2010 b paris (school failure) schleicher short
DESCRIPTION
What can PISA tell us about successful school systems?TRANSCRIPT
11A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Against the odds
Overcoming school failureParis, 11 February 2010
Andreas SchleicherEducation Policy Advisor of the OECD Secretary-General
22A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
In the current economic environment…… Labour-market entry becomes more
difficult– as young graduates compete with experienced
workers
… Job prospects for less qualified deteriorate… Young people with lower qualifications
who become unemployed are likely to spend long time out of work– In most countries over half of low-qualified
unemployed 25-34-year-olds are long-term unemployed
… Higher risks for systems with significant work-based training
… Gaps in educational attainment between younger and older cohorts likely to widen .
33A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
sAgainst the odds
1. There is nowhere to hide The yardstick for educational success is no
longer improvement by national standards but the best performing systems internationally
The impact of poor educational performance is growing rapidly
2. Where we are – and where we can be Where countries stand in terms of limiting
failure and moderating the impact of social background
What the best performing countries show can be achieved
3. How we can get there Some policy levers that emerge from
international comparisons
44A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
55A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
sA world of change in baseline
qualificationsApproximated by percentage of persons with high school or equivalent qualfications
in the age groups 55-64, 45-55, 45-44 und 25-34 yearsU
nit
ed S
tate
s
Czech R
epublic
Esto
nia
Germ
any
Sw
itzerl
and
Denm
ark
Canada
Norw
ay
Sw
eden
Russia
n F
edera
tion4
Austr
ia3
Slo
venia
Isra
el
Slo
vak R
epublic
New
Zeala
nd
Hungary
Fin
land
Unit
ed K
ingdom
3
Neth
erl
ands
Luxem
bourg
EU
19
avera
ge
OEC
D a
vera
ge
Fra
nce
Austr
alia
Icela
nd
Belg
ium
Pola
nd
Irela
nd
Kore
a
Chile2
Gre
ece
Italy
Spain
Turk
ey
Port
ugal
Mexic
o
Bra
zil2
0
10
20
30
40
50
60
70
80
90
100
1990s 1980s 1970s 1960s
%
1. Excluding ISCED 3C short programmes 2. Year of reference 20043. Including some ISCED 3C short programmes 3. Year of reference 2003.
13
1
1
27
66A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Latin America then…
GDP/pop 1960
Years schooling
Asia 1891 4
Sub-Saharan Africa 2304 3.3
MENA 2599 2.7
Latin America 4152 4.7
Europe 7469 7.4
Orig. OECD 11252 9.5
77A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
GDP/pop
1960
Years schoolin
g
Asia 1891 4
Sub-Saharan Africa 2304 3.3
MENA 2599 2.7
Latin America 4152 4.7
Europe 7469 7.4
Orig. OECD 11252 9.5
Latin America then and now…
GDP/pop 1960
Years schooling
Growth 1960-2000
GDP/pop 2000
Asia 1891 4 4.5 13571
Sub-Saharan Africa 2304 3.3 1.4 3792
MENA 2599 2.7 2.7 8415
Latin America 4152 4.7 1.8 8063
Europe 7469 7.4 2.9 21752
Orig. OECD 11252 9.5 2.1 26147
88A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Latin America then and now…Why quality is the key
Hanushek 2009
GDP/pop 1960
Years schooling
Growth 1960-2000
GDP/pop 2000
Test score
Asia 1891 4 4.5 13571 480
Sub-Saharan Africa 2304 3.3 1.4 3792 360
MENA 2599 2.7 2.7 8415 412
Latin America 4152 4.7 1.8 8063 388
Europe 7469 7.4 2.9 21752 492
Orig. OECD 11252 9.5 2.1 26147 500
99A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
sOECD’s PISA assessment of the
knowledge and skills of 15-year-oldsCoverage of world economy 77%81%83%85%86%87%
1010A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
sAverage performanceof 15-year-olds in science – extrapolate and apply
High science performance
Low science performance
… 18 countries perform below this line
I srael
I talyPortugal Greece
Russian Federation
LuxembourgSlovak Republic,Spain,Iceland Latvia
Croatia
Sweden
DenmarkFrancePoland
Hungary
AustriaBelgiumIreland
Czech Republic SwitzerlandMacao- ChinaGermanyUnited Kingdom
Korea
J apanAustralia
Slovenia
NetherlandsLiechtenstein
New ZealandChinese Taipei
Hong Kong- China
Finland
CanadaEstonia
United States LithuaniaNorway
445
465
485
505
525
545
565
616
But caution: Some systems with high average performance still have high proportion of poor performers
1212A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Ne
w Z
ea
lan
d
Fin
lan
d
Un
ite
d K
ing
do
m
Au
stra
lia
Jap
an
Ca
na
da
OE
CD
ave
rag
e
Po
rtu
ga
l
Ita
ly
Tu
rke
y
Me
xic
o
Un
ite
d S
tate
s
Ko
rea
60
40
20
0
20
40
60
80
100
Level 5 Level 4 Level 3 Level 2 Below Level 1 Level 1%
530 563 515 527 531 534 500 474 475 424 410 489 522
Large proportion of top performers
Top and bottom performers in science
Large prop. of poor perf.
