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PISA: Assessing 21st century life skills
Jakarta, 8 July 2019
Andreas Schleicher
Increased likelihood of positive outcomes
among adults with higher literacy skills (age 16-65)
1.0
1.5
2.0
2.5
3.0
Being Employed High wages Good to excellent
health
Participation in
volunteer activities
High levels of
political efficacy
High levels oftrust
(scoring at Level 4/5 on PIAAC compared with those scoring at Level 1 or below)
Odds ratio
PISA in brief - 2015
In 2015, over half a million students…
- representing 28 million 15-year-olds in 72 countries/economies
… took an internationally agreed 2-hour test…
- Goes beyond testing whether students can reproduce what they were taught…
… to assess students’ capacity to extrapolate from what they know and creatively apply
their knowledge in novel situations
- Total of 390 minutes of assessment material
… and responded to questions on…
- their personal background, their schools, their well-being and their motivation
Parents, principals, teachers and system leaders provided data on:
- school policies, practices, resources and institutional factors that help explain
performance differences
- 89,000 parents, 93,000 teachers and 17,500 principals responded
Map of PISA countries and economies
PISA 2015
OECD
Partners
PISA in brief – key principles
• ‘Crowd sourcing’ and collaboration
- PISA draws together leading expertise and institutions from participating countries to
develop instruments and methodologies…
… guided by governments on the basis of shared policy interests
• Cross-national relevance and transferability of policy experiences
- Emphasis on validity across cultures, languages and systems
- Frameworks built on well-structured conceptual understanding of academic disciplines
and contextual factors
• Triangulation across different stakeholder perspectives
- Comprehensive insights from students, parents, school principals and system-leaders
• Advanced methods with different grain sizes
- A range of methods to adequately measure what young people know and can do:
different grain sizes to serve different decision-making needs
- Productive feedback to fuel improvement at every level of the system
“the ability to engage with science-
related issues, and with the ideas of
science, as a reflective citizen”
A scientifically literate person is
willing to engage in reasoned discourse
about science and technology
Science in PISA
•Explain phenomena scientifically
•Evaluate and design scientific enquiry
•Interpret data and evidence scientifically
Competencies
Recognise, offer and
evaluate explanations for
a range of natural and
technological phenomena.
Describe and appraise
scientific investigations
and propose ways of
addressing questions
scientifically.
Analyse and evaluate
data, claims and
arguments in a variety of
representations and draw
appropriate scientific
conclusions.
•Explain phenomena scientifically
•Evaluate and design scientific enquiry
•Interpret data and evidence scientifically
Knowledge
•Content knowledge
•Knowledge of methodological
procedures used in science
•Knowledge of the epistemic
reasons and ideas used by
scientists to justify their claims
Competencies
Each of the scientific
competencies requires
content knowledge
(knowledge of theories,
explanatory ideas,
information and facts), but
also an understanding of
how such knowledge has
been derived (procedural
knowledge) and of the
nature of that knowledge
(epistemic knowledge)
“Epistemic knowledge”
reflects students’ capacity to
think like a scientist and
distinguish between
observations, facts,
hypotheses, models and
theories
•Explain phenomena scientifically
•Evaluate and design scientific enquiry
•Interpret data and evidence scientifically
Knowledge
•Content knowledge
•Knowledge of methodological
procedures used in science
•Knowledge of the epistemic
reasons and ideas used by
scientists to justify their claims
Competencies
Peoples’ attitudes and
beliefs play a significant role
in their interest, attention
and response to science
and technology.
PISA distinguishes between
attitudes towards science
(e.g. interest in different
content areas of science)
and scientific attitudes (e.g.
whether students value
scientific approaches to
enquiry)Attitudes
•Attitudes to science
•Scientific attitudes
Trends in science performance (PISA)
2006 2009 2012 2015
OECD
450
470
490
510
530
550
570
OECD average
Studentperformance
Trends in science performance (PISA)
450
470
490
510
530
550
570
2006 2009 2012 2015
OECD average
0%
10%
20%
30%
40%
50%
60%
70%
80%
300
325
350
375
400
425
450
475
500
2000 2003 2006 2009 2012 2015
Coverage
Reading Score
Math Score
Reading Score (39%
covered in PISA 2000)
Math Score (39%
covered in PISA 2000)
PISA outcomes and coverage in Indonesia
Routine cognitive skills Complex ways of thinking,
complex ways of doing, collective capacity
Some students learn at high levels (sorting) All students need to learn at high levels
Student inclusion
Curriculum, instruction and assessment
Standardisation and compliance High-level professional knowledge workers
Teacher education
‘Tayloristic’, hierarchical Flat, collegial
Work organisation
Primarily to authorities Primarily to peers and stakeholders
Accountability
Past Future
Lessons from high-performers
Some learn at high levels
All learn at high levels
60
40
20
0
20
40
60
80
Singapore4
Finland3
Japan5
Estonia7
Ireland4
Macao(China)12
HongKong(China)11
Germany4
Slovenia7
Korea8
Switzerland4
Russia5
Netherlands5
CABA(Argentina)0
Poland9
Denmark11
Australia9
ChineseTaipei15
Belgium7
NewZealand10
Canada16
Spain9
Norway9
CzechRepublic6
Latvia11
Sweden6
Portugal12
France9
OECDaverage11
Iceland7
UnitedKingdom16
Croatia9
Lithuania10
UnitedStates16
Hungary10
Austria17
Malta2
Luxembourg12
Israel6
SlovakRepublic11
Italy20
Greece9
Romania7
Moldova7
B-S-J-G(China)36
UnitedArabEmirates9
Chile20
Bulgaria19
Albania16
Qatar7
VietNam51
Montenegro10
Jordan14
Uruguay28
TrinidadandTobago24
Turkey30
Georgia21
Colombia25
Thailand29
FYROM5
CostaRica37
Mexico38
Tunisia7
Peru26
Brazil29
Indonesia32
Lebanon34
Algeria21
Kosovo29
DominicanRepublic32
Level 6 Level 5
Level 4 Level 3
Level 2 Below Level 1b
Level 1b Level 1a
Student performance (PISA, Science, 15-year-olds, 2015)
%
Percentage of 15-year-olds not covered by the PISA sample
60
40
20
0
20
40
60
80
Singapore4
Finland3
Japan5
Estonia7
Ireland4
Macao(China)12
HongKong(China)11
Germany4
Slovenia7
Korea8
Switzerland4
Russia5
Netherlands5
CABA(Argentina)0
Poland9
Denmark11
Australia9
ChineseTaipei15
Belgium7
NewZealand10
Canada16
Spain9
Norway9
CzechRepublic6
Latvia11
Sweden6
Portugal12
France9
OECDaverage11
Iceland7
UnitedKingdom16
Croatia9
Lithuania10
UnitedStates16
Hungary10
Austria17
Malta2
Luxembourg12
Israel6
SlovakRepublic11
Italy20
Greece9
Romania7
Moldova7
B-S-J-G(China)36
UnitedArabEmirates9
Chile20
Bulgaria19
Albania16
Qatar7
VietNam51
Montenegro10
Jordan14
Uruguay28
TrinidadandTobago24
Turkey30
Georgia21
Colombia25
Thailand29
FYROM5
CostaRica37
Mexico38
Tunisia7
Peru26
Brazil29
Indonesia32
Lebanon34
Algeria21
Kosovo29
DominicanRepublic32
Level 6 Level 5
Level 4 Level 3
Level 2 Below Level 1b
Level 1b Level 1a
