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Why quality in education matters And what it takes to improve it. Washington, April 28, 2010 Andreas Schleicher Education Policy Advisor of the OECD Secretary-General. Know w hy you are looking The yardstick for success is no longer just improvement by national standards… - PowerPoint PPT Presentation
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11A
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chle
iche
rW
ashi
ngto
n, A
pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
Why quality in education mattersAnd what it takes to improve it
Washington, April 28, 2010
Andreas SchleicherEducation Policy Advisor of the OECD Secretary-General
22A
ndre
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chle
iche
rW
ashi
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pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters 1. Know why you are looking
The yardstick for success is no longer just improvement by national standards…
… but the best performing education systems globally
2. Know what you are looking for The kind of ‘human capital’ that makes a
difference for individuals and nations3. How do we recognise it when we found it?
The link between skills, and economic and social outcomes
4. Policy implications Understanding what contributes to the success of
education systems and improving performance .
AustraliaAustriaCzech RepublicDenmarkFinlandGermanyGreeceHungaryIcelandIrelandItalyJapanNetherlandsNew ZealandNorwayPolandPortugalSlovak RepublicSpainSwedenUnited KingdomUnited States
0 10 20 30 40 50 60 700
5000
10000
15000
20000
25000
30000
1995Ex
pend
iture
per
stud
ent a
t ter
tiary
leve
l (U
SD)
Tertiary-type A graduation rate
A world of change – higher education
Graduate supply
Cost
per
st
uden
t
AustraliaAustriaCzech RepublicDenmarkFinlandGermanyGreeceHungaryIcelandIrelandItalyJapanNetherlandsNew ZealandNorwayPolandPortugalSlovak RepublicSpainSwedenUnited KingdomUnited States
0 10 20 30 40 50 60 700
5000
10000
15000
20000
25000
30000
1995Ex
pend
iture
per
stud
ent a
t ter
tiary
leve
l (U
SD)
Tertiary-type A graduation rate
A world of change – higher education
United States
Finland
Graduate supply
Cost
per
st
uden
t
AustraliaAustriaCzech RepublicDenmarkFinlandGermanyGreeceHungaryIcelandIrelandItalyJapanNetherlandsNew ZealandNorwayPolandPortugalSlovak RepublicSpainSwedenUnited KingdomUnited States
0 10 20 30 40 50 60 700
5000
10000
15000
20000
25000
30000
2000Ex
pend
iture
per
stud
ent a
t ter
tiary
leve
l (U
SD)
Tertiary-type A graduation rate
A world of change – higher education
AustraliaFinlandUnited
Kingdom
AustraliaAustriaCzech RepublicDenmarkFinlandGermanyGreeceHungaryIcelandIrelandItalyJapanNetherlandsNew ZealandNorwayPolandPortugalSlovak RepublicSpainSwedenUnited KingdomUnited States
0 10 20 30 40 50 60 700
5000
10000
15000
20000
25000
30000
2001Ex
pend
iture
per
stud
ent a
t ter
tiary
leve
l (U
SD)
Tertiary-type A graduation rate
A world of change – higher education
AustraliaAustriaCzech RepublicDenmarkFinlandGermanyGreeceHungaryIcelandIrelandItalyJapanNetherlandsNew ZealandNorwayPolandPortugalSlovak RepublicSpainSwedenUnited KingdomUnited States
0 10 20 30 40 50 60 700
5000
10000
15000
20000
25000
30000
2002Ex
pend
iture
per
stud
ent a
t ter
tiary
leve
l (U
SD)
Tertiary-type A graduation rate
A world of change – higher education
AustraliaAustriaCzech RepublicDenmarkFinlandGermanyGreeceHungaryIcelandIrelandItalyJapanNetherlandsNew ZealandNorwayPolandPortugalSlovak RepublicSpainSwedenUnited KingdomUnited States
0 10 20 30 40 50 60 700
5000
10000
15000
20000
25000
30000
2003Ex
pend
iture
per
stud
ent a
t ter
tiary
leve
l (U
SD)
Tertiary-type A graduation rate
A world of change – higher education
AustraliaAustriaCzech RepublicDenmarkFinlandGermanyGreeceHungaryIcelandIrelandItalyJapanNetherlandsNew ZealandNorwayPolandPortugalSlovak RepublicSpainSwedenUnited KingdomUnited States
0 10 20 30 40 50 60 700
5000
10000
15000
20000
25000
30000
2004Ex
pend
iture
per
stud
ent a
t ter
tiary
leve
l (U
SD)
Tertiary-type A graduation rate
A world of change – higher education
AustraliaAustriaCzech RepublicDenmarkFinlandGermanyGreeceHungaryIcelandIrelandItalyJapanNetherlandsNew ZealandNorwayPolandPortugalSlovak RepublicSpainSwedenUnited KingdomUnited States
0 10 20 30 40 50 60 700
5000
10000
15000
20000
25000
30000
2005Ex
pend
iture
per
stud
ent a
t ter
tiary
leve
l (U
SD)
Tertiary-type A graduation rate
A world of change – higher education
