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TRANSCRIPT
18TH OECD/JAPAN SEMINAR
EDUCATION 2030
Andreas Schleicher
Director for Education and Skills, OECD
The kind of things that are easy to teach are
now easy to automate, digitize or outsource
Changes in the nature of work Trends in different tasks in occupations (United States)
35
40
45
50
55
60
65
70
1960 1970 1980 1990 2000 2006 2009
Routine manual
Nonroutine manual
Routine cognitive
Nonroutine analytic
Nonroutine interpersonal
Mean task input in percentiles of 1960 task distribution
Source: Autor, David H. and Brendan M. Price. 2013. "The Changing Task Composition of the US Labor Market: An Update of Autor, Levy, and Murnane (2003)." MIT Mimeograph, June.
Where people lost and gained jobs between 2010-14
3 409
-3 134
-125
-100
-75
-50
-25
0
25
50
75
100
125
GRC ESP PRT SVN ITA NLD FIN DNK CZE POL IRL BEL FRA SVK HUN SWE AUT GBR EST DEU EU28
%
Public administration, education, health and other services Professional, scientific, technical and other business services
Financial, insurance and real estate activities Information and communication
Wholesale, retail, hotels, food services and transport Construction
Manufacturing Mining and utilities
Agriculture, forestry and fishing
2010-2014
Gains,
thousands
Source: OECD Science, Technology and Industry Scoreboard 2015 - © OECD 2015
Robotics
Google Autonomous Vehicle
>1m km,
one minor accident,
occasional human intervention
Inspired by: Center for curriculum redesign (CCR)
Augmented Reality
Inspired by: Center for curriculum redesign (CCR)
TomTom has 5 trillion data points on traffic, adding 6 billion per day.
BMW cars have 50 sensors, 7 cameras, could recognize open parking spots for other cars
GE expects to connect all its machines to the Internet, making them “smarter” and more efficient
Tesco exploits data on more than 100 market baskets a second and 6 million transactions a day
8 The Digital Economy is the economy…
…unleashing firms that gain
“scale without mass”…
• 50$B in sales,
• 54 000 employees,
• 1m / employee US Average = 120k / employee
• 70$B in sales
• 110 000 employees
• 600k / employee 200k / employee
10 …and leading to bifurcated productivity growth.
Labour productivity growth (2001 = 100)
Manufacturing Services
Source: OECD, The Future of Productivity, forthcoming
A lot more to come
• 3D printing
• Synthetic biology
• Brain enhancements
• Nanomaterials
• Etc.
Inspired by: Center for curriculum redesign (CCR)
The Race between Technology and Education
Inspired by “The race between technology and education” Pr. Goldin & Katz (Harvard)
Industrial revolution
Digital revolution
Social pain
Universal public schooling
Technology
Education
Prosperity
Social pain
Prosperity
14
Source: WEF 2015 Global Risks
15 Growing unequal
Gini Coefficients for OECD countries, in 1985 and 2008
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
Me
xic
o
Un
ited
Sta
tes
Isra
el
Un
ited
Kin
gd
om
Italy
Austr
alia
Ne
w Z
eala
nd
Ja
pa
n
Cana
da
Germ
any
Ne
the
rla
nds
Luxe
mb
ou
rg
Fin
land
Sw
ede
n
Cze
ch
Re
pub
lic
Norw
ay
Denm
ark
Turk
ey
Gre
ece
Fra
nce
Hung
ary
Belg
ium
1985 2008
16 Home alone: the rise of single-person households
Number of one person households early-mid-2000s to 2025-2030 (projected)
0
10
20
30
40
50
Fra
nce
Ne
the
rla
nds
Sw
itze
rla
nd
Germ
any
Austr
ia
Norw
ay
Eng
land
Ja
pa
n
Austr
alia
Ne
w Z
eala
nd
Un
ited
Sta
tes
Kore
a
Early-mid-2000s 2025-2030
17 17 Poverty is not destiny PISA math skills of 15-year-olds by decile of social background
30
03
25
35
03
75
40
04
25
45
04
75
50
05
25
55
05
75
60
06
25
65
06
75
Me
xico
Ch
ileG
ree
ceN
orw
aySw
ed
en
Ice
lan
dIs
rae
lIt
aly
Un
ite
d S
tate
sSp
ain
De
nm
ark
Luxe
mb
ou
rgA
ust
ralia
Ire
lan
dU
nit
ed
Kin
gdo
mH
un
gary
Can
ada
Fin
lan
dA
ust
ria
Turk
ey
Lie
chte
nst
ein
Cze
ch R
ep
ub
licEs
ton
iaP
ort
uga
lSl
ove
nia
Slo
vak
Re
pu
blic
Ne
w Z
eal
and
Ge
rman
yN
eth
erl
and
sFr
ance
Swit
zerl
and
Po
lan
dB
elg
ium
Jap
anM
acao
-Ch
ina
Ho
ng
Ko
ng-
Ch
ina
Ko
rea
Sin
gap
ore
Ch
ine
se T
aip
ei
Shan
ghai
-Ch
ina
Source: PISA 2012
Increasing migration towards the developed world
-20
-15
-10
-5
0
5
10
15
20
25
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
High income OECD members