Student performance (PISA, Science, 15-year-olds, 2015)
%
Percentage of 15-year-olds not covered by the PISA sample
%
551% GDP
12,448 bn$
153% GDP
27,929 bn$
86% GDP
402 bn$
Long-term estimated economic gains from
every 15-year-old achieving at least basic skills
889% GDP2
24,409 bn$
Low math performance
High math performance
Mathematics performance
of the 10% most disadvantaged
American 15-year-olds (~Mexico)
Mathematics performance
of the 10% most privileged
American 15-year-olds (~Japan)
Poverty need not be destiny:
PISA math performance by decile of social background (2012)
PISAmathematicsperformance
200
300
400
500
600
700
-3 -2 -1 0 1 2 3
PISA index of economic, social and cultural status
Public schools
Private schools
Below
1b
Level
1b
Level
1a
Level
2
Level
3
Level
4
Level
5
Lev
6
Brazil: School performance and schools’ socio-economic profile
Scorepoints
200
300
400
500
600
700
-3 -2 -1 0 1 2 3
PISA index of economic, social and cultural status
Public schools
Private schools
Below
1b
Level
1b
Level
1a
Level
2
Level
3
Level
4
Level
5
Lev
6
Scorepoints
Viet Nam: School performance and schools’ socio-economic profile
200
300
400
500
600
700
-3 -2 -1 0 1 2 3
PISA index of economic, social and cultural status
Public schools
Private schools
Below
1b
Level
1b
Level
1a
Level
2
Level
3
Level
4
Level
5
Lev
6
Brazil: School performance and schools’ socio-economic profile
Scorepoints
200
300
400
500
600
700
-3 -2 -1 0 1 2 3
PISA index of economic, social and cultural status
Public schools
Private schools
Below
1b
Level
1b
Level
1a
Level
2
Level
3
Level
4
Level
5
Lev
6
Relationship between
student performance
and students' socio-
economic status
Relationship between
student performance
and students' socio-
economic status
between schools
Relationship between
student performance
and students' socio-
economic status
within schools
Relationship between school performance and schools’ socio-economic profile:
Indonesia
Scorepoints
Aligning resources with needs
Average class size in <9th grade>, by quarter of school socio-economic profile
22
23
24
25
26
27
28
Highly disadvantaged Disadvantaged Advantaged Highly advantaged
OECD average
Averageclasssize
Schools by social background
%scienceteacherswithoutuniversitymajorinscience
Science teachers without a university major in science, by school socio-economic profile (OECD Average)
0
5
10
15
20
25
30
35
Highly disadvantaged Disadvantaged Advantaged Highly advantaged
OECD average
Aligning resources with needs
Schools by social background
Differences in educational resources
between advantaged and disadvantaged schools
Figure I.6.14
-3
-2
-2
-1
-1
0
1
1
CABA(Argentina)
Mexico
Peru
Macao(China)
UnitedArabEmirates
Lebanon
Jordan
Colombia
Brazil
Indonesia
Turkey
Spain
DominicanRepublic
Georgia
Uruguay
Thailand
B-S-J-G(China)
Australia
Japan
Chile
Luxembourg
Russia
Portugal
Malta
Italy
NewZealand
Croatia
Ireland
Algeria
Norway
Israel
Denmark
Sweden
UnitedStates
Moldova
Belgium
Slovenia
OECDaverage
Hungary
ChineseTaipei
VietNam
CzechRepublic
Singapore
Tunisia
Greece
TrinidadandTobago
Canada
Romania
Qatar
Montenegro
Kosovo
Netherlands
Korea
Finland
Switzerland
Germany
HongKong(China)
Austria
FYROM
Poland
Albania
Bulgaria
SlovakRepublic
Lithuania
Estonia
Iceland
CostaRica
UnitedKingdom
Latvia
Meanindexdifferencebetweenadvantaged
anddisadvantagedschools
Index of shortage of educational material Index of shortage of educational staff
Disadvantaged schools have more
resources than advantaged schools
Disadvantaged schools have fewer
resources than advantaged schools
Reproducing knowledge
Creating knowledge
Think for yourself and work with others
The rise of the global middle class
0
1
2
3
4
5
6
7
8
9
0
10
20
30
40
50
60
70
80
90
100
1951
1957
1963
1969
1975
1981
1987
1993
1999
2005
2011
2017
2023
2029
Headcount(billions)
%ofworldpopulation
World middle class share of world population
World middle class
World population
Within the next decade the majority of the world population will consist of the middle class
Estimates of the size of the global middle class, percentage of the world population (left axis) and headcount (right axis)
Source: Kharas, H. (2017), The unprecedented expansion of the global middle class, an update,
https://www.brookings.edu/wp-content/uploads/2017/02/global_20170228_global-middle-class.pdf. Kharas, H.
(2010), The emerging middle class in developing countries, https://www.oecd.org/dev/44457738.pdf. Figure 1.2
Growing unequal
Income gaps continues to grow
Trends in real household incomes by percentile, OECD average, 1985-2015
1
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1985
1990
1995
2000
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Bottom 10% Mean Median Top 10%
Source: OECD (2018), A Broken Social Elevator? How to Promote Social Mobility,
https://doi.org/10.1787/9789264301085-en.
Figure 2.1
Index 1985 = 1
Rising volatility
Household savings and debt
Household savings (% of disposable income, left axis) and household debt (% of disposable income, right axis),
OECD average, 1970-2016
Source: OECD (2018), OECD National Accounts Statistics (database), https://stats.oecd.org/.
0
20
40
60
80
100
120
140
160
0
2
4
6
8
10
12
14
16
18
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
Debtas%ofdisposableincome
Savingsas%ofdisposableincome
Savings (left axis) Debt (right axis)
Figure 3.9
The growth in AI technologies…
0
2 000
4 000
6 000
8 000
10 000
12 000
14 000
16 000
18 000
20 000
1991 1994 1997 2000 2003 2006 2009 2012 2015
Numberofpatents
Number of patents in artificial intelligence technologies, 1991-2015
Source: OECD (2017), OECD Science, Technology and Industry Scoreboard 2017: The digital transformation, ht
tp://dx.doi.org/10.1787/9789264268821-en.
Figure 1.10
…pushes us to think harder about what makes us truly human
32
Digitalisation
Democratizing
Concentrating
Particularizing
Homogenizing
Empowering
Disempowering
0
10
20
30
40
50
60
70
80
90
ChineseTaipei-2
Sweden-9
France-5
Portugal
Greece
Singapore-2
Thailand
Macao(China)-7
Brazil-2
Spain
UnitedKingdom
Bulgaria
HongKong(China)
Korea-7
Belgium-4
Denmark-4
Croatia-5
Israel-10
NewZealand-4
Netherlands-3
Uruguay
Hungary4
Australia
OECDaverage-3
DominicanRepublic
Ireland-7
Poland-3
CostaRica3
Lithuania
Japan-5
Mexico
Russia-8
CzechRepublic
Italy
Peru
Colombia4
Finland-6
Chile
Latvia
SlovakRepublic
B-S-J-G(China)11
Switzerland
Austria-3
Luxembourg
Iceland
Germany
Estonia
Slovenia
%
Boys Girls
15-year-olds feeling bad if not connected to the Internet (PISA)
34
Digitalisation
Democratizing
Concentrating
Particularizing
Homogenizing
Empowering
Disempowering
The post-truth world where reality becomes fungible
• Virality seems privileged over quality
in the distribution of information
• Truth and fact are losing currency
Scarcity of attention and abundance of information
• Algorithms sort us into groups of like-minded
individuals create echo chambers that amplify our
views, leave us uninformed of opposing arguments,
and polarise our societies
Creating new value connotes
processes of creating, making,
bringing into being and formulating;
and outcomes that are innovative,
fresh and original, contributing
something of intrinsic positive worth.
