Long version of presentation at UNESCO Mobile Learning Week. The argument is that we have to think about what to learn and to encourage frequent participation in learning. The question is how to encourage people, who tend not to participate - these are usually those who have a lower level of formal education and are older. However, these two groups are most likely to be affected by automation and other changes to our economies. Recognising people's acquired skill level through digital badges and connecting these to recognition pathways can be a way to ensure empower all learner groups - and to aid skills matching in the labour market.

1. Developing skills and
competencies for life and
work – what role digital
technologies?
[long version]
Dr. Dominic Orr
d.orr@fibs.eu @dominicorr
Source:ownphoto.Lalibela,Ethiopia.
Mobile Learning Week “Skills for a connected world” , UNESCO Paris 28.03.2018

2. Developing skills and competencies for life and work –
what role digital technologies?
Two central questions:
1. What to learn? – in the context of changes in a digital world
2. How to encourage more people to acquire skills more
to help people live good lives in the context of changes in a
a) Who participates in lifelong learning?
b) How can we encourage and empower other people to
Preamble

3. 1. The challenge: increasing automation and increasing
instability of career pathways
2. The good and the bad of formal education
3. The increasing need for ‘skills discovery’ and linked
‘learning pathways’
4. The new approach of community recognition of
informal learning using digital badges and learning
pathways
Agenda

4. The challenge: increasing automation and
increasing instability of career pathways
Q: What to learn? – in the context of changes in a
digital world
Agenda

5. Nedelkoska, L., & Quintini, G. (2018). Automation, skills use and training (OECD Social, Employment and Migration Working
Papers). https://doi.org/10.1787/2e2f4eea-en
• Social intelligence - the ability to
effectively negotiate complex social
relationships, to collaborate, to
empathize, to recognize cultural
sensitivities, to care for others
• Cognitive intelligence – the ability
to problem-solve, complex-
reasoning and the ability to be
creative, work outside or redefine
the ‘rules’
• Perception and manipulation – the
ability to carry out physical tasks in
an unstructured work environment
CC BY: Gerd Leonard, author of Technology vs. Humanity: The coming clash
between man and machine
Engineering bottlenecks to automation (Frey & Osbrey)

6. Source:PIAAC2012,2015
• OECD analysis (32
countries) used engineering
bottlenecks to calculate
probability of automation
• Unemployment rate
between the least and the
most automatable
occupation is 44 pp
• 33%+ of variance in the
occupational
unemployment rate
attributed automatability,
when not controlling for
other factors
Nedelkoska, L., & Quintini, G. (2018). Automation, skills use and training (OECD Social, Employment and
Migration Working Papers). https://doi.org/10.1787/2e2f4eea-en
Probability of automation by occupational group

7. McKinsey Global Institute (2017): Jobs lost, jobs gained: Workforce transitions in a time of automation
Need to switch occupations based on future scenarios
• In advanced economies,
one third of workers
projected to need to
change occupation by 2030
• In emerging economies less
due to differences in
economies (less complexity
and lower wages) and
infrastructure; one tenth of
workers projected to need
to change occupation by
2030

8. • 21st Skills according to Fadel et al.
• Bessen’s emphasis of skills need in
sectors (i.e. those most likely to be making
technology):
 Mature sectors have a consensus on
standardised knowledge required to
implement tasks
 In innovative areas knowledge on best
practice has yet to become
is difficult to define exactly what is
• In this case more fluid skills sets, which
person holding them, to adapt to new
will become more relevant.
Fadel, C.; Trilling, B.; Bialik, M. (2015). Four-Dimensional Education: The
Competencies. Center for Curriculum Redesign.
Bessen, J. (2015). Learning by Doing: The Real Connection between
Innovation, Wages, and Wealth. Yale University Press.
Types of skills and competencies

9. The good and the bad of formal education
Agenda
Q: How to encourage more people to acquire skills more
frequently? (How to help people live good lives in the context of
changes in a digital world?)
a) Who participates in lifelong learning?
b) How can we encourage and empower other people to
participate?

