.g. in relation to the burden of having to pay back student loans101). 

Figure 4.6. Financial aid to students as percentage of total public expenditure on education at 
tertiary level (ISCED 5 and 6) 

60

50

40

30

20

10

0

2000

2005

2010

U
E

E
B

G
B

Z
C

K
D

E
D

E
E

E
I

L
E

S
E

R
F

R
H

T
I

Y
C

V
L

T
L

U
H

T
M

L
N

T
A

L
P

T
P

I

O S
R

K
S

I
F

E
S

K
U

S
I

O
N

H
C

R
T

Source:  Eurostat  (UOE).  MT:  2003  instead  of  2005  data,  HR:  2003  instead  of  2000  data,  RO  and  SK:  2001  instead  of  2000 
data, TR: 2004 instead of 2005 data. 

Completion rates in higher education 

If  tertiary  qualifications,  and  thereby  attainment,  are  the  main  output  of  a  higher  education 
institution  and  public  and  private  resources  its  main  inputs,  then  efficiency  can  be  improved  by 
examining 'the black box' between the investment and the outcome. Although measuring process 
efficiency  is  inherently  complex,  one  way  to  approximate  the  efficiency  of  higher  education 
institutions  is  to  look  at  the  completion  rates;  i.e.  how  many  students  finish  their  degrees  once 
they  have  entered  a  higher  education  programme102.  Here,  the  assumption  is  that  it  is  an 
inefficient use of public resources when individuals start higher education courses but leave without 
a  qualification  by  dropping  out  of  the  system.  Low  completion  rates  can  therefore  be  seen  as  a 
proxy for process inefficiency.  

Figure 4.7. Completion rates in tertiary education (2011) 

90
80
70
60
50
40
30
20
10
0

DK

ES

FI

DE

TR BE nl NL

CZ

UK

SK

FR

PT

AT

PL

NO

SE

US

HU

Total Men Women

Source:  OECD  (2013),  Education  at  a  Glance  2013  (Table  A4.1,  www.oecd.org/edu/eag2013).  Notes:  SE:  Includes  students 
entering single courses  who  may never intend to study all courses needed  for a degree  (around one-third of all enrolments). 
DE, ES and FR: only type A education (ISCED 5A, bachelor and master types of education). For FR, the completion rate reaches 
80% if those successfully reoriented to an ISCED level 5B qualification are taken into account. 

Figure 4.7 shows significant differences in completion rates between countries (for which data are 
available)  with  rates  ranging  from  a  level  where  only  just  more  than  half  of  those  entering 

101  

102  

As a comparison, the US famously has a total student loan debt around 1 trillion USD, exceeding both its total credit 
card debt and car loan debt. 
Other dimensions of process efficiency are applicable here and are covered elsewhere in the Education and Training 
Monitor. Firstly, the  development  of Open Educational Resources  (OER) and Massive  Open Online Courses (MOOCs) 
(see  Section  2.2)  may  have  an  impact  on  traditional  funding  models  and  also  open  up  new  opportunities  to  bring 
tertiary education courses  to an  even  wider  population in a particularly flexible  and  efficient  manner. Secondly, the 
transparency and recognition of learning outcomes, even if obtained through informal or non-formal education, may 
increase skill levels (see Section 2.3). 

46 

 
 
 
 
 
 
 
 
 
 
                                               
 47 succeeded (HU and SE) to comparatively higher rates of 75% or more in DK, ES, FI, DE and TR (but still with scope for improvement). It should be noted that not only do women enter the tertiary levels in higher numbers than men but they have also higher completion rates for all the countries shown, significantly so in countries such as PL, PT, CZ, NL and BE nl.   A recent report from the Network of Experts on Social Aspects of Education and Training (NESET) offers a closer look at the underlying determinants of dropout from higher education103. The report shows that lack of individual resources is the most significant factor leading students to drop out. Coming from a poor socioeconomic background is found to dominate all other factors including gender and ethnicity in leading to dropout. Secondly, the report emphasises that it is not widening participation per se that causes dropout. The problem is rather a lack of attention to the needs of a more diverse student population and a lack of a student-centred approach in designing and delivering higher education programmes.  The evidence presented in this section provides a vivid illustration of the need for countries to consider how best to effectively employ resources within their systems in order to ensure students successfully obtain their qualifications and therefore contribute to a higher overall skill level in society.  The overall picture emerging is one of divergent structures within tertiary education and differing responses to an economic crisis which is far more prevalent in some parts of Europe than in others. Indeed, some countries are maintaining or even increasing spending levels and the number of academic staff while others have pulled the brake. The findings above also demonstrate the important scope for peer learning in relation to spending on tertiary education and the incentives for learning.   4.3. Promoting learning mobility in higher education  Learning mobility provides a key contribution to EU education and training policies. It provides students from across Europe with international experience, to strengthen their networks and to expand their horizons to other contexts within education and work104. This is valuable in itself and may contribute to a sense of European identity. But as new evidence shows, it can also help tackle skills bottlenecks. Being mobile during higher education increases the probability of being mobile after graduation, as a recent report shows105. Across 16 Member States studied, learning mobility increases the likelihood of subsequent work-related mobility by 14 percentage points.  Both the Council Conclusions on the modernisation of higher education106 as well the recent Commission Communication on European Higher Education in the World107 highlight the potential of mobility both within and beyond the EU to enhance students' prospects. Moreover, in the next multiannual programme Erasmus+ (2014-2020), 65% of the EU education and training budget is earmarked for mobility schemes such as Grundtvig, Leonardo da Vinci, Erasmus and Erasmus Mundus108.                                                103  NESET (2013), Drop-out and Completion in Higher Education in Europe: supporting students from under-represented groups (see: http://ec.europa.eu/education/news/20131017-neset_en.htm; and http://www.nesetweb.eu/). 104      Mobility and international networking is considered beneficial at all levels of tertiary education, including at doctorate level. International networking and the importance of transferable skills and exposure to industry and other employment sectors are part of seven Principles for Innovative Doctoral Training developed by the Commission together with experts from industry, academia and national research ministries (http://ec.europa.eu/euraxess/pdf/research_policies/Principles_for_Innovative_Doctoral_Training.pdf). 105   See JRC-CRELL (2013), Does Student Mobility During Higher Education Pay? Evidence From 16 European Countries (https://crell.jrc.ec.europa.eu); as well as OECD (2013), Education Indicators in Focus #14. For mobility at doctorate level the recent EU-wide study MORE2 provides findings on mobility patterns and career paths of researchers. Furthermore, the Commission’s Researchers’ Report 2013 provides information on national policies to address issues such as inward and outward mobility of researchers, attracting young people into science and equipping them with the right skills (http://ec.europa.eu/euraxess/index.cfm/services/researchPolicies).  106   OJ 2011/C 372/09. 107   COM(2013) 499 final. 108   The Commission's Erasmus Mundus programme provides grants/scholarships for students at master and doctorate level coming from outside EU countries to study in the EU. It also encourages partnerships between educational Learning mobility increases the likelihood of work-related mobility, potentially helping in tackling skills bottlenecks across Europe Effectiveness of tertiary education could be increased significantly if more students finish their degrees The  November  2011  Council  Conclusions  on  an  EU  benchmark  for  learning  mobility  is  based  on 
three  indicators;  one  targeting  learning  mobility  in  higher  education,  one  concerning  initial 
vocational  training  mobility  (see  section  5.1),  and  an  indicator  on  general  youth  mobility109.  The 
Bologna Process has also set a target in the domain of higher education defined in a similar way to 
the EU target but for the wider scope of the Bologna countries (covering 47 European countries). 

Table 4.3. International student mobility: enrolments and graduates in destination country (2011)  

EU  
Belgium 
Bulgaria 
Czech Republic* 
Denmark 
Germany** 
Estonia 
Ireland 
Greece* 
Spain 
France* 
Croatia 
Italy*** 
Cyprus 
Latvia 
Lithuania 
Luxembourg 
Hungary 
Malta* 
Netherlands 
Austria 
Poland 
Portugal 
Romania 
Slovenia 
Slovakia 
Finland 
Sweden 
United Kingdom 
Montenegro 
Iceland 
MK 
Serbia 
Liechtenstein 
Turkey* 
Norway 
Switzerland* 
USA 

Degree 
enrolments 

1,399,991 
37,866 
10,345 
38,041 
20,252 
181,220 
1,430 
12.695 
32,828 
62,636 
268,212 
690 
69,905 
8,990 
1,979 
3,004 
2,468 
16,465 
471 
38,367 
53,036 
20,711 
13,356 
16,075 
1,976 
8,748 
14,124 
36,522 
419,946 
: 
1,099 
: 
: 
777 
: 
3,407 
58943 
709,565 

% of all 
students 
enrolled 
7.0 
8.2 
3.6 
8.5 
7.8 
7.1 
2.1 
6.5 
5.0 
3.2 
11.9 
0.5 
3.5 
28.0 
1.9 
1.6 
40.6 
4.3 
4.1 
4.9 
14.7 
1.0 
3.4 
1.8 
1.8 
3.9 
4.6 
7.9 
16.9 
: 
5.8 
: 
: 
79.0 
2.6 
1.5 
22.9 
3.4 

Erasmus 
enrolments 

222,236 
7,837 
781 
5,198 
6,688 
24,733 
850 
5,381 
2,860 
37,432 
27,722 
13 
19,172 
611 
650 
1,540 
408 
3,211 
965 
9,189 
5,383 
7,583 
8,536 
1,563 
1,436 
1,181 
6,805 
10,034 
24,474 
: 
532 
: 
: 
56 
4,288 
4,281 
15 
na 

% of all 
students 
enrolled 
1.1 
1.7 
0.3 
1.2 
2.6 
0.9 
1.2 
2.7 
0.4 
1.9 
1.2 
0.01 
1.0 
1.9 
0.6 
0.8 
6.7 
0.8 
8.4 
1.2 
1.5 
0.4 
2.2 
0.2 
1.3 
0.5 
2.2 
2.2 
1.0 
: 
2.8 
: 
: 
5.7 
0.1 
1.9 
0.0 
: 

Graduates 

% of all 
graduates 

: 

: 
: 
: 
4,812 
30,386 
258 
4,409 
: 
6,006 
: 
182 
: 
1,078 
315 
355 
502 
: 
: 
7,003 
6,965 
3,375 
2,629 
2,142 
343 
: 
2,268 
7,079 
173,688 
: 
: 
: 
: 
197 
: 
1,285 
8,903 
165,113 

: 

: 
: 
: 
8.4 
5.8 
2.2 
7.4 
: 
1.6 
: 
0.5 
: 
18.2 
1.3 
0.8 
38.9 
: 
: 
5.0 
10.9 
0.5 
3.0 
0.8 
1.7 
: 
4.6 
10.2 
23.0 
: 
: 
: 
: 
76.4 
: 
3.2 
11.3 
5.2 

Source: Eurostat (UOE), online data codes educ_momo_gen and educ_mofo_gen; and DG EAC (Erasmus enrolments). Note: “:” 
=  missing.  na:  not  applicable.  EU  average:  estimate  by  DG  EAC  based  on  available  data.  *  CZ,  EL,  FR,  MT,  CH,  TR  foreign 
citizens  instead  of  mobile  students.  **  DE  2010  data.  ***  IT  2010  data,  foreign  citizens  instead  of  mobile  students.  The 
number of foreign citizens is normally higher than the number of mobile students in tertiary education; so the EU estimate is a 
slight overestimate. 