AustraliaAustriaCzech RepublicDenmarkFinlandGermanyGreeceHungaryIcelandIrelandItalyJapanNetherlandsNew ZealandNorwayPolandPortugalSlovak RepublicSpainSwedenUnited KingdomUnited States
0 10 20 30 40 50 60 700
5000
10000
15000
20000
25000
30000
2006Ex
pend
iture
per
stud
ent a
t ter
tiary
leve
l (U
SD)
Tertiary-type A graduation rate
A world of change – higher education
United States
Australia
Finland
1212 E
duca
tion
Indi
cato
rs
Prog
ram
me
2009
edi
tion
of
Educ
atio
n at
a G
lanc
e
DenmarkSwedenNorway
New ZealandFranceTurkey
GermanyAustralia
SpainAustria
BelgiumFinlandCanada
OECD averageKorea
IrelandHungary
PolandCzech RepublicUnited States
ItalyPortugal
-250,000 -150,000 -50,000 50,000 150,000 250,000 350,000 450,0007,342
18,80223,30640,036
40,26041,090
48,02448,714
55,69560,51963,414
64,66469,235
82,00785,586
104,410127,691
146,539146,673
169,945173,889
186,307
Direct cost Gross earnings benefits Income tax effect Social contribution effectTransfers effect Unemployment effect Net present value in USD equivalent
USD equivalentA8.3
Components of the private net present value for a male with higher education
Net present value in
USD equivalent
35K$56K$ 367K$105K$27K$ 26K$ 170K$
1313 E
duca
tion
Indi
cato
rs
Prog
ram
me
2009
edi
tion
of
Educ
atio
n at
a G
lanc
e
TurkeyDenmark
SwedenNorway
SpainKorea
CanadaNew Zealand
FranceAustria
AustraliaPortugal
OECD averageFinlandPoland
GermanyItaly
IrelandHungaryBelgium
United StatesCzech Republic
0 50,000 100,000 150,000 200,000
10,34614,23617,19717,85119,75221,28023,87528,193
36,73037,586
47,36850,27151,95455,61257,221
63,60463,756
74,21994,80496,186100,119
160,834
Public cost and benefits for a male obtaining post-secondary education
Public benefit
s
Public
costs
Net present value, USD equivalent
(numbers in orange show
negative values)
USD equivalent
1414A
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r16
Sep
tem
ber 2
009
Impa
ct o
f in
tern
atio
nal A
sses
smen
ts
Know what you are looking for
The kind of human capital that makes a difference for people and nations
1515A
ndre
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chle
iche
rW
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n, A
pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters Latin America then…
Hanushek 2009
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
1616A
ndre
as S
chle
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ngto
n, A
pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
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
Latin America then and now…GDP/pop
1960Years
schoolingGrowth
1960-2000GDP/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 26147Hanushek 2009
1717A
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as S
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n, A
pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters Latin America then and now…
Why quality is the key
Hanushek 2009
GDP/pop 1960
Years schooling
Growth 1960-2000
GDP/pop 2000
PISA testscore
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
1818A
ndre
as S
chle
iche
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pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
Coverage of world economy 77%81%83%85%86%87%
OECD’s PISA assessment of the knowledge and skills of 15-year-olds
1919A
ndre
as S
chle
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rW
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pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
Average 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 FederationLuxembourgSlovak Republic,Spain,
Iceland LatviaCroatia
SwedenDenmarkFrancePolandHungary
AustriaBelgiumIrelandCzech Republic SwitzerlandMacao- China
GermanyUnited Kingdom
Korea
J apanAustralia
SloveniaNetherlandsLiechtenstein
New ZealandChinese Taipei
Hong Kong- China
Finland
CanadaEstonia
United States LithuaniaNorway
445
465
485
505
525
545
565
616
Not just about poor kids in poor
neighborhoods but about many kids in
many neighborhoods
U.S. city of over 1m
U.S. small town (3-15k)
U.S. suburban (15-100k)
Poland 2000
2020A
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as S
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pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
New
Zea
land
Finl
and
Unite
d Ki
ngdo
m
Aust
ralia
Japa
n
Cana
da
OECD
ave
rage
Portu
gal
Italy
Turk
ey
Mex
ico
Unite
d St
ates
Kore
a
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…
2121A
ndre
as S
chle
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Sep
tem
ber 2
009
Impa
ct o
f in
tern
atio
nal A
sses
smen
ts
How do we know that we found it?