Low income Middle income
Source : OECD (2013), Trends Shaping Education. Primary source: World Bank (2012), World Databank: Net Migration.
Net migration (in millions of people) into regions,
with countries grouped by income level and OECD members, 1960-2010.
19
What does all this mean for education?
Education in the past
Education 2030
Knowledge Concepts, processes, methods, tools
Examples of disciplinary knowledge
Reading, writing
Mathematics Natural
sciences Social sciences
Foreign languages
History Economics,
politics and law Geography
Art
Physical education,
health education
Math teaching ≠ math teaching PISA = reason mathematically and understand, formulate, employ
and interpret mathematical concepts, facts and procedures
25
0.00
0.50
1.00
1.50
2.00
2.50V
iet N
am
Ma
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Hong
Kon
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ese
Taip
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Port
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Bra
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Serb
iaB
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aria
Sin
ga
po
reN
eth
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Ja
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tin
aC
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Ric
aL
ithu
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Tunis
iaN
ew
Ze
ala
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Czech R
ep
ub
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rael
Kore
aL
atv
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ata
rIt
aly
United
Sta
tes
Esto
nia
Irela
nd
Austr
alia
Me
xic
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nited
Ara
b E
mira
tes
Norw
ay
Ma
laysia
Kaza
kh
sta
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nited
Kin
gd
om
Rom
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OE
CD
ave
rag
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olo
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Sw
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ium
Peru
Thaila
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De
nm
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Ru
ssia
n F
ede
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nC
ana
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Slo
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epu
blic
Hung
ary
Germ
any
Cro
atia
Luxe
mb
ou
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on
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hile
Pola
nd
Fin
land
Austr
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iaF
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Sw
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Jo
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inS
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ela
nd
Ind
ex
of
ex
po
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re t
o w
ord
pro
ble
ms
Focus on word problems Fig I.3.1a 26
Formal math situated in a word problem, where it is obvious to
students what mathematical knowledge and skills are needed
0.00
0.50
1.00
1.50
2.00
2.50S
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ela
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Tu
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Ind
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Austr
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Chile
OE
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Th
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Port
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Italy
Belg
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Ho
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Spa
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on
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Turk
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Slo
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iet N
am
Hung
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Bulg
aria
Kaza
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Cana
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United
Sta
tes
Esto
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Rom