International  student  mobility  has  two  driving  forces;  the  push  factor  –  meaning  the  desire  of 
young people to go abroad and study or train in another country – and the pull factor; the ability of 
national education systems to attract students from abroad to study within their system. 

Currently,  the  available  statistics  on  learning  mobility  only  give  a  fragmented  picture  of 
international  mobility  flows;  the  number  of  students  enrolled  abroad  and  graduating  abroad 
(degree mobility) and the number of students who have enjoyed a study or training period abroad 

institutions and promotes European higher education in the rest of the world 

109  

  (http://ec.europa.eu/education/external-relation-programmes/mundus_en.htm).  
  The  benchmark  on  learning  mobility  in  higher  education  is  defined  as  follows:  By  2020,  an  EU  average  of  at  least 
20% of higher education graduates should have had a period of higher education-related study or training (including 
work placements) abroad, representing a minimum of 15 ECTS credits or lasting a minimum of three months. 

48 

 
 
 
 
 
 
 
 
 
                                                                                                                                                
 
(credit mobility). Eurostat has recently agreed on a regulation with Member States which foresees 
the obligatory transmission of tertiary education mobility data by Member States in the near future. 
This  means  that  benchmark  data  are  still  under  development.  Given  the  situation,  this  section 
concentrates  on  examining  how  many  mobile  students  and  graduates  are  studying in  EU  Member 
States. 

Table  4.3  shows,  that  across  Europe,  degree  mobility  is  the  most  dominant  form  of  learning 
mobility  but  that  the  EU  credit  mobility  programmes  also  contribute  significantly.  The  UK  is  the 
country  within  the  EU  which  attracts  the  most  students  from  abroad.  In  2011,  nearly  174,000 
mobile  students  graduated  in  the  UK, more  than  in  the  United  States  (23%  of  the  total  graduate 
population).  There  is  a  large  gap  between  the  UK  and  the  next  most  popular  EU  Member  States 
such  as  AT,  SE  and  DK  in terms of  relative share  of  international graduates  (around 10% of  total 
graduates). 

In addition, it should be noted that a few smaller countries  (e.g. CY, LU) attract a relatively large 
proportion of international students. This is likely due to their geographical position, proximity to a 
larger neighbouring country, or explicit policy measures.  

Worldwide mobility 

In  recent  decades,  there  has  been  a  continual  increase  in  learning  mobility  worldwide.  Europe 
remains an attractive destination for mobile learners with a stable share of around 40-45% of the 
internationally  mobile  student  population,  a  population  expected  to  grow  from  just  below  the 
current 4 million to 7 million by the end of the decade110. 

Figure 4.8. International student mobility: enrolments in EU Member States (%, 2010) 

45
40
35
30
25
20
15
10
5
0

Source: UNESCO Institute of Statistics.  

extra EU

intra EU

Figure  4.8  shows  that  nearly  70%  of  the  international  students  who  studied  in  one  of  the  EU 
Member States in 2010 (degree mobility) came from countries outside the EU. This percentage is 
more than 80% in countries such as BG, CY, FR, LT, SE, and SI. The high percentages of students 
coming from outside the EU may be the direct result of explicit policies but is often due to specific 
historical circumstances such as former colonial ties (e.g. FR, UK and BE), or proximity to a large 
neighbour outside the EU (e.g. BG, CY and LT).  

Figure 4.9 shows that EU Member States accommodate nearly 38% of the world's mobile students 
whereas  students  from  the  EU  only  make  up  18%  of  the  worldwide  mobile  student  population 
going  abroad.  The  United  States  and  Canada  are  other  big  recipients  of  international  students 
whereas Asian countries (particularly East-Asia including China) supply a large part of the world's 
international  students.  This  pattern  has  developed  over  recent  decades  and  is  becoming  more 
pronounced. 

Some  European  countries  have  adopted  specific  policies  both  at  central  level  and  at  the  higher 
from  abroad.  Examples  of  explicit 
education 
internationalisation  policies  at  both  institutional  and  at  country  level  are  becoming  more 

for  attracting  students 

institutional 

level 

110  

  UNESCO Institute of Statistics and Commission Communication European Higher Education in the World (COM(2013) 
499 final).  The  actual level  of international mobile  students  can only be  estimated roughly given missing data from 
some countries worldwide and the use of different concepts for defining a mobile student. 

49 

 
 
 
 
 
 
 
 
 
 
 
                                               
 50 Policy lessons  With the tertiary attainment rate now at 35.7%, the discussion is shifting towards improving completion rates which for many European countries is below 70%. The fairly scattered evidence shows that there are ample possibilities for institutions and governments to improve the effectiveness of higher education in addition to the benefits for the individual in actually gaining a qualification.   widespread throughout Europe with some countries setting explicit targets for attracting students and for sending their own students abroad. For example, it is envisaged that half of all students in DK will have followed a part of their studies abroad by 2020, and both universities and high level vocational institutions in AT and LU make study or training abroad a compulsory part of the programme111.  At the EU level, student mobility from countries outside the EU has recently been facilitated by the adoption of a Directive covering the harmonisation of rules governing the admission of third country nationals for study purposes. More concretely, this Directive determines the rules concerning the procedures for admitting third country nationals for a period exceeding three months for the purposes of studies, pupil exchange, unremunerated training or voluntary service, thereby harmonising national legislation in this area112.   Figure 4.9. Distribution of mobile students in tertiary education by region of origin (2010)  Further progress remains necessary. Education programmes should be organised in such a way that international mobility can become a practical reality (e.g. the planning of a course should take into account the possibility for such periods abroad). From the student perspective, the economic support offered (grant schemes) should be 'mobile' as well. Finally, language competences (Section 3.4) are essential for enabling effective international mobility.                                                   111   For examples see Eurydice and Eurypedia: chapter on mobility and internationalisation   (https://webgate.ec.europa.eu/fpfis/mwikis/eurydice/index.php/Mobility_and_Internationalisation). Also see European Migration Network (2012), Immigration of International Students to the EU. 112  Council Directive 2004/114/EC of 13 December 2004 on the conditions of admission of third-country nationals for the purposes of studies, pupil exchange, unremunerated training or voluntary service. See also SWD (2013) 77 final and detailed data on residence permits for third-country nationals (tables migr_resval and migr_resage; http://epp.eurostat.ec.europa.eu/portal/page/portal/population/data/database). EU-27 17,9 Europe, non-EU 27 8,6 North America 3,1 Latin America and the Caribbean 6,4 Arab States 8,6 Sub-Saharan Africa 8,4 Pacific 0,9 East Asia 31,1 Central, South and West Asia 15,0 EU-27 37,8 Europe, non-EU 27 7,3 North America 21,7 Latin America and the Caribbean 1,9 Arab States 5,9 Sub-Saharan Africa 2,5 Pacific 8,9 East Asia 12,4 Central, South and West Asia 1,4 Inbound mobility Outbound mobility Source: UNESCO Institute of Statistics. Notes: The totals used are at world-level (3.6 million students for inbound; 3.2 million for outbound). The difference is due to the fact that the country of origin is unknown for some students.  51 Policy lessons (continued)  The evidence-base needs to be strengthened in the area of equitable opportunities and outcomes in relation to private spending, tuition fees and public loans. The level of private spending on tertiary education in Europe is low and has not increased markedly during the last decade. The limited data currently available suggests that increases in private funding do not decrease overall public funding and have limited effects on the equitable access to tertiary education. Further research is needed if Member States are to exploit funding possibilities beyond relying on public funding.   New evidence on international mobility of students confirms the positive effects of mobility at both individual and societal level. Being mobile during higher education increases the probability of being mobile after graduation and may therefore help in tackling skills mismatches and bottlenecks across the European labour market.   5.  Facilitating  the  transition  from  education 
to  work  through  vocational  education 
and training 

In its recent Communications on youth unemployment113 and the social dimension of the Economic 
and  Monetary  Union114,  the  Commission  stressed  the  need  to  foster  the  employability  of  young 
people,  with  as  many  as  17%  of  recent  graduates115  unemployed  in  2012  compared  to  11%  in 
2008. The rise in unemployment is even more pronounced for people coming from upper secondary 
education  (21%  in  2012,  14%  in  2008).  Apprenticeships  are  one  important  driver  of  youth 
employability  and  should  be  significantly  reinforced  in  upper  secondary  vocational  programmes 
across the  EU.  Evidence from  Member States with strong vocational education and training  (VET) 
systems  shows  the  great  potential  of  work-based  learning  to  fight  youth  unemployment  and 
increase the employability of young graduates. 

This chapter  focuses  on labour market  outcomes of  formal education  and underlines the need  for 
higher  labour  market  relevance  of  education  and  training  systems.  Section  5.1  emphasises  the 
importance of combined school- and work-based learning and apprenticeship opportunities in order 
to  facilitate  the  transition  from  learning  to  work  for  millions  of  young  Europeans.  Subsequently, 
section 5.2 provides a closer look at the trends in employment rates of recent graduates, whether 
from  upper  secondary  or  tertiary  education.  Section  5.3,  finally,  stresses  the  need  to  develop 
further entrepreneurial competences among young people, in order to equip them with a sense of 
initiative and an ability to transform ideas into action, contributing to their employability.  

5.1.  Reshaping vocational education and training 

In  both  the  Rethinking  Education  Communication116  and  the  2013  youth  unemployment 
Communication,  the  Commission  called  on  Member States  to step  up  efforts in  developing world-
class  vocational  education  and  training  to  raise  the  quality  of  vocational  skills,  and  in  promoting 
work-based  learning  including  quality  traineeships,  apprenticeships  and  dual  systems117.  Work- 
based learning in its various forms facilitates the transition from learning to work and plays a key 
role in addressing skills shortages, in particular in sectors with growth potential. 

In the context  of  the 2013 European Semester,  the country-specific recommendations  for  sixteen 
Member  States  focused  on  increased  provision  of  apprenticeships  and  work-based  learning, 
improving  employability  of  young  people  through  the  Youth  Guarantee,  and  efforts  to  increase 
labour market relevance and attractiveness of VET118. 

In  its  Communication  on  the  Youth  Employment  Initiative  of  March  2013119,  the  Commission 
stressed  the  role  of  a  Youth  Guarantee120  in  all  Member  States  and  the  need  for  launching  a 
European Alliance for Apprenticeships as well as the second-stage social partner consultation on a 
Quality  Framework  on  Traineeships121.  The  European  Alliance  for  Apprenticeships  is  a  multi-
stakeholder  initiative  bringing  together  efforts  of  Member  States,  social  partners,  businesses  and 
other relevant actors along with the European Commission to develop high-quality apprenticeship-

113  
114  
115  

116  
117  

118  

119  
120  

COM(2013) 447 final. 

  COM(2013) 690. 
  Those aged 20-34 who graduated within the last three years from upper secondary or tertiary education and who are 

not in further education and training. 

  Rethinking Education: Investing in skills for better socio-economic outcomes (COM(2012) 669 final). 
  Combination  of  apprenticeships  in  a  company  and  vocational  education  in  an  educational  institution.  For  further 
information,  see  the  2011  CEDEFOP  report  on  the  benefits  of  Vocational  Education  and  Training  at 
http://www.cedefop.europa.eu/EN/Files/5510_en.pdf. 
The 2013 country-specific recommendations, approved by the Council, can be found at: 
http://ec.europa.eu/europe2020/making-it-happen/country-specific-recommendations/index_en.htm.  The  package 
was adopted by the Council on 19 June 2013. The recommendations concern BE, BG, DK, ES, FR, IT, LV, LT, LU, MT, 
PL, RO, SE, SK, SI and UK. 