The constructs that underpin the
competence are creativity/ creative
thinking/ inventive thinking, curiosity,
global mind-set, …
.
In a structurally imbalanced world,
the imperative of reconciling diverse
perspectives and interests, in local
settings with sometimes global
implications, will require young
people to become adept in handling
tensions, dilemmas and trade-offs.
Underlying constructs are empathy,
resilience/stress resistance
trust, …
Dealing with novelty, change,
diversity and ambiguity assumes that
individuals can think for themselves
and work with others. This suggests
a sense of responsibility, and moral
and intellectual maturity, with which
a person can reflect upon and
evaluate their actions in the light of
their experiences and personal and
societal goals; what they have been
taught and told; and what is right or
wrong
Underlying constructs include critical
thinking skills, meta-learning skills
(including learning to learn skills),
mindfulness, problem solving skills,
responsibility, …
Anticipation mobilises
cognitive skills, such as
analytical or critical thinking,
to foresee what may be
needed in the future or how
actions taken today might
have consequences for the
future
Reflective practice is the
ability to take a critical stance
when deciding, choosing and
acting, by stepping back from
what is known or assumed
and looking at a situation
from other, different
perspectives
Both reflective practice and
anticipation contribute to the
willingness to take responsible
actions
0
10
20
30
40
50
60
70
80
CriticalThinking
Com
m
unication
Problem
Solving
Cooperation/CollaborationRespect
Self-Regulation
Persistence/ResilienceEm
pathy
CreativeThinking
ConflictResolution
Responsibility
StudentAgency
ReflectionAction
Anticipation
GlobalCom
petency
DigitalLiteracy
LiteracyforSD
Com
putationalThinking
Entrepreneurship
Arts Humanities Mathematics National Language/s PE/Health Science Technologies
Numberofmappedcontentitems
Skills, Attitudes and Values Key concepts
2030 Learning
Framework
Competency
Development
Cycle
Compound
competencies
for 2030
Current curricula and 2030 aspirations
Preliminary findings of curriculum content mapping (lower secondary; Ontario, Canada)
Current curricula and 2030 aspirations
Preliminary findings of curriculum content mapping (lower secondary; Japan)
0
20
40
60
80
100
120
140
160
CriticalThinking
Com
m
unication
Problem
Solving
Cooperation/CollaborationRespect
Self-Regulation
Persistence/ResilienceEm
pathy
CreativeThinking
ConflictResolution
Responsibility
StudentAgency
ReflectionAction
Anticipation
GlobalCom
petency
DigitalLiteracy
LiteracyforSD
Com
putationalThinking
Entrepreneurship
Arts Humanities Mathematics National Language/s PE/Health Science Technologies
Numberofmappedcontentitems
Skills, Attitudes and Values Key
concepts
2030
Learning
Framewo
rk
Competency
Development
Cycle
Compound
competencies
for 2030
The kind of things that are
easy to teach are now easy
to automate, digitize or
outsource
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
What teachers say
and what teachers do
96% of teachers: My role as a teacher
is to facilitate students own inquiry
86%: Students learn best
by findings solutions on their own
74%: Thinking and reasoning is more
important than curriculum content
-2.00 -1.50 -1.00 -0.50 0.00
Prevalence of memorisation
rehearsal, routine exercises, drill and
practice and/or repetition
0.00 0.50 1.00 1.50 2.00
Switzerland
Poland
Germany
Japan
Korea
France
Sweden
Shanghai-China
Canada
Singapore
United States
Norway
Spain
Netherlands
United Kingdom
Prevalence of elaboration
reasoning, deep learning, intrinsic
motivation, critical thinking,
creativity, non-routine problems
High Low Low High
Memorisation is less useful as problems become more
difficult (OECD average)
R² = 0.81
0.70
1.00
300 400 500 600 700 800
Complexity of of mathematics tasks on the PISA scale
Source: Figure 4.3
47
Difficult problem
Easy problem
Greater
success
Less
success
Odds ratio
Elaboration strategies are more useful as problems
become more difficult (OECD average)
R² = 0.82
0.80
1.50
300 400 500 600 700 800
Complexity of mathematics tasks on the PISA scaleSource: Figure 6.2
48
Difficult
problem
Greater
success
Less
success
Easy problem
Odds ratio
Students’ use of elaboration strategies
Source: Figure 6.1
UnitedKingdom20
Iceland18
Australia20
Ireland23
France19
NewZealand19
Israel26
Canada26
Austria32
Japan29
Belgium22
Singapore31
Uruguay22
Germany33
Netherlands24
HK-China30
Luxembourg33
CostaRica33
Norway23
Finland23
UnitedStates30
Portugal29
OECDaverage30
Denmark23
Indonesia38
Switzerland32
Bulgaria27
Macao-China32
Chile24
Albania33
Sweden24
Kazakhstan29
Greece35
UAE32
Hungary37
Brazil25
Argentina35
Liechtenstein41
Estonia38
Mexico27
Spain39
Turkey28
Shanghai-China35
Poland27
Colombia33
Korea43
Latvia32
CzechRepublic40
VietNam41
Croatia48
Slovenia56
Romania36
RussianFed.41
Montenegro39
Malaysia38
Peru30
Italy46
Serbia50
SlovakRepublic40
Lithuania30
Thailand34
Qatar34
ChineseTaipei42
Jordan44
Tunisia44
Belowthe OECD average At the same level as the OECD average Above the OECD average
% of students who
understand new
concepts by relating
them to things they
already know
49
Elaboration
More
Less
Selected skills
• SSES: 19 skills
selected for the initial
testing
• SSES: 15 skills will be
included in the main
study
• PISA 2021: possible
skills for inclusion:
– Self-control
– Persistence
– Curiosity
– Perspective taking
– Empathy
– Trust
– Emotional control
– Resilience
SOCIABILITY
CURIOSITY
EMPATHY
ACHIEVEMENT
MOTIVATION
STRESSRESISTANCE
RESPONSIBILITY
SELF-CONTROL
OPTIMISMEMOTIONAL
CONTROL
TRUST
TOLERANCE
ASSERTIVENESS
CRITICAL THINKING
CO-OPERATION
META-COGNITION
SELF-EFFICACY
PERSISTENCE
ENERGY
CREATIVITY
EMOTIONAL	
REGULATION
TASK	
PERFORMANCE
THE	
‘BIG	FIVE’	
DOMAINS
ENGAGING	
WITH	OTHERS
COMPOUND	
SKILLS COLLABORATION
OPEN-
MINDEDNESS
STRONGEST RELATIONS WITH GRADES IN MATH
-0.2
-0.1
0
0.1
0.2
0.3
0.4
Persistence Curiosity Self-efficacy Optimism
Correlation
Math
STRONGEST RELATIONS WITH GRADES IN ART
0
0.1
0.2
Creativity Persistence Self-control
Correlation
Art
RELATIONSHIP WITH CHILD’S HEALTH
0
5
10
15
20
25
30
Socio-demographics Parent education Income SE skills
%ofexplainedvariance
General health
RELATIONSHIP OF SE SKILLS WITH HEALTH-
RELATED BEHAVIOURS
§ Best predictors: Self-control, Optimism
0
1
2
3
4
5
6
7
8
Socio-demographics Parent education Income SE skills
%ofexplainedvariance
Sleep 8 hours or more
Some lessons from high performers
• Rigor, focus and coherence
• Remain true to the disciplines
– but aim at interdisciplinary learning and the capacity of students to see
problems through multiple lenses
– Balance knowledge of disciplines and knowledge about disciplines
• Focus on areas with the highest transfer value
– Requiring a theory of action for how this transfer value occurs
• Authenticity
– Thematic, problem-based, project-based, co-creation in conversation
• Some things are caught not taught
– Immersive learning propositions
Prescription
Ownership of professional practice
Powerful learning environments are constantly creating synergies and
finding new ways to enhance professional, social and cultural capital with
others. They do that with families and communities, with higher education,
with other schools and learning environments, and with businesses.
