Building up evidence on work-based learning in VET : a reflection on sources for possible indicators or benchmarks on work-based learning.
Date: 2020-04-28
Institutions: Joint Research Centre
Subjects: activity report, adult education, continuing vocational training, education policy, educational reform, educational system, labour market, professional qualifications, vocational education, vocational training

Building up evidence on 

work-based learning in VET 

A reflection on sources 
for possible indicators or 
benchmarks on  
work-based learning 

Flisi, S. 

2020  

EUR 29883 EN 

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

Contact information  
Sara Flisi  
European Commission – Joint Research Centre 
Via E. Fermi 2749, I-21027 Ispra (VA), Italy 
Sara.FLISI@ec.europa.eu  

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

JRC118196 

EUR 29883 EN 

PDF 

ISBN 978-92-76-12117-6 

ISSN 1831-9424 

doi10.2760/645199 

Luxembourg: Publications Office of the European Union, 2020  

© European Union, 2020  

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How to cite this report: Flisi, S., Building up evidence on work-based learning in VET, EUR 29883 EN, Publications Office of the European 
Union, Luxembourg, 2020, ISBN 978-92-76-12117-6, doi:10.2760/645199, JRC118196 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Contents 

Acknowledgements .......................................................................................................................................................................................................... 1 

Abstract ................................................................................................................. 2 

1 

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

2  Definition of work-based learning ................................................................................. 4 

3  Overview of the 2016 LFS AHM on young people on the labour market ....................................... 5 

3.1  An overview of work experience during studies in the EU ................................................. 6 

3.2  Choices after graduation ................................................................................... 11 

3.3  Labour market outcomes .................................................................................. 12 

3.4  The characteristics of employment and job quality among the employed ............................. 16 

4  Work-based learning in UOE data ............................................................................... 21 

5  Overview of alternative potential data sources ................................................................ 23 

5.1  Previous LFS AHM on young people on the labour market .............................................. 23 

5.2 

Information from core LFS variables (TEMPREAS variable) ............................................. 25 

5.3  OECD Survey of Adult Skills (PIAAC) ....................................................................... 25 

5.4  OECD special survey ........................................................................................ 27 

5.5  Continuing Vocational Training Survey (CVTS) ............................................................ 27 

5.6  Cedefop European Skills and Jobs Survey (ESJS) ........................................................ 28 

5.7  Cedefop VET opinion survey ............................................................................... 29 

5.8  Labour Cost Survey (LCS) .................................................................................. 30 

5.9  Structure of Earnings Survey (SES) ........................................................................ 30 

6  Preliminary assessment of the potential data sources ........................................................ 31 

7  An in-depth analysis of the strengths and weaknesses of LFS AHM/HATWORK, LFS TEMPREAS and UOE  35 

7.1  Type of WBL experience .................................................................................... 35 

7.2 

ISCED levels ................................................................................................. 35 

7.3  Survey vs. administrative data ............................................................................ 35 

7.4  Stock vs. flow information ................................................................................. 36 

7.5  Comparability over time .................................................................................... 37 

8  Conclusions........................................................................................................ 38 

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

List of abbreviations ................................................................................................. 40 

List of figures ......................................................................................................... 41 

List of tables .......................................................................................................... 42 

Annex 1. Statistical Annex ........................................................................................... 43 

Annex 2. Definitions of work-based learning and apprentices/apprenticeships in Eurostat data sources ..... 45 

i 

Acknowledgements 

This report is part of the “Towards the development of analytical and monitoring frameworks for VET, adult 
learning, skills and tasks (VAST)” Administrative Agreement between DG EMPLOYMENT, SOCIAL AFFAIRS AND 
INCLUSION  (EMPL)  and  DG  JOINT  RESEARCH  CENTRE  (JRC).  Its  content,  “Statistical  analysis  of  work-based 
learning  (WBL)  in  VET  across  the  EU”,  is  stipulated  under  Task  1  of  the  Technical  Annex  accompanying  the 
VAST Agreement.  

The  author  would  like  to  thank  Mantas  Sekmokas,  Dana-Carmen  Bachmann  (DG  EMPL)  and  Enrique 
Fernández-Macías  (DG  JRC)  for  their  useful  comments  and  suggestions  to  improve  earlier  versions  of  this 
report, as well as colleagues from DG ESTAT (in particular Elodie Cayotte, Sabine Gagel, Malgorzata Stadnik, 
Alessandro  Albano,  Ines  Kolakovic  and  Mélina  Antuofermo)  and  members  of  the  OECD  INES  Network  (in 
particular Pascale Poulet-Coulibando of the French Ministry of Higher education, and Research and Innovation) 
for providing supporting information and special extractions. 

Authors 

Sara Flisi 
European Commission – Joint Research Centre 
Via E. Fermi 2749, I-21027 Ispra (VA), Italy 
Email: Sara.FLISI@ec.europa.eu  

1 

 
 
Abstract 

Work-based learning (WBL) has been high on the policy agenda of the European Commission for many years. 
Given the priority attributed to work-based learning in vocational education and training (VET) across the EU, 
the  Commission  is  currently  exploring  different  options  for  supporting  its  further  development  and  tracking 
progress in this field. One of the options is the development of indicators  or a benchmark to monitor work-
based learning in formal VET. This report provides evidence in support of this process. After elaborating the 
main  definitions  relevant  to  the  work-based  learning  domain,  it  presents  an  overview  of  the  main  data 
sources  currently  available  to  monitor  country  performance  in  WBL.  It  also  provides  an  assessment  of  the 
strengths  and  weaknesses  of  the  sources  that  could  underpin  a  possible  indicator  or  benchmark  on  work-
based learning. 

2 

 
1 

Introduction 

Vocational  education  and  training  (VET)  represents  a  fundamental  component  of  education  and  lifelong 
learning  systems,  providing  individuals  with  the  knowledge,  skills  and  competences  required  on  the  labour 
market.  Enhancing  provision  and  access  to  high-quality  learning  opportunities  has  been  at  the  heart  of 
European  education,  training  and  employment  policies  for  many  years.  One  of  the  main  priorities  in  the 
European Commission’s VET policy has been the promotion of work-based learning (WBL) and apprenticeships 
schemes in VET systems, as tools to deliver labour market relevant skills, ease transitions to labour market, 
and contribute to reducing youth unemployment. 

The  2002  Copenhagen  Declaration  launched  the  European  strategy  for  enhanced  cooperation  in  VET, 
commonly referred to as the "Copenhagen process". In 2010, the Bruges Communiqué on enhanced European 
cooperation  in  VET  for  2011-2020  was  adopted (1),  defining  common  objectives  for  2020  and  outlining  a 
series of actions to increase the quality of VET in Europe in order to make it more accessible and relevant to 
the  labour  market.  The  Bruges  Communiqué  provided  that  “work-based  learning  carried  out  in  partnership 
with businesses and non-profit organisations should become a feature of all initial VET courses.”  

European cooperation on VET was further enhanced by the 2015 Riga Conclusions, where Ministers in charge 
of VET together with the EU Social Partners and the Commission agreed  to “promote work-based learning in 
all its forms, with special attention to apprenticeships, by involving social partners, companies, chambers and 
VET providers, as well as by stimulating innovation and entrepreneurship”.  

In  the  New  Skills  Agenda  for  Europe (2),  the  European  Commission  committed,  in  cooperation  with  Member 
States,  social  partners  and  education  and  training  providers,  to  “support  the  implementation  of  the  Riga 
Conclusions  for  quality  and  labour  market  relevant  vocational  skills  and  qualifications,  by:  supporting 
opportunities for learners to undertake a work-based learning experience as part of their studies; increasing 
opportunities  for  VET  learners  to  combine  learning  experiences  acquired  in  different  settings  […];  improving 
data availability on labour market outcomes of VET”. 

In March 2018, the Council adopted a Recommendation on a European Framework for Quality and Effective 
Apprenticeships (3). The recommendation foresees different common criteria for the quality and effectiveness 
of  apprenticeships,  aimed  at  helping  Member  States  to  develop  and  promote  their  national  apprenticeship 
schemes.  

Given  the  priority  attributed  to  work-based  learning  in  VET  across  the  EU,  the  Commission  is  currently 
exploring different options for supporting  its further development and tracking progress in this field. One of 
the options that could be pursued in this respect is the development of an indicator(s) and/or a benchmark to 
monitor work-based learning in formal VET (4).   

This  report  is  aimed  at  providing  evidence  in  support  of  this  process.  After  providing  the  main  definitions 
relevant  to  the  work-based  learning  domain,  it  will  present  an  overview  of  the  main  data  sources  currently 
available  to  monitor  country  performance  in  WBL.  It  will  also  provide  an  assessment  of  the  strengths  and 
weaknesses of the sources that could underpin a possible indicator(s) or benchmark on work-based learning. 

The rest of the report is structured as follows. Section 2 provides the definition of the main concepts related 
to WBL. Sections 3 and 4 present an overview of what can be considered as the main sources to monitor the 
prevalence  of  work-based  learning  and  its  related  outcomes  (i.e.  the  Labour  Force  Survey  and  the  joint 
UNESCO-UIS/OECD/EUROSTAT  data  collection  on  education  statistics),  while  Section  5  describes  other 
potential sources of information that could be taken into account for monitoring purposes. Section 6 provides 
a preliminary assessment of all the potential data sources, while Section 7 analyses further the strengths and 
weaknesses of the main candidate data sources for a potential indicator or benchmark. Section 8 concludes.  

(1)   The  Bruges  Communiqué  on  enhanced  European  Cooperation  in  Vocational  Education  and  Training  for  the  period  2011-2020. 

https://www.eqavet.eu/Eqavet2017/media/Documents/brugescom_en.pdf 
(2)   https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52016DC0381 
(3)   http://data.consilium.europa.eu/doc/document/ST-6779-2018-INIT/en/pdf  
(4)   VET  can  take  place  either  during  initial  formal  education  (normally  at  upper  secondary  level,  before  beginning  working  life)  –  in 
which case it is generally defined initial vocational education and training (IVET) – or as continuing VET (CVET), that is after 
initial education and training, or after beginning working life. The current document focuses on IVET only.  

3 

                                           
2  Definition of work-based learning  

According to Cedefop (2014), work-based learning (WBL) can be defined as the “acquisition of knowledge and 
skills through carrying out – and reflecting on – tasks in a vocational context, either at the workplace (such as 
alternance training) or in a VET institution”. In line with the Rethinking Education Communication (5), European 
Commission (2013) identifies three main models of WBL: 

1.  Alternance schemes or apprenticeships: in these programmes, learners  spend a significant time on 
training in companies; in parallel, or in "alternating" periods, they acquire general and occupation-related 
knowledge  and  often  complementary  practical  skills  and  key  competences  in  VET  schools  or  other 
education/training institutes. These programmes are therefore fundamentally based on the integration of 
companies as training providers together with VET schools or other education/training institutes. They are 
typically  known  in  Austria  and  Germany  as  the  "dual  system".  Although  the  terms  alternance  and 
apprenticeship  are  often  used  interchangeably,  according  to  Cedefop  (2014)  the  latter  could  be 
considered as a specific form of the former: 

a.  Alternance  training  is  defined  as  education  or  training  combining  periods  in  an  educational 
institution or training centre and in the workplace. The alternance scheme can take place on a weekly, 
monthly  or  yearly  basis.  Depending  on  the  country  and  applicable  status,  participants  may  be 
contractually linked to the employer and/or receive a remuneration.  

b.  Apprenticeships, on the other hand, are systematic, long-term trainings alternating periods at the 
workplace  and  in  an  educational  institution  or  training  centre.  They  are  therefore  typically 
characterised  by  a  long-term  training  period  and  higher  amount  of  training  in  the  workplace  in 
comparison to other forms of alternance training. Moreover, the apprentice is contractually linked to 
the employer, and receives remuneration (wage or allowance). The employer assumes responsibility 
for providing the trainee with training leading to a specific occupation. 

2.  School-based  VET  which  includes  on-the-job  training  periods  in  companies.  On-the-job  training 
periods  typically  cover  internships,  work  placements  or  traineeships  that  are  incorporated  as  a 
compulsory  or  optional  element  of  VET  programmes  leading  to  formal  qualifications.  They  can  be  of 
varying duration but typically represent less than 50% of the training programme duration (often around 
25-30%  or  less).  They  are  primarily  intended  as  effective  school-to-work  transition  mechanisms  that 
allow young  people to familiarise themselves with the world of work and thus facilitate their transition 
from education to employment. 

3.  WBL  that  is  integrated  in  a  school-based  programme,  through  on-site  labs,  workshops,  kitchens, 

restaurants, junior or practice firms, simulations or real business/industry project assignments. 

Countries often combine these different models of WBL to some extent, and terminology and definitions tend 
to vary, so that the same term can have different connotations and underlying concepts.  It is therefore not 
easy  to  operationalise  the  concept  of  WBL  and  its  categories  for  the  purposes  of  collecting  data  on  this 
phenomenon. As a result, comparative statistics on WBL are still scarce, and comparable data is hard to come 
by.  

A few alternative data sources can provide information on prevalence and outcomes of WBL  in VET. Each of 
them can be valuable in providing insights into a particular aspect, category or target group for WBL, although 
the  fragmentation  of  data  sources  makes  them  hardly  comparable.  This  document  will  look  into  the  main 
data  sources  currently  available  to  monitor  country  performance  in  WBL  (or  some  aspects  of  it),  with  the 
purpose of evaluating their strengths and weaknesses. 

(5)   Commission  Staff  Working  Document  on  Vocational  education  and  training  for  better  skills,  growth  and  jobs,  accompanying  the 
Communication  from  the  Commission  on  Rethinking  Education:  Investing  in  skills  for  better  socio-economic  outcomes,  2012. 
SWD(2012) 375 final.  
https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:52012SC0375   

4 

                                           
3  Overview of the 2016 LFS AHM on young people on the labour market  

One of the main candidate data sources for monitoring WBL is the European Union Labour Force Survey (EU-
LFS).  The  2016  EU-LFS  Ad-Hoc  Module  (AHM)  on  young  people  on  the  labour  market  provides  new 
data  on  the  prevalence  and  associated  outcomes  of  work-based  learning  (understood  in  this  case  in  the 
narrow sense as learning by doing actual work in an external company or institution). In particular, the AHM 
provides information about the extent to which young people, during their highest level of completed formal 
education, acquired real-world work experience; if this experience was paid or not; what type of experience it 
was  (e.g.  if  it  was  an  apprenticeship);  if  it  was  part  of  or  linked  to  the  curriculum.  The  availability  of  this 
information  in  the  LFS  survey  allows  analysing  several  types  of  outcomes,  primarily  those  related  to  the 
labour  market.  While  these  data  allow  for  now  just  a  one-off  measure  of  WBL,  the  relevance  of  this  data 
source for a possible indicator(s) or benchmark is due to the fact that in the future, similar information will be 
available on a yearly basis. As a matter of fact, it was agreed that under the upcoming Integrated European 
Social Statistics Framework Regulation (IESS FR), the variable "work experience at a workplace as part of 
HATLEVEL"  (HATWORK)  will  be  included  into  the  core  LFS  as  from  2021.  This  will  imply  a  constant 
collection of information on WBL, allowing monitoring country progress in this domain. As will be explained in 
Section 7.5, the future HATWORK variable will not be entirely comparable to the variables currently available 
in the 2016 LFS AHM; however, it will be based on the same main dimensions on which the AHM information 
is built, which justifies the use of the currently available data to explore its relevance. In the rest of the report, 
LFS AHM and LFS HATWORK will be used to indicate this type of information.  

Detailed  information  on  the  content  of  the  2016  AHM  can  be  found  in  the  Commission  Implementing 
Regulation (6), as well as in the detailed specifications of the AHM 2016 (Eurostat, 2016b). 

The target group of the LFS Ad-Hoc Module 2016 is persons aged 15-34 living in private households. The first 
sub-module,  in  collecting  information  on  the  educational  background  of  young  people,  includes  the  two 
variables that are fundamental to identify WBL, namely WORKEXP and WORKSTUD.  