  COM(2013) 144 final. 
  COM(2012) 729 final. Member States should put in place measures to ensure that young people up to age 25 receive 
a  good  quality  offer  of  employment,  continued  education,  an  apprenticeship  or  a  traineeship  within  four  months  of 
leaving school or becoming unemployed. 

121  

  COM (2012) 728 final. 

52 

 
 
 
 
 
 
 
 
 
                                               
 
 53 type training and excellence in work-based learning in VET. Within the Youth Guarantee Recommendation, adopted by the Council on 28 April 2013, apprenticeships are one of the four options for its implementation.   Both the Youth Employment package and the European Alliance for Apprenticeships are meant in particular to: (i) improve the quality, attractiveness and supply of apprenticeships; (ii) strengthen the exchange of information and good practices amongst stakeholders of all EU Member States; and (iii) give young people more opportunities to work and train abroad.  Keeping up investments in work-based learning pays off as they have proven to significantly improve the employability of young people in some Member States. Indeed, students from Vocational Education and Training programmes experience a better transition from school to work in Member States having developed work-based learning, such as DK, CZ, DE, NL and AT (Table 5.1)122. In HU and SK, however, despite the provision of combined work- and school based programmes, youth unemployment ratios for recent graduates from upper secondary education is still of particular concern, far above the rates for recent tertiary graduates. This suggests that the skills acquired by VET graduates might not be considered as sufficiently relevant by employers.   Table 5.1. Students in school- and work-based learning and youth unemployment ratios   Percentage of ISCED 3 students in work-based VET programmes (2011)123 Unemployment ratios of recent graduates (2012)  Upper secondary  education Tertiary  education Belgium 3.1 17.6 6.8 Czech Republic 31.8 17.4 (6.5) Denmark 44.7 10.5 9.7 Germany 42.9 8.6 : Estonia 0.3 22.7 (7.6) Ireland 5.0 37.9 13.6 Spain 1.9 45.9 29.4 France 12.0 23.9 12.4 Hungary 16.6 28.5 9.9 Netherlands 20.9 6.2 5.6 Austria 34.8 6.3 : Poland 6.6 26.7 12.5 Slovenia 0.1 (26.9) 16.9 Slovakia 29.0 34.2 15.7 Finland 11.7 14.7 7.8 Source: Eurostat (UOE and LFS). Notes: 2010 data are used for IE and NL; "()" = Data lack reliability due to small sample size; ":" = data not reliable due to very small sample size (below 3%). The unemployment ratio of recent graduates is calculated as the share of unemployed persons aged 20-34 with upper secondary (incl. post-secondary non tertiary) or tertiary qualifications out of the population of the same age and educational attainment level. The ratio refers to people who left education within the last three years and who are no longer in education and training.  In eight Member States, less than 40% of graduates were from VET programmes at upper secondary level in 2010 (Figure 5.1). Providing more work-based learning in VET programmes will obviously take different forms according to the field of study (e.g. alternance schemes, on the job training periods, on-site labs), in particular in programmes of a less technical nature. Increasing awareness of VET programmes in all fields among employers and promoting their involvement in the design and supply of work-based learning is of particular relevance in this context.   Provision in the European Union budget is earmarked to support this process: Member States can use the European Social Fund, the Youth Employment Initiative and the Erasmus+ programme (2014-2020) to further improve the quality and efficiency of vocational education and training systems. Furthermore, a Review124 of existing apprenticeship and traineeship programmes is under                                                122   See also CEDEFOP (2012), From education to working life: the labour market outcomes of vocational education and training. 123  In the UOE data collection, a VET programme is classified as "combined work- and school-based "if 25% or more of the curriculum is presented outside the school environment. Programmes where the work-based component accounts for 90% or more of the curriculum are excluded from the UOE data collection. The category "Combined work- and school-based VET" is not applicable to the educational systems of BG, EL, IT and PT.  124   This will include an overview of available data. See the youth opportunities initiative and its technical assistance to Work-based learning strengthens youth employment and should become a central pillar of vocational education and training systems across Europe development  to  identify  the  most  successful  and  cost-effective  approaches.  A  helpdesk  on 
apprenticeship  and  traineeship  schemes  has  already  been  set  up  to  provide  strategic,  operational 
and  policy-focused  advice  to  stakeholders  at  national,  regional  and  local  level  that  are  planning, 
setting  up,  running  or  evaluating  apprenticeship  and  traineeship  schemes.  Additionally,  the 
Commission together with Member States' experts and CEDEFOP are developing guiding principles 
with respect to profiles and competence development of VET trainers for work-based learning. 

Figure 5.1. Graduates in VET as a share of graduates from upper secondary education (2010) 

100

90

80

70

60

50

40

30

20

10

0

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

Engineering, health, services

Humanities, social sciences, administration

Source: DG EAC calculation on the basis of Eurostat (UOE) data. Notes: the chart depicts the percentage of graduates in VET 
out of all graduates from upper secondary education and post-secondary non tertiary education (ISCED 3 and 4).  Data by field 
of study not available for EL, HR, IT, PT and UK. 

Learning mobility in initial vocational education and training 

The ET 2020125 benchmark on learning mobility in initial vocational education and training (IVET)126 
sets concrete targets to be achieved by 2020 and many EU Member States have followed up on the 
Europe-wide  targets  by  setting  their  own  national  targets  as  well.  Moreover,  the  Erasmus+ 
programme (2014-2020) aims to further foster cross-border vocational training. 

Figure 5.2. Percentage of ISCED 3 students participating in Leonardo da Vinci programmes 

8%

7%

6%

5%

4%

3%

2%

1%

0%

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

CH LI TR NO IS

2008

2011

Sources:  DG  EAC  estimates  based  on  Eurostat  (UOE)  and  DG  EAC  data  sources  (http://ec.europa.eu/education/leonardo-da-
vinci/statistics_en.htm).  Notes:  chart  depicts  the  number  of  students  participating  in  a  Leonardo  da  Vinci  project  (selection 
database) as a percentage of students enrolled in initial vocational training programmes (ISCED 3 upper secondary vocational 
orientation). 

The benchmark for learning mobility in initial vocational training (IVET), defined as the vocational 
orientation  within  upper  secondary  education  (apprenticeships  included),  stipulates  that  by  2020 
“an  EU  average  of  at  least  6%  of  18  to  34  year-olds  with  an  initial  vocational  education  and 

set  up  apprenticeship  schemes.  See  also  the  2012  report  on  "apprenticeship  supply  in  the  Member  States  of  the 
European Union". 

125  
126  

  ET 2020: A strategic framework for European cooperation in education and training (2009/C 119/02). 
  See: http://www.consilium.europa.eu/uedocs/cms_data/docs/pressdata/en/educ/126380.pdf. 

54 

 
 
 
 
 
 
 
 
 
 
                                                                                                                                                
 55 training qualification should have had an initial VET-related study or training period (including work placements) abroad lasting a minimum of two weeks”.  Very little evidence exists concerning the actual magnitude of IVET mobility across the EU. Eurostat is presently undertaking efforts to measure the benchmark via a sample survey with the aim of providing feedback on the benchmark by the end of 2015.  The Leonardo da Vinci strand of the Lifelong Learning Programme – covering IVET mobility – provides some indication of the level and development of annual IVET mobility flows (Figure 5.2). However, a recent study on mobility developments in school education, vocational education and training, adult education and youth exchanges commissioned by the European Commission, shows that the number of participants in schemes financed from other sources amount to nearly double the total participants in the EU action programmes127.    5.2. Enhancing the employability of young people  The year 2012 marked a further drop in employment rates of recent graduates in the European Union. The rate in 2012 was 75.7% for people aged 20-34 years and who had left education and training within the preceding three years, representing a decrease of 6.3 percentage points from 2008 (and 1.5 percentage points from 2011).   Compared to the overall population, the economic crisis had the most significant impact on the employment of young people. This trend was even more pronounced amongst recent graduates. For young people with upper secondary education qualifications, the employment rates have decreased by 4.6 percentage points since 2008 for all young people, and have decreased by 7.8 percentage points for recent graduates. Since 2008, the decrease for all young people with tertiary qualifications has been 3.8 percentage points versus 5.4 percentage points for recent graduates. The situation for young people with at most lower secondary education is even more alarming (see chapter 3 on early school leaving).   Figure 5.3. Employment rates of recent graduates: current performance and recent change     Source: Eurostat (LFS online data code edat_lfse_24). Note : Countries are shown according to their 20-34 cohort size, with five categories.                                                 127   http://ec.europa.eu/education/documents/more-information/mobility-study-report.pdf. LU LT MT EE LV SI FI SK DK IE BG SE PT AT HU EL NL CZ ES BE RO DE FR UK IT PL CY EU HR 40,050,060,070,080,090,0100,0-14,0-12,0-10,0-8,0-6,0-4,0-2,00,02,04,0EU employment rate of recent graduates is down by 8 percentage points for upper secondary education, 5 percentage points for tertiary education Average annual change in employment rate of recent graduates (%) over the period 2009-2012 Employment rate of recent graduates 2012 ET 2020 Benchmark Minimum progress needed  56 In 2012, the Council adopted a benchmark on the employability of graduates from education and training with a view to better monitor the contribution of education and training to the transition from education to employment128. The target is that by 2020 82% of young Europeans aged 20-34, graduating within the last three years and no longer in education or training, are in employment.   After the sharp decrease in employment rates of recent graduates between 2008 and 2009 across all countries, employment prospects for young graduates continued to deteriorate in many Member States. This is demonstrated by Figure 5.3, which plots the recent change (2009-2012) against the 2012 values.  Eight Member States had employment rates of recent graduates that were above 82% in 2012: CZ, DK, DE, LU, MT, NL, AT and SE. BE, FI and UK remain close to the EU target. Since 2012, employment rates started to increase in CZ, FI, and UK (all educational levels); in BE, DK and AT (for tertiary graduates); and in LU and MT (for upper secondary graduates). In DE and SE, rates increased significantly from 2009 to 2011 and remained high for all levels but decreased slightly between 2011 and 2012.  Employment rates of recent graduates were below 82% in other Member States. Some of these countries have experienced a continual decrease in their employment rates since 2009. This was particularly the case in EL, ES and PT (-22, -10 and -14 percentage points since 2009 respectively). More recently, employment rates have increased in BG, LV, and LT (all educational levels); in EE, and HU (for tertiary graduates); and in CY and RO (for upper secondary graduates).  While employment rates of recent graduates remain low in many countries, the transition from school to work is a particular issue for students from upper secondary programmes in BG, IE, EL, ES, HR, IT, LV and RO – with employment rates below 60% in 2012. In the same countries as well as in HU, employment rates for upper secondary graduates were lower by 20 percentage points when compared to their peers from tertiary education who reached employment rates close to 80% or above in 2012.   Figure 5.4. Employment rates of recent graduates by field of study (2009, 2012)    Source: Eurostat (LFS). Notes: Based on 1999 Eurostat Classification of fields of studies. The group “Humanities, social sciences, business” aggregates the categories 0 General Programmes, 1 Education, 2 Humanities and Arts, 3 Social Sciences, Business, Law. The group “Science, engineering, health, services” aggregates the categories 4 Science, Mathematics, Computing, 5 Engineering, Manufacturing, Construction, 6 Agriculture, Veterinary, 7 Health, Welfare, 8 Services. From left to right, the four groups represented respectively 19.9%, 28.7%, 28.6% and 22.9% of EU recent graduates in 2012. The category "upper secondary" includes post-secondary non tertiary education and corresponds to ISCED 3-4. Tertiary corresponds to ISCED 5-6.                                                 128   See: http://www.consilium.europa.eu/uedocs/cms_data/docs/pressdata/en/educ/130142.pdf. 60,065,070,075,080,085,090,0Humanities, social sciences,businessScience, engeneering,health, servicesHumanities, social sciences,businessScience, engeneering,health, servicesUPPER SECONDARYTERTIARYDecrease compared to 20092012In 2012, employment rates were below 60% for recent graduates from upper secondary education in eight Member States  In  2012,  43%  of  young  adults  were  employed  in  occupations  usually  requiring  tertiary 
education129. This increased by 5 percentage points over the last decade. However, with limited job 
creation  in  recent  years  (-1.8%  in  2009;  -0.4%  in  2012  at  EU  level),  young  people  with  tertiary 
education  have  fewer  opportunities  in  higher  occupations  and  some  tend  to  accept  occupations 
initially  meant  for  upper  secondary  graduates.  This  is  reflected  in  an  increase  of  the  number  of 
tertiary graduates who do not work, for example, as professionals, managers, or technicians (often 
referred  to  as  vertical  mismatch):  This  represented  21%  of  all  people  with  a  tertiary  educational 
attainment level in 2012 (14 million people)130.  