To what extent knowledge and skills matter for the success of individuals and economies
2222A
ndre
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chle
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n, A
pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
Age 19
Age 21
Age 21
048
121620
Level 2Level 3
Level 4Level 5
Increased likelihood of postsec. 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)Odds ratio
College entry
School marks at age 15
PISA performance at age
15
2323A
ndre
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chle
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n, A
pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters Modelling the 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 as new technologies are developed and implemented, making use of the new higher skills
Estimate the total gains over the lifetime of the generation born this year .
2424A
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pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
High science performance
Low science performance
Average performanceof 15-year-olds in science – extrapolate and apply
616310
360
410
460
510
560Finland
Hong Kong-ChinaCanadaChinese TaipeiEstonia JapanNew ZealandAustraliaNetherlandsLiechtenstein KoreaSloveniaGermanyUnited KingdomCzech Republic SwitzerlandMacao-China AustriaBelgiumIreland HungarySwedenPolandDenmark
France CroatiaIcelandLatviaUnited States Slovak Republic,Spain,LithuaniaNorway LuxembourgRussian FederationItalyPortugal Greece
Israel
TurkeyJordanThailand Romania
Montenegro Mexico
IndonesiaArgentinaBrazil ColombiaTunisia
Azerbaijan
Qatar
Kyrgyzstan
Imagine…
...we could improve every system by 25 PISA points over the
next 20 years
(which is what Poland did in the last 6 years)
2525A
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pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
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
rcen
t add
ition
to G
DP
2626A
ndre
as S
chle
iche
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n, A
pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
0
2000
4000
6000
8000
10000
12000
14000
Potential increase in economic output (bn $)
Increase average performance by 25 PISA points (Total 115 trillion $)
bn$
2727A
ndre
as S
chle
iche
rW
ashi
ngto
n, A
pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
High science performance
Low science performance
Average performanceof 15-year-olds in science – extrapolate and apply
616310
360
410
460
510
560Finland
Hong Kong-ChinaCanadaChinese TaipeiEstonia JapanNew ZealandAustraliaNetherlandsLiechtenstein KoreaSloveniaGermanyUnited KingdomCzech Republic SwitzerlandMacao-China AustriaBelgiumIreland HungarySwedenPolandDenmark
France CroatiaIcelandLatviaUnited States Slovak Republic,Spain,LithuaniaNorway LuxembourgRussian FederationItalyPortugal Greece
Israel
TurkeyJordanThailand Romania
Montenegro Mexico
IndonesiaArgentinaBrazil ColombiaTunisia
Azerbaijan
Qatar
Kyrgyzstan
Imagine…
...we could ensure that every child reaches at least the PISA baseline
performance level 2
2828A
ndre
as S
chle
iche
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n, A
pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
0
2000
4000
6000
8000
10000
12000
14000 Potential increase in economic output (bn $)
Raise everyone to minimum of 400 PISA pointsbn$
2929A
ndre
as S
chle
iche
rW
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ngto
n, A
pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
Mexico
Greece Ita
ly
United
State
sPo
land
Norway
Slova
k Rep
ublic
France
Austria
Icelan
d
Czech R
epub
lic
United
King
dom
Austral
iaJap
anKo
rea0%
200%
400%
600%
800%
1000%
1200%
Raise everyone to minimum of 400 PISA points% currrent
GDP
3030A
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n, A
pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters 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.
3131A
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chle
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Sep
tem
ber 2
009
Impa
ct o
f in
tern
atio
nal A
sses
smen
ts
Implications
Understanding what contributes to the success of education systems and improving
performance
3232A
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pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
Money 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) = 0.000612701270434402 x + 462.612736410929R² = 0.190354458948509
Scienceperformance
Cumulative expenditure (US$ converted using PPPs)
Question:If better education results in more money,
Does more money result in better education?