The  first  one,  WORKEXP  (Work  experience  during  studies),  is  aimed  at  capturing  if  the  highest  level  of 
completed formal education (HATLEVEL) included any practical work experience, with two separate questions 
for the paid and unpaid work. The resulting categories are: 

1.  Both paid and unpaid work experience; 

2.  Paid work experience only; 

3.  Unpaid work experience only; 

4.  No work experience during HATLEVEL. 

If the individual had working experience (whether paid or unpaid) during HATLEVEL (i.e. if WORKEXP=1-3), the 
second variable, WORKSTUD, identifies the type of work-based learning experience accrued during the highest 
level of education. In particular, it ascertains whether the work experience was part of the curriculum or not, 
i.e.  whether  it  had  a  relation  to  the  content  of  the  highest  educational  programme  completed  or  not.  The 
categories identified are the following: 

1.  Apprenticeship; 

2.  Mandatory traineeship; 

3.  Mandatory work-based training where distinction between 1 and 2 is not possible; 

4.  Optional traineeship (part of education); 

5.  Work outside the curriculum. 

Apprenticeship is defined in this context as mandatory work-based learning with a total duration of at least 
6 months and paid. Persons having been apprentices during their HATLEVEL education are practically defined 
in the LFS AHM as those who (1) had working experience, where (2) training was a mandatory part of their 
curricula,  (3)  the  period  spent  doing  on-the-job  training  had  a  total  duration  of  at  least  6  months,  and  (4) 
received  payment  for  that  work.  The  distinction  between  apprenticeship  and  mandatory  traineeship  is 
based on duration and payment; when it is not possible to make such distinction, code 3 applies. 

(6)   Commission Implementing Regulation (EU) 2015/459 of 19 March 2015 specifying the technical characteristics of the 2016 ad hoc 
module  on  young  people  on the  labour  market  provided  for  by  Council Regulation  (EC)  No  577/98.  https://eur-lex.europa.eu/legal-
content/EN/TXT/PDF/?uri=CELEX:32015R0459&from=EN    

5 

                                           
In order to provide an overview of data from the 2016 LFS AHM, this report relies on the figures available in 
the  Eurostat  website  under  the  lfso_16  series,  and  those  obtained  through  special  extractions  provided  by 
Eurostat.  

In the lfso_16  series of tables, Eurostat identifies six relevant categories of  people, based on the payment, 
duration and link to education breakdowns explained above; the six categories are the following: 

- 

- 

- 

no work experience: not carried out any form of work (neither paid nor unpaid) while being a student or 
pupil;  

outside curriculum: did carry out work while being a student or pupil, but the work was not connected to 
the person's ongoing studies; 

apprenticeship: had working experience which was a mandatory part of the curriculum, the work lasted 
at least 6 months and it was paid; 

-  mandatory traineeship: had working experience which was a mandatory part of the curriculum, the work 

lasted at least 6 months and it was not paid; 

-  mandatory work-based learning: had working experience which was a mandatory part of the curriculum, 

but no further information is available on the length of time, or if it was paid or not; 

- 

optional  traineeship:  had  working  experience  which  was  an  optional  part  of  the  curriculum,  and  no 
further information is available on the length of time, or if it was paid or not. 

Given  the  low  underlying  sample  size,  and  therefore  low  reliability  of  figures  for  some  of  these  individual 
categories, three main groups are identified based on work experience during studies, distinguishing between 
(a)  work-based  learning;  (b)  experience  outside  the  curriculum;  and  (c)  no  work  experience.  Work-based 
learning is considered as the sum of apprenticeship, mandatory traineeship, mandatory work-based learning, 
and  optional  traineeship;  within  this  broader  group,  apprenticeships  are  identified  as  the  most  relevant 
category whenever feasible, leaving “Other WBL” as residual category. 

The rest of the section will provide an overview of the prevalence and outcomes associated with participation 
in work-based learning for young people aged 15-34 (7). Three different groups can be distinguished by level 
and orientation of the highest qualification attained: those who have an upper secondary or post-secondary 
non-tertiary degree (i.e. levels 3-4 of the International Standard Classification of Education (ISCED), which can 
be considered as medium education) with vocational orientation as the highest level of education; those who 
have  a  degree  at  the  same  ISCED  level  but  with  general  orientation;  and  those  who  attained  a  tertiary 
education  degree  (i.e.  ISCED  5-8,  classified  as  higher  education) (8).  After  providing  a  snapshot  of  the 
prevalence and type of work experience during studies for the different educational attainments, the section 
will look into patterns related to continuation of studies, and then describe the main labour market outcomes 
of young people. 

3.1  An overview of work experience during studies in the EU 

Figure 1 shows the percentage of people in the age group 15-34 who had work experience while studying 
for  their  highest  attained  level  of  education.  In  the  EU  as  a  whole,  67.1%  of  young  people  with  a 
vocational medium-level education degree had some type of work experience during their studies; the share is 

(7)  

It  should  be  highlighted  that  given  current  data  availability,  it  is  however  impossible  to  establish  whether  the  differences  found 
between the sub-groups in the analysis are statistically significant.  

(8)   Besides  the  variable  HATLEVEL,  collecting  information  on  the  highest  level  of  education  successfully  completed,  the  LFS  collects 
information  on  the  orientation  of  the  programme  completed  at  the  highest  education  level  in  the  variable  HATVOC  for  medium 
levels  of  education  (levels  3-4,  see  Eurostat,  2016a).  This  variable  distinguishes  between  general  and  vocational  orientation  of 
educational programmes. General orientation programmes are those that are designed to develop learners’ general knowledge, 
skills  and  competencies,  as  well  as  literacy  and  numeracy  skills,  often  to  prepare  participants  for  more  advanced  education 
programmes at the same or a higher ISCED level and to lay the foundation for lifelong learning; these programmes are typically 
school- or college-based. General education includes education programmes that are designed to prepare participants for entry into 
vocational education but do not prepare for employment in a particular occupation, trade or class of occupations or trades, nor lead 
directly to a labour market-relevant qualification. Vocational programmes, on the other hand, are designed for learners to acquire 
the  knowledge,  skills  and  competencies  specific  to  a  particular  occupation,  trade,  or  class  of  occupations  or  trades.  Such 
programmes may have work-based components (e.g. apprenticeships, dual-system education programmes). Successful completion 
of  such  programmes  leads  to  labour  market-relevant  vocational  qualifications  acknowledged  as  occupationally-oriented  by  the 
relevant national authorities and/or the labour market.    

6 

 
                                           
very close to this level for higher education, where 2/3 of graduates gained some work experience, while it is 
much lower for those who studied for a general programme at ISCED 3-4 level (33.5%). In the vast majority 
of countries, the highest share of work experience while studying is found among tertiary graduates, followed 
by individuals with a vocational medium-level degree, with graduates from general medium-level education 
showing  the  lowest  rates.  This  pattern  across  education  levels  sees  few  exceptions,  namely  AT,  DE  and  CY 
(where work experience is most common among graduates from vocational ISCED 3-4 programmes) and DK 
(where  these  graduates  had  the  lowest  rates).  The  countries  where  it  is  most  common  for  graduates  from 
vocational  medium-level  education  and  from  tertiary  education  to  have  accrued  some  work  experience  are 
HU, FI and SE (with shares for both levels around or above 90%). At the opposite end of the distribution, the 
country with the highest share of graduates who did not work at all during studies is by far RO.  

Figure  1.  People  with  work  experience  while  studying  for  their  highest  qualification,  by 
educational  attainment,  2016  (%  of  people  aged  15-34  who  completed  formal  education  above 
ISCED2) 

Source: own elaborations on Eurostat data from LFS AHM 2016. Online data code: [lfso_16feduc]. 
Notes:  countries  are  ordered  by  decreasing  percentage  of  people  with  work  experience  while  studying  at  vocational  ISCED  3-4  level. 
Figures  for  vocational  medium  education  for  LU  not  reliable.  Individuals  who  did  not  respond  to  questions  on  work  experience  while 
studying are included in the denominator.  

Figure  2  provides  an  overview  of  the  different  categories  of  work  experience  during  studies  –  and  in 
particular of the prevalence of WBL – at different ISCED levels. It clearly shows how the prevalence of work-
based  learning  (captured  by  the  blue/green  parts  of  the  bars)  is  higher  among  those  with  an  ISCED  3-4 
vocational  degree  and  a  higher  education  one.  At  the  EU  level,  56.7%  of  graduates  with  an  ISCED  3-4 
vocational degree had a WBL experience during their studies; the prevalence of WBL is  around 40% among 
those  who  attained  a  tertiary  education  degree,  while  it  is  considerably  lower  among  those  with  a  general 
ISCED 3-4 degree (below 10%). Cross-country differences are wide; the prevalence of WBL among graduates 
from vocational medium education ranges from values above 80% in HU, AT, FI and DE, to around 10% in RO. 
The top values are lower at ISCED 5-8 level, with HU still around 80%, followed by FR with 76.7% and LT with 
65.8%. In the vast majority of the countries, the prevalence of WBL is higher at ISCED 3-4 vocational than in 
higher education; the main exceptions are BG, EL and SI. 

7 

  
 
 
 
Figure 2. Work experience during studies and type of experience, by educational attainment, 2016 
(% of people aged 15-34) 

Source: own elaborations on Eurostat data from LFS AHM 2016. Online data code: [lfso_16feduc]. 
Notes: countries are ordered by decreasing prevalence of work-based learning. Non-response rates are also reported to highlight cases 
where there might be a bias. 

8 

 
Among  graduates  from  vocational  medium-level  education (9),  for  the  EU28  as  a  whole,  around  half  WBL 
experiences  take  place  through  an  apprenticeship.  The  incidence  of  apprenticeships  varies  a  lot  between 
countries; in DE, AT and DK this category represents 80% or more of WBL experiences, while in some other 
countries it  is negligible  (below  5% in  IT  or RO).  The  relevance  of  apprenticeships is  also  significant  among 
tertiary  graduates, with  around a  quarter of  WBL experiences  in  higher education  taking  place  in  this form; 
particularly high percentages are found for EL (66.2%), DE and FR (around 40%). Finally, it is also interesting 
to see what percentage of the young population worked outside the curriculum; on average in the EU, one out 
of four graduates from both medium-level general education and higher education had such work experience.  

The distribution of field of study among individuals with WBL during studies varies greatly depending on 
the educational attainment; among those with vocational medium education, most individuals who had a WBL 
experience attended programmes in “engineering, manufacturing and construction”, “business, administration 
and law”, or “services”. As shown in Figure 3, in the EU as a whole, 3 out of 4 individuals were in one of these 
programmes, with percentages being especially high in CY, BG, EE and LT. The most common field of study for 
those with WBL at this education level was by far engineering, manufacturing and construction. More diversity 
in programmes is found among those who did WBL in higher education; on average in the EU, just over half 
individuals  were  enrolled  in  the  three  most  common  fields  (i.e.  “business,  administration  and  law”, 
“engineering, manufacturing and construction”, and “health and welfare”). Other relevant ones are “education” 
and “social sciences, journalism and information”. It should be noted however that these figures reflect two 
different components, i.e. the popularity of the individual fields of study in each country, and the prevalence 
of WBL in each field in each country. Indeed, a similar distribution of individuals with WBL experiences by field 
of study in two countries could hide a completely different relative importance of WBL across fields of study 
at  the  national  level.  As  an  example,  among  graduates  from  vocational  medium  education  with  WBL 
experience,  CZ  and  AT  show  a  similar  prevalence  of  “engineering,  manufacturing  and  construction”;  as 
reported in Table A 1 in the Annex, they also have similar relevance of this field of study among all graduates 
from vocational ISCED 3-4 programmes; however, within this field, the prevalence of WBL is very different in 
the  two  countries,  from  68.7%  in  CZ  to  93.3%  in  AT.  A  similar  situation  applies  among  higher  education 
graduates to LT and LV, which – as reported in Table A 2 – despite similar shares of “business, administration 
and law”, have very different levels of WBL among graduates in this field (60.3 and 44.0% respectively). This 
shows  that  all  the  different  components  should  be  taken  into  account  when  drawing  conclusions  on  the 
distribution of WBL across fields of study. 

(9)   For the majority of the countries, no reliable information is available on the relevance of apprenticeships for graduates from general 
medium-level education programmes. The distinction between this category and other WBL is therefore provided only for vocational 
ISCED 3-4 programmes and higher education ones.  

9 

                                           
Figure  3.  Field  of  study  among  individuals  with  WBL  experience  during  studies,  by  educational 
attainment, 2016 (% of people aged 15-34 who completed vocational medium education or higher 
education) 

Source: own elaborations on a Eurostat special extraction from LFS AHM 2016.  
Notes: general medium education not shown because of small sample size.  

10 

 
 
 
3.2  Choices after graduation 

A first outcome of interest when looking at young individuals graduating from upper-secondary VET, concerns 
the choice between entering the labour market or continuing studies at a higher level, and whether 
this varies depending on the presence of work experience during studies. It is well-known that continuation of 
studies  depends  on  the  level  and  orientation  of  education  attained,  and  that  medium-education  VET 
programmes  are  traditionally  aimed  at  fostering  the  immediate  employability  of  individuals  and  facilitate 
school-to-work transition. It is therefore interesting to see how the accrual of work experience  for those with 
this type of  qualification is associated  with the  choice to  participate in further studies.  Figure 4 shows that 
within  the  group  of  20-24  years-old  who  attained  a  vocational  ISCED  3-4  degree  as  highest  qualification, 
those who had a work-based learning experience as part of their curriculum are normally less likely to be still 
in  formal  education;  at  the  EU  level,  only  19.5%  of  this  group  continues  studying.  At  the  opposite  end,  the 
likelihood to continue studying is highest among those who had a work experience outside of their education 
curriculum (with a rate of participation in formal education of 29.3%). Among those with no work experience 
during studies, just above ¼ continue formal education. This general pattern applies to the vast majority of 
EU  countries,  although  the  difference  between  groups  varies  greatly,  ranging  from  around  20  p.p.  in  NL  to 
marginal differences in e.g. EL. Few exceptions to this pattern emerge, such as in ES, SE and the UK, where 
the continuation rate is lowest among those with no work experience at all.  

Figure 4. Young people in formal education by work experience during studies, 2016 (% of people 
aged 20-24 who have vocational ISCED 3-4 as highest qualification attained) 

Source: own elaborations on Eurostat data from LFS AHM 2016. Online data code: [lfso_16feduc] 
Notes: countries are ordered by decreasing share of individuals with WBL experience during studies continuing formal education. Missing 
values are not reliable. All figures reported are unreliable for CY, DK, EE, HR, LT, LV, MT, SI; figures for outside curriculum and WBL are 
unreliable for BG, EL, IE; figures for outside curriculum and no work experience are unreliable for AT, DE, FI, FR, HU; figures for outside 
curriculum are unreliable for PT and RO; figures for no work experience are unreliable for SE.  

The choice to enter the labour market after graduation from upper-secondary VET can be driven by different 
reasons.  Figure  5  shows  the  self-reported  reasons  behind  this  choice  for  individuals  who  attained  a 
vocational ISCED 3-4 degree. At the EU level (10), 47.1% of those who did an apprenticeship during studies did 
not continue to further education because they considered their attained level as appropriate. The same share 
is 27.2% for those who had another type of WBL experience, and 26.3% for those who had a work experience 
outside of their curriculum. This somehow suggests that participation in apprenticeships is associated with a 
stronger  feeling  of  preparation  for  entering  the  labour  market.  Overall,  74.9%  of  those  who  had  an 

(10)   Given the limited sample sizes for this indicator, results by country are not reliable and are therefore not reported here.  

11 

 
 
 
                                           
apprenticeship  did  not  continue  either because  they  considered  their  level  attained  high  enough  or because 
they  wanted  to  start  working,  and  not  because  of  specific  circumstances  not  allowing  or  favouring 
continuation. This percentage is visibly lower for all the other groups, between 67% and 70%.  

Figure  5.  Reason  for  not  starting  tertiary  education  by  work  experience  during  studies,  EU28, 
2016 (% of people aged 15-34 who have vocational ISCED 3-4 as highest qualification attained 
and who are not in formal education) 

Source: own elaborations on Eurostat data from LFS AHM 2016. Online data code: [lfso_16ymgnedns]. 
Notes: figures for reason being “Difficulty” unreliable for apprenticeship and not reported because unreliable for work experience outside 
curriculum. 