These students often confuse key features of a scientific investigation, apply incorrect information, mix personal beliefs with facts in support of a position…
These students can consistently identify, explain and apply scientific knowledge, link different information sources and explanations and use evidence from these to justify decisions, demonstrate advanced scientific thinking in unfamiliar situations…
1313A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
sPoland raised its reading performance by 28 PISA
points, equivalent to ¾ of a school year
OECD (2007), Learning for tomorrow’s world: First results from PISA 2006, Table 6.1a
OE
CD
20
06
Po
lan
d 2
00
0
Po
lan
d 2
00
3
Po
lan
d 2
00
6
30
20
70
Below Level 1 Level 2 Level 3 Level 4 Level 5%
In 2003, performance variation among
schools had fallen from 51% to 16% of the variation of student
performance
But did this lead to genuine
improvements of school performance?
Between 2000 and 2003 showed the second-largest increase in
reading (17 points) and a further 11 point
increase since 2003
Most of that increase resulted from smaller
proportions at the bottom level (23% in 2000, and
three-quarters in vocational tracks, 17%in
2003)
Did this harm the better performers?
1414A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
0
20
40
60
80
100
120
140
Ger
man
y
Cze
ch R
epub
lic
Aus
tria
Hun
gary
Net
herl
ands
Bel
gium
Jap
an
Ital
y
Gre
ece
Slo
vak
Rep
ublic
Tur
key
Swit
zerl
and
Kor
ea
Luxe
mbou
rg
Uni
ted
Sta
tes
Port
ugal
Mex
ico
Uni
ted
Kin
gdom
New
Zea
land
Aus
tral
ia
Can
ada
Irel
and
Den
mar
k
Spa
in
Pola
nd
Swed
en
Nor
way
Icel
and
Fin
land
Sources of performance varianceFailure an issue of school or student performance?
OECD (2007), Learning for tomorrow’s world: First results from PISA 2006, Table 4.1a
1515A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
- 80
- 60
- 40
- 20
0
20
40
60
80
100
Ger
man
y
Cze
ch R
epub
lic
Aus
tria
Hun
gary
Net
herl
ands
Bel
gium
Jap
an
Ital
y
Gre
ece
Slo
vak
Rep
ublic
Tur
key
Swit
zerl
and
Kor
ea
Luxe
mbou
rg
Uni
ted
Sta
tes
Port
ugal
Mex
ico
Uni
ted
Kin
gdom
New
Zea
land
Aus
tral
ia
Can
ada
Irel
and
Den
mar
k
Spa
in
Pola
nd
Swed
en
Nor
way
Icel
and
Fin
land
Variation of performance between
schools
Variation of performance within
schools
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Table 4.1a
Sources of performance varianceFailure an issue of school or student performance?