Employment  rates  of  recent  graduates  vary  significantly  according  to  the  field  of  study  (Figure 
5.4). At upper secondary level, graduates from humanities, social sciences and business (including 
administration) experienced the lowest employment rates in most Member States in 2012. 

Table 5.2. Employment rates of recent graduates by sex and country of birth (%) 

2009 

2012 

Total 

Total 

Males 

Females  Native-born 

Foreign-born ** 

EU28 
Belgium  
Bulgaria  
Czech Republic 
Denmark  
Germany  
Estonia  
Ireland  
Greece  
Spain  
France  
Croatia 
Italy  
Cyprus 
Latvia  
Lithuania  
Luxembourg  
Hungary  
Malta 
Netherlands  
Austria  
Poland  
Portugal  
Romania  
Slovenia  
Slovakia  
Finland  
Sweden  
United Kingdom 
Montenegro 
Iceland 
MK 
Serbia 
Turkey 
Liechtenstein 
Norway  
Switzerland 
Source: Eurostat (LFS, online data code edat_lfse_24). Notes: "()" = Data lack reliability due to small sample size; ":" = data 
either not available or not reliable due to very small sample size; * Results for foreign-born for Germany are not available by 
individual country of birth. EU figures are calculated without Germany. 

Sub-total 
68.3 
70.5 
:  
(80.4) 
73.4 
 : 
 : 
65.3 
(33.5) 
52.5 
61.6 
(35.6) 
49.7 
75.2 
: 
: 
81.3 
: 
(97.2) 
75.6 
84.3 
: 
69.0 
: 
(63.0) 
: 
72.7 
75.6 
78.7 
: 
73.7 
: 
: 
: 
: 
: 
82.8 

Non EU 
65.1 
59.7 
:  
(76.4) 
75.5 
: 
 : 
58.4 
(30.4) 
46.8 
60.4 
: 
49.9 
80.0 
: 
: 
(69.0) 
: 
: 
77.3 
80.1 
: 
68.5 
: 
(63.4) 
: 
71.7 
74.8 
76.0 
: 
: 
: 
: 
: 
: 
: 
73.4 

EU 
75.0 
81.0 
 : 
(82.9) 
(67.8) 
: 
 : 
69.4 
 : 
74.7 
 : 
: 
49.3 
72.4 
: 
: 
84.3 
: 
: 
(69.8) 
89.2 
: 
: 
: 
: 
: 
: 
78.5 
84.0 
: 
: 
: 
: 
: 
: 
: 
92.6 

78.0 
82.1 
67.2 
87.2 
87.5 
89.1 
81.6 
68.6 
45.9 
60.9 
76.6 
59.4 
58.0 
74.7 
74.7 
72.6 
88.9 
74.8 
93.3 
90.0 
91.8 
78.7 
71.5 
72.0 
78.3 
72.1 
81.7 
84.0 
83.6 
: 
90.0 
45.3 
: 
70.6 
: 
: 
86.4 

73.6 
79.7 
67.3 
77.2 
80.6 
85.5 
67.2 
69.8 
40.5 
63.7 
76.4 
57.7 
50.9 
71.6 
73.9 
79.4 
80.6 
72.2 
90.4 
88.7 
90.6 
68.2 
64.9 
66.9 
68.5 
65.3 
79.6 
82.4 
79.7 
: 
83.8 
44.4 
: 
53.4 
: 
: 
87.1 

78.3 
81.0 
73.6 
84.5 
87.9 
85.3 
67.6 
75.5 
64.7 
72.6 
77.2 
77.0 
60.6 
81.1 
71.4 
72.9 
85.5 
75.6 
94.1 
92.9 
88.6 
78.4 
82.6 
77.6 
82.3 
74.4 
77.8 
81.6 
80.0 
: 
84.4 
44.6 
: 
58.1 
: 
: 
86.7 

75.7 
80.9 
67.3 
82.3 
84.1 
87.3 
75.1 
69.3 
42.9 
62.4 
76.5 
58.7 
54.3 
73.0 
74.2 
76.0 
84.6 
73.4 
91.9 
89.3 
91.2 
73.3 
67.9 
69.4 
73.2 
68.6 
80.7 
83.2 
81.5 
: 
86.9 
44.8 
: 
62.0 
: 
: 
86.7 

76.0 
82.3 
67.3 
82.3 
85.5 
88.6 
74.9 
70.0 
43.3 
63.9 
77.9 
59.9 
54.7 
72.4 
73.8 
76.0 
87.7 
73.3 
91.6 
90.6 
92.4 
73.3 
67.8 
69.3 
73.6 
68.6 
81.1 
84.2 
82.2 
: 
88.4 

: 
: 
88.0 

: 

129 

130  

  Managers,  Professionals  Technicians  and  associate  professionals  as  defined  in  the  International  Standard 
Classification  of  Occupations  (ISCO).  Data  refer  to  people  up  to  39  years  old  (Eurostat,  LFS  online  data  code 
lfsa_egais). 

  Source:  Eurostat  (LFS),  employed  people  by  occupation  and  educational  attainment  level,  on-line  code  lfsa_egised. 
This accounted for 12.7 million in 2008 and 13.7 million in 2010, i.e. from 9.4% in 2008 to 10.5% in 2010 of people 
not  working  in  ISCO  1,  2  and  3  have  tertiary  qualifications.  This  percentage  further  increased  by  0.5  percentage 
points between 2011 and 2012 (based on ISCO 1988 until 2010, ISCO 2008 from 2011). 

57 

 
 
 
 
 
  
 
 
 
                                               