Learning time and science performance (PISA)
Figure II.6.23
6
7
8
9
10
11
12
13
14
15
16
0
10
20
30
40
50
60
70
Finland
Germany
Switzerland
Japan
Estonia
Sweden
Netherlands
NewZealand
Australia
CzechRepublic
Macao(China)
UnitedKingdom
Canada
Belgium
France
Norway
Slovenia
Iceland
Luxembourg
Ireland
Latvia
HongKong(China)
OECDaverage
ChineseTaipei
Austria
Portugal
Uruguay
Lithuania
Singapore
Denmark
Hungary
Poland
SlovakRepublic
Spain
Croatia
UnitedStates
Israel
Bulgaria
Korea
Russia
Italy
Greece
B-S-J-G(China)
Colombia
Chile
Mexico
Brazil
CostaRica
Turkey
Montenegro
Peru
Qatar
Thailand
UnitedArabEmirates
Tunisia
DominicanRepublic
Scorepointsinscienceperhouroflearningtime
Hours Intended learning time at school (hours) Study time after school (hours) Score points in science per hour of total learning time
Time in school
Learning out of school
Productivity
Making teaching not just financially,
but intellectually more attractive
Public confidence in profession and professionals
Professional preparation and learning
Collective ownership of professional practice
Decisions made in accordance with the body of knowledge o the profession
Professional responsibility in the name of the profession and accountability towards the profession
Policy levers to teacher professionalism
Knowledge base for teaching
(initial education and incentives for
professional development)
Autonomy: Teachers’ decision-
making power over their work
(teaching content, course offerings,
discipline practices)
Peer networks: Opportunities for
exchange and support needed
to maintain high standards of
teaching (participation in induction,
mentoring, networks, feedback from direct
observations)
Teacher
professionalism
Policy levers to teacher professionalism
Teacher professional collaboration
0
10
20
30
40
50
60
70
80
90
100
Discussindividualstudents
Shareresources
Teamconferences
Collaborateforcommon
standards
Teamteaching
CollaborativePD
Jointactivities
Classroomobservations
Percentageofteachers
Professional collaboration
Percentage of lower secondary teachers who report doing the following activities at least once per month
Exchange and co-ordination
(OECD countries)
11.40
11.60
11.80
12.00
12.20
12.40
12.60
12.80
13.00
13.20
13.40
Never
Onceayearorless
2-4timesayear
5-10timesayear
1-3timesamonth
Onceaweekormore
Teacherself-efficacy(level)
Teach jointly as a team in
the same class
Observe other teachers’
classes and provide
feedback
Engage in joint activities
across different classes
Take part in collaborative
professional learning
Less
frequently
More
frequently
Teachers’ self-efficacy and professional collaboration
Student-teacher ratios and class size
Figure II.6.14
CABA (Argentina)
Jordan
Viet Nam
Poland
United States
Chile
Denmark
Hungary
B-S-G-J
(China)
Turkey
Georgia
Chinese
Taipei
Mexico
Russia
Albania
Hong Kong
(China)
Japan
Belgium
Algeria
Colombia
Peru
Macao
(China)
Switzerland
Malta
Dominican Republic
Netherlands
Singapore
Brazil
Kosovo
Finland
Thailand
R² = 0.25
5
10
15
20
25
30
15 20 25 30 35 40 45 50
Student-teacherratio
Class size in language of instruction
High student-teacher ratios
and small class sizes
Low student-teacher ratios
and large class sizes
OECD
average
OECDaverage
Teachers’ job satisfaction and class size
10.00
10.50
11.00
11.50
12.00
12.50
13.00
15 or less 16-20 21-25 26-30 31-35 36 or more
Teachers'jobsatisfaction(level)
Class size (number of students)
0
10
20
30
40
50
60
70
Low professionalism
High professionalism
Fig II.3.3
Perceptions of
teachers’ status
Satisfaction with
the profession
Satisfaction with the
work environment
Teachers’
self-efficacy
Teacher job satisfaction and professionalism
Teachers perception of the value of teaching
0
10
20
30
40
50
60
70
80
90
100
Singapore
Korea
Finland
Alberta
(Canada)
Flanders
(Belgium)
Shanghai
(China)
NewZealand
Russia
Netherlands
Australia
England(UK)
UnitedStates
Average
Norway
Japan
Latvia
Denmark
Poland
Iceland
Estonia
Czech
Republic
Portugal
Sweden
France
Percentageofteachers
Fig II.3.3
Percentage of lower secondary teachers who "agree" or "strongly agree" that teaching profession is a valued profession in society
Australia
Brazil
Bulgaria
Chile
Croatia
Czech Republic
Denmark
Estonia Finland
France
Iceland
IsraelItaly
Japan
Korea
Latvia
Mexico
Netherlands
Norway
Poland
Portugal
Romania
Serbia
Singapore
Slovak Republic
SpainSweden
Alberta (Canada)
England (United Kingdom)
Flanders (Belgium)
United States
0
5
10
15
20
25
30
35
40
45
0 10 20 30 40 50 60 70 80
Shareofmathematicstopperformers
Percentage of teachers who agree that teaching is valued in society
Countries where teachers believe their profession is valued
show higher levels of excellence in learning outcomes (PISA)
6
7
Relationship between lower secondary teachers' views on the value of their profession in society and the country’s
share of top mathematics performers in PISA 2012
Standardisation and Conformity
Standardisation and compliance lead students to be e
ducated in batches of age, following the same standar
d curriculum, all assessed at the same time.
Ingenious
Building instruction from student passions and capacities,
helping students personalise their learning and assessme
nt in ways that foster engagement and talents.
%
Yes
No
If I am more innovative in my teaching
I will be rewarded (country average)
Ideosyncratic policy
Alignment of policies
• Balancing breadth and depth of framework coverage
– Core assessments in reading, math and science every three years
• With focus (increased sample) rotating
– One innovative assessment area every three years
• Digital literacy (2009)
• Individual problem-solving (2012)
• Collaborative problem-solving (2015)
• Global competency (2018)
• Creative thinking (2021)
– Matrix sampling with adaptive assessment instruments
Design choices and trade-offs
47th meeting of the PISA Governing Board
Individual enablers
Forms of engagementSocial Enablers
Domain
readiness
Goal
orientation
& beliefs
Openness
Cognitive
skills &
approaches
Motivation
Collaboration
with others
Creative
expression
Knowledge
creation
Innovative
solutions to
problems
Cultural
norms &
expectations
Classroom
climate
Educational
approaches
Creative thinking in the classroom
47th meeting of the PISA Governing Board
Individual enablers
Forms of engagementSocial Enablers
Domain
readiness
Goal
orientation
& beliefs
Openness
Cognitive
skills &
approaches
Motivation
Collaboration
with others
Creative
expression
Knowledge
creation
Innovative
solutions to
problems
Cultural
norms &
expectations
Classroom
climate
Educational
approaches
Creative thinking in the classroom
47th meeting of the PISA Governing Board
Competency model for PISA CT
Generate
Creative
Ideas
Evaluate
and Improve Ideas
Generate
Diverse
Ideas
Focuses on students’ capacities to
think flexibly across domains: for
example, providing different
solutions for a problem, writing
different story ideas, or creating
different ways to visually represent
an idea.