10. Nedelkoska, L., & Quintini, G. (2018). Automation, skills use and training (OECD Social, Employment and
Migration Working Papers). https://doi.org/10.1787/2e2f4eea-en
Link between automation and educational level
• Automation less likely in jobs
held by people the higher
their educational attainment
• Graduates of tertiary education
appear most protected from
risk of automation in their
occupation

11. 0
20
40
60
80
100
120
1 9 9 0 1 9 9 1 1 9 9 2 1 9 9 3 1 9 9 4 1 9 9 5 1 9 9 6 1 9 9 7 1 9 9 8 1 9 9 9 2 0 0 0 2 0 0 1 2 0 0 2 2 0 0 3 2 0 0 4 2 0 0 5 2 0 0 6 2 0 0 7 2 0 0 8 2 0 0 9 2 0 1 0 2 0 1 1 2 0 1 2 2 0 1 3 2 0 1 4
Gross enrolment ratio, tertiary, both sexes (%)
Total e nrollment i n te rtiary e ducation ( ISCED 5 to 8) , re gardless of age , e xpressed as a pe rcentage of
the total population of the f i ve- year age group f ollowing on f rom se condary school l e aving
High income countries Low income countries World
United States United Kingdom Poland
Brazil China India
Source: Orr
Growth in educational attainment across the world
• Huge growth in
formal education
participation
• E.g.: in tertiary
education:World x2,
India x4, China x10 in
two decades

12. Source: Busso, M., Cristia, J., Hincapié, D., Messina, J., & Ripa, L. (Eds.). (2017). Learning better - Public policy for skills
development. Inter-American Development Bank. Retrieved from http://www.iadb.org/es/investigacion-y-
http://www.iadb.org/es/investigacion-y-datos/aprender-mejor-politicas-publicas-para-el-desarrollo-de-
habilidades,20770.html
Where skills are formed
• Most of our life, we are
outside of the formal
education sector
• Increasing importance of
learning at work and at
home over time
• Empirical chart of location
of skills formation (here
using in LatinAmerican
and Caribbean regional
average)

13. Decision to
take part
<>
Taking part
+/- Gender
does not
contribute
after
controlling for
the other
predictors
+ Number of
co-workers:
employers in
larger firms are
more likely to
participate
+ Level of
education:
most likely to
participation
are graduates
of tertiary
education
++ Age: younger
persons under
50 years old are
more likely to
participate
++ Occupation:
academics,
craftsmen,
technicians
• Level of education
significant predictor
of taking part in
further education
• Data from multivariate
analysis of German
Education Survey
FiBS (unpublished)
• Model explains ca.
of variance – what
Who takes part in further education?
Source: FiBS analysis for project VoREFFI

14. • ABC model from Stern et al. to overcome
internalist-externalist dichotomy
• Behaviour (B) is an interactive product
product of personal sphere attitudinal
attitudinal variables (A) and contextual
contextual factors (C)
Attitude
Context
positive
negative
positivenegative
Adapted from: Jackson, T. (2005). Motivating Sustainable Consumption: A Review of the Evidence on Consumer Behaviour and
Behavioral Change. Sustainable Development Research Network. https://doi.org/10.1260/0958305043026573
Participation in training determined by attitude and context

15. The increasing need for ‘skills discovery’ and
linked ‘learning pathways’
Agenda
Q: How to encourage more people to acquire skills more
frequently? (How to help people live good lives in the context of
changes in a digital world?)
a) Who participates in lifelong learning?
b) How can we encourage and empower other people to
participate?

16. Source: World Economic Forum,
2016
Skill discovery &
learning
pathways
Taking a more holistic approach to be more
inclusive

17. Source: own analysis of CEDEFOP
European Skills and Jobs Survey
• Over one third of workers in
EU find their skill level is
higher than required by their
job
2 consequences:
• Need better methods to make
people’s skill profiles more
visible, so that both individuals
and society can fully harness
their skills and competencies
• Need to activate people’s
recognition of the need to
learn and support their learning
pathways (esp. in the dynamic
‘digital economy’).
A new insight: people’s perception of their skill level

18. The new approach of community recognition of
informal learning using digital badges and
learning pathways
Agenda

19. Technical tool to make skills more visible – open
badges

20. connected
metadata
New development: connecting Open Badges to skills standard
• Open Badge connected to ESCO - European
Skills, Competences, Qualifications and
Occupations standards
• e.g. “Manage quantitative data”

21. • E.g.: Start-up indorse.io from Singapore
• Ethereum-based decentralized recognition
system
• Skills validated in “an anonymous, simple and
objective way” through consensus of other expert
users
• E.g.: MIRVA project - Making Informal RecognitionVisible and Actionable through the
development of “open recognition hubs”, which recognition between individuals, between
individuals and organisations (O), between organisations, between organisations and systems
(S) and between systems
Open Recognition Hubs – context for badge technologies

22. 1. What to learn? – yes cognitive skills, but especially
metacognition (learning to learn), social and emotional skills,
are fluid and can be adapted to new situations
2. How to encourage more people to acquire skills more
frequently?
a) Who participates in lifelong learning? – attitudinal and
contextual barriers to learning on the one hand, those with
formal learning frequently undertake further education on
b) How can we encourage and empower other people to
participate? – provide a new context, recognise what they
can do now and support them (this will also have benefits
skills matching on the job market), digital badge
To sum up: responses to two central
questions

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