The  next  sections  will  look  into  the  labour  market  outcomes  of  young  people,  showing  how  they  vary 
depending  on  accrual  of  work  experience  during  studies.  They  will  focus  on  two  of  the  three  education 
qualifications considered so far, i.e. vocational medium-level education and higher education. As a matter of 
fact, these are the two education streams that can be considered as preparing individuals for a transition to 
employment. In order to take into account only individuals who are reasonably out of formal education, the 
age group 20-34 will be considered. 

3.3  Labour market outcomes  

Figure  6  provides  a  first  overview  of  the  labour  market  status  of  young  people  aged  20-34  and  not  in 
formal education, distinguishing between the two main streams of education, and the type of work experience 
during  studies.  For  both  education  levels,  individuals  who  had  an  apprenticeship  during  their  studies  show 
higher employment rates  and lower inactivity  rates  than  their peers.  Interestingly, work experiences outside 
the  curriculum  appear  to  be  associated  with  slightly  better  outcomes  than  work-based  learning  ones  other 
than apprenticeships; this might be linked to some particular personal motivation driving individuals to work, 
possibly  reflecting  a  higher  level  of  effort  on  the  labour  market.  Alternatively,  it  may  also  be  linked  to 
potentially  higher  likelihood  of  individuals,  coming  from  better  socio-economic  background  or  those  with 
better educational performance, of finding a job already during their studies or before graduation. The worst 
performance is found among individuals who had no work experience at all.  This suggests that work-based 
learning  could  indeed  pave  the  way  to  better  labour  market  outcomes,  but  only  when  carried  out  under 
specific conditions, which possibly allow higher quality of the on-the-job training experience.  

12 

 
 
 
 
Figure  6.  Labour  market  status  by  educational  attainment  and  work  experience  during  studies, 
EU28, 2016 (% of people aged 20-34 who are not in formal education) 

Source: own elaborations on a Eurostat special extraction from LFS AHM 2016.  

While  work  status  can  give  a  broad  impression  of  the  labour  market  performance  of  individuals,  more 
targeted indicators could provide useful insights into the school-to-work transition patterns of young people. A 
first  outcome  of  interest  is  the  employment  rate  of  recent  graduates.  This  indicator  is  defined  as  the 
share of employed population among those aged between 20 and 34 who graduated 1 to 3 years before the 
reference year, and who are not currently enrolled in any further (formal or non-formal) education or training 
activity; it is aimed at helping evaluate the success rate in the labour market of young people with different 
levels  of  educational  attainment  in  the  first  years  after  graduation,  and  can  be  valuably  used  also  to 
investigate differences in performance between individuals with and without work experience during studies. 
Figure  7  shows  a  similar  pattern  to  Figure  6:  for  the  EU  as  a  whole,  the  level  of  employability  of  recent 
graduates is highest among those who had an apprenticeship during their studies, followed by those who had 
work experience outside the curriculum. The lowest employment rates are found among those with no work 
experience  at  all.  These  patterns  hold  both  for  vocational  medium  education  and  for  higher  education 
graduates,  but  differences  between  groups  appear  to  be  much  larger  for  the  former  (possibly  due  to  the 
overall higher levels of employment of higher education graduates).  

13 

 
 
Figure  7.  Employment  rate  of  recent  graduates  by  educational  attainment  and  work  experience 
during studies, EU28, 2016 (% of people aged 20-34 who completed vocational medium education 
or higher education 1 to 3 years before and are not in formal or non-formal education or training) 

Source: own elaborations on a Eurostat special extraction from LFS AHM 2016.  
Notes:  the  employment  rate  of  recent  graduates  is  defined  as  the  share  of  employed  people  among  those  aged  20-34  having 
successfully completed upper secondary or tertiary education 1 to 3 years before the reference year of the survey, and who are no longer 
in (formal or non-formal) education or training. 

These EU-level figures are likely to hide a considerable underlying variation across countries. Figure 8 tries to 
investigate these differences further; however, when moving to the national level, sample sizes often do not 
allow distinguishing the performance of those with different types of work-based learning experience; these 
are  therefore  reported  together  in  the  following  figure.  The  figure  shows  that  indeed  patterns  –  and 
performance  gaps  –  can  differ  greatly  across  countries;  however,  the  advantage  of  having  some  work 
experience  over  the  studies  is  confirmed  in  most  of  the  cases.  Table  1  reports  employment  rates  for 
individuals  with  some  form  of  WBL,  distinguishing  between  apprenticeships  and  other  types  of  work-based 
learning; the table shows that – at least for countries where a reliable comparison can be made – in most of 
the cases, having been an apprentice is indeed associated with better employment rates.  

14 

 
 
 
Figure  8.  Employment  rate  of  recent  graduates  by  educational  attainment  and  work  experience 
during  studies,  2016  (%  of  people  aged  20-34  who  completed  vocational  medium  education  or 
higher education 1 to 3 years before and are not in formal or non-formal education or training) 

Source: own elaborations on a Eurostat special extraction from LFS AHM 2016.  
Notes:  the  employment  rate  of  recent  graduates  is  defined  as  the  share  of  employed  people  among  those  aged  20-34  having 
successfully completed upper secondary or tertiary education 1 to 3 years before the reference year of the survey, and who are no longer 
in (formal or non-formal) education or training.  

15 

 
 
Table  1.  Employment  rate  of  recent  graduates  by  educational  attainment  and  type  of  WBL 
experience  during  studies,  2016  (%  of  people  aged  20-34  who  completed  vocational  medium 
education or higher education 1 to 3 years before and are not in formal  or non-formal education 
or training) 

ISCED 3-4 Vocational 

ISCED 5-8 

Apprenticeship 

Other WBL 

Apprenticeship 

Other WBL 

Country 

% 

Flag 

% 

Flag 

% 

Flag 

% 

Flag 

EU28 

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 

87.5 

x 

94.8 
89.3 
89.3 

x 
87.1  u 
56.7  u 
76.8  u 
75.9  u 
x 
x 
x 

x 
x 

x 

81.6 

89.5 
83.1 
81.7 

x 
x 
64.5  u 
93.6 
84.8 

x 

88.9 

70.9 

77.0 

x 

81.9 

x 
x 
82.8  u 
71.1 

x 

60.4 
59.3 
72.1  u 
57.2 
89.2  u 
83.3 
78.6 

83.2 

x 

x 

86.5 
77.1  u 
69.7 
68.2 
62.1  u 
79.7  u 
77.0 
77.6 
80.3 
79.0 

88.8 

91.7  u 

90.8 

96.0 

x 

x 
100.0  u 

77.7 
85.7 
82.9 

x 
72.9  u 
86.1  u 
x 
x 
x 

86.0 

x 

94.1 
92.1  u 
88.8 

x 
x 
98.0  u 
89.0 
96.1 

x 

95.8 

83.9 

88.5 
83.3 
85.4 
87.3 
98.3 
71.7  u 
91.3 
45.4 
72.0 
80.7 
79.2  u 
66.8 
80.1 
96.2 
89.5 

x 

92.0 
94.4  u 
95.1 
85.5 
87.0 
74.2 
87.1 
69.1  u 
79.7 
79.4 
94.0 
86.0 

Source: own elaborations on a Eurostat special extraction from LFS AHM 2016.  
Notes: (x) not publishable because of very low reliability; (u) unreliable. The employment rate of recent graduates is defined as the share 
of employed people among those aged 20-34 having successfully completed upper secondary or tertiary education 1 to 3 years before 
the reference year of the survey, and who are no longer in (formal or non-formal) education or training.  

3.4  The characteristics of employment and job quality among the employed 

This section is devoted to analysing in more detail the situation of those who are employed. As a matter of 
fact,  being  in  employment  does  not  necessarily  guarantee  being  in  a  quality  job.  Several  aspects  can  be 
considered to give a picture of the level of quality of employment of young people.  

A  first  relevant  aspect  is  the  type  of  occupation  in  which  young  people  are  employed,  and  in  particular 
whether it is a skilled one or not. As a matter of fact, occupations can be broadly distinguished according to 
their equivalent skill level; “high-skilled occupations” are traditionally considered to be those falling under the 
first three groups of the International Standard Classification of Occupations (ISCO), which include managers, 
professionals, technicians and associated professionals. “Medium-skilled occupations” are those falling under 
ISCO  occupational  groups  4  to  8.  Skilled  jobs  can  be  considered  the  typical  destination  for  graduates  from 
higher education; similarly, graduates from ISCED 3-4 can be expected to be employed at least in medium-

16 

 
 
 
 
 
 
  
  
  
 
  
 
 
  
 
  
  
  
 
  
 
 
 
  
  
  
  
  
  
  
 
 
  
 
  
  
  
  
  
  
 
 
  
  
  
  
  
 
  
  
 
 
 
  
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
 
  
  
  
  
 
  
 
 
  
  
  
  
  
  
 
  
  
  
 
 
  
 
 
  
  
  
  
 
level  occupations  (or  higher).  Figure  9  shows  an  overview  of  the  share  of  employment  in  “matching” 
occupations – i.e. in high- and medium-skilled occupations for graduates from vocational medium education, 
and in high-skilled ones for higher education graduates – by work experience during studies. At the EU level, 
77.1%  of  those  who  had  an  apprenticeship  during  their  university  studies  are  employed  in  a  skilled 
occupation; this is an expected outcome, as apprenticeships during university are common in fields of study 
leading  to  careers  as  professionals,  which  are  skilled  occupations  by  definition.  The  share  is a  bit  lower for 
those with other types of WBL (73.2%), and the lowest (69%) among those with no  work experience at all. 
Even  when  looking  at  the  national  level,  in  the  majority  of  the  countries  skilled  employment  is  more 
widespread among young people who did an apprenticeship, and less common among those who did not have 
any work experience, although the differences between groups vary a lot.  

Figure  9.  Share  of  employment  in  (medium-  and)  high-skilled  occupations  by  educational 
attainment and work experience during studies, 2016 (% of people aged 20-34 who are employed 
and not working in the armed forces) 

Source: own elaborations on a Eurostat special extraction from LFS AHM 2016.  
Notes: the share of employment in skilled occupations is defined as the share of employed people aged 20-34 who work as managers 
and professionals (ISCO 1-2) or as technicians and associated professionals (ISCO 3), out of all those employed (excluding those in the 
armed forces). The share of employment in high- and medium-skilled occupations covers those employed in ISCO categories 1 to 8 (i.e. 
all non-elementary occupations). 

17 

 
 
Among  EU  graduates  from  vocational  medium  education,  having  been  an  apprentice  during  studies  is 
associated  with  the  highest  share  of  employment  in  medium-  and  high-skilled  occupations  (93.8%);  the 
lowest share is found among those with no work experience at all (88.7%). This outcome is likely driven by 
results  in  a  few  of  the  biggest  EU  countries  (e.g.  ES,  IT,  UK),  but  when  looking  at  the  national  level,  more 
diverse patterns emerge. On one hand, in quite a few countries the highest shares are indeed found among 
individuals with apprenticeship experiences, while in others these are registered among those with experience 
outside the curriculum, with no clear advantage of having a WBL experience during studies; on the other hand, 
the gaps between sub-groups within country vary a lot, between 2 and 17 percentage points.  

A more revealing aspect might be the level of match or mismatch between the current job and the individual’s 
education. The 2016 AHM investigates this issue by asking young people about the appropriateness of the 
job given the level of education; respondents can select an option between these four categories: the job 
corresponds well to the education (which can be considered as a high level of match); the job corresponds to 
some extent to the education (medium level of match); the job does not correspond very well to the education 
(low  level  of  match);  the  job  does  not  correspond  at  all  to  the  education  (no  match).  The  first  category 
therefore covers individuals that feel a complete match between their studies and their current job; the others 
signal a more or less severe degree of mismatch between education and job. Figure 10 (11) shows that at both 
education levels, individuals who had an apprenticeship experience during their latest studies are those who 
report  the  highest  level  of  complete  fit  between  education  and  current  job,  and  the  lowest  level  of  severe 
mismatch. The incidence of the latter is similar across the other three categories of work experience during 
studies;  however,  at  least  for  vocational  medium  education,  having  other  types  of  WBL  during  studies  is 
associated with a higher level of match when compared to individuals with experience outside the curriculum 
or no experience at all.  

Figure 10. Self-reported level of match between education and job by educational attainment and 
work experience during studies, EU28, 2016 (% of total employed persons, age group 20-34)  

Source: own elaborations on Eurostat data from LFS AHM 2016. Online data code: [lfso_16oklev]. 
Notes: “high”: the job corresponds well to the education; “medium”: the job corresponds to some extent to the education; “low”: the job 
does not correspond very well to the education; “none”: the job does not correspond at all to the education.  

Besides the skills and match level of the jobs, other relevant dimensions  of job quality to be considered are 
related  to  contract  and  the  presence  of  underemployment.  A  first  category  of  underemployment  is 

(11)   Given the limited sample sizes for this indicator, results by country are not reliable and are therefore not reported here. The same 

applies to the following figures.  

18 

 
 
 
                                           
involuntary  part-time  work,  i.e.  the  situation  in  which  a  part-time  worker  would  like  to  work  additional 
hours and is available to do so. This underemployment indicator highlights situations of insufficient volume of 
work  and  underutilised  labour among  persons  already  employed.  Figure  11  shows  how  this indicator varies 
depending on participation in work experience during studies. Among those who work part-time, the incidence 
of involuntary part-time is highest among young people who had no work experience whatsoever during their 
studies,  both  at  vocational  medium level  education  and  higher  education.  Participation  in  an  apprenticeship 
during  studies  appears  to  be  associated  with  the  lowest  shares  of  involuntary  part-time  work,  followed  by 
those who had a work experience outside of the curriculum.  

Figure 11. Employed persons working part-time involuntarily by educational attainment and work 
experience  during  studies,  EU28,  2016  (%  of  total  number  of  part-time  employed  persons,  age 
group 20-34) 

Source: Eurostat data from LFS AHM 2016. Online data code: [lfso_16invpt]. 
Notes: WBL (total) covers all individuals having had some form of work-based learning, including apprenticeship. Current data availability 
does not allow computing this indicator for the “other WBL” category available for some other indicators. The figure for apprenticeship for 
ISCED 5-8 is unreliable. 

A partially different situation is found when looking at the incidence of  involuntary temporary contracts 
on total temporary employees. As shown in Figure 12, having had an experience as apprentice during studies 
is  associated  with  better  outcomes  for  graduates  from  both  vocational  medium  education  and  tertiary 
education.  Other  types  of  WBL  do  not  appear  to  be  associated  with  similar  performances.  The  highest 
likelihood  of  having  an  unwanted  temporary  contract  is  found  among  those  who  did  not  have  any  work 
experience during studies, at both education levels.  

Similarly, Figure 13 shows that graduates who did an apprenticeship during their studies appear to have the 
best outcomes also in terms of incidence of precarious employment situations (defined as having a work 
contract of only up to 3 months), both at medium vocational and high education level, although for the latter 
differences  are  rather  small (12).  For  graduates  from  tertiary  education,  having  had  another  type  of  WBL 
experience during the studies is associated with the highest probability of having a short work contract. 

(12)   As  already  mentioned,  and  especially  considering  the  small  differences  and  sample  sizes  for  this  indicator,  it  is  impossible  to 

establish whether these differences are statistically significant.  

19 

 
 
 
 
                                           
Figure 12.  Employees  with involuntary temporary contracts by  educational attainment and work 
experience  during  studies,  EU28,  2016  (%  of  total  number  of  employees  with  temporary 
contracts, age group 20-34) 

Source: Eurostat data from LFS AHM 2016. Online data code: [lfso_16invtemp]. 
Notes: WBL (total) covers all individuals having had some form of work-based learning, including apprenticeship. Current data availability 
does not allow computing this indicator for the “other WBL” category available for some other indicators.  