47th meeting of the PISA Governing Board
Competency model for PISA CT
Generate
Creative
Ideas
Evaluate
and Improve Ideas
Generate
Diverse
Ideas
focuses on students’ capacities to
search for original ideas across
domains: for example, an original
story idea, an original way to
communicate an idea in visual form,
or an original solution to a social or
scientific problem.
47th meeting of the PISA Governing Board
Competency model for PISA CT
Generate
Creative
Ideas
Evaluate
and Improve Ideas
Generate
Diverse
Ideas
focuses on students’ capacities to
evaluate limitations in given ideas
and find original ways to improve
them
47th meeting of the PISA Governing Board
Competency model for PISA CT
Generate
Creative
Ideas
Evaluate
and Improve Ideas
Generate
Diverse
Ideas
Find out more about our work at www.oecd.org/pisa
– All publications
– The complete micro-level database
Email: Andreas.Schleicher@OECD.org
Twitter: SchleicherOECD
Wechat: AndreasSchleicher
Thank you

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Seminar On PISA

  • 1. PISA: Assessing 21st century life skills Jakarta, 8 July 2019 Andreas Schleicher
  • 2. Increased likelihood of positive outcomes among adults with higher literacy skills (age 16-65) 1.0 1.5 2.0 2.5 3.0 Being Employed High wages Good to excellent health Participation in volunteer activities High levels of political efficacy High levels oftrust (scoring at Level 4/5 on PIAAC compared with those scoring at Level 1 or below) Odds ratio
  • 3. PISA in brief - 2015 In 2015, over half a million students… - representing 28 million 15-year-olds in 72 countries/economies … took an internationally agreed 2-hour test… - Goes beyond testing whether students can reproduce what they were taught… … to assess students’ capacity to extrapolate from what they know and creatively apply their knowledge in novel situations - Total of 390 minutes of assessment material … and responded to questions on… - their personal background, their schools, their well-being and their motivation Parents, principals, teachers and system leaders provided data on: - school policies, practices, resources and institutional factors that help explain performance differences - 89,000 parents, 93,000 teachers and 17,500 principals responded
  • 4. Map of PISA countries and economies PISA 2015 OECD Partners
  • 5. PISA in brief – key principles • ‘Crowd sourcing’ and collaboration - PISA draws together leading expertise and institutions from participating countries to develop instruments and methodologies… … guided by governments on the basis of shared policy interests • Cross-national relevance and transferability of policy experiences - Emphasis on validity across cultures, languages and systems - Frameworks built on well-structured conceptual understanding of academic disciplines and contextual factors • Triangulation across different stakeholder perspectives - Comprehensive insights from students, parents, school principals and system-leaders • Advanced methods with different grain sizes - A range of methods to adequately measure what young people know and can do: different grain sizes to serve different decision-making needs - Productive feedback to fuel improvement at every level of the system
  • 6. “the ability to engage with science- related issues, and with the ideas of science, as a reflective citizen” A scientifically literate person is willing to engage in reasoned discourse about science and technology Science in PISA
  • 7. •Explain phenomena scientifically •Evaluate and design scientific enquiry •Interpret data and evidence scientifically Competencies Recognise, offer and evaluate explanations for a range of natural and technological phenomena. Describe and appraise scientific investigations and propose ways of addressing questions scientifically. Analyse and evaluate data, claims and arguments in a variety of representations and draw appropriate scientific conclusions.
  • 8. •Explain phenomena scientifically •Evaluate and design scientific enquiry •Interpret data and evidence scientifically Knowledge •Content knowledge •Knowledge of methodological procedures used in science •Knowledge of the epistemic reasons and ideas used by scientists to justify their claims Competencies Each of the scientific competencies requires content knowledge (knowledge of theories, explanatory ideas, information and facts), but also an understanding of how such knowledge has been derived (procedural knowledge) and of the nature of that knowledge (epistemic knowledge) “Epistemic knowledge” reflects students’ capacity to think like a scientist and distinguish between observations, facts, hypotheses, models and theories
  • 9. •Explain phenomena scientifically •Evaluate and design scientific enquiry •Interpret data and evidence scientifically Knowledge •Content knowledge •Knowledge of methodological procedures used in science •Knowledge of the epistemic reasons and ideas used by scientists to justify their claims Competencies Peoples’ attitudes and beliefs play a significant role in their interest, attention and response to science and technology. PISA distinguishes between attitudes towards science (e.g. interest in different content areas of science) and scientific attitudes (e.g. whether students value scientific approaches to enquiry)Attitudes •Attitudes to science •Scientific attitudes
  • 10. Trends in science performance (PISA) 2006 2009 2012 2015 OECD 450 470 490 510 530 550 570 OECD average Studentperformance
  • 11. Trends in science performance (PISA) 450 470 490 510 530 550 570 2006 2009 2012 2015 OECD average
  • 12. 0% 10% 20% 30% 40% 50% 60% 70% 80% 300 325 350 375 400 425 450 475 500 2000 2003 2006 2009 2012 2015 Coverage Reading Score Math Score Reading Score (39% covered in PISA 2000) Math Score (39% covered in PISA 2000) PISA outcomes and coverage in Indonesia
  • 13. Routine cognitive skills Complex ways of thinking, complex ways of doing, collective capacity Some students learn at high levels (sorting) All students need to learn at high levels Student inclusion Curriculum, instruction and assessment Standardisation and compliance High-level professional knowledge workers Teacher education ‘Tayloristic’, hierarchical Flat, collegial Work organisation Primarily to authorities Primarily to peers and stakeholders Accountability Past Future Lessons from high-performers
  • 14. Some learn at high levels
  • 15. All learn at high levels
  • 16. 60 40 20 0 20 40 60 80 Singapore4 Finland3 Japan5 Estonia7 Ireland4 Macao(China)12 HongKong(China)11 Germany4 Slovenia7 Korea8 Switzerland4 Russia5 Netherlands5 CABA(Argentina)0 Poland9 Denmark11 Australia9 ChineseTaipei15 Belgium7 NewZealand10 Canada16 Spain9 Norway9 CzechRepublic6 Latvia11 Sweden6 Portugal12 France9 OECDaverage11 Iceland7 UnitedKingdom16 Croatia9 Lithuania10 UnitedStates16 Hungary10 Austria17 Malta2 Luxembourg12 Israel6 SlovakRepublic11 Italy20 Greece9 Romania7 Moldova7 B-S-J-G(China)36 UnitedArabEmirates9 Chile20 Bulgaria19 Albania16 Qatar7 VietNam51 Montenegro10 Jordan14 Uruguay28 TrinidadandTobago24 Turkey30 Georgia21 Colombia25 Thailand29 FYROM5 CostaRica37 Mexico38 Tunisia7 Peru26 Brazil29 Indonesia32 Lebanon34 Algeria21 Kosovo29 DominicanRepublic32 Level 6 Level 5 Level 4 Level 3 Level 2 Below Level 1b Level 1b Level 1a Student performance (PISA, Science, 15-year-olds, 2015) % Percentage of 15-year-olds not covered by the PISA sample