3333A
ndre
as S
chle
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n, A
pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
Portu
gal
Spain
Switz
erlan
d
Turk
ey
Belg
ium
Kore
a
Luxe
mbo
urg
Germ
any
Gree
ce
Japa
n
Aust
ralia
Unite
d Ki
ngdo
m
New
Zeala
nd
Fran
ce
Neth
erlan
ds
Denm
ark
Italy
Aust
ria
Czec
h Re
publ
ic
Hung
ary
Norw
ay
Icela
nd
Irelan
d
Mexic
o
Finlan
d
Swed
en
Unite
d St
ates
Polan
d
Slov
ak R
epub
lic
-10
-5
0
5
10
15
Salary as % of GDP/capita Instruction time 1/teaching time 1/class sizePo
rtuga
l
Spain
Switz
erlan
d
Turk
ey
Belg
ium
Kore
a
Luxe
mbo
urg
Germ
any
Gree
ce
Japa
n
Aust
ralia
Unite
d Ki
ngdo
m
New
Zeala
nd
Fran
ce
Neth
erlan
ds
Denm
ark
Italy
Aust
ria
Czec
h Re
publ
ic
Hung
ary
Norw
ay
Icela
nd
Irelan
d
Mexic
o
Finlan
d
Swed
en
Unite
d St
ates
Polan
d
Slov
ak R
epub
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
3434A
ndre
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chle
iche
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n, A
pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
High ambitions and universal
standardsRigor, focus and
coherence
Great systems attract great teachers and
provide access to best practice and quality
professional development
3535A
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pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
Challenge and support
Weak support
Strong support
Lowchallenge
Highchallenge
Strong performanceSystemic improvement
Poor performanceImprovements idiosyncratic
ConflictDemoralisation
Poor performanceStagnation
3636A
ndre
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n, A
pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters 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
3737A
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pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters 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
3838A
ndre
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pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
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
3939A
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pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
NoYes
0
10
20
30
40
50
60
70
No
Yes0
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
4040A
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pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
Public and private schools
0 20 40 60 80 100
LuxembourgJ apanI taly
SwitzerlandFinland
DenmarkCzech Republic
SwedenHungaryAustria
PortugalUnited States
NetherlandsSlovak Republic
KoreaI reland
SpainCanadaMexico
New ZealandGermany
OECDUnited Kingdom
Government schoolsGovernment dependent privateGovernment independent private
- 150 - 100 - 50 0 50 100
Observed perf ormance diff erence
Diff erence af ter accounting f or socio-economic background of students and schools
Private schools perform better
Public schools perform better
%Score point difference
4141A
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pril
28, 2
010
Why
qua
lity
in e
duca
tion
mat
ters
Pooled 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
Scor
e po
int d
iffer
ence
in s
cienc
e
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 effectEffect after accounting for the socio-economic
background of students, schools and countries
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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
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Durchschnittliche Schülerleistungen im Bereich Mathematik
Low average performanceLarge socio-economic disparities
High average performanceLarge socio-economic disparities
Low average performanceHigh social equity
High average performanceHigh 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
KoreaCzech Republic United Kingdom
AustriaGermany
Netherlands
SwitzerlandIrelandBelgium
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 stratificationLow degree of stratification
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•Principled•Strategic partnership
•Negotiated•Pragmatic .
•Top-down•Antagonistic .
•Leading•Evidence-driven•Achieving high reliability and innovation .
• Enabling• Incentivising
.
•World class performance.
•Continuous learning and innovation .
Good Great
•Accommodating•Evidence-based•Adopting best . practice
•Regulating .•Capacity-building
•Transparency .•Spreading best practice
• Implementing•Accepting evidence•Adopting minimum standards
•Prescribing .• Justifying
• Tackling underperformance
Adequate GoodPoor Adequate
Main focus of assessment
Role of government
Role of professions
Nature of relationship between government
and professions
Phases of development
Main outcomes• Improvement in outcomes
•Reduction of public anxiety.
•Steady improvement
•Growing public satisfaction .
•Consistent quality•Public engagement and co-production .
Getting the order right
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Paradigm shiftsThe old bureaucratic system The modern enabling system
Hit and miss Universal high standards
Uniformity Embracing diversity
Provision Outcomes
Bureaucratic look-up Devolved – look outwards
Talk equity Deliver equity
Prescription Informed profession
Conformity Ingenious
Curriculum-centred Learner-centred
Interactive Participative
Individualised Community-centred
Delivered wisdom User-generated wisdom
Management Leadership
Public vs private Public with private
Culture as obstacle Culture as capital
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Thank you !
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