1616A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
sAverage performanceof 15-year-olds in science – extrapolate and apply
Low average performance
Large socio-economic disparities
High average performance
Large socio-economic disparities
Low average performance
High social equity
High average performance
High social equity
Strong socio-economic impact on
student performance
Socially equitable distribution of
learning opportunities
High science performance
Low science performance
I srael
I talyPortugal Greece
Russian Federation
LuxembourgSlovak Republic,Spain,Iceland Latvia
Croatia
Sweden
DenmarkFrancePoland
Hungary
AustriaBelgiumIreland
Czech Republic SwitzerlandMacao- ChinaGermanyUnited Kingdom
Korea
J apanAustralia
Slovenia
NetherlandsLiechtenstein
New ZealandChinese Taipei
Hong Kong- China
Finland
CanadaEstonia
United States LithuaniaNorway
445
465
485
505
525
545
565
616
1717A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Durchschnittliche Schülerleistungen im Bereich Mathematik
Low average performance
Large socio-economic disparities
High average performance
Large socio-economic disparities
Low average performance
High social equity
High average performance
High social equity
Strong socio-economic impact on
student performance
Socially equitable distribution of
learning opportunities
High science performance
Low science performance
I srael
GreecePortugal I talyRussian Federation
LuxembourgSlovak Republic SpainIcelandLatvia
Croatia
Sweden
DenmarkFrancePoland
Hungary
AustriaBelgiumIreland
Czech Republic Switzerland Macao- China
Germany United Kingdom
Korea
J apanAustralia
Slovenia
NetherlandsLiechtenstein
New ZealandChinese Taipei
Hong Kong- China
Finland
CanadaEstonia
United States Lithuania Norway
440
460
480
500
520
540
560
21222
1919A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
-3 -2 -1 0 1 2 3300
500
700
School performance and socio-economic background Germany
Stu
dent
perf
orm
ance
AdvantagePISA Index of socio-economic background
Disadvantage
Schools proportional to size
Student performance and students’ socio-economic background within
schoolsSchool performance and schools’ socio-economic
background
2020A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
-3 -2 -1 0 1 2 3300
500
700
School performance and socio-economic background Germany
Stu
dent
perf
orm
ance
AdvantagePISA Index of socio-economic background
Disadvantage
Schools proportional to size
Student performance and students’ socio-economic background within
schoolsSchool performance and schools’ socio-economic
background
Universal policies Increasing educational performance of all
children through reforms applied equally across the school system, e.g.
– Altering content or pace of curriculum– Improving instructional techniques– Changing the learning environment in schools
and classrooms– Standards and accountability– Teacher professional development
2121A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
-3 -2 -1 0 1 2 3300
500
700
School performance and socio-economic background Germany
Stu
dent
perf
orm
ance
AdvantagePISA Index of socio-economic background
Disadvantage
Schools proportional to size
Student performance and students’ socio-economic background within
schoolsSchool performance and schools’ socio-economic
backgroundCompensatory policies Providing additional economic resources to
students from disadvantaged backgrounds– Different to socio-economically targeted
policies, efforts are directed to ameliorating economic circumstances, rather than providing specialised curriculum or additional educational resources
2222A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
-3 -2 -1 0 1 2 3300
500
700
School performance and socio-economic background Germany
Stu
dent
perf
orm
ance
AdvantagePISA Index of socio-economic background
Disadvantage
Schools proportional to size
Student performance and students’ socio-economic background within
schoolsSchool performance and schools’ socio-economic
backgroundSocio-economically targeted policies Providing a specialised curriculum or
additional educational resources to students from disadvantaged backgrounds
– Students are often also identified through other risk factors, e.g. immigration, ethnicity, low-income community
2323A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
-3 -2 -1 0 1 2 3300
500
700
School performance and socio-economic background Germany
Stu
dent
perf
orm
ance
AdvantagePISA Index of socio-economic background
Disadvantage
Schools proportional to size
Student performance and students’ socio-economic background within
schoolsSchool performance and schools’ socio-economic
background
Performance targeted policies Providing additional economic resources to
students based on their academic performance
– Early intervention programmes– Remedial and recovery programmes– Performance-based tracking or streaming
2525A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
-3 -2 -1 0 1 2 3300
500
700
School performance and socio-economic background United States
Stu
dent
perf
orm
ance
AdvantagePISA Index of socio-economic background
Disadvantage
Schools proportional to size
Student performance and students’ socio-economic background within schools
School performance and schools’ socio-economic background
2626A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
-3 -2 -1 0 1 2 3300
500
700
School performance and socio-economic background
NorwayStu
dent
perf
orm
ance
AdvantagePISA Index of socio-economic background
Disadvantage
Schools proportional to size
Student performance and students’ socio-economic background within schools