Figure  13.  Employees  in  precarious  employment  by  educational  attainment  and  work  experience 
during studies, EU28, 2016 (% of total number of employees, age group 20-34) 

Source: Eurostat data from LFS AHM 2016. Online data code: [lfso_16precemp]. 
Notes: WBL (total) covers all individuals having had some form of work-based learning, including apprenticeship. Current data availability 
does not allow computing this indicator for the “other WBL” category available for some other indicators. Figures for experience outside 
curriculum for ISCED 3-4 Vocational and for apprenticeship for ISCED 5-8 are unreliable. 

20 

 
 
 
 
4  Work-based learning in UOE data 

The  joint  UNESCO-UIS/OECD/EUROSTAT  (UOE)  data  collection  on  education  statistics  provides 
internationally comparable data on key aspects of formal education systems, specifically on the participation 
and completion of education programmes, as well as the cost and type of resources dedicated to education. 
The  results  of  the  UOE  data  collection  on  education  statistics  are  compiled  on  the  basis  of  national 
administrative sources (normally census or administrative registers), reported by Ministries of Education or 
National Statistical Offices on the basis of commonly agreed definitions. 

As reported in UOE (2017), this data collection covers formal education programmes (13) that represent at 
least  the  equivalent  of  one  semester  (or  one-half  of  a  school/academic  year)  of  full-time  study  and  are 
provided  within  the  reporting  country’s  own  territory.  The  UOE  data  collection  covers  formal  vocational 
education programmes (14) provided they are delivered either as entirely school-based programmes (i.e. they 
take place entirely in educational institutions) or as combined school- and work-based programmes in which 
the school-based component represents at least 10% of the total study over the whole programme. Entirely 
work-based training is excluded. 

Among  these  programmes,  a  further  distinction  is  made  (at  the  upper  secondary  and  post-secondary  non-
tertiary  levels)  between  “school-based  programmes”  and  “combined  school  and  work-based  programmes”; 
this  distinction  is  based  on  the  amount  of  training  that  is  provided  in-school  as  opposed  to  training  in  the 
work place.  

In school-based programmes instruction takes place (either partly or exclusively) in educational institutions. 
These  include  special  training  centres  for  vocational  education  run  by  public  or  private  authorities  or 
enterprise-based special training centres if these qualify as educational institutions. These programmes can 
have  an  on-the-job  training  component,  i.e.  a  component  of  some  practical  experience  at  the  workplace. 
Programmes should be classified as school-based if at least 75 per cent of the curriculum is presented in the 
school environment (covering the whole educational programme) or through distance education.  

On  the  other  hand,  a  programme  is  classified  as  combined  school-  and  work-based  if  less  than  75  per 
cent of the curriculum is presented in the school environment or through distance education. The 75 per cent 
cut-off point should be regarded as a general guideline that may need to be operationalized differently across 
countries. These programmes include:  

- 

- 

apprenticeship  programmes  organised  in  conjunction  with  educational  authorities  or  educational 
institutions that involve concurrent school-based and work-based training; and  

programmes organised in conjunction with educational authorities or educational institutions that involve 
alternating  intervals  of  attendance  at  educational  institutions  and  participation  in  work-based  training 
(programmes of training in alternation, sometimes referred to as “sandwich” programmes). 

Experience  shows  that  for  combined  school-  and  work-based  programmes  the  coverage  of  work-based 
components in national data collections is uneven.  

UOE  data  on  the  prevalence  of  combined  school-  and  work-based  programmes  is  provided  in  Eurostat 
datasets  concerning  “Pupils  enrolled  in  upper  secondary  education  by  programme  orientation,  sex,  type  of 
institution and intensity of participation” (Eurostat online data code educ_uoe_enrs04) and “Pupils enrolled in 
post-secondary  non-tertiary  education  by  programme  orientation,  sex,  type  of  institution  and  intensity  of 
participation” (Eurostat online data code educ_uoe_enrs07). Table 2 shows the percentage of pupils enrolled 
in ISCED 3 and 4 vocational programmes who are attending combined school- and work-based programmes. 

(13)   Formal education is institutionalised, intentional and planned and provided by public organizations and recognised private bodies.  
(14)   According to  the  UOE  manual,  vocational  education  is  designed  for  learners to  acquire  the  knowledge,  skills and  competencies 
specific to a particular occupation, trade, or class of occupations or trades. Vocational education may have work-based components. 
Successful  completion  of  such  programmes  leads  to  labour  market-relevant  vocational  qualifications  acknowledged  as 
occupationally-oriented by the relevant national authorities and/or the labour market. 

21 

 
                                           
Table 2. Prevalence of WBL by ISCED level, 2016 (% of students in the respective vocational 
ISCED level who were enrolled in school- and work-based programmes) 

ISCED 3 Vocational 

ISCED 4 Vocational 

ISCED 3-4 Vocational 

EU28 

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 

25.3 

5.9 

: z 

8.8 

80.0 

87.1 

2.2 

: z 

: z 

2.0 

24.2 

: z 

: z 

: z 

100.0 

: z 

21.4 

100.0 

22.5 

: 

46.0 

15.5 

: z 

7.9 

: z 

10.5 

12.9 

4.5 

37.5 

33.8 

: z 

: z 

55.5 

: z 

51.1 

3.4 

15.0 

: 

22.8 

: z 

: z 

: d 

: z 

100.0 

: z 

100.0 

100.0 

: 

: z 

57.9 

: z 

: z 

14.6 

: z 

11.4 

66.1 

89.3 

: z 

26.4 

5.2 

: 

10.0 

80.0 

74.1 

2.6 

15.0 

: 

2.8 

23.8 

: 

: 

: 

100.0 

: 

24.9 

100.0 

22.5 

: 

46.9 

11.4 

: 

9.2 

: 

10.6 

17.4 

10.8 

37.5 

Source: own elaborations on Eurostat UOE data. Online data code: [educ_uoe_enrs04] and [educ_uoe_enrs07].  
Notes: WBL is defined as combined school- and work-based (SW) programmes. (:) missing; (z) SW not applicable; (d) definition differs. 
EU28 for ISCED 4 and ISCED 3-4 is the sum of the available countries. When SW is not applicable at one ISCED level, the ISCED 3-4 rate 
is  computed  with  the  SW  of  the  available  level  at  the  numerator,  and  the  sum  of  students  in  both  vocational  ISCED  levels  at  the 
denominator. ISCED 3 VET not applicable for IE, therefore the ISCED 3-4 rate is computed as ISCED 4; ISCED 4 not applicable for DK and 
UK, therefore the ISCED 3-4 rate is computed as ISCED 3. ISCED 4 VET not applicable for HR, NL and SI.  

22 

  
 
5  Overview of alternative potential data sources 

Sections  3  and  4  provided  a  description  of  what  can  be  reasonably  considered  the  two  main  candidate 
sources of information for potential indicator(s) and/or a benchmark on WBL. However, other data sources can 
provide  information  on  prevalence  and  outcomes  of  WBL.  An  overview  of  these  alternative  data  sources  is 
presented in this section.  

5.1  Previous LFS AHM on young people on the labour market 

Before 2016, the EU-LFS Ad-Hoc Module (AHM) focused on the topic of young people on the labour market 
already  two  times, in  2000  and 2009.  The  target  population  in  2009  was  the  same  as for  the  2016  AHM, 
namely individuals aged 15-34, while the 2000 module considered the age group 15-35.  

No information on work during studies was collected in the 2000 AHM. The 2009 AHM on the entry of young 
people  into  the  labour  market,  on  the  other  hand,  provided  information  on  work  during  studies  in  formal 
education through a specific question, aimed at distinguishing individuals who: (i) did not work or worked less 
than one month per year; (ii) worked (only) as part of their educational programme; (iii) worked while studying 
but  outside  educational  programmes;  (iv)  worked  (only)  during  an  interruption  of  studies;  or  worked  as 
different combinations of these options. The 2009 AHM could therefore identify work which was part or not of 
the curriculum, but – unlike the 2016 AHM – it excluded short work experiences (lasting less than one month), 
and did not provide information on its characteristics (whether paid or not, whether mandatory or not). As a 
consequence, it did not allow isolating apprenticeships as defined in Section 3.  

Based  on  2009  AHM  data,  Figure  14  provides  an  overview  of  the  incidence  of  different  types  of  work 
experience  during  studies at  different  ISCED  levels,  similar to  what  Figure  2  did  with  2016  data.  Given  the 
differences  in  the  questions  asked,  it  is  not  possible  to  draw  direct  comparisons  between  the  two  years  to 
discuss trends over time. Overall higher levels of WBL are found in 2016 when compared to 2009; however, 
in the latter only work experiences of at least one month are considered, which might account for part of the 
differences.  

23 

 
 
Figure  14.  Work  experience  during  studies  and  type  of  experience,  by  educational  attainment, 
2009 (% of people aged 15-34 who completed formal education above ISCED 2) 

Source: own elaborations on a Eurostat special extraction from LFS AHM 2009.  
Notes: countries are ordered by decreasing prevalence of work-based learning. No data for HR, hence the EU value refers to EU27. Non-
response rates are also reported to highlight cases where there might be a bias.  

24 

 
5.2 

Information from core LFS variables (TEMPREAS variable) 

The  standard  LFS  questionnaire  includes  a  variable  (TEMPREAS)  investigating  the  reasons  for  having  a 
temporary  job/a  work  contract  of  limited  duration.  Among  the  options  available,  one  captures  situations  in 
which  the  person  has  a  temporary  job  because  his/her  contract  covers  a  period  of  training  (as  apprentices, 
trainees,  research  assistants,  etc.);  optionally,  countries  can  also  allow  separate  answers  for  contracts 
covering  a  period  of  apprenticeship,  and  contracts  covering  a  period  of  training  other  than  apprenticeship 
(trainees, internships, research assistants, etc.).  

As  reported  in  the  LFS  explanatory  notes,  the  criteria  for  a  contract  to  qualify  as  an  apprenticeship  are  as 
follows:  

- 

- 

- 

- 

- 

there is a contract or formal agreement for a prescribed period of time between the employer and the 
apprentice  or  an 
institution  representing  the  apprentice,  defining  the  characteristics  of  the 
apprenticeship;  

learning time alternates between periods of practical training at the work place and general/theoretical 
education in an educational institution or training centre on a weekly, monthly or yearly basis;  

all  apprenticeships  are  formal  education  programmes;  successful  completion  is  evidenced  by  a 
qualification;  

in apprenticeships, the participant (apprentice) always receives remuneration in cash or in kind;  

the duration is between 6 months and 6 years. The duration refers to the programme and not only to the 
work-based component.  

Only paid apprenticeships, traineeships or other trainings are captured by this variable.  

This  variable  of  the  core  LFS  questionnaire  can  provide  useful  information  on  the  number  of  individuals 
working  as  apprentices or  in  another  period  of  training;  moreover,  the  existence  of  these  precise  criteria  to 
identify  apprenticeships,  rather  than  the  application  of  national  definitions,  allows  to  obtain  comparable 
results across countries. For the time being, only few EU countries report  data using the optional distinction 
between  apprenticeships  and  other  types  of  training,  and  reliable  results  for  both  groups  are  available  for 
even fewer countries (i.e. AT, DE, EL, PL and UK for the age group 15-24 in 2018). Moreover, Eurostat plans to 
further investigate the overall quality of results distinguishing apprentices and other forms of training from 
this  variable.  From  2021,  under  the  IESS  FR,  the  distinction  between  the  two  types  of  training  will  become 
mandatory, therefore increasing the relevance of this variable for monitoring purposes.  

Nevertheless, a few inherent features of this question should be borne in mind when evaluating its suitability 
for building a WBL indicator. First, the question on the reason for having a temporary contract is asked only to 
employees, so by definition it only applies to paid apprenticeships and trainings. Second, the variable aims at 
identifying  current  apprenticeships  and  trainings;  however,  this  does  not  necessarily  translate  into  the 
identification  of  all  individuals  participating  in  apprenticeship  programmes:  as  some  apprenticeship 
programmes alternate between longer periods in school or at the workplace, a student currently in a longer 
school  period  of  the  apprenticeship  programme  would  not  be  captured  through  this  question.  Despite  the 
uncertainty concerning the practical level of coverage provided by this variable, it surely represents a valuable 
source of complementary information on ongoing WBL experiences of individuals in formal education.  

5.3  OECD Survey of Adult Skills (PIAAC) 

The OECD Survey of Adult Skills represents another potential source of information for work-based learning. 
The Survey of Adult Skills is conducted in over 40 countries as part of the Programme for the International 
Assessment  of  Adult  Competencies  (PIAAC).  It  measures  adults’  proficiency  in  key  information-processing 
skills – literacy, numeracy and problem solving – and gathers information and data on how adults use their 
skills  at  home,  at  work  and  in  the  wider  community.  It  focuses  on  individuals  aged  16  to  65,  and  it  is 
administered every 10 years.  

Based on evidence provided in the first PIAAC wave, Quintini (2015) tries to draw a picture of work and study 
among individuals aged 16-29 in 23 countries/regions, by combining information on student and work status, 
educational pathway and apprenticeship status. In particular, it identifies individuals who work and study as 
the sum of: 

25 

 
- 

- 

- 

Those who are in education and work (i.e. those who are in employment while reporting that they are also 
currently studying for a formal qualification) (15); 

Those  who  say  they  are  an  apprentice  or  in  an  internship  when  self-reporting  their  current  status (16), 
irrespective of their answers to the labour force and education status questions (as per previous point); 

Those  salaried  employees  who,  when  asked  about  their  type  of  employment  contract,  reply  having  “an 
apprenticeship  or  other  training  scheme” (17),  irrespective  of  their  answers  to  the  labour  force  and 
education status questions. 

As shown in Figure 15, the study reports that overall, 39% of 16-29 year-old students worked in 2012. 

Figure 15. Share of youth (16-29) combining work and study (a), 2012 (% of all students (b)) 

Source: Quintini (2015); OECD calculations based on Survey of Adult Skills (PIAAC) (2012).  
Notes: (a) All apprentices – by labour market status and/or by contract type – are counted as combining work and study, irrespective of 
what  they  report.  Indeed,  some  apprentices  classify  themselves  as  students  while  others  see  themselves  as  simply  working.  (b) 
Apprentices who do report “only work” as a labour force status are added to the total of student. This is done for consistency with their 
inclusion among youth who are working and studying. Countries are ordered by increasing prevalence of work-based learning.  

More fine-tuned disaggregations of this measure of working while studying would allow a better identification 
of the group of interest for the current analysis; however, it should be pointed out that the group is identified 
based  on  general  variables  that  do  not  have  the  purpose  of  capturing  work-based  learning  as  it  would  be 
ideally  defined.  No  information  on  the  length  of  the  work  experience  is  available,  nor  on  whether  it  was 
mandatory or part of the curriculum. It also only captures a snapshot of the situation in a particular moment, 
since  the  questions  on  the  employment  status  have  the  last  week  as  reference  period;  this  implies  that  a 
student who is not currently involved in a work experience while studying will not be taken into account, even 
if  she  might  have  been  working  in  the  past  or  might  do  so  over  the  course  of  the  studies.  Finally,  while 
contributing to provide information on the issue, PIAAC is not a suitable source of information for monitoring 
purposes, given the frequency with which it is carried out.  

(15)   These  individuals  are  captured  by  the  PIAAC  derived  variable  summarising  information  on  labour  market  and  education  status 

(EDWORK), which combines answers from questions C_D05 and B_Q02a. 

(16)   The relative question is C_q07. 
(17)   The relative question is D_q09. 

26 

 
 
 
 
                                           
5.4  OECD special survey 

In  2015/17,  the  OECD/INES  Network  for  Data  Development  on  Labour  Market  and  Social  Outcomes  of 
Education  (LSO)  carried  out  a  pilot  study  on  work-study  programmes  (“Improve  and  develop  indicators  on 
vocational work-study programmes and qualifications”). The aim of the pilot was to gather information on the 
prevalence  of  work-study  qualifications,  as  well  as  on  the  labour  market  outcomes  of  adults  educated 
through  work-study  programmes.  Participation  in  the  pilot  study  was  voluntary,  and  only  few  countries 
managed to provide data (normally from national labour force surveys) to detect their graduates’ outcomes; 
as a consequence, the survey covered only four countries, namely Austria, France, Germany and Switzerland. 
OECD (2019) provides information on the survey, as well as an overview of the different definitions of work-
study  programmes  and  of  their  prevalence  based  on  different  sources.  The  pilot  study  was  also  a  good 
opportunity to achieve conceptual and technical clarifications, and served as a basis for discussion towards a 
classification of education programmes by types of work-based components within the LSO network.  