 58 Employment perspectives were better for those with extended studies in that field; close to 80% for tertiary graduates. When comparing with 2009, the economic crisis has generally impacted employment rates equally, with the exception of BE, IE, ES, IT, HU and NL where there has been a larger decrease for young people with upper secondary qualifications in the field of humanities, social sciences and business. This calls for education and training systems to ensure higher labour market relevance and to provide improved career and counselling services at early stages of upper secondary education, in closer collaboration with employers of all sectors.  More worrying, beyond the sharp increase of unemployment, is the large share of young graduates who are no longer in education and training and who are not actively searching for work. The inactivity rates of recent graduates increased by one percentage point between 2008 and 2012. This was the case for all educational attainment levels, males and females, but in particular for upper secondary education graduates (2.3 percentage points for males, 1.2 percentage points for females)131.  The 2012 employment rates continued to be higher for males than for females. However, the difference between male and female employment rates of recent graduates has tended to narrow in the last 10 years, mainly due to a stronger decrease of employment rates for males since 2009. The disadvantage for recent female graduates increased from 2.7 percentage points in 2009 to 4.4 percentage points in 2012 at EU level (Table 5.2). This was largely due to the gender gap in employment rates for recent upper secondary graduates: from 3.6 percentage points in 2009 to 7.1 percentage points in 2012.   The gender gap remained rather stable for recent tertiary graduates (3.9 percentage points in 2009 versus 4.3 percentage points in 2012). The gender gap increased sharply from 2009 in DK, EE, PL and UK (for upper secondary graduates); in PT and SI (for tertiary graduates); and in LU (for all levels).   In all countries in 2012, with the exception of BG, IE, ES and LT, employment rates were higher for males than females. The gender gap was most prevalent in CZ, EE, IT, LU, PL and SI (between 7 and 14 percentage points). In FR, HR, LV, AT, NL and SE, the gender gap was smallest (between 0.2 and 1.7 percentage points) and slightly more favourable to women in BG (0.1 percentage points) and IE (1.2 percentage points). In IE, ES, LT and UK, 2012 employment rates of recent graduates from tertiary education were higher for females than for males (by 2 percentage points or more). Gender gaps at these ages are, of course, closely related to the provision of quality early childhood education and care (ECEC) in each country for young parents (see chapter 3).  Since 2009, employment rates of recent graduates have decreased for both native-born and foreign-born individuals but this is more pronounced for the latter. The gap between native-born and foreign-born individuals was more acute in 2012 than previously. In all countries except CY and PT, native-born graduates had a higher likelihood of being employed than their foreign-born counterparts. This was generally more noticeable among those born outside the European Union and was particularly the case in BE and ES.   5.3. Fostering entrepreneurship education  The EU is promoting entrepreneurship education as one of the key factors for employability and highlights the importance of advancing a European entrepreneurial culture by fostering the right mind-set and skills. Consequently, the Europe 2020 strategy has underlined the need to improve the entrepreneurial and innovative capabilities of European citizens through three flagships: Innovation Union, Youth on the Move and An agenda for new skills and jobs.  In the ET 2020 strategic framework, the fourth long-term strategic objective of EU education and training policies is enhancing creativity and innovation, including entrepreneurship, at all levels of                                                131   Source: Eurostat, inactivity rates of recent graduates, on-line code edat_lfse_26. Besides the sharp increase of unemployment, inactivity also increased among recent graduates  Employment opportunities still differ significantly by field of study at all educational levels   59 education and training. Entrepreneurship and a sense of initiative is the seventh of eight key competences for lifelong learning defined in the European reference framework and refers to an individual’s ability to turn ideas into action. It includes creativity, innovation and risk taking, as well as the ability to plan and manage projects in order to achieve objectives.     Entrepreneurship is becoming more important as the focus increases on the economic impact of education and training, as well as its social impact. The 2013 Annual Growth Survey132 highlighted that all young people should develop entrepreneurial skills for employability and new business creation. Further to this, the Rethinking Education Communication133 underlined the need to drive up the economic impact of education – and entrepreneurship education has been identified as one tool to achieve this at both EU and Member State level. The importance of the entrepreneurship agenda is also highlighted through several of the 2013 country-specific recommendations134. Moreover, entrepreneurship education and skills is also highly visible as one of the three pillars in the Entrepreneurship 2020 Action Plan.    Figure 5.5. Percentage of individuals aged 18 to 64 who believe to have the required skills and knowledge to start a business (2012)  Source: Global Entrepreneurship Monitor 2012.   Self-efficacy, the belief in one's own ability to complete tasks and reach goals, is considered as an important driver of individuals' entrepreneurial activity. The 2012 results from the annual Global Entrepreneurship Monitor in figure 5.5 show that only in a handful of the Member States do more than half of the adult population believe they have the required skills and knowledge to start a business. The decrease in this (business start-up focussed) self-efficacy measure for IT has been considerable (from 42% in 2010 to 30% in 2012), but overall the country patterns remain rather stable135. It is however not possible, based on the existing internationally comparable data, to draw firm conclusions on the contribution of entrepreneurship education to entrepreneurial self-efficacy.  As illustrated in Figure 5.6, recent results from the 2012 Flash Eurobarometer (354) Entrepreneurship in the EU and beyond show that only half of the EU population aged 15 years and above agree that their school education helped them to develop a sense of initiative and a sort of entrepreneurial attitude, with 22% totally agreeing and 28% tending to agree. Young people (15-24) agree to a larger extent (64%) than the rest of the population and so do those who are still studying (66% agree) or who left education after the age of 20 (55%)136.   Compared with 2009, the EU average has remained stable for the indicator on entrepreneurial attitude/sense of initiative, but in several of the Member States there have been significant developments. LV and LT have had the most notable change, with                                                132   http://ec.europa.eu/europe2020/making-it-happen/annual-growth-surveys/index_en.htm.  133   http://ec.europa.eu/education/news/rethinking_en.htm.  134   The 2013 country-specific recommendations, approved by the Council, can be found at:   http://ec.europa.eu/europe2020/making-it-happen/country-specific-recommendations/index_en.htm. The package was adopted by the Council on 19 June 2013. 135   See Figure 2.8 in the Education and Training Monitor 2012 at:   http://ec.europa.eu/education/news/rethinking/sw373_en.pdf. 136   For further qualitative information about entrepreneurship education at school, see Eurydice (2012), Entrepreneurship Education at School in Europe: National Strategies, Curricula and Learning Outcomes.  0102030405060ITDKFIFRBEDESEROLTHUNLEEHRLVIEPTUKESATSKSIPLOnly half of the EU population aged 15 and above agree that their school education helped them develop entrepreneurial competences  60 the percentage in agreement increasing by almost 30 percentage points. UK has seen the largest drop (10 percentage points), bringing it further below the EU average.   Figure 5.6. Percentage of individuals 15 years+ agreeing that their school education has helped them to develop a sense of initiative/sort of entrepreneurial attitude  Source: 2012 Flash Eurobarometer (354) Entrepreneurship in the EU and beyond.  There are marked differences between Member States. In 2012, the percentage agreeing that their school education helped them to develop a sense of initiative and a sort of entrepreneurial attitude ranged from 75% in PT to 35% in UK. Except for RO, all the countries that have a value above the EU average on the entrepreneurial attitude/sense of initiative indicator also have a higher percentage than the EU average stating that they have taken part, at school or university, in any course or activity concerning entrepreneurship (defined as turning ideas into action, developing your own project). One should, however, be cautious about drawing firm conclusions on the impact of entrepreneurship education based on this Eurobarometer data.  In general, most available data has a strong focus on the business start-up dimension of entrepreneurship and is not clearly linked to the impact of the education environment. There is therefore a need to further strengthen the availability of internationally comparable indicators on entrepreneurship education and entrepreneurship as a key competence137. This need is underlined in the forthcoming Commission Staff working document on entrepreneurship in education.  Nevertheless, studies, both at EU and Member State level complement the existing EU-wide indicators, and point to a positive link between entrepreneurship education and entrepreneurial competence and activity. A 2012 study on Effects and Impact of Entrepreneurship Programmes in Higher Education138 covering nine institutions across Europe found that it seemed easier for entrepreneurship alumni to find a position in paid employment immediately after graduation (78% versus 59% for the control group). Furthermore, the study found that entrepreneurship alumni had a higher propensity to be running their own business (8% versus 3% for the control group) or to have been involved in initiatives to start non-commercial projects (49% versus 38% for the control group).   Findings at national level in countries with well-developed monitoring structures for entrepreneurship education also illustrate the benefits of entrepreneurship education. Denmark is an example in point, and recent short-term findings from an on-going Danish longitudinal study139 on the impact of secondary and university level entrepreneurship education showed that entrepreneurship as a method140 has a positive effect on lower secondary pupils' school engagement. At university level, the study found that during their education, entrepreneurship                                                137   For a useful overview of indicators and data sources for entrepreneurship education in 10 Member States see http://ec.europa.eu/education/more-information/doc/2011/entrepreneurship_en.pdf. 138   http://ec.europa.eu/enterprise/newsroom/cf/_getdocument.cfm?doc_id=7428. 139   The Danish Foundation for Entrepreneurship/Young Enterprise Danmark (2013), Impact of Entrepreneurship Education in Denmark. 140        Entrepreneurship as a method is in the Danish study distinguished from more business start-up oriented entrepreneurship education and includes the pupils being taught innovative thinking, developing and turning ideas into action and creating new activities. 0102030405060708020122009The evidence-base on entrepreneurship education needs to be strengthened  61 students strengthen their entrepreneurial attitude and creative skills considerably more than otherwise comparable students who have not participated in entrepreneurship education, and that such education also leads to more students starting their own business.     Policy lessons  The employment rate of recent graduates with at least upper secondary education stands at 75.7%, down from 82% in 2008. There is still a premium of tertiary education attainment over upper secondary education attainment but there is evidence of skills bottlenecks and mismatches, with 21% of people with tertiary qualifications active in jobs that are below their qualifications. This calls for a better alignment of the supply and demand of skills and a higher labour market relevance of education and training systems.  The transition from school to work is a particular issue for students from upper secondary programmes in BG, IE, EL, ES, HR, IT, LV and RO – with employment rates below 60%. Students from vocational education and training programmes experience a better transition from education to work in Member States with developed work-based learning (e.g. DK, DE, NL and AT). Work-based learning helps bring together the worlds of work and education.  Efforts to develop entrepreneurial skills are needed to support new business creation, employee innovation within existing companies, to improve employability levels of the young and increase business creation. Only half of the EU population aged 15 years and above agree that their school education helped them to develop a sense of initiative and a sort of entrepreneurial attitude. Improvements in the availability of internationally comparable data are needed to provide broader information on entrepreneurial self-efficacy and the impact of entrepreneurship education.  6.  Upgrading skills through lifelong learning 

6.1.  Taking a closer look at the Survey of Adult Skills 

In  highlighting  the  challenge  of  skills  supply,  the  2012  Rethinking  Education  Communication141 
recalled that "European education and training systems continue to fall short in providing the right 
skills for employability […]". Until now, evidence on the actual levels of key skills of the workforce 
has been rather limited but the recent OECD Survey of Adult Skills (PIAAC)142, which was carried 
out  with  support  from  the  European  Commission,  serves  to  close  this  gap.  It  provides 
comprehensive evidence on the levels of proficiency in 17 EU Member States143, plus other OECD 
and  partner  countries,  in  the  three  key  information  processing  skills  of  literacy,  numeracy  and 
problem solving in technology-rich environments.  

Global performance of EU education systems  

On  average,  participating  EU  countries  demonstrate  similar  performance  to  the  US  but  slightly 
worse  than  several  non-EU  OECD  countries.  Japan  outperforms  all  other  countries  with  its  high 
share of performers at levels 3-5 and very few low performers. Large differences in the distribution 
of skills across participating EU countries exist. Three groups can be identified: (1) countries with 
high  shares  of  top  performing  adults  and  low  levels  of  low  performers  such  as  NL,  FI  and  SE 
(among  which  FI  comes  closest  to  Japan);  (2)  countries  with  varying  patterns  but  whose  results 
are  not  significantly  different  from  the  EU17  average,  and  (3)  countries  with  few  top  performers 
and rather high shares of low performers such as ES and IT.  

Figure 6.1. Share of the population 16 to 65 years-old at each level of proficiency in literacy 

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

Missing

Level 5

Level 4

Level 3

Level 2

Level 1

Below Level 1

Source: Survey of Adult Skills (PIAAC). Notes: countries ordered by share of levels 1 and below combined. Missing: not taken 
the test.  

In the domain of literacy (Figure 6.1), on average, one fifth of adults in the EU17 reaches at most 
proficiency level 1 out of 5144 (16% at level 1 and 4% below level 1). In the domain of numeracy 

141  
142  

143  

144  

  Rethinking Education: Investing in skills for better socio-economic outcomes (COM(2012) 669 final). 
  PIAAC is the Programme for the International Assessment of Adult Competencies. The Survey of Adult Skills directly 
assesses  the  skills  of  about  5,000  individuals  per  participating  country,  representing  the  countries'  working  age 
population  (16-65  year  olds).  The  skills  tested  are  literacy,  numeracy  and  problem  solving  in  technology-rich 
environments (solving problems in a computer environment). The survey also asks about the use of ICT at work and 
in everyday life, generic skills required at work, whether the skills and qualification match the work requirements and 
questions  about  e.g.  education,  work  and  the  socio-economic  background.  The  first  round  was  carried  out  in 
2011/2012 in 24 countries, among them 17 EU Member States, representing about 83% of the EU28 population. The 
proficiency  that  respondents  showed  in  the  test  is  reported  on  a  scale  from  0  to  500  points,  which  is  divided  into 
"Skills levels" ("below 1" to "5" for literacy and numeracy; "below 1" to "3" for problem solving – see Table A.2 in the 
Annex). For more technical information see Volume II of the survey report: http://www.oecd.org/site/piaac. 
Referred to in this section as "EU17": BE (Flanders), CZ, DK, DE, ES, EE, FR, IE, IT, CY, NL, AT, PL, SK, FI, SE and UK 
(England/Northern  Ireland  –  87%  of  the  UK  working  age  population).  For  FR,  only  limited  results  are  available.  As 
such,  “EU16”  refers  to  the  same  set  of  countries  excluding  FR.  Other  OECD  countries:  Australia,  Canada,  Japan, 
Korea, Norway, United States. The Russian Federation participated but no results are reported. "OECD" in this section 
refers to all participating OECD countries, unless stated differently. 
See Table A.2 in the Annex for an explanation of the proficiency levels. 