School performance and schools’ socio-economic background
2727A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
-3 -2 -1 0 1 2 3300
500
700
School performance and socio-economic background Finland
Stu
dent
perf
orm
ance
AdvantagePISA Index of socio-economic background
Disadvantage
Schools proportional to size
Student performance and students’ socio-economic background within
schoolsSchool performance and schools’ socio-economic
background
3131A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
High expectationsand universal
standards
Rigor, focus and coherence
Great systems attract great teachers and
provide access to best practice and quality
professional development
3232A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
sChallenge and support
Weak support
Strong support
Lowchallenge
Highchallenge
Strong performance
Systemic improvement
Poor performance
Improvements idiosyncratic
Conflict
Demoralisation
Poor performance
Stagnation
3333A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Human capital
International Best Practice• Principals who are trained,
empowered, accountable and provide instructional leadership
• Attracting, recruiting and providing excellent training for prospective teachers from the top third of the graduate distribution
• Incentives, rules and funding encourage a fair distribution of teaching talent
The past
• Principals who manage ‘a building’, who have little training and preparation and are accountable but not empowered
• Attracting and recruiting teachers from the bottom third of the graduate distribution and offering training which does not relate to real classrooms• The best teachers are in the most advantaged communities
3434A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Human capital (cont…)
International Best Practice• Expectations of teachers are
clear; consistent quality, strong professional ethic and excellent professional development focused on classroom practice
• Teachers and the system expect every child to succeed and intervene preventatively to ensure this
The past
• Seniority and tenure matter more than performance; patchy professional development; wide variation in quality
• Wide achievement gaps, just beginning to narrow but systemic and professional barriers to transformation remain in place
3535A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
High ambitions
Access to best practice and quality professional development
Accountability and intervention in
inverse proportion to success
Devolved responsibility,
the school as the centre of action
3636A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
No
Yes
0
10
20
30
40
50
60
70
No
Yes
0
41
46
63
Standards based external
examinations School autonomyin selecting teachers for hire
PISA score in science
School autonomy, standards-based examinations and science performance
School autonomy in selecting teachers for hire
3737A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
sPooled international dataset, effects of selected
school/system factors on science performance after accounting for all other factors in the model
OECD (2007), PISA 2006 – Science Competencies from Tomorrow’s World, Table 6.1a
Gross Net30
20
10
0
10
20
30
40
50
60
70
80
90
100
Approx. one school year
Sco
re p
oin
t d
iffe
ren
ce in
sci
en
ce
Schools practicing ability grouping (gross and net)
Academically selective schools (gross and net)
but no system-wide effect
School results posted publicly (gross and net)
One additional hour of science learning at
school (gross and net)
One additional hour of out-of-school lessons
(gross and net)
One additional hour of self-study or homework
(gross and net)
School activities to promote science
learning(gross and net)
Schools with greater autonomy (resources)
(gross and net)
Each additional 10% of public funding(gross only)
Schools with more competing schools
(gross only)
School principal’s perception that lack of
qualified teachers hinders instruction
(gross only)
School principal’s positive evaluation of quality of educational
materials(gross only)
Measured effect
Effect after accounting for the socio-economic
background of students, schools and countries
3838A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Strong ambitions
Access to best practice and quality professional development
Accountability
Devolvedresponsibility,
the school as the centre of action
Integrated educational
opportunities
From prescribed forms of teaching and assessment towards personalised learning
3939A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Durchschnittliche Schülerleistungen im Bereich Mathematik
Low average performance
Large socio-economic disparities
High average performance
Large socio-economic disparities
Low average performance
High social equity
High average performance
High social equity
Strong socio-economic impact on
student performance
Socially equitable distribution of
learning opportunities
High science performance
Low science performanceTurkey
AustraliaJ apan
Finland
CanadaNew Zealand
Korea
Czech Republic United KingdomAustria
Germany
Netherlands
SwitzerlandI relandBelgium
PolandSwedenHungary
IcelandFrance Denmark
United States SpainLuxembourg NorwaySlovak Republic
I talyGreecePortugal
420
440
460
480
500
520
540
560
580
21222
Early selection and institutional differentiation
High degree of stratification
Low degree of stratification
4040A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Resilience to social disadvantage Resilience: the ability of some individuals
to show positive adaptation despite encountering significant adversity.