As shown in Table 3, the pilot found that, in the four countries, at least 75% of the population aged 25-34 
year-olds  with  upper  secondary  or  post-secondary  non-tertiary  level  attainment  attended  vocational 
programmes. In Austria, Germany and Switzerland, over 60% of the population aged 25-34 at this attainment 
level had a work-study qualification, while in France a majority attended a school-based programme (OECD, 
2017a). In all four countries, young people with a work-study qualification have higher employment rates and 
lower  inactivity  levels  than  their  peers  who  attended  a  programme  with  general  orientation;  however,  the 
comparison  between  individuals  with  work-study  qualifications  and  those  with  other  forms  of  vocational 
qualifications shows mixed results. 

Table 3. Educational attainment among 25-34 year-olds, by programme orientation and type of 
vocational programme, 2015 

Below upper 
secondary 

% 

10 
14 
13 
8 

S.E. 

(0.2) 
(0.2) 
(0.1) 
(0.2) 

Upper secondary or post-secondary non-tertiary 

Vocational orientation 

All 
vocational 
orientation 

% 

43 
31 
51 
33 

S.E. 

(0.4) 
(0.2) 
(0.2) 
(0.4) 

Work-study 
programme 

School-based 
programme 

General 
orientation 

Tertiary 

% 

32 
9 
34 
30 

S.E. 

(0.3) 
(0.1) 
(0.2) 
(0.4) 

% 

11 
22 
16 
2 

S.E. 

(0.2) 
(0.2) 
(0.1) 
(0.1) 

% 

8 
10 
7 
10 

S.E. 

(0.2) 
(0.1) 
(0.1) 
(0.3) 

% 

39 
45 
30 
49 

S.E. 

(0.3) 
(0.2) 
(0.2) 
(0.4) 

Austria 
France 
Germany 
Switzerland 

Source: OECD (2017a). Box A5.1 – Labour market outcomes for adults with a work-study qualification. Table A5.b (Web only). 
Notes: Standard errors have been estimated using a simple random sample assumption. The real standard errors taking into account the 
complex sample design may be higher.  

An  update  of  the  data  provided  in  this  pilot  on  the  outcomes  of  work-study  programmes  is  planned  for 
Education at a Glance 2020. However, despite the unquestionable value of such information, this cannot be 
considered a systematic monitoring exercise which could potentially underpin a future indicator or benchmark 
on WBL.  

5.5  Continuing Vocational Training Survey (CVTS)  

The  Continuing  Vocational  Training  Survey  (CVTS)  collects  information  on  enterprises’  investment  in  the 
continuing  vocational  training  (CVT)  of  their persons  employed.  Five  waves  of  the  survey  have  been  carried 
out so far, for reference years 1993, 1999, 2005, 2010 and 2015.  

The primary objective of CVTS is to collect data on CVT (18) in enterprises, and in particular on: the strategies 
of enterprises in training their persons employed; the costs of training (CVT courses); the training modalities; 

(18)   The  CVT  considered  is  the  one  where  the  training  activity  is  the  result  of  a  decision  in  the  enterprise,  and  where  the  primary 
objective is the acquisition of new competences or the development and improvement of existing competences. The training activity 

27 

 
 
 
 
 
                                           
the  training  intensity  (number  of  participants,  training  hours).  Since  2005,  the  CVTS  was  extended  to  cover 
questions on participation in initial vocational training (IVT), with the purpose of understanding the strategies 
of  enterprises  offering  IVT.  IVT  within  enterprises  is  defined  as  a  formal  education  programme  (or  a 
component of it) where working time alternates between periods of education and training at the work place 
and in educational institutions or training centres. For the last wave of CVTS, the operational definition for IVT 
participants explicitly refers to apprentices. As explained in the CVTS  5  manual, apprenticeships are  defined 
based on a list of criteria, namely: 

- 

- 

- 

- 

- 

The  apprenticeship  must  be  a  formal  education  programme  (or  a  component  of  it).  Within  the 
(workplace)  and 
programme, 
general/theoretical education (at the educational institution/training centre); 

learning  time  alternates  between  periods  of  practical  training 

Successful completion of the programme is evidenced by a qualification; 

The duration of the apprenticeship is from 6 months to 6 years; 

The apprentices receive remuneration (wage or allowance, in cash or in kind); 

Usually, there is a training contract (work contract) defining the characteristics of the apprenticeship. 

The questions related to IVT differ across subsequent CVTS waves; in 2005 the survey asked information on 
the total number of IVT participants in the enterprise in the year of reference, as well as on costs incurred by 
the enterprise in relation to its provision of IVT. The latter was replaced in 2010 by a question on the reasons 
for  usually  offering  apprenticeships.  In  the  last  wave  (for  reference  year  2015),  CVTS  investigates  whether 
the enterprise usually employs IVT participants (19), and what are the main reasons for this.  

This brief overview of the survey clearly shows that CVTS is not an ideal candidate for monitoring WBL. First, 
the unit of observation in the survey is the enterprise, and not the individual, so that the reference population 
is different from the one of  interest.  Second, the definition of IVT  differs  between CVTS waves,  limiting the 
monitoring potential of this component of the survey even from the side of the hosting firms; as a matter of 
fact, the last wave of CVTS does not even collect data on the number of apprentices in the companies, which 
would  be  the  most  relevant  piece  of  information  the  survey  could  provide  given  its  scope  and  target 
population. Finally, given that the survey does not collect individual-level data, no information is available on 
the level and orientation of the educational programme that apprentices are attending.  

5.6  Cedefop European Skills and Jobs Survey (ESJS)  

The Cedefop European Skills and Jobs Survey (ESJS) is a survey of adult employees (aged 24 to 65) carried 
out  in  2014  in  the  28  Member  States  of  the  European  Union  by  Cedefop,  the  European  Centre  for  the 
Development  of  Vocational  Training.  The  survey  focused  on  collecting  information  on  the  match  of  adult 
workers’  skills  with  the  skill  needs of  their jobs.  It  was  financed  and  developed  by  Cedefop  in  collaboration 
with  a  network  of  experts  on  skills.  The  aim  of  the  survey  is  to  help  inform  the  development  of  European 
policies on initial and continuing education and training and employment policies. 

In the section on educational attainment, the ESJS questionnaire includes a specific question on work-based 
learning,  namely:  “Did  your  study  take  place  only  within  an  educational  institution  (e.g.  a  school,  college  or 
university) or  did it involve  some learning in a  workplace (e.g. through apprenticeships, internships, or other 
forms of work-based learning)?”. This question is asked to all those with ISCED level 3 or above. Based on this 
question, respondents are classified according to whether they had workplace learning or not. 

Figure 16 shows the share of employees who had a work-based learning experience for the EU as a whole; 
the highest shares of WBL are found among those with a vocational degree at ISCED 3-4 level. 56% of adult 
employees  with  this  education  stream  had  this  type  of  experience  during  studies;  the  share  reaches  60% 
among  young  employees  aged  25-34.  Around  35%  of  higher  education  graduates  had  WBL  during  their 
studies. Evidence from ESJS (Cedefop, 2015 and 2018) shows that indeed work-based learning is associated 
with a faster transition to a first job, as well as to higher levels of job satisfaction.  

should be identifiable as a specific and separate period of training, rather than an on-going activity that cannot be  distinguished 
from work. 

(19)   According to the latest data, around 30% of enterprises in the survey employed IVT participants in 2015; this share is higher for 
bigger enterprises (with 250 or more persons employed), where it reaches 59%, and lower (27%) for small companies (with 10-49 
persons employed). See Eurostat online dataset [trng_cvt_34s]. 

28 

 
 
                                                                                                                                    
Figure  16.  Share  of  employees  who  had  a  work-based  learning  experience  during  studies,  by 
educational attainment and age, 2014, EU28 (% of total employees) 

Source: own elaborations on Cedefop ESJS data.  
Notes: the sample considered is the one of respondents who completed a degree at ISCED 3 level or above, and answered to the question 
on vocational orientation of their degree.  

Despite offering valuable information on prevalence and outcomes of WBL, the ESJS suffers from a few main 
shortcomings for the purposes of monitoring. The first one is that it is carried out on adult employees only; 
this means that (i) it does not cover the total population, therefore not  providing information on non-working 
individuals (as well as self-employed ones); (ii) it does not cover young people up to the age of 23. The second 
drawback  is  that  when  trying  to  distinguish  between  educational  levels,  as  in  Figure  16,  sample  sizes  for 
individuals with WBL experiences become quite small, especially when focussing on the young population. In 
the age group 24-34, only 9 EU countries have samples of graduates from vocational medium education with 
WBL experience of 50 individuals or above; for higher education graduates, the number increases to 16. This 
suggests  sample  sizes  are  likely  not  adequate  for  an  in-depth  analysis.  Finally,  another  issue  concerns  the 
frequency of the survey; as mentioned, the first wave was carried out in 2014, and a second one is foreseen 
for 2021. This makes the survey not an ideal candidate for monitoring WBL. 

5.7  Cedefop VET opinion survey  

In 2016 Cedefop launched its first ever opinion survey aimed at investigating European citizens’ opinions on 
VET.  In  that  year,  more  than  35  thousand  interviews  were  conducted  among  the  citizens  of  the  Member 
States to seek their opinions on VET and get key insights on awareness, attractiveness and effectiveness of 
vocational education and training in Europe.  

A  section  of  this  survey  was  dedicated  to  investigating  the  respondents’  experience  in  upper  secondary 
education; among other aspects, the survey asked about mode of delivery, i.e. whether it had any work-based 
components or was entirely school-based. 

As reported in Cedefop (2017), general education was more likely to be entirely school-based, while VET was 
more  likely  to  include  some  work-based  components.  89%  of  respondents  reporting  upper  secondary 
education  with  a  general  orientation  stated  that  it  occurred  entirely  in  a  school  environment;  the  rate  for 
those  reporting  vocational  medium  education  was  43%,  while  for  24%  it  took  place  mostly  at  school  and 
partly  in  the  workplace,  for  18%  it  was  split  equally  between  school  and  workplace,  and  for  13%  it  was 
mostly in the workplace and partly in school.  

The primary purpose of the survey was to understand  how European citizens view vocational education  and 
training; as a consequence, the survey is not targeted at or particularly suited for monitoring prevalence and 
outcomes of VET or WBL, but more at capturing VET perceptions. It therefore cannot represent a candidate to 
replace other official data sources in this field, but rather complements information that can be drawn from 
them. 

29 

 
 
 
5.8  Labour Cost Survey (LCS) 

The  Labour  Cost  Survey  (LCS)  is  a  survey  conducted  every  four  years  in  EU  Member  States  measuring  the 
level  and  structure  of  labour  costs,  or  total  expenditure  borne  by  employers  for  the  purpose  of  employing 
staff. The reference years of the surveys so far are 1996, 2000, 2004, 2008, 2012 and 2016.  

The  survey  covers  enterprises  with  10  employees  or  more,  and  all  economic  activities  except  agriculture, 
fishing,  public  administration,  private  households  and  extra-territorial  organisations.  In  the  LCS,  detailed 
information  is  collected  to  calculate  the  various  components  of  labour  costs  (wage  components  and  social 
security contributions), as well as information on costs of vocational training, and taxes and subsidies relating 
to the employment of staff. The survey also records data on the number of full-time jobs and the number of 
hours  worked  and  paid;  among  employees,  the  number  of  apprentices  is  recorded  separately,  as  well  as 
information on their wages and salaries, and social security contributions. 

As  reported  in  Eurostat  (2015),  in  order  to  harmonise  and  ensure  comparability  across  countries  –  and  to 
avoid  that  data  for  apprentices  include  forms  of  traineeship  –  the  LCS  2016  introduced  an  operational 
definition envisaging that an individual should be classified as apprentice if: 

- 

- 

- 

- 

- 

An employment contract exists between the individual and the enterprise;  

The apprentice receives remuneration in the form of wage or allowance;  

The educational programme is of less than 6 years of duration and leads to a formal qualification;  

The apprenticeship contract is of at least 6 months and leads to a formal qualification;  

There  is  alternance  between  practical  training  at  workplace  and  general/theoretical  education  in  an 
educational institution or training centre on a weekly, monthly or yearly basis. 

No such definition was included in Eurostat’s implementing arrangements for LCSs before 2016.  

As for CVTS, several limitations are evident for this survey as potential data source for monitoring WBL. First, 
the unit of observation in the survey is not the individual but the enterprise; as a consequence, no individual-
level  information  (e.g.  on  the  educational  programme  attended)  is  collected.  Second,  only  information  on 
apprenticeships  is  recorded,  and  no  data  on  other  types  of  WBL.  Moreover,  the  definition  of  apprentice 
appears to have been standardised only from 2016 onwards. For all these reasons, it is possible to conclude 
that the LCS is not a good candidate for monitoring WBL. 

5.9  Structure of Earnings Survey (SES)  

The Structure of Earnings Survey (SES) is a large enterprise survey conducted in all EU Member States every 
four years. Up until now, it is available for reference years 2002, 2006, 2010 and 2014, with the next survey 
with reference year 2018. It provides comparable information at EU level on relationships between the level 
of  earnings,  individual  characteristics  of  employees  (sex,  age,  highest  successfully  completed  level  of 
education,  occupation,  length  of  service,  type  of  contract  and  working  time)  and  their  employer  (economic 
activity, size of the enterprise, etc.). It covers enterprises with at least 10 employees operating in all areas of 
the  economy  except  agriculture,  forestry  and  fishing,  and  public  administration.  Information  on  public 
administration as well as enterprises with less than 10 employees is also available from some countries on a 
voluntary basis.  

Among individual-level data, the SES collects information on the type of contract of employees, distinguishing 
between contracts of permanent and temporary duration, and apprenticeships. However, no precise definition 
of apprentices is available in the documentation. It also registers the highest successfully completed level of 
education  of  employees;  this  would  however  not  allow  drawing  a  link  between  an  apprentice  and  the 
educational programme currently attended.  

When  compared  to  other  enterprises  surveys,  the  SES  appears  to  be  able  to  provide  more  information  on 
apprentices among employees; however, the information included can only draw a very partial picture of WBL 
features  and  participants  and  of  their  outcomes.  As  a  consequence,  the  SES  does  not  represent  an  ideal 
candidate data source for monitoring WBL.  

30 

 
6  Preliminary assessment of the potential data sources 

In  order  to  evaluate  a  data  source  for  underpinning  potential  indicator(s)  and/or  a  benchmark  on  WBL, it  is 
fundamental  to  assess  its  “fitness  for  use”.  This  is  a  multi-faceted  concept,  which  can  be  defined  starting 
from the dimensions used in data quality frameworks. . OECD (2017b) captures quality – defined as “fitness 
for use” for users’ needs – in terms of the following seven dimensions (20): 

-  Relevance is achieved when data/statistics meet the needs of users; 

-  Accuracy is the degree to which the data correctly estimate or describe the quantities or characteristics 

that they are designed to measure; 

- 

- 

Credibility (similarly to reliability) is the confidence that users place in data products based simply on 
their  image  of  the  data  producer,  i.e.  the  brand  image;  it  is  determined  in  part  by  the  integrity  of  the 
production process; 

Timeliness reflects the length of time between data becoming available and the events or phenomena 
they describe. The notion of timeliness is assessed on the time period that permits the information to be 
of value and still acted upon; 

-  Accessibility reflects how readily data products can be located and accessed; 

- 

- 

Interpretability (or clarity) reflects the ease with which users may  understand and properly use and 
analyse  the  data.  The  adequacy  of  the  definitions  of  concepts,  target  populations,  variables  and 
terminology  underlying  the  data,  and  information  describing  the  limitations  of  the  data,  if  any,  largely 
determines the degree of interpretability; 

Coherence  (or  consistency/comparability)  reflects  the  degree  to  which  the  data  are  logically 
connected and mutually consistent; it can apply to different dimensions, among which: 

  Coherence  over  time  implies  that  the  data  are  based  on  common  concepts,  definitions  and 
methodology  over time,  or  that  any  differences are  explained  and  can  be  allowed  for.  Incoherence 
over  time  refers  to  breaks  in  a  series  resulting  from  changes  in  concepts,  definitions  or 
methodologies; 

  Coherence  across  countries  implies  that  the  data  are  based  on  common  concepts,  definitions, 
classifications and methodology, or that any differences are explained and can be allowed for (21). 