62 

 
 
 
 
 
 
 
 
 
                                               
 63 (Figure 6.2), overall levels of proficiency are slightly lower. The share of low achievers is much larger, with 24% of the population scoring at level 1 (17%) or below (6%).   ES and IT have the largest proportion of people scoring at lower skill levels (level 1 and below) both for literacy and numeracy with around 30%. In DE, IE, FR, PL and UK, the share of the population scoring at most level 1 in literacy is rather high (around 18%) but close to values in Canada and the US (17%). All other EU and non-EU countries have values between 10% and 15% except Japan (5%). For proficiency in numeracy, the share of the population scoring at most at level 1 is largest in IE, ES, FR, IT and UK. All other EU countries are below the EU average with values between 12% and 15%, with the exception of DE (18%).  In the EU17, the share of high performers in numeracy (scoring at levels 4 and 5) is 10%, slightly lower than the overall OECD average. Japan outperforms all EU Member States with 63% of the working age population scoring at levels 3-5 (second is FI with 58%). Other non-EU countries are somewhat below (US) or above (Canada) the EU17 average. Some EU countries show a better performance at the top of the proficiency scale with a larger share of higher achievers (levels 4 and 5) in numeracy, namely CZ, DE, PL, AT and SK.    Figure 6.2. Share of the population 16 to 65 years-old at each level of proficiency in numeracy Source: Survey of Adult Skills (PIAAC). Notes: countries ordered by share of levels 1 and below combined. Missing: not taken the test.   Proficiency by age and sex  On average and across countries, men and women show comparable levels of skills. An interesting finding is that the skills disadvantage, in particular for literacy among young men of school age, as repeatedly found by large scale skills surveys such as PISA, cannot be found among the younger age groups of the Survey of Adult Skills. Here, young men broadly perform on a par with young women. Whether young men are catching up through education later, or whether other reasons play a role is difficult to establish, but it underlines the need for flexible and open educational pathways after compulsory school age.  The youngest age group (16 to 24 years) performs on average significantly better than the overall working age population, with an advantage of 7 score points in literacy (equalling roughly one year of education) and 5 score points in numeracy. But these differences vary widely across countries. In BE nl, EE, ES, FR, IT, NL and PL, the younger generation scores 10 or more points better in literacy than the overall population (14 points in PL), while in a few countries the young hardly show any skills advantage (CY, SK) or even score worse than the overall population (UK). Overall, a comparison of the proficiency levels of these age groups that participated in different rounds of the PISA survey shows that country performance in both surveys is broadly comparable.   Another phenomenon observed is that on average, the level of skills rises from the youngest age group to the group aged 25-34, and afterwards shows a steady decline up to the oldest age group (55-65 years old). These results reflect the actual performance of different age groups at a given point of time rather than the development of skills levels over time, which means that this finding 0%10%20%30%40%50%60%70%80%90%100%MissingLevel 5Level 4Level 3Level 2Level 1Below Level 1One in five European adults has only basic levels of skills in literacy and numeracy  64 might point at two different explanations. Firstly, improvements in European education systems in recent decades might be equipping younger cohorts with better skills than the previous generations. Secondly, the lower proficiency for older cohorts might point to a decline in skills over the working life, emphasising the importance of lifelong learning.  Proficiency of unemployed people  Those in employment have on average higher skills than the unemployed at EU level, by about half a proficiency level (17 points for literacy and 24 points for numeracy, equalling up to roughly 4 years of education). The gap is more pronounced in DE, SE and the UK for literacy (19, 30 and 26 points respectively) and for numeracy in the same countries (30, 32 and 33 points respectively) as well as in SK (27 points). In IE, ES, FR, IT and UK, youth unemployment rates are higher by 16 percentage points compared to people in the age bracket 25-74 (close to 30 percentage points higher in ES and IT). In these countries, a large share of young people (close to 20% or above) has low-skills in literacy or numeracy (i.e. at most at level 1).  Those in employment also have higher skills than inactive people at EU level. The gap is similar to that between employed and unemployed at EU level (17 points for literacy and 24 points for numeracy) but more pronounced in DK, NL, FI and SE (25 points or more for literacy and numeracy) as well as in DE and ES (25 points for numeracy). In addition, the Survey shows that there is a substantial pool of highly skilled individuals who are out of the labour market (inactive) in some Member States. CZ, IT, PL and SK have large proportions of inactive people among the high-skilled population (about 24%). This is below 15% in most of the other EU17 countries.  Impact of parental education and country of birth  Parental education is almost as closely correlated to proficiency levels as educational attainment. Adults with highly educated parents reach on average higher scores than those with a less advantageous socio-economic background. However, the strength of the association between skills proficiency and parental education varies widely across countries. Within the EU16 (EU17 less FR), it is strongest in DE and PL, whereas it is weakest in EE, CY and SE.  In all participating countries, foreign-born adults score lower than native-born adults, with the difference being on average half a proficiency level (25 points, which equates to about 4 years of education) in literacy. The differences are above EU average in some countries with large foreign-born populations such as BE (FL), DK, DE, FR, NL and SE. The disadvantage for those who are born elsewhere is slightly more pronounced for numeracy with a 29 point difference. The wide variation in the proficiency scores of foreign-born adults across countries not only reflects the mere skills, but also the composition of this group and the immigration history of the countries.   Skills and educational attainment across countries   For the first time, the Survey of Adult Skills allows linking educational attainment of individuals, i.e. the formal outcome of education, with their proficiency in key information processing skills like literacy and numeracy. This makes it possible to compare average proficiency levels by education attainment within a given country, but also to compare proficiency levels across different countries, looking at comparable levels of education attainment (Figure 6.3).  When comparing results in literacy across countries, young tertiary graduates in FI, NL, SE, BE nl, AT, EE and DE score amongst the highest of any participating country in the survey, with tertiary degree holders in FI reaching the lower end of level 4. Upper secondary graduates on average (EU16) perform at the lower end of level 3, scoring 20 points lower (equalling roughly three years of education) than tertiary graduates.  It is a striking finding that people with lower levels of education attainment in some countries outperform people with higher formal qualifications in other countries. For example, upper secondary graduates in FI and NL score better than tertiary graduates in IE, ES, IT, CY, SK and UK.   Literacy and numeracy skills of graduates with comparable degrees vary strongly across countries, raising questions about the underlying causes  65 Comparing the skills levels of young people from different levels of education within countries also reveals large discrepancies. In SE, IT, AT and PL, tertiary graduates in literacy perform half a proficiency level better than upper secondary graduates (25 score points), with 32 points in BE nl. In ES and DK, tertiary graduates outperform upper secondary graduates by no more than 12 score points.   Figure 6.3. Average proficiency in literacy (16-29 year-olds) by educational attainment    Source: Survey of Adult Skills (PIAAC). Note: countries are ordered by average score at tertiary education level.  Differences in performance between upper and lower secondary graduates within countries are significantly larger. However, in PL almost no difference exists (upper secondary graduates performing only 2 points better); and in CZ, IE, CY and IT the difference is no larger than 14 points (roughly equalling two years of education). Large differences are found in ES, NL, AT and SE, where people with at most lower secondary education perform at least half a proficiency level (25 score points) below upper secondary graduates. The largest gap is found in the UK, where the skills gap between lower and upper secondary education is almost one proficiency level (45 points).  The survey reveals significant differences in the levels of skills at certain levels of education attainment across countries and within countries. However, it should be stressed that the results reflect an interplay of factors. Success in formal education opens up opportunities for individuals to access high skill jobs, which in turn help maintain and develop high skills levels. And there are other factors that might override the impact of education, like work experience, long unemployment spells or non-formal learning. Nevertheless, the analysis does provide relevant information for the monitoring of education and training systems in the EU, particularly on the performance of secondary and tertiary education systems and lifelong learning policies.  Proficiency in problem solving in technology rich environments   Across the EU17, 13% of the working age population either lacked any computer experience or had such low levels of proficiency that they could not take the computer based test (Figure 6.4). This share ranges from less than 10% in DK, NL, FI, and SE to more than 20% in ES, CY, IT, PL and SK. On average across EU countries145, 43% only showed basic levels of proficiency (scoring at level 1 or below). At the top end, in NL, FI and SE, more than 40% showed high proficiency (40% or more at levels 2 and 3), outperforming all non-EU countries except NO.  Among the younger generation of 16 to 24 year-olds, the share of those with very low problem solving skills (9%) or very little to no computer experience (4%) is much smaller than in the overall population. However, compared to the overall working age population, roughly the same share of young adults (around 30%) has only low levels of proficiency in problem solving (level 1).                                                 145   In ES, FR, CY and IT the module problem solving in technology-rich environments (ICT) was not applied. Computer experience was also measured by the other survey tests. 200225250275300325350FINLSEBE nlATEEDECZPLDKSKIEITUKESCYEU16Mean score points Lower secondaryUpper secondaryTertiaryLevel 3 Level 2 Level 4 Level 1 High literacy and ICT use are strongly connected, making poor problem solving skills of one fourth of Europe's workforce a concern  66 Figure 6.4. Share of the population 16 to 65 years-old at each level of proficiency in problem solving in technology rich environments (%)   Source: Survey of Adult Skills (PIAAC). Notes: countries are ordered by share of 'Failed ICT core test/No experience'. Missing: test not taken. 'Opted out': participants chose the paper based version of test over the computer based version.  The survey also reveals a strong relationship between ICT use at or outside work and literacy proficiency. On average in the EU and rather consistently across countries, those who report the strongest use of ICT at the workplace score about 14 points higher on the literacy scale than those who use ICT least at the workplace, independently of other factors such as age, education or sex146; a proficiency difference that corresponds to roughly two years of education.   6.2. Raising adult participation in lifelong learning  Maintaining and upgrading skills through continued learning after initial education is crucial in light of structural changes and technical developments, in order to stay employed, advance in one’s career or to re-enter the labour market147. For these reasons, the ET 2020148 benchmark for adult participation in lifelong learning149 is 15% by 2020 - a target set “with a view to increasing the participation of adults in lifelong learning, particularly that of the low-skilled”150. Indeed, whether looking at the average skill levels or the highest level of education attained151, continued learning is a necessity in the majority of Member States.  Lifelong learning is far from being a reality for most European citizens, which caused EU Member States to take action152. Between 2009 and 2012, the EU adult participation rate in lifelong learning went down 0.3 percentage points – an average annual decrease of 1.1% –  while in fact it should have increased on average 4.4% per year in order to reach the benchmark of 15% by 2020 (Figure 6.5).   Though part of this trend, for instance in PT and UK, is due to on-going harmonisation of the measurement of formal and non-formal education and training153 across Europe, neither current performance nor recent change meet the necessary requirements. In light of this, country-specific recommendations on the topic of lifelong learning have been issued for a number of countries (BE, EE, ES, FI, FR, LU, PL, RO and SI).                                                146   Differences are adjusted for background characteristics such as age, education attainment, sex, immigration and language background, etc. 147  See, for example, European Commission, Directorate-General for Research & Innovation (2013), Adult and continuing education in Europe. Using public policy to secure a growth in skills (http://ec.europa.eu/research/social-sciences/pdf/kina25943enc.pdf). 148   ET 2020: A strategic framework for European cooperation in education and training (2009/C 119/02). 