Positive Adaptation: academic success Adversity: socio-economic disadvantage
Resilient students: Students who score on a country’s top tertile in
science and whose socio-economic background is within the country’s bottom tertile
Disadvantaged students: Students whose socio-economic background is
within the country’s bottom tertile
4141A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
sNatives are not overrepresented
among resilient students everywhere
Luxem
bou
rg
Sw
itze
rlan
d
Au
stri
a
Belg
ium
Germ
an
y
Neth
erl
an
ds
Sw
ed
en
Den
mark
Un
ited
Sta
tes
Est
on
ia
Slo
ven
ia
OEC
D a
vera
ge
Sp
ain
Port
ug
al
Gre
ece
Fra
nce
Norw
ay
Cro
ati
a
Un
ited
Kin
gd
om
New
Zeala
nd
Can
ad
a
Italy
Au
stra
lia
Ru
ssia
n F
ed
era
tion
Latv
ia
Irela
nd
Hon
g K
on
g-C
hin
a
Kore
a
Rom
an
ia
Isra
el
Serb
ia
Maca
o-C
hin
a
Mon
ten
eg
ro
Jord
an
0
10
20
30
40
50
60
70
80
90
100
% of native students among disadvantaged students% of native students among resilient students% of native students among disadvantaged low achievers
% of native students among…
4545A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Instrumental motivation and resilience
Austra
lia
Belgi
um
Czech
Rep
ublic
Finla
nd
Germ
any
Hunga
ry
Irela
nd
Japa
n
Luxe
mbo
urg
Nethe
rland
s
Norway
Portu
gal
Spai
n
Switz
erla
nd
Unite
d Kin
gdom
OECD a
vera
ge
Argen
tina
Brazil
Chile
Croat
ia
Hong
Kong-
China
Israe
l
Kyrgy
zsta
n
Lithu
ania
Monte
negr
o
Russian
Fed
erat
ion
Slov
enia
Thai
land
Urugu
ay0.0
0.5
1.0
1.5
2.0
Odd
ratio
s for
resil
ient
Increased likelihood of being resilient associated with one unit on the PISA index of instrumental motivation to learn science
4646A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Instrumental motivation is associated with higher performance across all
students…
Austra
lia
Belgi
um
Czech
Rep
ublic
Finla
nd
Germ
any
Hunga
ry
Irela
nd
Japa
n
Luxe
mbo
urg
Nethe
rland
s
Norway
Portu
gal
Spai
n
Switz
erla
nd
Unite
d Kin
gdom
OECD A
vera
ge
Argen
tina
Brazil
Chile
Croat
ia
Hong
Kong-
China
Israe
l
Kyrgy
zsta
n
Lithu
ania
Monte
negr
o
Russian
Fed
erat
ion
Slov
enia
Thai
land
Urugu
ay-30
-20
-10
0
10
20
30Overall relationship
Chan
ge in
PIS
A sc
ienc
e sc
ore
4747A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
… equally
Austra
lia
Belgi
um
Czech
Rep
ublic
Finla
nd
Germ
any
Hunga
ry
Irela
nd
Japa
n
Luxe
mbo
urg
Nethe
rland
s
Norway
Portu
gal
Spai
n
Switz
erla
nd
Unite
d Kin
gdom
OECD A
vera
ge
Argen
tina
Brazil
Chile
Croat
ia
Hong
Kong-
China
Israe
l
Kyrgy
zsta
n
Lithu
ania
Monte
negr
o
Russian
Fed
erat
ion
Slov
enia
Thai
land
Urugu
ay-15
-10
-5
0
5
10
Differential effect for disadvantaged students
Chan
ge in
PIS
A s
cien
ce s
core
4949A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Participation in science courses
Austra
lia
Belgi
um
Czech
Rep
ublic
Finla
nd
Germ
any
Hunga
ry
Irela
nd
Japa
n
Luxe
mbo
urg
Nethe
rland
s
Norway
Portu
gal
Spai
n
Switz
erla
nd
Unite
d Kin
gdom
OECD a
vera
ge
Argen
tina
Brazil
Chile
Croat
ia
Hong
Kong-
China
Israe
l
Kyrgy
zsta
n
Lithu
ania
Monte
negr
o
Russian
Fed
erat
ion
Slov
enia
Thai
land
Urugu
ay0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
Odd
ratio
s for
resil
ienc
e
5050A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Attending a compulsory course is associated with higher performance across all students…
Austra
lia
Belgi
um
Czech
Rep
ublic
Finla
nd
Germ
any
Hunga
ry
Irela
nd
Japa
n
Luxe
mbo
urg
Nethe
rland
s
Norway
Portu
gal