For the purposes of the current analysis, a few of these “fitness for use” criteria are generally respected. With 
the exception of the Cedefop ones, the data sources considered are part of a regulated data collection, carried 
out by Eurostat or other international organisations such as OECD, so that credibility and reliability as defined 
above are normally ensured. Apart from the OECD special survey, which represented a pilot exercise, all these 
data  sources  are  easily  accessible  and  provide  all  the  necessary  metadata  and  supporting  documents  for 
interpretation  and  understanding  of  definitions,  coverage  and  limitations.  They  also  normally  ensure 
coherence across countries, in that they try and apply standard definitions instead of national ones; for WBL, 
this  is  especially  true  for  LFS  (both  AHM/  future  HATWORK  and  TEMPREAS  variables)  and  UOE  data,  as  in 
these cases particular attention is devoted to its conceptualisation and international comparability. Given all 
these features, it is also reasonable to say that the data sources accurately capture what they are designed 
to measure. 

The  remaining  dimensions  (namely  timeliness,  coherence  over  time  and  relevance)  are  more  discriminating 
between potential data sources. An overview of the data sources and of the evaluation of these criteria for 
each  of  them  is  provided  in  Table  4,  which  also  provides  the  main  features  of  the  sources  in  terms  of 
geographical and time coverage, as well as of target population. 

(20)   Eurostat (2019) measures quality of the statistical output by “the extent to which the statistics are relevant, accurate and reliable, 
timely, coherent, comparable across regions and countries, and readily accessible by users, i.e. the Principles of Statistical Output”. 
These dimensions are in line with those described by OECD, and are also used to draw a more comprehensive description of each of 
them.  

(21)   Other levels of coherence can be considered. The first one is coherence within a dataset, which implies that the elementary data 
items are  based  on  compatible  concepts,  definitions  and  classifications  and  can  be  meaningfully  combined.  Incoherence  within a 
dataset occurs, for example, when two sides of an implied balancing statement, such as inflows and outflows, do not balance. A 
second  one  is  coherence  across  datasets,  which  implies  that  the  data  are  based  on  common  concepts,  definitions  and 
classifications,  or  that  any  differences  are  explained  and  can  be  allowed  for.  While  relevant,  these  levels  of  coherence  are  less 
directly related to the assessment of potential data sources for WBL monitoring. 

31 

                                           
A  first  conclusion  that  can  be  drawn  is  that  all  surveys  targeting  enterprises  are  not  ideal  candidates  for 
monitoring WBL. Even though they can provide information on the number and relevance of apprentices in the 
companies,  these  surveys  cannot  deliver any  information  on  (i)  the  level  and  orientation  of  the  educational 
programmes  that  apprentices  are  attending;  (ii)  other  outcomes  of  individuals  with  WBL  experiences,  e.g. 
labour  market  outcomes  after  finishing  their  studies;  (iii)  work-based  learning  experiences  other  than 
apprenticeships.  

As  far  as  the  Cedefop  data  sources  are  concerned,  the  VET  opinion  survey  is  not  an  ideal  source  of 
information  because  of  its  nature  and  purpose.  The  ESJS,  on  the  other  hand,  qualifies  as  an  extremely 
relevant  source;  nevertheless,  two  main  drawbacks  emerge:  the  first  one  is  that  it  only  interviews  adult 
employees;  the  second  one  is  that  for  now  only  one  wave  is  available,  and  the  foreseen  frequency  for 
repeating the survey is not adequate for monitoring purposes. As a consequence, its “overall quality” as data 
source underpinning possible indicator(s) and/or a benchmark can be considered as low.  

The  frequency  of  survey  implementation  represents  a  major  shortcoming  also  for  the  OECD  special  survey 
(together with its current geographical coverage), as well as for PIAAC. The latter has another limitation, i.e. 
the fact of providing only a snapshot of the situation of apprenticeships/WBL in a particular moment; this is 
because  the  relevant  questions  for  capturing  WBL  or  apprentices  have  the  “last  week"  as  reference  period. 
While this can still represent a source of valuable complementary information about ongoing apprenticeships 
of individuals currently in formal education, it is likely not to capture  all possible WBL occurrences. A similar 
concern  could  partially  apply  to  information  from the  LFS  TEMPREAS  variable; despite  in  principle  capturing 
ongoing  apprenticeships  and  trainings,  the  ability  of  this  variable  to  identify  all  individuals  participating  in 
apprenticeship  programmes,  especially  when  a  student  might  take  the  apprenticeship  as  optional  in  the 
future, is yet to be fully established.  

For all these reasons, it can be concluded that no alternative source is able to ensure the same overall data 
quality  (including  relevance,  timeliness  and  coverage)  provided  by  the  LFS  AHM  (and  future  LFS  HATWORK) 
and by  UOE. These are therefore the only realistic candidate data sources for a  potential WBL  indicator, on 
which  Section  7  concentrates  for  a  more  in-depth  assessment.  Given  the  relevance  of  TEMPREAS  as  a 
complementary source of information, it is also taken into account in the following assessment. 

A final remark that can be drawn from the overview of data sources provided in the previous section concerns 
the definitions of WBL and apprenticeship adopted in each of them. The reported definitions show that there 
is still a relative lack of coherence across sources. An overview of the definitions used and planned under the 
IESS FR is reported in Annex 2.  

32 

 
 
Table 4. Overview of the main characteristics of the potential data sources identified to underpin a possible indicator on WBL. 

Data source 

LFS AHM/ 
Future LFS 
HATWORK 

UOE 

LFS 
TEMPREAS 

PIAAC 

OECD special 
survey 

CVTS 

ESJS 

Cedefop 
VET 
opinion 
survey 

Years 
available 

2009, 2016, 
yearly under 
IESS FR 
(from 2021) 

Yearly from 
2013 

Yearly; 
singling out 
apprentices is 
optional since 
2016, 
mandatory 
from 2021 

Every 10 
years (first 
cycle 2011-
2018) 

First wave 
2015/17; to be 
repeated 
2018/20 

1993, 1999, 
2005, 2010 
and 2015 
(every 5 
years) 

2014 

2016 

LCS 

SES 

1996, 2000, 
2004, 2008, 
2012 and 
2016 
(every 4 
years) 

2002, 2006, 
2010 and 
2014 
(every 4 years) 

Geographical 
coverage (EU 
countries)  

Target 
population  

Complete 

Complete 

Complete 

Partial 

Very partial 

Complete 
from 2005 

Complete 

Complete 

Complete 
from 2004 

Complete from 
2010 

Up to 2016: 
population 
aged 15-34; 
from 2021: 
population 
aged 20-34 
with at least 
upper 
secondary 
educational 
attainment 

Students in 
ISCED levels 
3 to 5 

Employees 
aged 15 and 
over with a 
fixed-term 
contract 

Adult 
population 
aged 16-65 

All population 
aged 15 and 
over 

Enterprises 

Adult 
employees 
aged 25-64 

All 
population 
aged 15 
and over 

Enterprises 

Enterprises 
(and their 
employees) 

33 

Relevance  

High 

High 

Medium 
(partial 
information) 

Medium 
(partial 
information) 

High 

Low 

High, but only 
for a sub-
group of 
individuals 
(employees) 

Low 

Low 

Medium 
(partial 
information) 

Timeliness 

High 

High 

High 

Low 

Low 

Medium 

Low 

Low 

Medium 

Medium 

Coherence 
over time 

High under 
IESS FR 

High 

High 

- 

- 

Low 

- 

- 

Low 

Low (no 
definition) 

Fitness for 
use for a 
WBL 
indicator (22) 

High 

High 

Medium 

Medium 

Medium 

Low 

Low 

Low 

Low 

Low 

(22)   This row reports an overall evaluation of “fitness for use” of a data source for underpinning potential indicator(s) and/or a benchmark on WBL. It is classified as “high”, “medium” or “low”; “high” means that 
based on the combination of the criteria above (including relevance, timeliness and coverage), the data source qualifies as a realistic candidate source for a potential WBL indicator; “low” shows that a source 
is not fit for a WBL indicator; “medium” captures situations where the source can provide relevant information on WBL, but (i) limited to some categories of WBL; or (ii) only for a subset of EU countries; or (iii) 
not with the required time frequency. 

34 

                                           
7  An  in-depth  analysis  of  the  strengths  and  weaknesses  of  LFS 

AHM/HATWORK, LFS TEMPREAS and UOE 

Section 6 established that the LFS AHM (and the future LFS HATWORK variable) and UOE ensure an adequate 
overall  level  of  “fitness  for  use”  of  the  data  source  in  terms  of  the  main  dimensions  identified  above.  This 
section goes beyond the general overview, and looks in more detail into the main aspects that  can be taken 
into account in order to evaluate the relevance and usefulness of the two data sources to underpin a possible 
indicator on WBL. 

7.1  Type of WBL experience 

The two  different  data sources allow identifying different types of WBL experience;  however, it is generally 
not easy to reconcile the types of WBL that can be analysed in the data with the three main models of WBL 
described in European Commission (2013)  presented in Section  2.  The  UOE data  collection allows  capturing 
programmes resembling the first and second model of WBL, i.e. alternance schemes or apprenticeships, and 
school-based  VET  which  includes  on-the-job  training  periods  in  companies;  however,  it  does  not  allow 
distinguishing  them.  The  LFS  AHM  attempts  to  capture  more  precisely  different  kinds  of  WBL,  taking  into 
account  duration,  payment  and  whether  the  work  experience  was  mandatory  or  not;  this  ideally  allows  a 
better  identification  of  the  types  of  work  experience,  and  in  particular  a  better  grasp  of  what  can  be 
considered as part of the first model of WBL, especially apprenticeships.  

The  third  model  of  WBL,  i.e.  WBL  that  is  integrated  in  a  school-based  programme,  cannot  be  identified  in 
either data source. 

7.2 

ISCED levels 

While  the  UOE  data  collection  distinguishes  combined  school  and  work-based  programmes  only  among 
formal vocational education programmes at ISCED levels 3 and 4, the LFS AHM allows identifying work-based 
learning also for general medium education programmes and higher education ones.  While this can provide 
interesting insights into the prevalence of WBL at different levels, the policy relevance of work-based learning 
is  mostly  focused  on  medium-level  vocational  education;  as  a  consequence,  this  is  not  necessarily  to  be 
considered a defining factor in the choice of a data source for possible WBL indicator(s) and/or a benchmark. 

7.3  Survey vs. administrative data 

The advantage of having a WBL indicator based on survey data rather than administrative registers lies in the 
possibility to link the information on participation in WBL with several other characteristics of the individuals 
covered in the survey. This ideally allows observing the relationship between participation in WBL and: 

- 

- 

- 

individual socio-demographic features, e.g. immigrant background; 

characteristics of the education programme, e.g. field of study; 

relevant  labour  market  and  other  socio-economic  outcomes,  e.g.  the  choice  of  continuing  studies  or 
employability. 

These links are impossible to make using administrative data from UOE.  

On the other hand, there are limitations to the extent to which it is possible to analyse the links between WBL 
and  these  characteristics  and  outcomes  using  survey  data.  This  is  particularly  the  case  when  the  analysis 
focuses  on  a  narrowly  defined  population  of  reference.  In  these  cases  sample  size  issues  might  severely 
affect the reliability of the figures that can be derived.  

Moreover, survey data is sometimes prone to issues related to misunderstandings of the questions among the 
respondents, which could bias the responses and make the resulting information less reliable. The evaluation 

35 

 
 
 
report of the 2016 EU Labour Force Survey Ad-Hoc Module (Eurostat, 2018) reports that this issue was raised 
in several countries (23).  

Sample  size  restrictions  or  difficulty  of  individual  interpretations  of  survey  questions,  do  not  apply  to  UOE 
administrative data which are based on general definitions of the features of the programmes to be identified 
in  administrative  registers.  Nevertheless,  some  concerns  can  be  raised  also  regarding  the  relevance  of  the 
UOE  definition  for  combined  school  and  work-based  programmes  and/or  the  applicability  of  such  definition 
and  its  reliability  in  practice.  As  mentioned  above,  the  UOE  WBL  definition  is  based  on  a  differentiation  of 
programmes depending on the proportion of time in the curriculum that is supposed to be spent in the school, 
as  opposed  to  work  environment.  The  actual  operationalisation  of  this  definition  in  the  national  education 
systems  might  prove  difficult  in  practice,  for  example  in  cases  where  work-based  learning  experience  is 
optional  and/or  different  students  from  the  same  programme  may  spend  a  different  amount  of  time  in  a 
work  environment.  This  may  be  even  more  complex  in  modular  VET  systems,  where  the  requirements  for 
work-based  learning  may  be  defined  not  in  a  single  programme,  but  in  each  individual  module  taken  by  a 
student.  As  a  matter  of  fact,  a  comparison  between  data  from  UOE  and  LFS  on  students/graduates  from 
vocational ISCED 3-4 programmes shows much higher levels of WBL in the latter, which might suggest that 
countries are not able to report all types of WBL in administrative data.  

7.4  Stock vs. flow information 

The  2016  LFS  AHM  provides  a  snapshot  of  the  prevalence  of  work-based  learning  in  all  highest  attained 
education  qualifications  in  a  given  moment  in  time.  As  such,  it  provides  what  can  be  considered  as  “stock” 
information  on  WBL,  i.e.  information  on  individuals  who  did  have  this  type  of  work  experience  during  their 
studies.  On  the  other  hand,  in  giving  information  on  current  enrolments,  UOE  data  provide  what  could  be 
considered as “flow” information on work-based learning – that is, data on current students who will then be 
included in the future stock of individuals who participated in work-based learning. 

As mentioned above, the “stock” information provided in the LFS data allows evaluating more aspects of the 
WBL phenomenon than flow information from administrative registries can do. However, an important caveat 
applies to the LFS AHM collection, in particular when trying to assess the prevalence of WBL at ISCED 3 and 4. 
As a matter of fact, the AHM enquires about work experience during the highest  attained level of education; 
this  implies  a  potential  loss  of  information  on  lower  education  levels,  and  as  a  consequence,  the  risk  of 
miscalculating the real prevalence of WBL. This problem is likely to affect especially participation at ISCED 3 
level,  which  is  the  most  relevant  one  for  VET  policy.  Given  the  data  currently  available,  it  is  not  easy  to 
evaluate the incidence of the potential loss of information in the LFS AHM. It is possible to get an impression 
of it by looking at the group of young people aged 20-24 who reported having a WBL experience, and who at 
the  time  of  the  interview  had  an  ISCED  3-4  vocational  degree  as  their  highest  level  of  education  attained. 
Figure  4  showed  that  according  to  LFS  AHM  data,  the  share  of  individuals  in  this  group  who  were  still  in 
formal education at the time of the survey was 19.5% for the EU as a whole, representing around 1 million 
people;  six  EU  countries  (SI,  BG,  NL,  RO,  ES  and  CZ)  had  shares  above  25%.  Assuming  these  individuals 
successfully complete a higher level of education, if they were interviewed a few years later, the information 
on  their  WBL  experience  at  ISCED  3-4  would  be  lost (24).  The  magnitude  –  and  even  the  direction  –  of  the 
impact  this  could  have  on  a  possible  WBL  indicator  is  however  hard  to  assess,  as  it  would  depend  on  the 
relative prevalence of WBL among those continuing and not continuing formal education. 