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Latv
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Alb
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ussia
n F
ede
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Focus on conceptual understanding Fig I.3.1b 27
Examples of interdisciplinary knowledge
Financial literacy Cultural literacy/
intercultural literacy
Global knowledge Entrepreneurship,
Business, Economics
ICT literacy Media literacy Ecology,
environmental literacy
STEM
Programming Engineering Robotics Practical/
vocational-related knowledge
Exposure and financial literacy Perf
orm
ance
in f
inanci
al lite
racy
30
Australia
Colombia
Czech Republic
Flemish Community
(Belgium)
Latvia
New Zealand
OECD average-13 Poland
Russian Federation
Shanghai-China
Slovak Republic
United States
375
425
475
525
575
625
40 50 60 70 80 90 100
% of students in schools where the principal reports that financial literacy is available for at least 2 years
Some examples of themes in which knowledge can be developed
Systems
thinking
Design
thinking
Information
literacy
Digital
literacy
Global
literacy
Inspired by: Center for curriculum redesign (CCR)
Emotional (e.g. beauty)
Cognitive (e.g. creativity, critical thinking)
Disciplinary/practical use (e.g. relevance to application in work and life)
Selecting and prioritising what students should learn
Inspired by: Center for curriculum redesign (CCR)
Cognitive competencies
Examples of cognitive competencies
Problem Solving
Creativity Critical
Thinking Analytical
skills
Innovation Synthesising Systems thinking
Researching
Foresight thinking
Higher order thinking skills
Data gathering
Sources: Green - OECD (2015), Lippman, L. et all. (2015), Literature review of
34 empirical studies, Kauz et al.(2014),
100 80 60 40 20 0 20 40 60 80 100
Poland
Ireland
Slovak Republic
Estonia
Korea
United States
Austria
Czech Republic
Average
Flanders (Belgium)
Japan
England/N. Ireland (UK)
Germany
Canada
Australia
Denmark
Norway
Netherlands
Finland
Sweden
Basic digital
problem-solving
skillsAdvanced digital
problem-solving
skills
Young adults (16-24 year-olds) All adults (16-65 year-olds)
36 Digital problem solving skills of adults
%
PIAAC/OECD
37
Evolution of employment in occupational groups defined by problem-
solving skills
-20
-15
-10
-5
0
5
10
15
20
25
%
Medium-low problem-solving skills
Low problem-solving skills
High level problem-solving skills
Average is over
Knowledge
Social competencies
Examples of social Competencies
Collaboration Cross cultural
skills Communication
Team work Conflict
resolution skills Leadership
Collaborative Problem Solving in PISA 2015
Collaborative problem solving competency is the
capacity of an individual to effectively engage in a
process whereby two or more agents attempt to
solve a problem by sharing the understanding and
effort required to come to a solution and pooling their
knowledge, skills and efforts to reach that solution.
Global Competence in PISA 2018
Global Competence is the capability and disposition
to act and interact appropriately and effectively,
both individually and collaboratively,
when participating in an interconnected,
interdependent and diverse world.
43 Physical competencies and well-being
Subjective health
Health habits (good nutrition; making good
choices about sleep and exercise)
Kinesthetic ability (the ability to
coordinate movement) dexterity, motor
skills
Risk-avoidance behaviours (avoiding
substance abuse, smoking, drinking,
unsafe sexual practices, and violence)
Health outcomes (e.g. obesity, body-mass index – BMI)
Ability to use physical tools,
operations, functions including manual
skills (ICT, new
machines)
Physical Competencies and Well-being
Overweight and obesity among children 1
1
21
21
17
15
26
15
16
17
15
16
24
23
17
18
17
18
16
24
21
24
14
29
23 24
27
28
16
22
25
32
25
37
34
35 36
34
33
36
44
8 9
13
14
14
14
15
15
15
15
16
16
17
17
17
18
18
18
19
19
20
21
21
22
22
23
23
24
24
24
30
31
32
34
32
34
34
35
36
38
0
10
20
30
40
50
% of children at various ages
Boys Girls
Measured overweight (including obesity) among children, 2013 (or latest year)
Source: World Obesity Federation (2015), KIGGS (2003-06) for Germany and KNHANES (2013) for Korea.