Spai
n
Switz
erla
nd
Unite
d Kin
gdom
OECD A
vera
ge
Argen
tina
Brazil
Chile
Croat
ia
Hong
Kong-
China
Israe
l
Kyrgy
zsta
n
Lithu
ania
Monte
negr
o
Russian
Fed
erat
ion
Slov
enia
Thai
land
Urugu
ay-40
-20
0
20
40
60
80
Overall relationship
Chan
ge in
PIS
A sc
ienc
e sc
ore
5151A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
… and more so for disadvantaged students
Austra
lia
Belgi
um
Czech
Rep
ublic
Finla
nd
Germ
any
Hunga
ry
Irela
nd
Japa
n
Luxe
mbo
urg
Nethe
rland
s
Norway
Portu
gal
Spai
n
Switz
erla
nd
Unite
d Kin
gdom
OECD A
vera
ge
Argen
tina
Brazil
Chile
Croat
ia
Hong
Kong-
China
Israe
l
Kyrgy
zsta
n
Lithu
ania
Monte
negr
o
Russian
Fed
erat
ion
Slov
enia
Thai
land
Urugu
ay-30
-20
-10
0
10
20
30
40
Differential effect for disadvantaged students
Chan
ge in
PIS
A sc
ienc
e sc
ore
5252A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Some conclusions on resilience No gender gap in resilience Language and immigrant background are
associated with resilience only marginally and only in few countries
Resilient students are more motivated, more engaged and more self-confident than their disadvantaged low-achieving peers
Holding student demographics, school characteristics and other approaches to learning constant, the more confident students are, the greater are their odds of being resilient
Motivation is also associated with student resilience in many countries, even if the relationship is weaker .
5353A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Some conclusions on resilience Learning time is one of the strongest
predictors of resilience even after accounting for student
demographics, school characteristics and other factors that are considered to be closely related with performance
Schools can play an important role in promoting resilience by
developing activities, classroom practices and modes of instruction that foster disadvantaged students’ motivation and confidence in their abilities…
… and even more so by providing opportunities for disadvantaged students to spend more time learning science at school .
5454A
ndre
as S
chle
iche
r16
Sep
tem
ber
2009
Imp
act
of
inte
rnat
ion
al A
sse
ssm
en
ts
Does it matter?
To what extent knowledge and skills matter for the success of individuals and economies
5555A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Age 19
Age 21
Age 21
048
121620
Level 2Level 3
Level 4Level 5
Increased likelihood of tertiary particip. at age 19/21 associated with PISA reading proficiency at age 15
(Canada)after accounting for school engagement, gender, mother
tongue, place of residence, parental, education and family income (reference group PISA Level 1)
Increased chance of successful tertiary participation
School marks at age 15
PISA performance at age
15
5656A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Economic impact Programmes to improve cognitive skills through
schools take time to implement and to have their impact on students.
Assume that it will take 20 years to implement reform The impact of improved skills will not be realised
until the students with greater skills move into the labour force
Assume that improved PISA performance will result in improved skill-based of 2.5% of the labour-force each year
The economy will respond over time, making use of the new higher skills to the same extent as observed today in better performing systems
Estimate the total gains over the lifetime of the generation born this year .