An additional aspect to be taken into account in the comparison between the relevance and usefulness of this 
stock  and  flow  information  is  timeliness.  As  a  matter  of  fact,  if  the  purpose  of  the  indicator  is  to  monitor 
progress for policy purposes, then the ideal situation would be to have information as soon as possible. Past 
experience  on  a  few  of  the  current  Education  and  Training  (ET)  2020  benchmarks  highlighted  how  some 
countries  decided  to  complement  EU  “stock”  benchmarks  such  as early  leavers  from  education  and training 
and  tertiary  educational  attainment  with  national  “flow”  indicators  to  reduce  the  delay  in  monitoring  and 
facilitate timely policy interventions. A similar issue should be considered for possible WBL indicator(s) and/or 

(23)   As an example, the LFS AHM initially published for DE showed very low levels of WBL even among individuals who have a vocational 
ISCED 3-4 degree as highest level of attained education. This under-reporting of WBL was allegedly due to an error in the national 
questionnaire,  where  work-based  learning  and  apprenticeships  were  wrongly  reported.  Data  were  revised  in  April  2019,  using 
national variables which allow the identification of apprentices in particular.  

(24)   In a similar way, the approach adopted in the LFS of asking about work experience during the  highest attained level of education 
implies that information on WBL taking place in an education level which is not yet completed can be captured only partially  (i.e. 
identifying apprenticeships and other paid trainings) through the TEMPREAS variable, and not through HATWORK.  

36 

 
                                           
a benchmark. The LFS TEMPREAS variable could contribute to filling in this gap, by complementing the “stock” 
information  provided  by  LFS  AHM  (and  future  HATWORK)  variables  with  a  “flow”  component  accounting  for 
recent apprentices.  

A possible solution to both issues mentioned in this section would be to focus on recent graduates only, in line 
with  the  definition  applied  for  the  ET  2020  benchmark  on  employment  rate  of  recent  graduates  used  in 
Section 3.3 – but considering all individuals irrespective of whether they are still in formal education or not. 
Provided  such  solution  could  rely  on  a  sufficient  sample  size,  it  would  reduce  the  possible  effect  of  losing 
information  on  lower  education  levels  that  then  highest  one  completed,  as  well  as  ensure  more  timely 
information.  

7.5  Comparability over time  

UOE  data  on  school  and  work-based  vocational  programmes  at  ISCED  levels  3  and  4  are  available  yearly 
since  2013,  after  the  implementation  of  ISCED2011.  Moreover,  following  a  request  from  DG  EMPL  and 
Cedefop, Eurostat published trend data based on ISCED2011 for enrolments and graduates  with a focus on 
programme  orientation  for  reference  years  2005  and  2010  as  well.  Although  it  is  not  easy  to  assess  the 
reliability of these time series, in principle the UOE data collection has been carried out in a consistent way for 
a few years already. 

Data  from  the  Labour  Force  Survey  are  more  fragmented.  Until  now,  information  on  WBL  in  the  LFS  was 
collected  only  in  the  2009  and  2016  Ad-Hoc  Modules  on  young  people  on  the  labour  market.  However,  as 
mentioned  in  Section  3,  it  was  agreed  that  under  the  upcoming  Integrated  European  Social  Statistics 
Framework Regulation, the variable "work experience at a workplace as part of HATLEVEL" (HATWORK) will be 
included into the core LFS from 2021. This new variable will avoid the use of terms such as “apprenticeships” 
or “traineeships”, which appear to be still potentially confusing when operationalising definitions at national 
level. Instead, it will distinguish five main modalities of work-based learning, based on duration and payment. 
Concerning duration, it will identify work experience(s) at a workplace with duration of 7 months or over; from 
1  to  less  than  7  months;  and  less  than  1  month  (or  no  experience).  As  far  as  the  payment  component  is 
concerned, the  new  variable  will  distinguish  work  experiences  where  at  least  one  work  experience  was  paid 
from those where all work experiences were unpaid. This information will not be entirely comparable to that 
provided  in  the  LFS  AHM;  however,  the  inclusion  of  this  variable  in  the  core  LFS  will  lead  to  a  constant 
collection of information on WBL, therefore representing a fundamental source of information for monitoring 
country progress in this domain. 

37 

 
 
 
 
 
8  Conclusions 

Enhancing  provision  and  access  to  high-quality  learning  opportunities  has  been  at  the  heart  of  European 
education, training and employment policies for many years.  One of the main priorities in the EU VET policy 
has  been  the  promotion  of  work-based  learning  and  apprenticeships  schemes,  as  tools  to  deliver  labour 
market  relevant  skills,  ease  transitions  to  labour  market,  contribute  to  reducing  youth  unemployment  and 
support  the  training  of  adults.  Given  the  relevance  attributed  to  work-based  learning  in  VET  across  the  EU, 
including  the  2018  Council  Recommendation  on  a  European  framework  for  quality  and  effective 
apprenticeships,  it  is  important  to  find  ways  to  ensure  reliable  and  comparable  data  collection  that  could 
support better tracking of progress and inform policymaking.   

This report provided evidence in support of this process.  It presented an overview of the main data sources 
currently available to monitor WBL in VET programmes, and an assessment of the strengths and weaknesses 
of the sources that could underpin a possible indicator or benchmark on work-based learning.  

The main conclusion of this report is that, based on the overall evaluation of “fitness for use” of the available 
data  sources  (including  dimensions  such  as  relevance,  timeliness  and  coverage  of  the  data),  there  are 
currently  two  sources  that  can  be  used  to  obtain  regular,  quality  and  comparable  data  on  WBL  in  VET 
programmes: the 2016 EU-LFS Ad-Hoc  Module on young  people on the labour market  (and future  core LFS 
HATWORK variable), and the UOE data collection. The report also highlighted that – despite the narrow focus 
on  specific  types  of  WBL,  and  some  degree  of  uncertainty  concerning  the  practical  level  of  coverage  –  the 
core LFS variable TEMPREAS can represent a valuable source of complementary information on ongoing WBL 
experiences of individuals in formal education. 

Several remarks can be done on the differences between these data sources. A first one concerns the nature 
of the data, and in particular the comparison between  survey and administrative data.  Survey  data  such as 
LFS have the clear advantage of allowing linking participation in WBL with both individual characteristics and 
education/labour market outcomes, as well as  granting a  broader coverage of  different levels of education; 
however,  possible  limitations  due  to  sample  size  and  reliability  issues  need  to  be  taken  into  account. 
Administrative data can be considered more reliable in this perspective; however, the operationalisation of the 
adopted definitions of WBL might prove difficult in some countries.  

Secondly,  the  two  data  sources  provide  different  types  of  information:  the  LFS  AHM  (and  future  HATWORK 
variable) provides “stock” information on WBL, i.e. a snapshot of the prevalence of work-based learning in all 
highest attained education qualifications in a given moment in time; UOE – and (partially) LFS TEMPREAS – on 
the other hand, provide “flow” information, i.e. data on current students who will then be included in the future 
stock  of  individuals  who  participated  in  WBL.  In  this  sense,  the  two  data  sources  are  therefore 
complementary.  The  “stock”  information  from  LFS  data  allows  evaluating  more  aspects  of  the  WBL 
phenomenon  than  flow  information  from  administrative  registries  can  do;  however,  given  the  fact  that  the 
LFS captures work experience during the highest  attained level of education, a potential loss of information 
on lower education levels might occur, with unclear impacts on a possible WBL indicator. Moreover, a concern 
about  the  timeliness  of  “stock”  information  can  arise,  as  it  implies  some  level  of  delay  when  compared  to 
“flow”  data.  A  possible  solution  to  both  issues  would  be  to  focus  on  recent  graduates  only  (provided  a 
sufficient sample size is available to ensure reliability). 

Finally, another relevant aspect in the evaluation of the potential data sources is the definition of work-based 
learning (and of more specific categories within it) applied in each of them. The report showed that  there is 
still a relative lack of coherence across sources, which can however be addressed in the future in light of the 
ongoing effort to rationalise classifications of WBL and apprenticeships in Eurostat data sources. In particular, 
the  future  HATWORK  variable  (included  in  the  core  LFS  from  2021)  will  avoid  the  use  of  terms  such  as 
“apprenticeships”  or  “traineeships”  –  which  appear  to  be  still  potentially  confusing  when  operationalising 
definitions at national level. Instead, the categorisations will be designed around two main dimension, namely 
duration of work experience and whether the work experience was paid or not, in order to make data more 
easily comparable across countries.  

Overall, based on the analysis above and  the experience with LFS  Ad-Hoc modules in 2009 and 2016, LFS-
based indicators appear to be much more promising for monitoring and analysis of work-based learning. This 
is due to  better coverage and accuracy across countries  and levels of education, better timeliness, possible 
linkage  with  multiple  other  variables  in  the  LFS,  as  well  as  more  comparable  operationalisation  of  the 
definition of WBL. 

38 

 
References 

Cedefop  (2014).  Terminology  of  European  education  and  training  policy.  Luxembourg:  Publications  Office  of 
the European Union, 2014. http://www.cedefop.europa.eu/files/4117_en.pdf  

Cedefop  (2015).  Skills,  qualifications  and  jobs  in  the  EU:  the  making  of  a  perfect  match?  Evidence  from 
Cedefop’s European skills and jobs survey. Luxembourg: Publications Office. Cedefop reference series; No 103. 
http://dx.doi.org/10.2801/606129  

Cedefop (2017). Cedefop European public opinion survey  on vocational education and  training. Luxembourg: 
Publications Office. Cedefop research paper; No 62. http://dx.doi.org/10.2801/264585  

Cedefop (2018). Insights into skill shortages and skill mismatch: learning from Cedefop’s European skills and 
jobs 
106. 
Office. 
http://data.europa.eu/doi/10.2801/645011  

Luxembourg: 

Publications 

reference 

Cedefop 

survey. 

series; 

No 

European  Commission 
http://ec.europa.eu/education/policy/vocationalpolicy/doc/alliance/work-based-learning-in-europe_en.pdf  

in  Europe.  Practices  and  Policy  Pointers. 

(2013).  Work-Based  Learning 

Eurostat (2015). Labour Cost Survey 2016. Eurostat’s arrangements for implementing the Council Regulation 
(October  2015).  Available  at 
530/1999  and 
https://ec.europa.eu/eurostat/cache/metadata/Annexes/lcs_r2_esms_an3.pdf 

the  Commission  Regulation  1737/2005 

-  FINAL 

Eurostat (2016a). EU Labour Force Survey Explanatory Notes. https://ec.europa.eu/eurostat/documents/19789
84/6037342/EU-LFS-explanatory-notes-from-2016-onwards.pdf  

Eurostat (2016b). LFS ad-hoc module 2016 on young people on the labour market. Detailed specifications of 
the AHM 2016. https://ec.europa.eu/eurostat/documents/1978984/6037334/Explanatory-notes-AHM-2016.pdf  

Eurostat (2018). Young people on the labour market. Evaluation of the 2016 EU Labour Force Survey ad  hoc 
module. https://ec.europa.eu/eurostat/documents/1978984/6037334/Evaluation_report_LFS_ad_hoc_module_
2016.pdf  

(2019).  Quality  Assurance  Framework  of  the  European  Statistical  System,  Version  2.0. 

Eurostat 
https://ec.europa.eu/eurostat/documents/64157/4392716/ESS-QAF-V1-2final.pdf/bbf5970c-1adf-46c8-afc3-
58ce177a0646  

OECD (2017a). Education at a Glance 2017: Indicator A5. Box A5.1 – Labour market outcomes for adults with 
a work-study qualification. 

OECD  (2017b).  OECD  Handbook  for  Internationally  Comparative  Education  Statistics:  Concepts,  Standards, 
Definitions and Classifications. OECD Publishing, Paris, https://doi.org/10.1787/9789264279889-en. 

OECD  (2019).  Developing  indicators  on  work-based  learning.  Paper  by  the  INES  Network  for  Data 
Development on Labour Market and Social Outcomes of Education. EDU/EDPC/INES/LSO/RD(2019)10. 

Quintini,  G.  (2015).  Working  and  learning:  A  diversity  of  patterns.  OECD  Social,  Employment  and  Migration 
Working Papers, No. 169, OECD Publishing, Paris. http://dx.doi.org/10.1787/5jrw4bz6hl43-en  

UOE  (2017).  UOE  data  collection  on  formal  education  –  Manual  on  concepts,  definitions  and  classifications. 
Montreal, Paris, Luxembourg, 2017. 

39 

 
List of abbreviations  

Country codes  

AT  

BE  

BG  

CY  

CZ  

DE  

DK  

EE  

EL  

ES  

FI  

FR  

HR  

HU  

Austria  

Belgium 

Bulgaria 

Cyprus  

Czechia 

Germany  

Denmark 

Estonia 

Greece  

Spain   

Finland 

France  

Croatia 

Hungary 

IE  

IT  

LT  

LU  

LV  

MT 

NL  

PL  

PT  

RO  

SE  

SI  

SK  

UK  

Ireland  

Italy 

Lithuania 

Luxembourg 

Latvia   

Malta  

Netherlands 

Poland  

Portugal 

Romania 

Sweden 

Slovenia 

Slovakia 

United Kingdom 

Abbreviations 

AHM 

Ah-Hoc Module 

Cedefop 

European Centre for the Development of Vocational Training  

CVTS  

ESJS  

EU 

EU-LFS  

IESS FR  

ISCED 

ISCO  

IVET 

LCS  

OECD 

UOE 

PIAAC  

SES  

VET 

WBL 

Continuing Vocational Training Survey 

European Skills and Jobs Survey 

European Union 

EU Labour Force Survey  

Integrated European Social Statistics Framework Regulation  

International Standard Classification of Education 

International Standard Classification of Occupations 

Initial VET 

Labour Cost Survey  

Organisation for Economic Co-operation and Development 

UIS (UNESCO Institute of Statistics)/OECD/Eurostat data collection 

Survey  of  Adult  Skills  (part  of  the  Programme  for  the  International  Assessment  of  Adult 
Competencies)  

Structure of Earnings Survey  

Vocational education and training 

Work-based learning 

ISCED 2011 levels 

ISCED 3 

ISCED 4 

Upper secondary education; 

Post-secondary non-tertiary education 

ISCED 5-8  

Tertiary (or higher) education  

40 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
List of figures 

Figure 1. People with work experience while studying for their highest qualification, by educational attainment, 
2016 (% of people aged 15-34 who completed formal education above ISCED2) .................................................................7 

Figure 2. Work experience during studies and type of experience, by educational attainment, 2016 (% of 
people aged 15-34) ...........................................................................................................................................................................................................8 

Figure 3. Field of study among individuals with WBL experience during studies, by educational attainment, 
2016 (% of people aged 15-34 who completed vocational medium education or higher education) .................... 10 

Figure 4. Young people in formal education by work experience during studies, 2016 (% of people aged 20-24 
who have vocational ISCED 3-4 as highest qualification attained) ................................................................................................ 11 

Figure 5. Reason for not starting tertiary education by work experience during studies, EU28, 2016 (% of 
people aged 15-34 who have vocational ISCED 3-4 as highest qualification attained and who are not in 
formal education)............................................................................................................................................................................................................ 12 

Figure 6. Labour market status by educational attainment and work experience during studies, EU28, 2016 (% 
of people aged 20-34 who are not in formal education) ...................................................................................................................... 13 

Figure 7. Employment rate of recent graduates by educational attainment and work experience during studies, 
EU28, 2016 (% of people aged 20-34 who completed vocational medium education or higher education 1 to 
3 years before and are not in formal or non-formal education or training) ............................................................................. 14 

Figure 8. Employment rate of recent graduates by educational attainment and work experience during studies, 
2016 (% of people aged 20-34 who completed vocational medium education or higher education 1 to 3 years 
before and are not in formal or non-formal education or training) ............................................................................................... 15 

Figure 9. Share of employment in (medium- and) high-skilled occupations by educational attainment and work 
experience during studies, 2016 (% of people aged 20-34 who are employed and not working in the armed 
forces) .................................................................................................................................................................................................................................... 17 

Figure 10. Self-reported level of match between education and job by educational attainment and work 
experience during studies, EU28, 2016 (% of total employed persons, age group 20-34) ............................................ 18 

Figure 11. Employed persons working part-time involuntarily by educational attainment and work experience 
during studies, EU28, 2016 (% of total number of part-time employed persons, age group 20-34) ...................... 19 

Figure 12. Employees with involuntary temporary contracts by educational attainment and work experience 
during studies, EU28, 2016 (% of total number of employees with temporary contracts, age group 20-34) ... 20 

