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What is behind of the PISA trends across the world?Andreas Schleicher, Vilnius 16 October 2017
Trends in science performance (PISA)
2006 2009 2012 2015
OECD
450
470
490
510
530
550
570
OECD average
Stu
de
nt
pe
rfo
rma
nc
e
Trends in science performance (PISA)
450
470
490
510
530
550
570
2006 2009 2012 2015
OECD average
Hig
her
pe
rfo
man
ce
Science performance and equity in PISA (2015)
Some countries
combine excellence
with equity
High performance
High equity
Low performance
Low equity
Low performance
High equity
High performance
Low equity
More equity
Poverty is not destiny - Science performanceby international deciles of the PISA index of economic, social and cultural status (ESCS)
280
330
380
430
480
530
580
630D
om
inic
an
Rep
ublic
40
Alg
eri
a 5
2K
oso
vo
10
Qa
tar
3F
YR
OM
13
Tun
isia
39
Mo
nte
ne
gro
11
Jo
rdan
21
Un
ite
d A
rab
Em
ira
tes 3
Ge
org
ia 1
9L
eb
ano
n 2
7In
do
nesia
74
Me
xic
o 5
3P
eru
50
Co
sta
Ric
a 3
8B
razil
43
Turk
ey 5
9M
old
ova 2
8T
ha
ilan
d 5
5C
olo
mb
ia 4
3Ic
ela
nd
1T
rin
ida
d a
nd T
oba
go 1
4R
om
an
ia 2
0Is
rae
l 6
Bu
lga
ria
13
Gre
ece
13
Russia
5U
rugu
ay 3
9C
hile
27
Latv
ia 2
5L
ith
ua
nia
12
Slo
vak R
ep
ublic
8It
aly
15
Norw
ay 1
Sp
ain
31
Hu
ng
ary
16
Cro
atia
10
Denm
ark
3O
EC
D a
ve
rage
12
Sw
ede
n 3
Ma
lta 1
3U
nite
d S
tate
s 1
1M
acao
(C
hin
a)
22
Irela
nd
5A
ustr
ia 5
Po
rtu
gal 2
8L
uxem
bou
rg 1
4H
ong
Ko
ng
(C
hin
a)
26
Czech R
ep
ub
lic 9
Po
lan
d 1
6A
ustr
alia
4U
nite
d K
ingd
om
5C
ana
da 2
Fra
nce 9
Ko
rea
6N
ew
Ze
ala
nd 5
Sw
itze
rla
nd 8
Neth
erl
an
ds 4
Slo
ven
ia 5
Be
lgiu
m 7
Fin
lan
d 2
Esto
nia
5V
iet
Nam
76
Ge
rma
ny 7
Ja
pan
8C
hin
ese
Ta
ipe
i 12
B-S
-J-G
(C
hin
a)
52
Sin
ga
po
re 1
1
Score
poin
ts
Bottom decile Second decile Middle decile Ninth decile Top decile
Figure I.6.7
% of students
in the bottom
international
deciles of
ESCS
OECD median student
Students expecting a career in scienceFigure I.3.2
0
5
10
15
20
25
30
35
40
45
50
Do
min
ican
Rep
. 1
2C
osta
Ric
a 1
1Jord
an
6
Un
ite
d A
rab E
m.
11
Me
xic
o
6C
olo
mbia
8Le
ban
on
15
Bra
zil
19
Peru
7Q
ata
r 19
Un
ite
d S
tate
s
13
Ch
ile 1
8T
un
isia
1
9C
anad
a 2
1S
loven
ia 1
6T
urk
ey 6
Austr
alia
1
5U
nite
d K
ing
dom
1
7M
ala
ysia
4
Kazakhsta
n
14
Spain
1
1N
orw
ay
21
Uru
guay 1
7S
ing
apo
re 1
4T
rin
ida
d a
nd T
. 13
Isra
el 2
5C
AB
A (
Arg
.)