  • 17. 60 40 20 0 20 40 60 80 Singapore4 Finland3 Japan5 Estonia7 Ireland4 Macao(China)12 HongKong(China)11 Germany4 Slovenia7 Korea8 Switzerland4 Russia5 Netherlands5 CABA(Argentina)0 Poland9 Denmark11 Australia9 ChineseTaipei15 Belgium7 NewZealand10 Canada16 Spain9 Norway9 CzechRepublic6 Latvia11 Sweden6 Portugal12 France9 OECDaverage11 Iceland7 UnitedKingdom16 Croatia9 Lithuania10 UnitedStates16 Hungary10 Austria17 Malta2 Luxembourg12 Israel6 SlovakRepublic11 Italy20 Greece9 Romania7 Moldova7 B-S-J-G(China)36 UnitedArabEmirates9 Chile20 Bulgaria19 Albania16 Qatar7 VietNam51 Montenegro10 Jordan14 Uruguay28 TrinidadandTobago24 Turkey30 Georgia21 Colombia25 Thailand29 FYROM5 CostaRica37 Mexico38 Tunisia7 Peru26 Brazil29 Indonesia32 Lebanon34 Algeria21 Kosovo29 DominicanRepublic32 Level 6 Level 5 Level 4 Level 3 Level 2 Below Level 1b Level 1b Level 1a Student performance (PISA, Science, 15-year-olds, 2015) % Percentage of 15-year-olds not covered by the PISA sample % 551% GDP 12,448 bn$ 153% GDP 27,929 bn$ 86% GDP 402 bn$ Long-term estimated economic gains from every 15-year-old achieving at least basic skills 889% GDP2 24,409 bn$
  • 18. Low math performance High math performance Mathematics performance of the 10% most disadvantaged American 15-year-olds (~Mexico) Mathematics performance of the 10% most privileged American 15-year-olds (~Japan) Poverty need not be destiny: PISA math performance by decile of social background (2012) PISAmathematicsperformance
  • 19. 200 300 400 500 600 700 -3 -2 -1 0 1 2 3 PISA index of economic, social and cultural status Public schools Private schools Below 1b Level 1b Level 1a Level 2 Level 3 Level 4 Level 5 Lev 6 Brazil: School performance and schools’ socio-economic profile Scorepoints
  • 20. 200 300 400 500 600 700 -3 -2 -1 0 1 2 3 PISA index of economic, social and cultural status Public schools Private schools Below 1b Level 1b Level 1a Level 2 Level 3 Level 4 Level 5 Lev 6 Scorepoints Viet Nam: School performance and schools’ socio-economic profile
  • 21. 200 300 400 500 600 700 -3 -2 -1 0 1 2 3 PISA index of economic, social and cultural status Public schools Private schools Below 1b Level 1b Level 1a Level 2 Level 3 Level 4 Level 5 Lev 6 Brazil: School performance and schools’ socio-economic profile Scorepoints
  • 22. 200 300 400 500 600 700 -3 -2 -1 0 1 2 3 PISA index of economic, social and cultural status Public schools Private schools Below 1b Level 1b Level 1a Level 2 Level 3 Level 4 Level 5 Lev 6 Relationship between student performance and students' socio- economic status Relationship between student performance and students' socio- economic status between schools Relationship between student performance and students' socio- economic status within schools Relationship between school performance and schools’ socio-economic profile: Indonesia Scorepoints
  • 23. Aligning resources with needs Average class size in <9th grade>, by quarter of school socio-economic profile 22 23 24 25 26 27 28 Highly disadvantaged Disadvantaged Advantaged Highly advantaged OECD average Averageclasssize Schools by social background
  • 24. %scienceteacherswithoutuniversitymajorinscience Science teachers without a university major in science, by school socio-economic profile (OECD Average) 0 5 10 15 20 25 30 35 Highly disadvantaged Disadvantaged Advantaged Highly advantaged OECD average Aligning resources with needs Schools by social background
  • 25. Differences in educational resources between advantaged and disadvantaged schools Figure I.6.14 -3 -2 -2 -1 -1 0 1 1 CABA(Argentina) Mexico Peru Macao(China) UnitedArabEmirates Lebanon Jordan Colombia Brazil Indonesia Turkey Spain DominicanRepublic Georgia Uruguay Thailand B-S-J-G(China) Australia Japan Chile Luxembourg Russia Portugal Malta Italy NewZealand Croatia Ireland Algeria Norway Israel Denmark Sweden UnitedStates Moldova Belgium Slovenia OECDaverage Hungary ChineseTaipei VietNam CzechRepublic Singapore Tunisia Greece TrinidadandTobago Canada Romania Qatar Montenegro Kosovo Netherlands Korea Finland Switzerland Germany HongKong(China) Austria FYROM Poland Albania Bulgaria SlovakRepublic Lithuania Estonia Iceland CostaRica UnitedKingdom Latvia Meanindexdifferencebetweenadvantaged anddisadvantagedschools Index of shortage of educational material Index of shortage of educational staff Disadvantaged schools have more resources than advantaged schools Disadvantaged schools have fewer resources than advantaged schools
  • 27. Creating knowledge Think for yourself and work with others
  • 28. The rise of the global middle class 0 1 2 3 4 5 6 7 8 9 0 10 20 30 40 50 60 70 80 90 100 1951 1957 1963 1969 1975 1981 1987 1993 1999 2005 2011 2017 2023 2029 Headcount(billions) %ofworldpopulation World middle class share of world population World middle class World population Within the next decade the majority of the world population will consist of the middle class Estimates of the size of the global middle class, percentage of the world population (left axis) and headcount (right axis) Source: Kharas, H. (2017), The unprecedented expansion of the global middle class, an update, https://www.brookings.edu/wp-content/uploads/2017/02/global_20170228_global-middle-class.pdf. Kharas, H. (2010), The emerging middle class in developing countries, https://www.oecd.org/dev/44457738.pdf. Figure 1.2
  • 29. Growing unequal Income gaps continues to grow Trends in real household incomes by percentile, OECD average, 1985-2015 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1985 1990 1995 2000 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Bottom 10% Mean Median Top 10% Source: OECD (2018), A Broken Social Elevator? How to Promote Social Mobility, https://doi.org/10.1787/9789264301085-en. Figure 2.1 Index 1985 = 1
  • 30. Rising volatility Household savings and debt Household savings (% of disposable income, left axis) and household debt (% of disposable income, right axis), OECD average, 1970-2016 Source: OECD (2018), OECD National Accounts Statistics (database), https://stats.oecd.org/. 0 20 40 60 80 100 120 140 160 0 2 4 6 8 10 12 14 16 18 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 Debtas%ofdisposableincome Savingsas%ofdisposableincome Savings (left axis) Debt (right axis) Figure 3.9
  • 31. The growth in AI technologies… 0 2 000 4 000 6 000 8 000 10 000 12 000 14 000 16 000 18 000 20 000 1991 1994 1997 2000 2003 2006 2009 2012 2015 Numberofpatents Number of patents in artificial intelligence technologies, 1991-2015 Source: OECD (2017), OECD Science, Technology and Industry Scoreboard 2017: The digital transformation, ht tp://dx.doi.org/10.1787/9789264268821-en. Figure 1.10 …pushes us to think harder about what makes us truly human
  • 34. 34 Digitalisation Democratizing Concentrating Particularizing Homogenizing Empowering Disempowering The post-truth world where reality becomes fungible • Virality seems privileged over quality in the distribution of information • Truth and fact are losing currency Scarcity of attention and abundance of information • Algorithms sort us into groups of like-minded individuals create echo chambers that amplify our views, leave us uninformed of opposing arguments, and polarise our societies
  • 35.