Figure 13. Employees in precarious employment by educational attainment and work experience during 
studies, EU28, 2016 (% of total number of employees, age group 20-34) .............................................................................. 20 

Figure 14. Work experience during studies and type of experience, by educational attainment, 2009 (% of 
people aged 15-34 who completed formal education above ISCED 2) ....................................................................................... 24 

Figure 15. Share of youth (16-29) combining work and study (a), 2012 (% of all students (b)) ...................................... 26 

Figure 16. Share of employees who had a work-based learning experience during studies, by educational 
attainment and age, 2014, EU28 (% of total employees) .................................................................................................................... 29 

41 

 
List of tables 

Table 1. Employment rate of recent graduates by educational attainment and type of WBL experience during 
studies, 2016 (% of people aged 20-34 who completed vocational medium education or higher education 1 to 
3 years before and are not in formal or non-formal education or training) ............................................................................. 16 

Table 2. Prevalence of WBL by ISCED level, 2016 (% of students in the respective vocational ISCED level who 
were enrolled in school- and work-based programmes) ....................................................................................................................... 22 

Table 3. Educational attainment among 25-34 year-olds, by programme orientation and type of vocational 
programme, 2015 ........................................................................................................................................................................................................... 27 

Table 4. Overview of the main characteristics of the potential data sources identified to underpin a possible 
indicator on WBL.............................................................................................................................................................................................................. 33 

Table A 1. Main fields of study among individuals with vocational medium education as highest qualification 
attained, and share of WBL within each field, 2016 (% of people aged 15-34) ................................................................... 43 

Table A 2. Main fields of study among individuals with higher education as highest qualification attained, and 
share of WBL within each field, 2016 (% of people aged 15-34)................................................................................................... 44 

42 

 
 
 
Annex 1. Statistical Annex 

Table A 1. Main fields of study among individuals with vocational medium education as highest 
qualification attained, and share of WBL within each field, 2016 (% of people aged 15-34) 

Engineering, manufacturing 
and construction 

Business, administration 
and law 

Services 

Health and welfare 

% on total 

35.3    
36.4 

70.0 

43.0 

37.4 

31.6 

61.6 

6.6 

34.7 

28.9 

41.9 

38.0 

30.5 

64.3 

47.1 

49.6 

   x 

44.0 

31.9 

19.0 

39.6 

46.8 

21.9 

50.2 

41.1 

40.8 

37.1 

43.1 

16.3 

EU28 

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 

Of which 
WBL (%) 

60.3 

52.8 

22.2 

68.7 

62.2 

88.6 

59.5 

42.4 

12.3 

29.1 

77.2 

31.7 

34.6 

53.8 

55.8 

63.4 

  x 

89.0 

63.7  u 

68.6 

93.3 

56.5 

35.4 

10.9 

36.4 

60.3 

82.9 

64.6 

60.5 

% on total 

20.8    
20.0 

9.0 

19.7 

26.6 

31.4 

11.5 

3.8 

7.1 

23.1 

23.0 

13.6 

30.8 

5.5  u 

5.8  u 

14.6 

   x 

17.8 

16.5  u 

19.8 

28.2 

11.7 

19.7 

7.4 

20.7 

20.5 

9.6 

6.7 

9.7 

Of which 
WBL (%) 
59.6    
49.8 

25.4  u 

47.0 

47.4 

85.7 

46.9  u 

  x 

18.5 

23.7 

74.5 

20.2  u 

25.8 

  x 

59.7 

  x 

% on total 

15.1    
12.8 

6.4 

19.9 

10.9 

13.6 

9.0 

23.7 

15.1 

13.2 

25.9 

15.3 

19.1 

25.3 

25.5 

Of which 
WBL (%) 
61.4    
55.3 

33.2  u 

81.9 

81.8 

52.7 

30.8 

23.7 

25.7 

80.3 

31.2 

51.2 

61.1 

61.6 

69.2 

   x 

  x 

83.9 

19.5 

86.9 

  x 

19.3  u 

66.7  u 

65.7 

70.9 

50.2 

33.1 

12.1 

38.0 

46.9 

75.1 

70.1 

50.8 

20.7 

16.8 

19.1 

20.3 

8.2 

12.6 

20.7 

26.5 

13.0 

18.2 

68.5 

84.5 

62.3 

51.8 

14.8 

44.3  u 

69.6 

82.2 

67.3 

39.4 

Source: own elaborations on a Eurostat special extraction from LFS AHM 2016.  
Notes: (x) not publishable because of very low reliability; (u) unreliable. 

% on total 

Of which 
WBL (%) 

10.1    
13.3 

   x 

5.5 

25.0 

15.8 

60.8 

69.0 

75.0 

37.0 

59.3 

   x 

  x 

9.8 

13.2 

16.4 

14.5 

3.9  u 

2.0 

   x 
   x 
   x 
   x 

4.4 

9.6  u 

20.8 

6.5 

2.6 

11.0 

3.0 

10.5 

4.1 

13.6 

13.2 

13.1 

32.1 

20.2 

33.0 

78.1 

34.8  u 

50.9 

  x 

  x 

  x 

88.5 

  x 

74.8 

90.6 

53.5 

38.3 

19.4  u 

44.5  u 

82.4 

89.9 

61.2 

51.0 

43 

 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
 
 
 
 
 
 
 
Table A 2. Main fields of study among individuals with higher education as highest qualification 
attained, and share of WBL within each field, 2016 (% of people aged 15-34) 

Business, administration 
and law 

Engineering, 
manufacturing and 
construction 

Health and welfare 

Education 

% on total 

Of which 
WBL (%) 

% on total 

Of which 
WBL (%) 

% on total 

EU28 

22.7   

40.5 

20.9 

39.2 

13.0 

20.6 

27.0 

22.0 

11.4 

19.3 

21.6 

31.0 

49.6 

36.2 

49.0 

24.0 

31.7 

45.3 

18.6 

23.8 

29.8 

80.6 

14.2 

11.9 

16.4 

15.3 

14.3 

19.9 

16.4 

3.3 

15.9 

13.2 

16.9 

43.7 

49.9 

34.1 

60.0 

25.2 

32.6 

52.3 

19.1  u 

24.3 

28.1 

82.9 

11.2 

18.6 

4.9 

13.7 

25.2 

8.5 

11.5 

5.7 

10.7 

14.4 

11.6 

Of which 
WBL (%) 

52.8 

67.2 

55.2  u 

75.9 

29.3 

35.2 

58.1 

32.4 

28.9 

26.3 

81.4 

14.2  u 

  x 

13.6  u 

  x 

7.9  u 

28.2  u 

20.0 

31.1 

31.6 

30.4 

31.4 

21.0 

23.7 

26.1 

25.1 

23.0 

18.3 

32.9 

21.7 

21.2 

23.6 

16.4 

14.4 

29.4 

11.7 

44.0 

60.3 

53.3 

78.7 

32.9  u 

47.2 

24.6 

27.1 

20.4 

8.2 

30.0  u 

33.8 

53.3 

21.1 

17.8 

15.2 

10.1 

14.0 

18.6 

7.4  u 

11.7 

8.7  u 

9.0 

24.6 

12.1 

17.7 

17.9 

16.0 

13.9 

18.7 

21.3 

7.9 

28.3 

29.1 

47.8 

68.9 

13.6 

10.4 

8.4 

9.9 

59.1 

58.4 

73.4 

84.9 

  x 

7.8  u 

68.8  u 

89.3 

  x 

50.0 

52.0 

42.1 

13.1 

10.2 

46.3  u 

37.8 

65.9 

20.3 

34.7 

7.0 

19.3 

19.1 

5.6 

7.3 

18.5 

4.5 

11.3 

13.1 

18.2 

18.7 

8.7 

91.3 

65.7 

67.4 

55.8 

63.7 

35.5 

22.3  u 

59.1  u 

49.2 

87.6 

55.0 

37.2 

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 

% on total 

8.0 

8.9 

6.2 

9.3 

6.3 

13.7 

6.0 

3.3 

6.9 

12.9 

2.1  u 

17.1  u 

4.4 

6.9 

3.7  u 

6.2 

8.7  u 

12.1 

12.5 

9.9 

8.9 

12.3 

7.9 

2.2 

12.3 

14.8 

6.4 

10.1 

5.4 

Of which 
WBL (%) 

42.0 

64.4 

40.1  u 

70.8 

33.1  u 

22.9 

56.5  u 

16.6  u 

21.1 

32.0 

73.6  u 

31.4  u 

52.4 

44.8 

  x 

84.3 

  x 

78.6 

52.5  u 

69.4 

39.1 

47.6 

29.3 

  x 

43.7  u 

58.3 

80.9 

63.9 

35.7 

Source: own elaborations on a Eurostat special extraction from LFS AHM 2016.  
Notes: (x) not publishable because of very low reliability; (u) unreliable. 

44 

 
 
 
 
 
 
 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
Annex 2. Definitions of work-based learning and apprentices/apprenticeships in 
Eurostat data sources  

LFS AHM 2016 (Ad-Hoc Module 2016 – Young people on the labour market) 

Source:  explanatory  notes,  https://ec.europa.eu/eurostat/documents/1978984/6037334/Explanatory-notes-
AHM-2016.pdf  

The  variable  WORKEXP  (work  experience  during  studies)  distinguishes  whether  a  person  had  paid  and/or 
unpaid work experiences (or no work experiences) during  the studies that led to the  highest level of formal 
education successfully completed. For those who had a work experience, the variable WORKSTUD (work-based 
learning) further classifies the work experience into two kinds of work-based learning, “apprenticeships” and 
“traineeships”, and work experiences outside the curriculum. 

In the AHM 2016 context, “apprenticeships” are defined as work experiences that  were a mandatory part of 
the  curriculum  of  the  formal  programme  that  led  to  the  highest  level  of  education  successfully  completed, 
where the work-based learning was paid and had a total duration of at least 6 months. “Traineeships” are all 
other  forms  of  work-based  learning  as  part  of  the  curriculum,  i.e.  traineeships  might  be  mandatory  or 
voluntary, paid or unpaid, and they might be shorter than six months.   

  For  the  definition  of  apprenticeships,  “duration”  refers  to  the  duration  of  the  work-based  learning 

component.  

LFS variable HATWORK from 2021 

Source: draft 2021 LFS explanatory notes, not yet publicly available. 

The new variable HATWORK (work experience at a workplace as part of HATLEVEL, i.e. the studies that led to 
the highest level of education successfully completed) will be collected annually as from 2021 for those aged 
20 to 34 with at least upper secondary educational attainment. The variable aims at categorising the target 
population into five groups as follows: 

-  Work experience(s) at a workplace from 1 to 6 months, at least one (work experience) paid; 

-  Work experience(s) at a workplace from 1 to 6 months, all unpaid; 

-  Work experience(s) at a workplace 7 months or over, at least one paid; 

-  Work experience(s) at a workplace 7 months or over, all unpaid; 

- 

No or less than 1 month work experience. 

The  terms  “apprenticeships”  or  “traineeships”  are  not  used  on  purpose,  as these  terms remain  confusing  at 
national level. The split of duration into  “1-6 months” and “7 months or over” was introduced on request of 
countries who found these intervals more relevant/meaningful. There is no information collected  on whether 
the work experience was mandatory or voluntary. 

  “Duration” refers to work experience at a work place. 

LFS variable TEMPREAS since 2016 

Source:  2017  LFS  explanatory  notes,  https://ec.europa.eu/eurostat/documents/1978984/6037342/EU-LFS-
explanatory-notes-from-2017-onwards.pdf 

The variable TEMPREAS (reasons for having a temporary job/work contract of limited duration) is only asked 
to employees with a contract of limited duration. The variable identifies the reason why the respondent has in 
the main job a fixed-term contract. One reason for having a fixed-term contract is training, and since 2016 
two  categories  of  TEMPREAS  aim  at  singling  out  “apprentices”  vs.  “other  forms  of  training”  on  a  voluntary 
basis.  

The criteria to qualify as an apprenticeship are as follows: 

45 

 
 
 
- 

- 

- 

- 

- 

there is a contract or formal agreement for a prescribed period of time between the employer and the 
apprentice  or  an 
institution  representing  the  apprentice,  defining  the  characteristics  of  the 
apprenticeship; 

learning time alternates between periods of practical training at the work place and general/theoretical 
education in an educational institution or training centre on a weekly, monthly or yearly basis; 

all apprenticeships are (part of) formal education programmes; successful completion is evidenced by a 
qualification; 

in apprenticeships, the participant (apprentice) always receives remuneration in cash or in kind; 

the duration is between 6 months and 6 years. The duration refers to the programme and not only to the 
work-based component. 

In the context of this variable, training other than apprenticeship covers all other categories of paid training 
such  as  trainees  (either  linked  to  formal  or  non-formal  education  programmes);  research  assistants; 
internships (e.g. for physicians); periods of practice after courses and before recognition of qualifications (e.g. 
for lawyers). 

  Here, “duration” refers to the formal programme and not to the work-based component. This was decided 
in view of how formal education is covered both in UOE and in surveys: only formal programmes with a 
duration of at least 6 months are considered as formal education. 

LFS variable TEMPREAS from 2021  

Source: draft 2021 LFS explanatory notes, not yet publicly available 

From 2021, new legislation will apply to the EU-LFS, and for TEMPREAS, singling out “apprentices” vs. “other 
forms  of  training”  becomes  mandatory.  The  explanatory  notes  are  rephrased  for  better  clarity  but  remain 
largely unchanged in terms of contents. They read as follows: 

Criteria  to  qualify  an  apprenticeship:  in  order  to  achieve  comparable  results,  only  apprentices  who  fulfil  all 
these criteria should be included, regardless of national definitions of apprentices: 

- 

- 

- 

- 

- 

All apprenticeships are (part of) formal education programmes; successful completion is evidenced by a 
formal qualification. 

There is a contract or formal agreement for a prescribed period of time between the employer and the 
apprentice  and/or  an  institution  representing  the  apprentice,  defining  the  characteristics  of  the 
apprenticeship  (such  as  the  rights  and  obligations  of  the  employer  and  of  the  apprentice,  learning 
objectives, etc.). 

Learning  time  combines  or  alternates  periods  of  education  and  training  at  the  work  place  and  in 
educational institutions or training centres on a weekly, monthly or yearly basis. 

In apprenticeships, the participant (apprentice) always receives remuneration in cash or in kind. 

The duration is between 6 months and 6 years. The duration refers to the programme and not only to 
the work-based component. 

Training (other than apprenticeship) covers all other categories of paid training such as: 

- 

- 

- 

- 

trainees as defined in the explanatory notes for WKSTAT (either linked to formal or non-formal education 
programmes); 

research assistants; 

internships (e.g. for physicians); 

periods of practice after courses and before recognition of qualifications (e.g. for lawyers). 

46 

 
 
LCS 

Source:  Eurostat  (2015).  Labour  Cost  Survey  2016.  Eurostat’s  arrangements  for  implementing  the  Council 
Regulation 
FINAL, 
Regulation 
Commission 
https://ec.europa.eu/eurostat/cache/metadata/Annexes/lcs_r2_esms_an3.pdf 

1737/2005 

530/1999 

and 

the 

– 

According to the LCS 2016 implementing arrangements, an individual should be classified as apprentice if: 

- 

- 

- 

- 

- 

An employment contract exists between the individual and the enterprise;  

The apprentice receives remuneration in the form of wage or allowance;  

The educational programme is of less than 6 years of duration and leads to a formal qualification;  

The apprenticeship contract is of at least 6 months and leads to a formal qualification;  

There  is  alternance  between  practical  training  at  workplace  and  general/theoretical  education  in  an 
educational institution or training centre on a weekly, monthly or yearly basis. 

  “Duration” refers to the apprenticeship contract. 

CVTS 

The definitions used for CVTS are aligned to the LFS variable TEMPREAS. 

UOE 

School-based programmes: at least 75% of the curriculum is presented in a school environment. 

Combined school and work-based programmes: the work-based component is between 25% and 90% of the 
curriculum. 

Work-based programmes: over 90% of the curriculum is presented in a work-based environment. These are 
by definition not formal education but the qualification might be recognised as formal. 

47 

 
 
 
 
 
 
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