19
Port
ug
al 18
Bulg
aria
2
5Ir
ela
nd
1
3K
osovo
7A
lge
ria
12
Ma
lta
1
1G
reece
12
Ne
w Z
eala
nd 2
4A
lba
nia
2
9E
sto
nia
1
5O
EC
D a
vera
ge 1
9B
elg
ium
1
6C
roa
tia
1
7F
YR
OM
2
0Lithu
ania
2
1Ic
ela
nd
2
2R
ussia
1
9H
KG
(C
hin
a)
2
0R
om
an
ia
20
Ita
ly 1
7A
ustr
ia
23
Mo
ldova
7La
tvia
1
9M
onte
neg
ro 1
8F
rance
21
Lu
xe
mbo
urg
1
8P
ola
nd
13
Ma
ca
o (
Ch
ina
) 10
Ch
ine
se
Taip
ei 2
1S
wede
n 2
1T
ha
iland
2
7V
iet
Nam
1
3S
witzerl
and
2
2K
ore
a
7
Hu
nga
ry 2
2S
lovak R
epub
lic
24
Japa
n 1
8F
inla
nd
24
Geo
rgia
2
7C
zech R
epu
blic
2
2B
-S-J
-G (
Chin
a)
31
Ne
therl
and
s
19
Germ
any 3
3In
don
esia
1
9D
enm
ark
4
8
%Percentage of students who expect to work in science-related professional and technical occupations when they are 30
Science-related technicians and associate professionals
Information and communication technology professionals
Health professionals
Science and engineering professionals
% o
f st
ud
ents
wit
hva
gu
e o
r m
issi
ng
exp
ecta
tio
ns
SingaporeCanadaSloveniaAustralia
United KingdomIreland
Portugal
Chinese TaipeiHong Kong (China)
New ZealandDenmark
JapanEstoniaFinland
Macao (China)Viet Nam
B-S-J-G (China)Korea
GermanyNetherlandsSwitzerland
BelgiumPoland
SwedenLithuaniaCroatiaIcelandGeorgiaMalta
United StatesSpainIsrael
United Arab Emirates
BrazilBulgaria
ChileColombiaCosta Rica
Dominican RepublicJordanKosovo
LebanonMexico
PeruQatar
Trinidad and TobagoTunisiaTurkey
Uruguay
Above-average science performance
Stronger than average beliefs in science
Above-average percentage of students expecting to work in a science-related occupation
Norway
Multip
le o
utc
om
es
0
10
20
30
40
50
300 400 500 600 700
Pe
rce
nta
ge
of
stu
de
nts
ex
pe
cti
ng
a
ca
ree
r in
sc
ien
ce
Score points in science
Low enjoyment of science
High enjoyment of science
Students expecting a career in scienceby performance and enjoyment of learning
Figure I.3.17
Change between 2006 and 2015 in students’
enjoyment of learning science
Enjoyment of science decreased
Enjoyment of science increased
Figure I.3.10
Lessons f
rom
PIS
A
Low impact on outcomes
High impact on outcomes
Low feasibility High feasibility
Money pits
Must haves
Low hanging fruits
Quick wins
Lessons f
rom
PIS
A
Low impact on outcomes
High impact on outcomes
Low feasibility High feasibility
Money pits
Must haves
Low hanging fruits
Quick wins
Commitment to universal achievement
Gateways, instructional systems
Capacity at point of delivery
Incentive structures and accountability
Resources where they yield most
A learning systemCoherence
Lessons f
rom
PIS
A
Low impact on outcomes
High impact on outcomes
Low feasibility High feasibility
Money pits
Must haves
Low hanging fruits
Quick wins
Commitment to universal achievement
Gateways, instructional systems
Capacity at point of delivery
Incentive structures and accountability
Resources where they yield most
A learning systemCoherence
A commitment to education and the belief that competencies can be learned and therefore all children can achieve
Universal educational standards and personalization as the approach to engage with diversity…
… as opposed to a belief that students have different destinations to be met with different expectations, and selection/stratification as the approach to heterogeneity
Clear articulation who is responsible for ensuring student success and to whom
Students’ self-efficacy in science and
science performance
Score-point difference associated with one-unit increase in the index of self-efficacy
Lessons f
rom
PIS
A
Low impact on outcomes
High impact on outcomes
Low feasibility High feasibility
Money pits
Must haves
Low hanging fruits
Quick wins
Commitment to universal achievement
Gateways, instructional systems
Capacity at point of delivery
Incentive structures and accountability
Resources where they yield most
A learning systemCoherence
Investing resources where they can make mostof a difference
Alignment of resources with key challenges (e.g. attracting the most talented teachers to the most challenging classrooms)
Effective spending choices that prioritise high quality teachers over smaller classes
Spending per student from the age of 6 to 15 and
science performance
Figure II.6.2
Luxembourg
SwitzerlandNorwayAustria
Singapore
United States
United Kingdom
Malta
Sweden
Belgium
Iceland
Denmark
Finland
Netherlands
Canada
JapanSlovenia
Australia
Germany
IrelandFranceItaly
Portugal
New Zealand
Korea Spain
PolandIsrael
Estonia
Czech Rep.