149  The percentage of the population aged 25-64 participating in formal or non-formal education and training during the 4 weeks prior to the EU Labour Force Survey. The ET 2020 Framework emphasises explicitly that benefit can also be drawn from the information on adult participation in lifelong learning gathered through the Adult Education Survey (See Annex 1 in 2009/C 119/02). 150   2009/C 119/02, Annex 1. 151  Across the EU, one in four individuals aged 25 to 64 has at most a lower secondary education attainment; more than 40% in PT, MT, ES and IT. See Figure A.1 in the Annex for a full distribution of education attainment across Europe. 152   OJ 2011/C 372/01.  153  Formal, non-formal and informal learning are defined in the Eurostat Classification of learning activities: http://epp.eurostat.ec.europa.eu/portal/page/portal/product_details/publication?p_product_code=KS-BF-06-002. 0102030405060708090100MissingOpted outLevel 3Level 2Level 1Below 1Failed ICT/NoexperienceProgress in adult learning is lagging far behind the EU's commitment  67 Only DK, SE, FI, NL and UK are above the ET 2020 target, with NL and UK no longer making any progress. Of all the Member States below the 15% benchmark, only LV, EE, LT and MT are progressing beyond the requirements for the EU as a whole to reach the target. The remaining Member States are making insufficient progress, with some even showing an average annual decrease in participation rates (BE, EL, CY, PL, RO, SI and PT, the latter despite progress in its provision of continuing vocational training by enterprises – see below).   Figure 6.5. Adult participation in lifelong learning: current performance and recent change    Source: JRC-CRELL and DG EAC calculations based on Eurostat (LFS) data. Notes: Countries are shown according to their 25-64 cohort size, with five categories. The average annual change rate is calculated without including breaks in series, i.e. for CZ (2011), LV (2011), LU (2009), NL (2010) and PT (2011). UK’s change from 2010 to 2011 is excluded due to a revision of the LFS questionnaire, which altered the participation rates in adult lifelong learning.  Participants in lifelong learning constitute a diverse group. Taking a closer look at the actual adult participants in formal and non-formal learning does, therefore, shed light on the underrepresented groups that might require extra incentives if Member States are to reach the 15% target by 2020.  A gender pattern in lifelong learning participation  Table 6.1 shows that average participation in lifelong learning is higher for females (9.7%) than for males (8.4%). This is true for all Member States with the exception of DE, EL, LU and RO and is most pronounced in SE and DK (about 13 percentage points).  Foreign-born learners  Participation in lifelong learning is, on average, slightly higher for the foreign-born population than it is for the native-born population – and amongst the former, those born outside the EU participate more than those born in another EU Member State. One reason for this might be the participation of foreign-born learners in language courses, which could positively affect the overall average. Adult learning is especially relevant for foreign-born individuals as it offers an opportunity to develop their potential, adapt their competences to the local labour market, and to foster inclusion and social participation.  The effect of age, education attainment and skills  Young adults have by far the highest participation rate in formal and non-formal learning (Figure 6.6), indicating both higher participation in formal learning (i.e. initial tertiary education) and activities to adapt to skills needs at an early stage of the working life. More pronounced, the participation rate for adults with high education attainment is double that LU LT MT EE LV SI FI SK DK IE BG SE PT AT HU EL NL ES BE RO DE FR UK IT PL CY EU CZ HR 0,05,010,015,020,025,030,035,0-10,0-8,0-6,0-4,0-2,00,02,04,06,08,010,0Minimum progress required ET 2020 benchmark Adult participation in lifelong learning 2012 Average annual change in adult learning rate (%) over the period 2009-2012 Adult learning is most prominent amongst the young and highly educated  68 of medium-educated and four times that of low-educated adults. The latter illustrates the use of lifelong learning programmes to get ahead rather than to get by, which still does not match the emphasis on the low-skilled as set out in the ET 2020 strategic framework.   Table 6.1. Adult participation in lifelong learning by sex and country of birth (%)   2009 2012 Total Total Males Females Native-born Foreign-born EU Non EU Sub-total EU 28 9.2 9.0p 8.3 9.7 8.9 9.8 11.0 10.6 Belgium 6.8 6.6 6.2 6.9 6.1 8.0 9.1 8.7 Bulgaria 1.4 1.5 1.4 1.5 1.5 : : : Czech Republic 6.8 10.8 10.5 11.1 10.9 8.8 6.4 7.9 Denmark 31.2 31.6 25.4 37.8 31.6 30.2 32.1 31.5 Germany 7.8 7.9 8.0 7.8 8.2 : : : Estonia 10.5 12.9 10.6 14.9 13.8 : 6.6 7.0 Ireland 6.3 7.1 6.7 7.4 6.7 6.9 12.3 8.5 Greece 3.3 2.9 3.1 2.7 3.1 (2.8) 1.3 1.6 Spain 10.4 10.7 9.9 11.6 11.2 7.2 9.2 8.6 France 5.7 5.7 5.4 6.0 5.8 4.5 5.1 5.0 Croatia 2.3 2.4 2.3 2.6 2.4 : (2.1) (2.3) Italy 6.0 6.6 6.1 7.0 7.0 3.3 3.6 3.5 Cyprus 7.8 7.4 7.0 7.8 8.1 5.1 5.8 5.4 Latvia 5.3 7.0 6.0 7.9 7.3 : 5.1 5.2 Lithuania 4.5 5.2 4.3 5.9 5.2 : : : Luxembourg 13.4b 13.9 14 13.8 15.6 11.7 15.5 12.4 Hungary 2.7 2.8 2.6 3.0 2.8 (4.3) : 4.2 Malta 6.1 7.0 6.7 7.4 7.1 : (7.9) 6.1 Netherlands 17.0 16.5p 16.0 17.0 16.2 18.6 17.7 17.9 Austria 13.8 14.1 13.0 15.2 14.7 16.4 8.8 11.7 Poland 4.7 4.5p 3.8 5.1 4.4 : : : Portugal 6.5 10.6 10.3 10.9 10.2 12.0 14.8 14.1 Romania 1.5 1.4 1.4 1.3 1.4 : : : Slovenia 14.6 13.8 11.5 16.1 14.6 (8.3) 5.7 5.9 Slovakia 2.8 3.1 2.7 3.5 3.0 : : : Finland 22.1 24.5 20.7 28.4 24.3 25.7 29.7 28.0 Sweden 22.2p 26.7 20.0 33.5 26.7 22.9 28.0 26.5 United Kingdom 20.1 15.8 14.3 17.4 15.3 16.1 20.0 18.7 Montenegro : : : : : : : : Iceland 25.1 27.3 23.5 31.0 28.1 23.8 14.7 20.5 MK 3.3 4.0 4.0 3.9 : : : : Serbia : : : : : : : : Turkey 2.3 3.2 3.2 3.1 : : : : Liechtenstein : : : : : : : : Norway  18.1 20.0 18.8 21.3 19.7 18.9 23.3 21.5 Switzerland 23.9i 29.9 31.1 28.7 32.9 26.2 21.2 24.0 Source: Eurostat (LFS online data code trng_lfse_01). Notes: Data cover formal and non-formal learning activities alike. Intermediate breaks in time series for the Czech Republic (2011), Latvia (2011), the Netherlands (2010), Luxembourg (2009) and Portugal (2011) and changes to the methodology in the UK (2011). Notes: "b" = break in time series; "p" = provisional; "()" = Data lack reliability due to small sample size; ":" = data either not available or not reliable due to very small sample size.  The Survey of Adult Skills (see section 6.1) confirms that those with higher skills have higher access rates to education and training154. An individual with high skills is, on average, more than five times as likely to attend adult learning activities compared to someone with skills at the lowest level (below level 1). In DE, ES, IT, AT and PL, there is 5 to 7 times less chance for low-skilled workers to participate in job-related learning compared to high-skilled people, with the difference being largest in SK. In other words, 20% of the EU population aged 16-65 (those with skills at level 1 and below) is caught in a low skills trap, which means that they are unlikely to leave                                                154   Based on one year preceding the interview. Due to survey design and time of data collection, results slightly differ from those of the Adult Education Survey. With little likelihood of continuing learning, adults with low skills may be caught in a "low skills trap"  69 the group of low-skilled workers. A key policy challenge is to help low-skilled adults to escape this trap.  Job-related learning  Data on individuals from latest Adult Education Survey (AES) 2011 and data on enterprises from the Continuing Vocational Training Survey (CVTS) 2010 reveal complementary evidence on adult learning with a focus on access to job-related education and training155 over a period of one year.   Figure 6.6. Adult participation in lifelong learning by education level and age (%)  Source: Eurostat (LFS online data code trng_lfse_01 and trng_lfse_03).   A closer look at adult learning activities based on the AES shows that on average the access rate in non-formal training is fifteen times that in formal training (38.4% as opposed to 2.4%), with strong variations across countries. While more than half (52.7%) of the non-formal activities were sponsored by enterprises, 28.4% was otherwise job-related, meaning that in total four out of five activities were job-related (81.4%). This is a consistent phenomenon across Europe, ranging from slightly above 70% in EL and SI to more than 90% in BG, MT and SK.  High non-formal access rates (close to 50% or above) in a country tend to correspond with frequent job-related activities at the workplace (two thirds or more), which is the case in DK, DE, FR, NL, FI and SE. In BG, ES, IT, MT, SK and UK, job-related activities outside the workplace were predominant. They represented about half of more of all non-formal activities, much more than the EU average. Access rates to non-formal learning were below the EU average in these countries (close to 34%; 24% in BG) except in SK and UK (close to 40%).  More generally, there are still large gaps in access rates by employment status. 45.2% of employed people aged 25-64 had a non-formal learning activity, almost double the rate of unemployed people (22.9%) according to the AES. This gap was even larger in BG, LT, HU, PL and SK; only one third of the access rate of employed people. In these countries, as well as in EL, less than 15% of the unemployed received training in 2011 (17% in HU). As regards access to formal learning, the employed and unemployed had about the same opportunities in 2011; close to 6% at EU level, with 16% or more in DK, PT, SE and UK.                                                   155   The analysis in this section covers only formal and non-formal learning, in line with the ET 2020 benchmark on adult learning. This excludes informal learning; any intentional learning resulting from activities related to work, family or leisure that is not organised or structured in terms of objectives, time or learning support. Informal learning is, however, an increasingly important dimension of continued learning. With the increasing availability of digital devices and ICT-based learning resources, informal learning becomes more important for adult lifelong learning policies. 024681012141618Low education(ISCED 1-2)Mediumeducation(ISCED 3-4)High education(ISCED 5-6)25-34 years35-44 years45-54 years55-64 years2012Decrease compared to 2009Education level Age group Four out of five adult learning activities in Europe are job-related Only 1 in 5 unemployed had a non-formal learning activity in 2011 at EU level; no more than 1 in 7 in BG, EL, LT, HU, PL and SK  70 Policy lessons  New evidence from the Survey of Adult Skills shows that low achievement in literacy and numeracy is alarming for many Member States. Across the seventeen EU Member States participating in the survey, 20% of 16 to 65 year-olds is unable to exceed a basic level of literacy and 24% is unable to do so in numeracy.  Striking differences in literacy and numeracy proficiency of young adults with comparable educational attainment across countries raise questions about the underlying causes.  These results underline the need for lifelong learning. However, skills levels and participation in adult learning are strongly connected in many countries, confirming that lifelong learning is still not profited from by those who would benefit from it most. Adult participation in lifelong learning stands at only 9% and is most prevalent amongst the young and highly educated.  On average, two thirds of enterprises in the EU provide continuing vocational training. It is less than a third in BG, EL, PL and RO. Only one in five unemployed had a non-formal learning activity in 2011; no more than one in seven in BG, EL, LT, HU, PL and SK.  Engagement of enterprises in continuing vocational training (CVT)  Participation in job-related training is dependent on learning opportunities at the workplace (i.e. during working time or paid at least partially by enterprises), which is reflected in the latest CVTS results156. On average two thirds of enterprises in the EU provided continuing vocational training in 2010. It was less than a third in BG, EL, PL and RO, and, conversely, 70% or more in BE, CZ, DE, ES, FR, CY, LU, NL, AT, FI, SE and UK.   In BG, PL and RO, a high share of employees had access to CVT (above EU average), while a comparatively low share of enterprises offered training, pointing at an active role of larger enterprises in CVT in these countries. In EL, HR, LT and HU the share of enterprises providing training and the share of employees having access to CVT within these enterprises was significantly below average. Looking at the intensity of CVT, these countries were close to the EU average (EL, HR) or above (LT, HU).   Limited average hours per participant (15 hours or less per year) was recorded in CZ, ES and LV. MT, PT and SI were the countries with the highest number of training hours per year (37 to 42).   Costs of CVT activities represented 0.9% of labour costs in 2010 on average in the EU, with more than 1% in FR, HU, NL and MT157. This includes direct costs incurred for the organisation of courses as well as contributions paid to mutual funds and payments from such funds or other financial subsidies. On average for all enterprises providing training or not, average contributions were higher than average subsidies in FR, HU and RO (close to 0.5% of labour costs). Furthermore, about one third of enterprises reported that public measures, mostly of financial nature, had a direct impact on their CVT plans.   Across the EU, no more than 40% of enterprises declared having a training plan or budget in 2010. In IT, HU, LV, LT, MT and RO more than 35% and in BG and PL more than 50% of enterprises reported that they did not provide any CVT because the skills of the employees matched the current needs of the enterprise. These results underline that CVT still has to be promoted further and that a solid assessment of future changes in skills needs is required.                                                     156   The Continuing Vocational Training Survey (CVTS 2010) reports CVT activities in the past 12 months. 157   http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/Continuing_vocational_training_statistics. Two thirds of European enterprises provide continuing vocational training, with huge variations across countries, ranging from 31% to 87% Annex 