  • 36.
  • 37. Creating new value connotes processes of creating, making, bringing into being and formulating; and outcomes that are innovative, fresh and original, contributing something of intrinsic positive worth. The constructs that underpin the competence are creativity/ creative thinking/ inventive thinking, curiosity, global mind-set, … . In a structurally imbalanced world, the imperative of reconciling diverse perspectives and interests, in local settings with sometimes global implications, will require young people to become adept in handling tensions, dilemmas and trade-offs. Underlying constructs are empathy, resilience/stress resistance trust, … Dealing with novelty, change, diversity and ambiguity assumes that individuals can think for themselves and work with others. This suggests a sense of responsibility, and moral and intellectual maturity, with which a person can reflect upon and evaluate their actions in the light of their experiences and personal and societal goals; what they have been taught and told; and what is right or wrong Underlying constructs include critical thinking skills, meta-learning skills (including learning to learn skills), mindfulness, problem solving skills, responsibility, …
  • 38. Anticipation mobilises cognitive skills, such as analytical or critical thinking, to foresee what may be needed in the future or how actions taken today might have consequences for the future Reflective practice is the ability to take a critical stance when deciding, choosing and acting, by stepping back from what is known or assumed and looking at a situation from other, different perspectives Both reflective practice and anticipation contribute to the willingness to take responsible actions
  • 39. 0 10 20 30 40 50 60 70 80 CriticalThinking Com m unication Problem Solving Cooperation/CollaborationRespect Self-Regulation Persistence/ResilienceEm pathy CreativeThinking ConflictResolution Responsibility StudentAgency ReflectionAction Anticipation GlobalCom petency DigitalLiteracy LiteracyforSD Com putationalThinking Entrepreneurship Arts Humanities Mathematics National Language/s PE/Health Science Technologies Numberofmappedcontentitems Skills, Attitudes and Values Key concepts 2030 Learning Framework Competency Development Cycle Compound competencies for 2030 Current curricula and 2030 aspirations Preliminary findings of curriculum content mapping (lower secondary; Ontario, Canada)
  • 40. Current curricula and 2030 aspirations Preliminary findings of curriculum content mapping (lower secondary; Japan) 0 20 40 60 80 100 120 140 160 CriticalThinking Com m unication Problem Solving Cooperation/CollaborationRespect Self-Regulation Persistence/ResilienceEm pathy CreativeThinking ConflictResolution Responsibility StudentAgency ReflectionAction Anticipation GlobalCom petency DigitalLiteracy LiteracyforSD Com putationalThinking Entrepreneurship Arts Humanities Mathematics National Language/s PE/Health Science Technologies Numberofmappedcontentitems Skills, Attitudes and Values Key concepts 2030 Learning Framewo rk Competency Development Cycle Compound competencies for 2030
  • 41. The kind of things that are easy to teach are now easy to automate, digitize or outsource 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
  • 42. What teachers say and what teachers do
  • 43. 96% of teachers: My role as a teacher is to facilitate students own inquiry
  • 44. 86%: Students learn best by findings solutions on their own
  • 45. 74%: Thinking and reasoning is more important than curriculum content
  • 46. -2.00 -1.50 -1.00 -0.50 0.00 Prevalence of memorisation rehearsal, routine exercises, drill and practice and/or repetition 0.00 0.50 1.00 1.50 2.00 Switzerland Poland Germany Japan Korea France Sweden Shanghai-China Canada Singapore United States Norway Spain Netherlands United Kingdom Prevalence of elaboration reasoning, deep learning, intrinsic motivation, critical thinking, creativity, non-routine problems High Low Low High
  • 47. Memorisation is less useful as problems become more difficult (OECD average) R² = 0.81 0.70 1.00 300 400 500 600 700 800 Complexity of of mathematics tasks on the PISA scale Source: Figure 4.3 47 Difficult problem Easy problem Greater success Less success Odds ratio
  • 48. Elaboration strategies are more useful as problems become more difficult (OECD average) R² = 0.82 0.80 1.50 300 400 500 600 700 800 Complexity of mathematics tasks on the PISA scaleSource: Figure 6.2 48 Difficult problem Greater success Less success Easy problem Odds ratio
  • 49. Students’ use of elaboration strategies Source: Figure 6.1 UnitedKingdom20 Iceland18 Australia20 Ireland23 France19 NewZealand19 Israel26 Canada26 Austria32 Japan29 Belgium22 Singapore31 Uruguay22 Germany33 Netherlands24 HK-China30 Luxembourg33 CostaRica33 Norway23 Finland23 UnitedStates30 Portugal29 OECDaverage30 Denmark23 Indonesia38 Switzerland32 Bulgaria27 Macao-China32 Chile24 Albania33 Sweden24 Kazakhstan29 Greece35 UAE32 Hungary37 Brazil25 Argentina35 Liechtenstein41 Estonia38 Mexico27 Spain39 Turkey28 Shanghai-China35 Poland27 Colombia33 Korea43 Latvia32 CzechRepublic40 VietNam41 Croatia48 Slovenia56 Romania36 RussianFed.41 Montenegro39 Malaysia38 Peru30 Italy46 Serbia50 SlovakRepublic40 Lithuania30 Thailand34 Qatar34 ChineseTaipei42 Jordan44 Tunisia44 Belowthe OECD average At the same level as the OECD average Above the OECD average % of students who understand new concepts by relating them to things they already know 49 Elaboration More Less
  • 50. Selected skills • SSES: 19 skills selected for the initial testing • SSES: 15 skills will be included in the main study • PISA 2021: possible skills for inclusion: – Self-control – Persistence – Curiosity – Perspective taking – Empathy – Trust – Emotional control – Resilience SOCIABILITY CURIOSITY EMPATHY ACHIEVEMENT MOTIVATION STRESSRESISTANCE RESPONSIBILITY SELF-CONTROL OPTIMISMEMOTIONAL CONTROL TRUST TOLERANCE ASSERTIVENESS CRITICAL THINKING CO-OPERATION META-COGNITION SELF-EFFICACY PERSISTENCE ENERGY CREATIVITY EMOTIONAL REGULATION TASK PERFORMANCE THE ‘BIG FIVE’ DOMAINS ENGAGING WITH OTHERS COMPOUND SKILLS COLLABORATION OPEN- MINDEDNESS
  • 51. STRONGEST RELATIONS WITH GRADES IN MATH -0.2 -0.1 0 0.1 0.2 0.3 0.4 Persistence Curiosity Self-efficacy Optimism Correlation Math
  • 52. STRONGEST RELATIONS WITH GRADES IN ART 0 0.1 0.2 Creativity Persistence Self-control Correlation Art
  • 53. RELATIONSHIP WITH CHILD’S HEALTH 0 5 10 15 20 25 30 Socio-demographics Parent education Income SE skills %ofexplainedvariance General health
  • 54. RELATIONSHIP OF SE SKILLS WITH HEALTH- RELATED BEHAVIOURS § Best predictors: Self-control, Optimism 0 1 2 3 4 5 6 7 8 Socio-demographics Parent education Income SE skills %ofexplainedvariance Sleep 8 hours or more
  • 55. Some lessons from high performers • Rigor, focus and coherence • Remain true to the disciplines – but aim at interdisciplinary learning and the capacity of students to see problems through multiple lenses – Balance knowledge of disciplines and knowledge about disciplines • Focus on areas with the highest transfer value – Requiring a theory of action for how this transfer value occurs • Authenticity – Thematic, problem-based, project-based, co-creation in conversation • Some things are caught not taught – Immersive learning propositions
  • 57. Ownership of professional practice Powerful learning environments are constantly creating synergies and finding new ways to enhance professional, social and cultural capital with others. They do that with families and communities, with higher education, with other schools and learning environments, and with businesses.