Knowledge
Social competence
Character qualities
47 Some examples of character qualities
Empathy Resilience Mindfulness
Inclusion Curiosity Ethics
Courage Leadership
College Completion (USA)
OECD (2015)
Source: NLS
Y
Cognitive skills deciles Social & emotional skills deciles
Bullying at 15 (Korea)
OECD (2015)
Source: KYP
S
Happy at 20 (New Zealand)
OECD (2015)
Source: CC
51
Immigrant students’ PISA performance in mathematics,
by country of origin and destination
300 350 400 450 500 550 600
Australia
Macao-China
New Zealand
Hong Kong-China
Qatar
Finland
Denmark
United Arab Emirates
Netherlands
PISA score points in mathematics
First-generation immigrants' score, after accounting for socio-economic status
Students from Arabic-speaking
countries in:
Students from China in:
50 55 60 65 70 75 80 85 90 95
Denmark
Qatar
United Arab Emirates
Netherlands
Finland
%
Percentage of students with an immigrant background
who reported that they feel like they belong at school
Country of origin and country of destination
Students from Arabic-speaking
countries in:
52 Meta-competencies
reflecting on learning goals, strategies and results
Meta-competencies reflecting on learning goals, strategies and results
Global awareness
Growth mindset/ locus
of control
Learning strategies
Self-awareness
Conditional knowledge
Metacognitive
knowledge
Metacognitive
regulation
Self-regulation/ self-control
Planning
Monitoring
Evaluating
Source: Green - Emily R. Lai (2011); Simone R. D, & L. Salganik (2015)
Reflection/ self-reflection
(subject-specific)
Self-efficacy (subject-specific)
Relationship management
(GC) Task-initiation
Stress resistance
Goal-orientation
Adaptation Self-
responsibility
Organising Time
management
Metacognitive
reflection/ action
United States
Poland
Hong Kong-China
Brazil
New Zealand
Greece
Uruguay
United Kingdom
Estonia Finland
Albania
Croatia
Latvia
Slovak Republic Luxembourg
Germany
Lithuania
Austria
Czech Republic
Chinese Taipei
France
Thailand
Japan
Turkey Sweden
Hungary Australia
Israel
Canada
Ireland Bulgaria
Jordan
Chile
Macao-China
U.A.E.
Belgium
Netherlands
Spain
Argentina
Indonesia
Denmark
Kazakhstan
Peru
Costa Rica
Switzerland
Montenegro
Tunisia
Iceland
Slovenia
Qatar
Singapore
Portugal
Norway
Colombia
Malaysia
Mexico
Liechtenstein
Korea
Serbia
Russian Fed.
Romania
Viet Nam
Italy
Shanghai-China
R² = 0.36
300
350
400
450
500
550
600
650
-0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00 1.20
Me
an
ma
the
ma
tics
perf
orm
an
ce
Mean index of mathematics self-efficacy
OE
CD
ave
rag
e
Countries where students have stronger beliefs
in their abilities perform better in mathematics 55 Fig III.4.5
Perceived self-responsibility for failure
in mathematics
Percentage of students who reported "agree" or "strongly agree" with the following statements:
0 20 40 60 80 100
I’m not very good at solving mathematics problems
My teacher did not explain the concepts wellthis week
This week I made bad guesses on the quiz
Sometimes the course material is too hard
The teacher did not get students interested inthe material
Sometimes I am just unlucky
%
France Shanghai-China OECD average
Fig III.3.6 56
-20
-10
0
10
20
30
40
Colo
mb
iaC
osta
Ric
aP
eru
Isra
el
Luxe
mb
ou
rgC
hile
Tunis
iaS
lovak R
epu
blic
Lie
ch
tenste
inIt
aly
Kore
aS
pa
inA
rgen
tin
aB
razil
Port
ug
al
Gre
ece
Ja
pa
nA
ustr
iaU
rug
ua
yM
exic
oH
ong
Kon
g-C
hin
aB
ulg
aria
Tu
rke
yIn
do
ne
sia
Hu
ng
ary
Vie
t N
am
Un
ited
Sta
tes
Rom
ania
U.A
.E.