Table A.1. Population trends by five-year age groups 

Less than 5 years old 
2020 
2015 
2010 
: 
: 
4.6 
-2.5 
0.8 
4.6 
2.0 
4.8 
9.4 
-11.7 
1.3 
10.8 
-6.6 
2.0 
21.2 
1.2 
-4.0 
-0.6 
-0.7 
-2.7 
-6.7 
-5.8 
2.6 
17.2 
-8.0 
3.9 
18.9 
-7.4 
0.8 
9.9 
-9.3 
-3.3 
13.3 
-0.6 
1.4 
2.0 
: 
: 
4.1 
-4.7 
-2.3 
4.1 
5.3 
13.4 
12.0 
-7.2 
-5.2 
13.5 
-3.6 
10.2 
6.2 
4.4 
7.3 
2.6 
-5.1 
-2.3 
2.4 
-1.2 
1.7 
1.2 
1.2 
-0.5 
-8.5 
1.6 
-1.4 
-1.2 
-6.4 
6.6 
8.8 
-6.4 
-7.9 
-6.1 
-7.9 
-2.7 
2.2 
-5.2 
8.2 
14.5 
-5.6 
7.5 
7.8 
1.5 
4.5 
5.1 
5.1 
7.3 
12.9 
3.0 
5.4 
12.0 

EU28 
EU27 
BE 
BG 
CZ 
DK 
DE 
EE 
IE 
EL 
ES 
FR 
HR 
IT 
CY 
LV 
LT 
LU 
HU 
MT 
NL 
AT 
PL 
PT 
RO 
SI 
SK 
FI 
SE 
UK 

 5 to 14 years old 
2015 
: 
1.5 
4.7 
6.5 
12.9 
-1.6 
-6.8 
11.3 
12.2 
5.9 
10.0 
2.0 
: 
3.6 
-1.7 
8.7 
-6.8 
1.5 
-1.2 
-7.2 
-2.3 
-4.8 
-2.5 
-1.4 
-0.9 
7.3 
-1.5 
1.0 
8.9 
4.0 

2010 
-4.1 
-4.1 
-1.4 
-11.2 
-12.4 
-2.2 
-7.9 
-11.6 
8.4 
-2.4 
8.4 
2.9 
-8.6 
2.0 
-7.6 
-19.0 
-22.2 
4.4 
-10.4 
-13.3 
-0.5 
-7.9 
-16.4 
0.3 
-8.8 
-6.3 
-16.4 
-6.4 
-8.8 
-5.5 

2020 
: 
2.6 
6.2 
4.6 
10.9 
-1.6 
-4.0 
9.2 
9.5 
5.4 
3.2 
1.7 
: 
0.5 
11.1 
3.8 
9.0 
3.3 
-0.1 
2.0 
-4.2 
-1.0 
7.8 
-6.2 
-0.1 
10.9 
7.9 
4.7 
8.6 
8.6 

15 to 24 years old 
2015 
: 
-6.8 
0.6 
-21.7 
-14.8 
4.6 
-8.8 
-24.2 
-6.9 
-5.9 
-5.6 
-2.4 
: 
0.3 
-7.3 
-27.7 
-18.8 
8.6 
-9.4 
-8.8 
1.5 
-2.2 
-16.7 
-3.4 
-20.8 
-12.2 
-15.5 
-1.6 
-4.6 
-3.1 

2010 
-3.6 
-3.5 
4.0 
-12.2 
-3.6 
13.5 
-4.4 
-10.4 
-11.9 
-13.3 
-8.0 
-1.8 
-8.3 
-0.2 
10.9 
-9.2 
-3.2 
10.3 
-5.2 
-1.1 
4.1 
1.2 
-12.7 
-11.0 
-11.1 
-11.3 
-9.3 
1.2 
13.4 
5.2 

2020 
: 
-4.2 
-1.9 
-11.9 
-11.6 
-2.2 
-6.5 
-12.4 
14.5 
-2.0 
4.3 
1.1 
: 
0.7 
-11.3 
-19.2 
-21.9 
1.9 
-10.1 
-13.5 
-0.5 
-6.7 
-16.4 
1.4 
-8.5 
-6.2 
-15.8 
-6.2 
-9.5 
-5.0 

25 to 34 years old 
2015 
: 
-1.6 
3.5 
-7.4 
-10.3 
-1.2 
3.2 
6.3 
-14.0 
-13.1 
-16.9 
3.8 
: 
-7.0 
5.3 
6.2 
6.2 
6.4 
-11.0 
-0.3 
4.1 
2.3 
-0.6 
-12.1 
-1.6 
-3.2 
-4.4 
1.2 
10.0 
10.0 

2010 
-1.5 
-1.6 
1.1 
-2.7 
-1.4 
-9.0 
-3.2 
4.0 
14.9 
-4.0 
0.2 
-3.5 
3.5 
-10.0 
16.3 
2.3 
-1.9 
8.9 
-2.9 
7.7 
-8.5 
-1.4 
10.2 
-3.9 
-2.3 
3.7 
4.8 
7.1 
-0.6 
1.6 

2020 
: 
-3.6 
2.5 
-13.4 
-4.8 
8.8 
-3.7 
-10.0 
-20.2 
-13.0 
-11.4 
-1.0 
: 
-0.4 
-0.6 
-8.8 
-2.5 
3.0 
-3.7 
-1.1 
4.0 
2.0 
-11.2 
-9.0 
-10.7 
-10.5 
-8.1 
1.0 
9.8 
3.8 

Source: Eurostat (Demographic statistics; online data code: demo_pjangroup and proj_10c2150p). 

Figure A.1. The distribution of education attainment for individuals aged 25-64 (2012) 

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

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

TR MK IS NO CH

Lower secondary education

Upper secondary education

Tertiary education

Source: Eurostat (LFS). 

71 

 
 
 
 
 
  
 
 
 
 
 
 
 
Table A.2. Survey of Adult Skills - Brief description of proficiency levels and score points 

Level 

Score range 

Literacy 

Numeracy 

5 

500 to 376 

4 

375 to 326 

3 

325 to 276 

2 

275 to 226 

1 

225 to 176 

Below 1  Below 176  

Adults are able to e.g. perform tasks that 
involve searching for and integrating 
information across multiple, dense texts; 
constructing syntheses of similar and 
contrasting ideas or points of view, or 
evaluating evidence and arguments.  

Adults can perform multiple-step 
operations to integrate, interpret, or 
synthesise information from complex or 
lengthy continuous, non-continuous, 
mixed, or multiple-type texts that involve 
conditional and/or competing information. 

Adults can understand and respond to 
dense or lengthy texts, including 
continuous, non-continuous or multiple 
pages. They understand text structures and 
rhetorical devices and can identify, 
interpret or evaluate one or more pieces of 
information and make appropriate 
inferences. 

Adults can integrate two or more pieces of 
information based on criteria, compare and 
contrast or reason about information and 
make low-level inferences. They can 
navigate within digital texts to access and 
identify information from various parts of a 
document. 

Adults can e.g. understand complex representations, 
and abstract and formal mathematical and statistical 
ideas, sometimes embedded in complex texts. They 
can integrate several types of mathematical 
information where considerable translation is required. 

Adults understand a broad range of mathematical 
information that may be complex, abstract or 
embedded in unfamiliar contexts. They can perform 
tasks involving multiple steps and select appropriate 
problem-solving strategies and processes. 

Adults can complete tasks that require an 
understanding of mathematical information that may 
be less explicit, embedded in contexts that are not 
always familiar, and represented in more complex 
ways. They can perform tasks requiring several steps 
and that may involve a choice of problem-solving 
strategies. 

Adults can perform tasks that require identifying and 
acting upon mathematical information and ideas 
embedded in a range of common contexts where the 
mathematical content is fairly explicit or visual with 
relatively few distractors. The tasks may require 
applying two or more steps. 

Adults can read relatively short digital or 
print continuous, non-continuous, or mixed 
texts to locate a single piece of 
information, which is identical to or  
synonymous with the information given in 
the question or directive. 

Adults at Level 1 can complete tasks involving basic 
mathematical processes in common, concrete contexts 
where the mathematical content is explicit with little 
text and minimal distractors. They can perform one-
step or simple processes involving e.g. counting, 
sorting and basic arithmetic operations. 

Individuals can read brief texts on familiar 
topics and locate a single piece of specific 
information identical in form to information 
in the question or directive. They are not 
required to understand the structure of 
sentences and only basic vocabulary 
knowledge is required. 

Adults can only cope with very simple tasks set in 
concrete, familiar contexts where the mathematical 
content is explicit and that require only simple 
processes such as counting; sorting; performing basic 
arithmetic operations with whole numbers or money. 

Level 

Score range 

Problem solving in technology rich environments 

3 

2 

1 

500 to 340 

340 to 291 

290 to 241 

Adults complete tasks involving multiple applications, a large number of steps, impasses, and 
the discovery and use of ad hoc commands in a novel environment. 

Adults can complete problems that have explicit criteria for success, a small number of 
applications, and several steps and operators. They can handle unexpected outcomes or 
impasses. 

Adults can complete tasks in which the goal is explicitly stated and for which the necessary 
operations are performed in a familiar environment. They can solve problems whose solutions 
involve a small number of steps. 

Below 1 

Below 241  

Tasks are based on well-defined problems involving the use of only one function within a 
generic interface to meet one explicit criterion. Few steps are required and no sub-goal has to 
be generated. 

Failed ICT 
core 

- 

No computer 
experience 

- 

Opted out 

- 

Adults had prior computer experience but failed the ICT core test, which assesses basic ICT 
skills. Therefore, they did not take part in computer-based assessment, but took the paper-
based version of the assessment. 

Adults reported having no prior computer experience; therefore, they took the paper-based 
version of the assessment, which does not include the problem solving in technology-rich 
environment domain.  

Adults in this category opted to take the paper-based test without first taking the ICT core 
assessment, even if they reported some prior experience with computers.  

Source: OECD (2013), International report on the Survey of Adult Skills, Volume II. 

72