LatviaSlovak Rep.
Russia
CroatiaLithuania
HungaryCosta Rica
Chinese Taipei
Chile
Brazil
Turkey
UruguayBulgaria
Mexico
Thailand MontenegroColombia
Dominican Republic
Peru
Georgia
11,7; 411
R² = 0,01
R² = 0,41
300
350
400
450
500
550
600
0 20 40 60 80 100 120 140 160 180 200
Scie
nce p
erf
orm
an
ce (
sco
re p
oin
ts)
Average spending per student from the age of 6 to 15 (in thousands USD, PPP)
Differences in educational resourcesbetween advantaged and disadvantaged schools
Figure I.6.14
Disadvantaged schools have more
resources than advantaged schools
Disadvantaged schools have fewer
resources than advantaged schools
Starting strong
Attendance at pre-primary school by schools’ socio-economic profile
Table II.6.51
OECD average
Lessons f
rom
PIS
A
Low impact on outcomes
High impact on outcomes
Low feasibility High feasibility
Money pits
Must haves
Low hanging fruits
Quick wins
Commitment to universal achievement
Gateways, instructional systems
Capacity at point of delivery
Incentive structures and accountability
Resources where they yield most
A learning systemCoherence
Capacity at the point of delivery
Attracting, developing and retaining high quality teachers and school leaders and a work organisation in which they can use their potential
Instructional leadership and human resource management in schools
Keeping teaching an attractive profession
System-wide career development …
The ‘productivity’ puzzle
Making learning time productive so that students can build their academic, social and emotional
skills in a balanced way
Learning time and science performanceFigure II.6.23
Finland
Germany Switzerland
Japan Estonia
Sweden
NetherlandsNew Zealand
Macao(China)
Iceland
Hong Kong(China) Chinese Taipei
Uruguay
Singapore
PolandUnited States
Israel
Bulgaria
Korea
Russia Italy
Greece
B-S-J-G (China)
Colombia
Chile
Mexico
Brazil
CostaRica
Turkey
MontenegroPeru
QatarThailand
UnitedArab
Emirates
Tunisia
Dominican Republic
R² = 0,21
300
350
400
450
500
550
600
35 40 45 50 55 60
PIS
A s
cie
nce s
co
re
Total learning time in and outside of school
OECD average
OECD average
OE
CD
ave
rage
Learning time and science performanceFigure II.6.23
6
7
8
9
10
11
12
13
14
15
16
0
10
20
30
40
50
60
70
Fin
lan
dG
erm
an
yS
witzerla
nd
Japa
nE
sto
nia
Sw
ede
nN
eth
erla
nds
New
Zeala
nd
Austr
alia
Czech R
epublic
Ma
ca
o (
Chin
a)
United
Kin
gd
om
Can
ada
Belg
ium
Fra
nce
Norw
ay
Slo
ven
iaIc
ela
nd
Lu
xe
mbou
rgIr
ela
nd
La
tvia
Hon
g K
ong
(C
hin
a)
OE
CD
avera
ge
Chin
ese T
aip
ei
Austr
iaP
ort
uga
lU
rugu
ay
Lithu
ania
Sin
gapo
reD
en
mark
Hun
gary
Pola
nd
Slo
vak R
ep
ublic
Spain
Cro
atia
United
Sta
tes
Isra
el
Bulg
aria
Kore
aR
ussia
Ita
lyG
reece
B-S
-J-G
(C
hin
a)
Colo
mbia
Chile
Me
xic
oB
razil
Costa
Ric
aT
urk
ey
Mo
nte
negro
Peru
Qata
rT
haila
nd
United
Ara
b E
mirate
sT
unis
iaD
om
inic
an R
epub
lic
Score
poin
ts in s
cie
nce p
er
hour
of
tota
l le
arn
ing t
ime
Hours Intended learning time at school (hours) Study time after school (hours) Score points in science per hour of total learning time
Developing Teaching
as a profession
Recruit top candidates into the profession
Support teachers in continued
development of practice
Retain and recognise effective teachers –path for growth
Improve the
societal view of
teaching as a
profession
Mean mathematics performance, by school location, after acc
ounting for socio-economic status2
3
Implementing highly effective teacher policy and practice
Mean mathematics performance, by school location,
after accounting for socio-economic status24
Teachers' perceptions of the value of teaching in society
Percentage of lower secondary education teachers who "agree" or "strongly agree" that teaching is a
valued profession in society
0
10
20
30
40
50
60
70
80
90
100
Mala
ysia
Sin
gapore
Kore
a
Abu D
habi (U
nited A
rab…
Finla
nd
Mexi
co
Alb
erta (Canada)
Flanders
(Belg
ium
)
Neth
erlands
Aust
ralia
Engla
nd (United K
ingdom
)
Rom
ania
Isra
el
United S
tate
s
Chile
Ave
rage
Norw
ay
Japan
Latv
ia