Ch
inese
Taip
ei
Cana
da
Irela
nd
Belg
ium
Kaza
kh
sta
nC
ze
ch R
ep
ub
licO
EC
D a
ve
rag
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roa
tia
Fra
nce
Sha
ngh
ai-
Ch
ina
Mo
nte
neg
roP
ola
nd
Serb
iaM
ala
ysia
Esto
nia
Qata
rM
aca
o-C
hin
aN
eth
erla
nds
Ne
w Z
eala
nd
Norw
ay
Lithu
ania
Slo
ven
iaD
enm
ark
Jo
rdan
Sw
itze
rla
nd
Austr
alia
Germ
any
Latv
iaR
ussia
n F
ed.
Sw
ede
nS
inga
po
reU
nited
Kin
gd
om
Thaila
nd
Fin
land
Icela
nd
Sc
ore
-po
int
dif
fere
nc
e (
bo
ys
-gir
ls)
Gender gap among the highest-achieving students (90th percentile)
Gender gap adjusted for differences in mathematics self-efficacy between boys and girls
Gender gap
Greater self-efficacy among girls could shrink the gender gap in mathematics
performance, particularly among the highest-performing students 57 Fig III.7.12
Boys do better
Girls do better
58
Making change happen
0 20 40 60 80 100
If I am more innovative in myteaching, I will be rewarded
Innovative practices will beconsidered in appraisal with high or
moderate importance
Average
Mean mathematics performance, by school location, after
accounting for socio-economic status Fig II.3.3 59 59 What do teachers say about innovation?
Percentage of lower secondary teachers
%
Students who use computers at school only
moderately score the highest in reading
450
460
470
480
490
500
510
520
-2 -1 0 1 2
Sc
or
e p
oin
ts
Index of ICT use at school
Source: Figure 6.5
Relationship between students’ skills in reading and computer use at school (average across OECD countries)
OECD average
Highest score
Digital reading
61 Mobilise innovation
Innovation
inspired by
science (15/1)
Innovation
inspired by
practitioners
Innovation
inspired by
users
Entrepreneurial
development of
new products
and services
62 Making change happen
Four
dimensions
Regrouping
educators
Regrouping
learners
Rescheduling
learning
Widening
pedagogic
repertoires
• To gain the benefits of collaborative planning, work, and shared professional development strategies
• To open up pedagogical options • To give extra attention to groups of
learners • To give learners a sense of belonging
& engagement • To mix students of different ages • To mix different abilities and strengths • To widen pedagogical options,
including peer teaching • To allow for deeper learning • To create flexibility for more
individual choices • To accelerate learning • To use out-of-school learning in
effective & innovative ways
• Inquiry, authentic learning, collaboration, and formative assessment
• A prominent place for student voice & agency
• Make costs and benefits of educational innovation as symmetric as possible – Everyone supports innovation
• (except for their own children)
– The benefits for ‘winners’ are often insufficient to mobilise support, the costs for ‘losers’ are concentrated
• That’s the power of interest groups
– Need for consistent, co-ordinated efforts to persuade those affected of the need for change and, in particular, to communicate the costs of inaction
Making change happen
• Given the uncertainties that accompany change, education stakeholders will always value the status quo.
• Successful innovations… – are good at communicating the need for change and building
support for change
– tend to invest in capacity development and change-management skills
– develop evidence and feed this back to institutions along with tools with which they can use the information
– Are backed by sustainable financing
• Teachers need to be active agents, not just in the implementation of innovations, but also in their design
Making change happen
What competencies are needed by students in 2030?
Internationally validated OECD 21st century curriculum framework
Curriculum guideline and reform
OECD Education 2030
Etc etc
Policy dialogue
Assessment framework
Making change
happen in
education systems
Average school systems High performers in PISA
Some students learn at high levels
All students learn at high levels
Uniformity Embracing diversity
Curriculum-centred Learner-centred
Learning a place Learning an activity
Prescription Informed profession
Delivered wisdom User-generated wisdom
Provision Outcomes
Bureaucratic look-up Devolved – look outwards
Administrative control and accountability
Professional forms of work organisation
Conformity Ingenious
Standardise distribution of resources
Attract the most talented teachers to the most challenging classrooms
Management Leadership
Public vs private Public with private
Idiosyncratic reforms Alignment of policies, coherence over time, fidelity of implementation
67
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