5757A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
20102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044204520462047204820492050205120522053205420552056205720582059206020612062206320642065206620672068206920702071207220732074207520762077207820792080208120822083208420852086208720882089209020912092209320942095209620972098209921002101210221032104210521062107210821092110-5%
0%
5%
10%
15%
20%
25%
30%
35%
40%
Relationship between test performance and economic outcomes
Annual improved GDP from raising performance by 25 PISA pointsPe
rcent
add
itio
n t
o G
DP
6161A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
sHigh science performance
Low science performance
Average performanceof 15-year-olds in science – extrapolate and apply
616310
360
410
460
510
560
Finland
Hong Kong-ChinaCanadaChinese Taipei
Estonia JapanNew ZealandAustraliaNetherlandsLiechtenstein KoreaSloveniaGermanyUnited KingdomCzech Republic Switzerland
Macao-ChinaAustriaBelgiumIreland HungarySwedenPolandDenmark
France CroatiaIcelandLatvia
United States Slovak Republic,Spain,LithuaniaNorwayLuxembourgRussian Federation
ItalyPortugal Greece
Israel
TurkeyJordanThailand
RomaniaMontenegro Mexico
IndonesiaArgentinaBrazil
ColombiaTunisiaAzerbaijan
Qatar
Kyrgyzstan
6262A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Unite
d St
ates
Turk
eyIta
ly
Fran
ce
Unite
d Ki
ngdo
m
Canad
a
Kore
a
Portu
gal
Nethe
rland
s
Swed
en
Czech
Rep
ublic
Hunga
ry
Irela
nd
New Z
eala
nd
Finl
and
0
2000
4000
6000
8000
10000
12000
14000
Raise everyone to minimum of 400 PISA points
(aggregate gain across OECD countries $200 trillion)bn$
6363A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Mex
ico
Greec
eIta
ly
Unite
d St
ates
Pola
nd
Norway
Slov
ak R
epub
lic
Fran
ce
Austri
a
Icel
and
Czech
Rep
ublic
Unite
d Ki
ngdo
m
Austra
lia
Japa
n
Kore
a0%
200%
400%
600%
800%
1000%
1200%
% currrent GDP
Raise everyone to minimum of 400 PISA points
(aggregate gain across OECD countries $200 trillion)
6464C
ounci
l, 1
8 S
ep
tem
ber
20
08
Ed
uca
tion a
t a G
lance
Some conclusions The higher economic outcomes that improved
student performance entails dwarf the dimensions of economic cycles
Even if the estimated impacts of skills were twice as large as the true underlying causal impact on growth, the resulting present value of successful school reform still far exceeds any conceivable costs of improvement.
6565A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
sMoney matters - but other things do too
0 10000 20000 30000 40000 50000 60000 70000 80000 90000 100000400
425
450
475
500
525
550
575
495
410
488
f(x) = 0.000612701270434404 x + 462.612736410929R² = 0.19035445894851
Scienceperformance
Cumulative expenditure (US$ converted using PPPs)
One caution:
Although better education results in more money,
More money does not automatically result in better education .
6666A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Port
ug
al
Sp
ain
Sw
itze
rlan
d
Tu
rkey
Belg
ium
Kore
a
Lu
xem
bou
rg
Germ
an
y
Gre
ece
Jap
an
Au
stra
lia
Un
ited
Kin
gd
om
New
Zeala
nd
Fra
nce
Neth
erl
an
ds
Den
mark
Italy
Au
stri
a
Cze
ch
Rep
ub
lic
Hu
ng
ary
Norw
ay
Icela
nd
Irela
nd
Mexic
o
Fin
lan
d
Sw
ed
en
Un
ited
Sta
tes
Pola
nd
Slo
vak R
ep
ub
lic
-10
-5
0
5
10
15
Salary as % of GDP/capita Instruction time 1/teaching time 1/class sizePort
ug
al
Sp
ain
Sw
itze
rlan
d
Tu
rkey
Belg
ium
Kore
a
Lu
xem
bou
rg
Germ
an
y
Gre
ece
Jap
an
Au
stra
lia
Un
ited
Kin
gd
om
New
Zeala
nd
Fra
nce
Neth
erl
an
ds
Den
mark
Italy
Au
stri
a
Cze
ch
Rep
ub
lic
Hu
ng
ary
Norw
ay
Icela
nd
Irela
nd
Mexic
o
Fin
lan
d
Sw
ed
en
Un
ited
Sta
tes
Pola
nd
Slo
vak R
ep
ub
lic
-10
-5
0
5
10
15
Difference with OECD average
Spending choices on secondary schoolsContribution of various factors to upper secondary teacher compensation costs
per student as a percentage of GDP per capita (2004)
Percentage points
6767A
ndre
as S
chle
iche
r11
Feb
ruar
y 20
10A
ga
ins
t th
e o
dd
s
Thank you !
www.oecd.org; www.pisa.oecd.org– All national and international publications– The complete micro-level database
email: [email protected]
…and remember:
Without data, you are just another person with an opinion