Serb
ia
Bulg
aria
Denm
ark
Pola
nd
Icela
nd
Est
onia
Bra
zil
Italy
Cze
ch R
epublic
Portugal
Cro
atia
Spain
Sw
eden
France
Slo
vak R
epublic
Perc
enta
ge o
f te
ach
ers
Items are ranked in descending order, based on the percentage of teachers who strongly agree or agree that teaching is a valued profession in society.
Mean mathematics performance, by school location,
after accounting for socio-economic statusFig II.3.32
5
Relationship between the perceived value of the teaching
profession and the share of PISA top performers (math)
Relationship between lower secondary education teachers' views on the value of their profession in society and the
share of top mathematics performers in PISA 2012
Australia
Brazil
BulgariaChile
Croatia
Czech Republic
Denmark
Estonia FinlandFrance
IcelandIsrael
Italy
Japan
Korea
Latvia
Mexico
Netherlands
Norway
Poland
Portugal
RomaniaSerbia
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
Share
of
math
em
atics
top p
erf
orm
ers
Percentage of teachers who agree that teaching is valued in society
External forces
exerting pressure and
influence inward on
an occupation
Internal motivation and
efforts of the members
of the profession itself
26 Professionalism
Professionalism is the level of autonomy and internal regulation exercised by members of an
occupation in providing services to society
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
Teacher professionalism
Autonomy: Teachers’ decision-making power over their work (teaching content, course offerings, discipline practices)
Knowledge base for teaching (initial education and incentives for professional development)
Peer networks: Opportunities for exchange and support needed to maintain high standards of teaching (participation in induction,
mentoring, networks, feedback from direct observations)
0
1
2
3
4
5
6
7
8
9
10S
pain
Ja
pa
n
Fra
nce
Bra
zil
Fin
lan
d
Fla
nd
ers
No
rway
Alb
ert
a (
Ca
na
da
)
Au
str
alia
De
nm
ark
Isra
el
Ko
rea
Un
ite
d S
tate
s
Cze
ch R
epu
blic
Sh
an
gh
ai (C
hin
a)
Latv
ia
Ne
the
rlan
ds
Po
land
En
gla
nd
Ne
w Z
eala
nd
Sin
ga
po
re
Esto
nia
Networks Autonomy Knowledge
Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.32929 TALIS Teacher professionalism index
0
10
20
30
40
50
60
70
80
90
100
Discu
ss indiv
idual
students
Share
reso
urc
es
Team
confe
rence
s
Colla
bora
te for
com
mon s
tandard
s
Team
teach
ing
Colla
bora
tive
PD
Join
t act
ivitie
s
Cla
ssro
om
obse
rvations
Perc
enta
ge o
f te
ach
ers
Average
Professional collaboration
Percentage of lower secondary teachers who report doing the following activities at least once per month
Professional collaboration among teachers
Exchange and co-ordination
(OECD countries)
Teachers Self-Efficacy and Professional Collaboration
11,40
11,60
11,80
12,00
12,20
12,40
12,60
12,80
13,00
13,20
13,40
Never
Once
a y
ear
or
less
2-4
tim
es
a y
ear
5-1
0 t
imes
a y
ear
1-3
tim
es
a m
onth
Once
a w
eek o
r m
ore
Teach
er
self-e
ffic
acy
(le
vel)
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
Morefrequently
Student-teacher ratios and class sizeFigure II.6.14
High student-teacher ratios
and small class sizes
Low student-teacher ratios
and large class sizes
OECD
average
OE
CD
ave
rage
Lessons f
rom
PIS
A
Low impact on outcomes
High impact on outcomes
Low feasibility High feasibility
Money pits
Must haves
Low hanging fruits
Quick wins
Commitment to universal achievement
Gateways, instructional systems
Capacity at point of delivery
Incentive structures and accountability
Resources where they yield most
A learning systemCoherence
Governance, incentives, accountability, knowledge management
Aligned incentive structures
For students How gateways affect the strength, direction, clarity and nature of the incentives
operating on students at each stage of their education
Degree to which students have incentives to take tough courses and study hard
Opportunity costs for staying in school and performing well
For teachers Make innovations in pedagogy and/or organisation