  • 58. Learning time and science performance (PISA) Figure II.6.23 6 7 8 9 10 11 12 13 14 15 16 0 10 20 30 40 50 60 70 Finland Germany Switzerland Japan Estonia Sweden Netherlands NewZealand Australia CzechRepublic Macao(China) UnitedKingdom Canada Belgium France Norway Slovenia Iceland Luxembourg Ireland Latvia HongKong(China) OECDaverage ChineseTaipei Austria Portugal Uruguay Lithuania Singapore Denmark Hungary Poland SlovakRepublic Spain Croatia UnitedStates Israel Bulgaria Korea Russia Italy Greece B-S-J-G(China) Colombia Chile Mexico Brazil CostaRica Turkey Montenegro Peru Qatar Thailand UnitedArabEmirates Tunisia DominicanRepublic Scorepointsinscienceperhouroflearningtime Hours Intended learning time at school (hours) Study time after school (hours) Score points in science per hour of total learning time Time in school Learning out of school Productivity
  • 59. Making teaching not just financially, but intellectually more attractive Public confidence in profession and professionals Professional preparation and learning Collective ownership of professional practice Decisions made in accordance with the body of knowledge o the profession Professional responsibility in the name of the profession and accountability towards the profession
  • 60. Policy levers to teacher professionalism Knowledge base for teaching (initial education and incentives for professional development) Autonomy: Teachers’ decision- making power over their work (teaching content, course offerings, discipline practices) Peer networks: Opportunities for exchange and support needed to maintain high standards of teaching (participation in induction, mentoring, networks, feedback from direct observations) Teacher professionalism Policy levers to teacher professionalism
  • 62. 11.40 11.60 11.80 12.00 12.20 12.40 12.60 12.80 13.00 13.20 13.40 Never Onceayearorless 2-4timesayear 5-10timesayear 1-3timesamonth Onceaweekormore Teacherself-efficacy(level) Teach jointly as a team in the same class Observe other teachers’ classes and provide feedback Engage in joint activities across different classes Take part in collaborative professional learning Less frequently More frequently Teachers’ self-efficacy and professional collaboration
  • 63. Student-teacher ratios and class size Figure II.6.14 CABA (Argentina) Jordan Viet Nam Poland United States Chile Denmark Hungary B-S-G-J (China) Turkey Georgia Chinese Taipei Mexico Russia Albania Hong Kong (China) Japan Belgium Algeria Colombia Peru Macao (China) Switzerland Malta Dominican Republic Netherlands Singapore Brazil Kosovo Finland Thailand R² = 0.25 5 10 15 20 25 30 15 20 25 30 35 40 45 50 Student-teacherratio Class size in language of instruction High student-teacher ratios and small class sizes Low student-teacher ratios and large class sizes OECD average OECDaverage
  • 64. Teachers’ job satisfaction and class size 10.00 10.50 11.00 11.50 12.00 12.50 13.00 15 or less 16-20 21-25 26-30 31-35 36 or more Teachers'jobsatisfaction(level) Class size (number of students)
  • 65. 0 10 20 30 40 50 60 70 Low professionalism High professionalism Fig II.3.3 Perceptions of teachers’ status Satisfaction with the profession Satisfaction with the work environment Teachers’ self-efficacy Teacher job satisfaction and professionalism
  • 66. Teachers perception of the value of teaching 0 10 20 30 40 50 60 70 80 90 100 Singapore Korea Finland Alberta (Canada) Flanders (Belgium) Shanghai (China) NewZealand Russia Netherlands Australia England(UK) UnitedStates Average Norway Japan Latvia Denmark Poland Iceland Estonia Czech Republic Portugal Sweden France Percentageofteachers Fig II.3.3 Percentage of lower secondary teachers who "agree" or "strongly agree" that teaching profession is a valued profession in society
  • 67. Australia Brazil Bulgaria Chile Croatia Czech Republic Denmark Estonia Finland France Iceland IsraelItaly Japan Korea Latvia Mexico Netherlands Norway Poland Portugal Romania Serbia Singapore Slovak Republic SpainSweden Alberta (Canada) England (United Kingdom) Flanders (Belgium) United States 0 5 10 15 20 25 30 35 40 45 0 10 20 30 40 50 60 70 80 Shareofmathematicstopperformers Percentage of teachers who agree that teaching is valued in society Countries where teachers believe their profession is valued show higher levels of excellence in learning outcomes (PISA) 6 7 Relationship between lower secondary teachers' views on the value of their profession in society and the country’s share of top mathematics performers in PISA 2012
  • 68. Standardisation and Conformity Standardisation and compliance lead students to be e ducated in batches of age, following the same standar d curriculum, all assessed at the same time.
  • 69. Ingenious Building instruction from student passions and capacities, helping students personalise their learning and assessme nt in ways that foster engagement and talents.
  • 70. % Yes No If I am more innovative in my teaching I will be rewarded (country average)
  • 73. • Balancing breadth and depth of framework coverage – Core assessments in reading, math and science every three years • With focus (increased sample) rotating – One innovative assessment area every three years • Digital literacy (2009) • Individual problem-solving (2012) • Collaborative problem-solving (2015) • Global competency (2018) • Creative thinking (2021) – Matrix sampling with adaptive assessment instruments Design choices and trade-offs
  • 74. 47th meeting of the PISA Governing Board Individual enablers Forms of engagementSocial Enablers Domain readiness Goal orientation & beliefs Openness Cognitive skills & approaches Motivation Collaboration with others Creative expression Knowledge creation Innovative solutions to problems Cultural norms & expectations Classroom climate Educational approaches Creative thinking in the classroom
  • 75. 47th meeting of the PISA Governing Board Individual enablers Forms of engagementSocial Enablers Domain readiness Goal orientation & beliefs Openness Cognitive skills & approaches Motivation Collaboration with others Creative expression Knowledge creation Innovative solutions to problems Cultural norms & expectations Classroom climate Educational approaches Creative thinking in the classroom
  • 76. 47th meeting of the PISA Governing Board Competency model for PISA CT Generate Creative Ideas Evaluate and Improve Ideas Generate Diverse Ideas Focuses on students’ capacities to think flexibly across domains: for example, providing different solutions for a problem, writing different story ideas, or creating different ways to visually represent an idea.
  • 77. 47th meeting of the PISA Governing Board Competency model for PISA CT Generate Creative Ideas Evaluate and Improve Ideas Generate Diverse Ideas focuses on students’ capacities to search for original ideas across domains: for example, an original story idea, an original way to communicate an idea in visual form, or an original solution to a social or scientific problem.
  • 78. 47th meeting of the PISA Governing Board Competency model for PISA CT Generate Creative Ideas Evaluate and Improve Ideas Generate Diverse Ideas focuses on students’ capacities to evaluate limitations in given ideas and find original ways to improve them
  • 79. 47th meeting of the PISA Governing Board Competency model for PISA CT Generate Creative Ideas Evaluate and Improve Ideas Generate Diverse Ideas
  • 80. Find out more about our work at www.oecd.org/pisa – All publications – The complete micro-level database Email: Andreas.Schleicher@OECD.org Twitter: SchleicherOECD Wechat: AndreasSchleicher Thank you