Improve their own performance and the performance of their colleagues
Pursue professional development opportunities that lead to stronger pedagogical practices
A balance between vertical and lateral accountability
Effective instruments to manage and share knowledge and spread innovation – communication within the system and with stakeholders around it
A capable centre with authority and legitimacy to act
Lessons f
rom
PIS
A
Low impact on outcomes
High impact on outcomes
Low feasibility High feasibility
Money pits
Must haves
Low hanging fruits
Quick wins
Commitment to universal achievement
Gateways, instructional systems
Capacity at point of delivery
Incentive structures and accountability
Resources where they yield most
A learning systemCoherence
Clear ambitious goals that are shared across the system and aligned with high stakes gateways and instructional systems
Well established delivery chain through which curricular goals translate into instructional systems, instructional practices and student learning (intended, implemented and achieved)
High level of metacognitive content of instruction
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
Robotics
The Auto-auto>1m km,
one minor accident,
occasional human intervention
Augmented Reality
Dimensions of student learning
The expanding world of knowledge
The multi-faceted world of knowledge
The human world of knowledge
The small world of the curriculum
The small world of the curriculum
The small world of the curriculum
The small world of the curriculum
The small world of the curriculum
The small world of the curriculum
The TrueThe realm of human knowledge The Good
The realm of ethics and judgement
The Just and Well-OrderedThe realm of political and civic life The Beautiful
The realm of creativity, esthetics and designThe Sustainable
The realm of natural and physical health The Prosperous
The realm of economic life
The big world of learning
• 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
• Equity– Not just a proposition for the few but for the many
•49 Challenges of curriculum design
Students’ use of memorisation strategies
Source: Figure 4.1
% of students who report they learn by heart
50
Me
mo
ris
ati
on
More
Less
Memorisation is less useful as problems become more difficult (OECD average)
R² = 0,81
0,70
1,00
300 400 500 600 700 800
Difficulty of mathematics item on the PISA scale
Source: Figure 4.3
5
1
Difficult problem
Easy problem
Greater success
Less success
Odds ratio
There are large international differences in the use of control strategies
Source: Figure 5.1
% of students whotry to work out what the most
important parts to learn are
52
Co
ntr
ol
More
Less
Control strategies are always helpful but less so as problems become more difficult (OECD average)
Source: Figure 5.253
Difficult problem
Greater success
Less success
Easy problem
Odds ratio
Students’ use of elaboration strategies
Source: Figure 6.1
% of students who understand new
concepts by relating them to things they
already know
54
Ela
bo
ra
tio
n
More
Less
Elaboration strategies are more useful as problems become more difficult (OECD average)
Source: Figure 6.2
5
5
Difficultproblem
Greater success
Less success
Easy problem
Odds ratio
Lessons f
rom
PIS
A
Low impact on outcomes
High impact on outcomes
Low feasibility High feasibility
Money pits
Must haves
Low hanging fruits
Quick wins
Commitment to universal achievement
Gateways, instructional systems
Capacity at point of delivery
Incentive structures and accountability
Resources where they yield most
A learning systemCoherence
Schooling today Schooling tomorrow
Some students learn at high levels
All students learnat 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
58
58 Thank you
Find out more about our work at www.oecd.org/edu– All publications
– The complete micro-level database
Discover PISA 2015 results by country www.compareyourcountry.org/pisa
Email: [email protected]
Twitter: SchleicherOECDand remember:
