what can we learn about the gender gap from pisa...2011/10/03 · what can we learn about the...
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![Page 1: What can we learn about the gender gap from PISA...2011/10/03 · What can we learn about the gender gap from PISA? Francesca Borgonovi and Maciej Jakubowski Paris 3 October 2011](https://reader035.vdocuments.us/reader035/viewer/2022071105/5fdf7530677f9f3f473ca7fe/html5/thumbnails/1.jpg)
1 1 P
ISA
O
ECD
Pro
gram
me
for
Inte
rnat
iona
l Stu
dent
Ass
essm
ent
Wha
t can
we
lear
n ab
out t
he
gend
er g
ap fr
om P
ISA
? Fr
ance
sca
Bor
gono
vi a
nd M
acie
j Jak
ubow
ski
Par
is 3
Oct
ober
201
1
What can we learn about the gender gap from PISA
Francesca Borgonovi Maciej Jakubowski
OECD Programme for International Student Assessment
Paris, 3 October 2011
Programme for International Student Assessment
![Page 2: What can we learn about the gender gap from PISA...2011/10/03 · What can we learn about the gender gap from PISA? Francesca Borgonovi and Maciej Jakubowski Paris 3 October 2011](https://reader035.vdocuments.us/reader035/viewer/2022071105/5fdf7530677f9f3f473ca7fe/html5/thumbnails/2.jpg)
2 2 P
ISA
O
ECD
Pro
gram
me
for
Inte
rnat
iona
l Stu
dent
Ass
essm
ent
Wha
t can
we
lear
n ab
out t
he
gend
er g
ap fr
om P
ISA
? Fr
ance
sca
Bor
gono
vi a
nd M
acie
j Jak
ubow
ski
Par
is 3
Oct
ober
201
1
This document, not published by IIEP, is distributed with the authorization of the author and has been presented on the occasion of the IIEP Policy Forum on Gender Equality in Education held on the 3-4 October, 2011 in Paris, France. The views and opinions expressed in this document are those of the author and do not necessarily represent the views of UNESCO or IIEP. The designations employed and the presentation of material throughout this document do not imply the expression of any opinion whatsoever on the part of UNESCO or IIEP concerning the legal status of any country, territory, city or area or its authorities, or concerning its frontiers or boundaries.
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3 3 P
ISA
O
ECD
Pro
gram
me
for
Inte
rnat
iona
l Stu
dent
Ass
essm
ent
Wha
t can
we
lear
n ab
out t
he
gend
er g
ap fr
om P
ISA
? Fr
ance
sca
Bor
gono
vi a
nd M
acie
j Jak
ubow
ski
Par
is 3
Oct
ober
201
1 Gender Gap in Reading
0
10
20
30
40
50
60
70
Colo
mbi
aCh
ilePe
ruA
zerb
aija
nN
ethe
rlan
dsU
nite
d St
ates
Mex
ico
Uni
ted
King
dom
Belg
ium
Braz
ilD
enm
ark
Spai
nTu
nisi
aSi
ngap
ore
Liec
hten
stei
nH
ong
Kong
-Chi
naPa
nam
aM
acao
-Chi
naCa
nada
Kore
aIn
done
sia
Arg
enti
naA
ustr
alia
Chin
ese
Taip
eiTh
aila
ndH
unga
ryPo
rtug
alSw
itze
rlan
dJa
pan
Irel
and
Luxe
mbo
urg
Serb
iaGe
rman
ySh
angh
ai-C
hina
Fran
ceA
ustr
iaU
rugu
ayIs
rael
Rom
ania
Kaza
khst
anTu
rkey
Icel
and
Esto
nia
Russ
ian
Fede
rati
onSw
eden
New
Zea
land
Ital
yGr
eece
Nor
way
Latv
iaCz
ech
Repu
blic
Pola
ndQ
atar
Dub
ai (U
AE)
Croa
tia
Slov
ak R
epub
licM
onte
negr
oKy
rgyz
stan
Slov
enia
Finl
and
Jord
anTr
inid
ad a
nd T
obag
oLi
thua
nia
Bulg
aria
Alb
ania
Girls perform better in all countries/economies
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4 4 P
ISA
O
ECD
Pro
gram
me
for
Inte
rnat
iona
l Stu
dent
Ass
essm
ent
Wha
t can
we
lear
n ab
out t
he
gend
er g
ap fr
om P
ISA
? Fr
ance
sca
Bor
gono
vi a
nd M
acie
j Jak
ubow
ski
Par
is 3
Oct
ober
201
1 The Gender Gap in Mathematics
-50
-30
-10
10
30
50
70
Colo
mbi
aLi
echt
enst
ein
Belg
ium
Chile
Uni
ted
King
dom
Uni
ted
Stat
esSw
itze
rlan
dLu
xem
bour
gA
ustr
iaSp
ain
Peru
Net
herl
ands
Fran
ceD
enm
ark
Germ
any
Braz
ilIt
aly
Hon
g Ko
ng-C
hina
Gree
ceM
exic
oU
rugu
ayTu
nisi
aM
onte
negr
oH
unga
ryCa
nada
Port
ugal
Serb
iaM
acao
-Chi
naTu
rkey
Croa
tia
Arg
enti
naA
ustr
alia
Japa
nEs
toni
aIs
rael
Aze
rbai
jan
New
Zea
land
Irel
and
Sing
apor
ePa
nam
aN
orwa
yCz
ech
Repu
blic
Chin
ese
Taip
eiTh
aila
ndPo
land
Icel
and
Rom
ania
Kore
aSl
ovak
Rep
ublic
Finl
and
Dub
ai (U
AE)
Russ
ian
Fede
rati
onLa
tvia
Slov
enia
Jord
anKa
zakh
stan
Shan
ghai
-Chi
naIn
done
sia
Swed
enBu
lgar
iaQ
atar
Kyrg
yzst
anLi
thua
nia
Trin
idad
and
Tob
ago
Alb
ania
Girls perform worse in these countries/economies
Girls perform better in these
countries/economies
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5 5 P
ISA
O
ECD
Pro
gram
me
for
Inte
rnat
iona
l Stu
dent
Ass
essm
ent
Wha
t can
we
lear
n ab
out t
he
gend
er g
ap fr
om P
ISA
? Fr
ance
sca
Bor
gono
vi a
nd M
acie
j Jak
ubow
ski
Par
is 3
Oct
ober
201
1 Gender Gap in Science
-50
-30
-10
10
30
50
70Jo
rdan
Alb
ania
Dub
ai (U
AE)
Qat
arKy
rgyz
stan
Bulg
aria
Trin
idad
and
Tob
ago
Lith
uani
aFi
nlan
dSl
oven
iaTh
aila
ndM
onte
negr
oTu
rkey
Japa
nRo
man
iaGr
eece
Indo
nesi
aCr
oati
aKa
zakh
stan
Arg
enti
naA
zerb
aija
nLa
tvia
New
Zea
land
Pola
ndCz
ech
Repu
blic
Swed
enN
orwa
yPo
rtug
alRu
ssia
n Fe
dera
tion
Isra
elIr
elan
dM
acao
-Chi
naKo
rea
Pana
ma
Ital
ySe
rbia
Uru
guay
Sing
apor
eCh
ines
e Ta
ipei
Aus
tral
iaEs
toni
aSl
ovak
Rep
ublic
Shan
ghai
-Chi
naH
unga
ryTu
nisi
aIc
elan
dH
ong
Kong
-Chi
naBr
azil
Fran
ceN
ethe
rlan
dsPe
ruCa
nada
Germ
any
Belg
ium
Mex
ico
Luxe
mbo
urg
Spai
nA
ustr
iaSw
itze
rlan
dCh
ileU
nite
d Ki
ngdo
mD
enm
ark
Uni
ted
Stat
esLi
echt
enst
ein
Colo
mbi
a
Girls perform worse in these countries/economies
Girls perform better in these
countries/economies
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6 6 P
ISA
O
ECD
Pro
gram
me
for
Inte
rnat
iona
l Stu
dent
Ass
essm
ent
Wha
t can
we
lear
n ab
out t
he
gend
er g
ap fr
om P
ISA
? Fr
ance
sca
Bor
gono
vi a
nd M
acie
j Jak
ubow
ski
Par
is 3
Oct
ober
201
1 Reading proficiency - boys and girls
1.8
6.6
16.6
26.0
27.0
16.8
4.8
0.5
05101520253035
Below Level 1b
Level 1b
Level 1a
Level 2
Level 3
Level 4
Level 5
Level 6
%
Boys
0.5
2.6
9.5
21.9
30.9
24.7
8.8
1.2
-5 5 15 25 35%
Girls
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7 7 P
ISA
O
ECD
Pro
gram
me
for
Inte
rnat
iona
l Stu
dent
Ass
essm
ent
Wha
t can
we
lear
n ab
out t
he
gend
er g
ap fr
om P
ISA
? Fr
ance
sca
Bor
gono
vi a
nd M
acie
j Jak
ubow
ski
Par
is 3
Oct
ober
201
1 Gender gap across assessment areas and at different proficiency levels
-49
5
-8
-39
12
0
-27
18
9
-60
-50
-40
-30
-20
-10
0
10
20
30
reading mathematics science
p10meanp90
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8 8 P
ISA
O
ECD
Pro
gram
me
for
Inte
rnat
iona
l Stu
dent
Ass
essm
ent
Wha
t can
we
lear
n ab
out t
he
gend
er g
ap fr
om P
ISA
? Fr
ance
sca
Bor
gono
vi a
nd M
acie
j Jak
ubow
ski
Par
is 3
Oct
ober
201
1
Trends in gender gap
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9 9 P
ISA
O
ECD
Pro
gram
me
for
Inte
rnat
iona
l Stu
dent
Ass
essm
ent
Wha
t can
we
lear
n ab
out t
he
gend
er g
ap fr
om P
ISA
? Fr
ance
sca
Bor
gono
vi a
nd M
acie
j Jak
ubow
ski
Par
is 3
Oct
ober
201
1
-25
-20
-15
-10
-5
0
5
10
15
Chile
Indo
nesia
Peru
Alb
ania
Latv
iaPo
rtug
alPo
land
Isra
elLiec
hten
stein
Braz
ilHun
gary
Germ
any
Mex
ico
Switze
rlan
dGr
eece
Den
mar
kNor
way
Belgium
OEC
D a
vera
ge-2
6Ro
man
iaHon
g Ko
ng-C
hina
Unite
d St
ates
ussian
Fed
erat
ion
Kore
aNew
Zea
land
Bulgar
iaCa
nada
Finlan
dAus
tralia
Italy
Icelan
dSp
ain
Japa
nFr
ance
Swed
enCz
ech
Repu
blic
Thailand
Irelan
dArg
entina
%
Change in the percentage of boys below proficiency Level 2
Change in the percentage of girls below proficiency Level 2
Share of students below proficiency Level 2 increased
Change in the share of boys and girls who are low performers in reading between 2000 and 2009
Share of students below proficiency Level 2 decreased
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10 10 P
ISA
O
ECD
Pro
gram
me
for
Inte
rnat
iona
l Stu
dent
Ass
essm
ent
Wha
t can
we
lear
n ab
out t
he
gend
er g
ap fr
om P
ISA
? Fr
ance
sca
Bor
gono
vi a
nd M
acie
j Jak
ubow
ski
Par
is 3
Oct
ober
201
1 Trends in reading gender gap
0
10
20
30
40
50
60
70Ch
ile
oPe
ru
oU
nite
d St
ates
o
Mex
ico
o
Belg
ium
o
Braz
il
+De
nmar
k
oSp
ain
o
Liec
hten
stei
n
oHo
ng K
ong-
Chin
a
+Ca
nada
o
Kore
a
+In
done
sia
+Ar
gent
ina
o
Aust
ralia
o
Thai
land
o
Hung
ary
o
Port
ugal
+
Switz
erla
nd
oJa
pan
o
Irela
nd
oGe
rman
y
oFr
ance
+
Isra
el
+Ro
man
ia
+Ic
elan
d
oRu
ssia
n Fe
dera
tion…
Swed
en
+N
ew Z
eala
nd
oIta
ly
oGr
eece
o
Nor
way
o
Latv
ia
oCz
ech
Repu
blic
o
Pola
nd
oFi
nlan
d
oBu
lgar
ia
oAl
bani
a
o
Scor
e po
int d
iffer
ence
Gender difference in performance in 2000
Gender difference in performance in 2009
Girls perform better in all countries/economies
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11 11 P
ISA
O
ECD
Pro
gram
me
for
Inte
rnat
iona
l Stu
dent
Ass
essm
ent
Wha
t can
we
lear
n ab
out t
he
gend
er g
ap fr
om P
ISA
? Fr
ance
sca
Bor
gono
vi a
nd M
acie
j Jak
ubow
ski
Par
is 3
Oct
ober
201
1 Reading performance improvement among boys
and girls
0 10 20 30 40 50
Korea
Poland
Chile
Score point change between 2000 and 2009
Girls Boys
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12 12 P
ISA
O
ECD
Pro
gram
me
for
Inte
rnat
iona
l Stu
dent
Ass
essm
ent
Wha
t can
we
lear
n ab
out t
he
gend
er g
ap fr
om P
ISA
? Fr
ance
sca
Bor
gono
vi a
nd M
acie
j Jak
ubow
ski
Par
is 3
Oct
ober
201
1
Gendered Career Expectations
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13 13 P
ISA
O
ECD
Pro
gram
me
for
Inte
rnat
iona
l Stu
dent
Ass
essm
ent
Wha
t can
we
lear
n ab
out t
he
gend
er g
ap fr
om P
ISA
? Fr
ance
sca
Bor
gono
vi a
nd M
acie
j Jak
ubow
ski
Par
is 3
Oct
ober
201
1 Ambitious girls and boys
0
10
20
30
40
50
60
70
80
90
100
Jord
anAz
erba
ijan
Turk
eyM
exic
oTu
nisia
Colo
mbi
aIs
rael
Uru
guay
Kyrg
yzst
anCh
ileBu
lgar
iaAr
gent
ina
Thai
land
Russ
ian
Fede
ratio
nM
acao
-Chi
naCh
ines
e Ta
ipei
Uni
ted
Stat
esIn
done
siaLi
thua
nia
Braz
ilSp
ain
Kore
aIc
elan
dPo
rtug
alG
reec
eLu
xem
bour
gIre
land
Italy
Cana
daSl
ovak
Rep
ublic
Belg
ium
Slov
enia
Latv
iaHo
ng K
ong-
Chin
aN
ew Z
eala
ndPo
land
Aust
ralia
OEC
D av
erag
eRo
man
iaM
onte
negr
oEs
toni
aU
nite
d Ki
ngdo
mSe
rbia
Nor
way
Hung
ary
Net
herla
nds
Czec
h Re
publ
icFr
ance
*Ja
pan*
Denm
ark
Finl
and
Croa
tiaSw
eden
Aust
riaG
erm
any*
Switz
erla
nd
All students Boys Girls
Percentage of students who plan to work in ISCO major occupational group 1 & 2, by gender
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14 14 P
ISA
O
ECD
Pro
gram
me
for
Inte
rnat
iona
l Stu
dent
Ass
essm
ent
Wha
t can
we
lear
n ab
out t
he
gend
er g
ap fr
om P
ISA
? Fr
ance
sca
Bor
gono
vi a
nd M
acie
j Jak
ubow
ski
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Oct
ober
201
1
ISCO code Boys Number of OECD
countries
Number of partner
countries
ISCO code Girls Number of OECD
countries
Number of partner
countries
3475 athletes, sports persons 27 13 2221 medical doctors 32 21
2221 medical doctors 26 15 5141 hairdressers, barbers, beauticians etc workers 28 10
7231 motor vehicle mechanics & fitters 25 6 2421 lawyers 25 17
2140 architects, engineers 14 11 2445 psychologists 25 10
5162 police officers 14 9 2451 authors journalists & other writers 20 8
2141 architects town & traffic planners 13 2 3471 decorators & commercial designers 16 8
5122 cooks 12 7 2230 nursing & midwifery profess 13 6
7137 building etc electricians 10 1 2300 teaching professionals 12 10
7124 carpenters & joiners 10 0 2331 primary education teaching professionals 12 4
2132 computer programmers 10 10 2223 veterinarians 12 5
2421 lawyers 10 10 2141 architects town & traffic planners 10 2
2130 computing professionals 8 1 3231 nursing associate professionals 9 2
2131 computer systems designers & analysts 7 5 2320 secondary education teaching professionals 7 3
2411 accountants 6 5 2332 pre-primary educ. teaching professionals 9 1
2149 architects engineers 6 11 3226 physiotherapists etc associate professionals 7 0
3121 computer assistants 6 1 5220 shop salespersons & demonstrators 6 2
1310 small enterprise general managers 6 11 2411 accountants 5 9
2300 teaching professionals 6 5 3320 pre-primary education teaching associate professionals 5 0
7136 plumbers & pipe fitters 5 1 4100 office clerks 4 3
2451 authors journalists & other writers 4 0 5131 child-care workers 4 0
3471 decorators & commercial designers 4 1 2211 biologists, botanists zoologists etc professionals 3 3
2320 secondary education teaching professionals 4 2 2321 sec. teachers, academic track incl. middle school 4 6
Source: OECD PISA 2006 Database.
Most popular careers according to PISA
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15 15 P
ISA
O
ECD
Pro
gram
me
for
Inte
rnat
iona
l Stu
dent
Ass
essm
ent
Wha
t can
we
lear
n ab
out t
he
gend
er g
ap fr
om P
ISA
? Fr
ance
sca
Bor
gono
vi a
nd M
acie
j Jak
ubow
ski
Par
is 3
Oct
ober
201
1
0 5 10 15 20 25 30 35
Montenegro* 4.5Kyrgyzstan 5.0
Netherlands 5.1Azerbaijan 5.2
Macao-China 5.7Finland 6.0
United Kingdom 7.2Korea 7.5
New Zealand 7.6Hong Kong-China 8
Denmark 8.2Germany 8.9
Japan 9.0Austria 9.1
Switzerland 9.1Indonesia* 9.3
United States 9.4Australia 9.5Sweden 9.8Tunisia 10.2Croatia 10.2France 10.3
Luxembourg 10.4Ireland 10.5Serbia 10.6
Iceland 10.6Canada 10.7
Israel 10.8Brazil 11.0
Romania 11.0Uruguay 11.0
OECD average 11.3Bulgaria* 11.5Hungary 11.6
Argentina 11.7Lithuania 11.9
Belgium 12.2Russian Federation 12.4
Greece 12.5Czech Republic 12.9
Italy 13.1Slovak Republic 13.1
Chinese Taipei 13.1Norway 13.4Estonia 13.7Turkey 14.1
Spain 14.4Portugal 14.9
Latvia 14.9Slovenia 15.2
Chile 16.4Colombia 16.6
Mexico 16.7Thailand 17.5
Poland 19.6Jordan 24.1
Girls Boys
Proportion of boys and girls
planning a career in
engineering or computing
Percentage of all students who plan a career
engineering or computing
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16 16 P
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0 5 10 15 20 25 30 35
Kyrgyzstan 24.3Colombia 23.2
Brazil 22.3Chile 20.5
United States 20.3Tunisia 20.1
Israel 19.1Canada 18.9Jordan* 18.7
Bulgaria* 18.0Portugal 17.4Uruguay 16.9
Indonesia 16.3France 15.8
Azerbaijan 15.6Thailand 15.6
Mexico 15.2Iceland 14.6
New Zealand 14.3Ireland 13.9
Argentina 13.7Slovenia 13.1
Spain 13.1Italy 11.9
Serbia 11.7Japan 11.5
OECD average 11.5Australia 11.3
Turkey 11.1Poland 10.7
Denmark 10.5United Kingdom 10.5
Romania 10.4Hong Kong-China* 10.3
Norway 10.1Croatia 9.7
Montenegro 9.7Macao-China 9.4Netherlands 9.2
Finland 9.1Greece 9.0
Belgium 8.6Russian Federation 8.5
Luxembourg 8.3Switzerland 8.2
Sweden 8.2Austria 7.7
Lithuania 7.6Germany 7.5
Chinese Taipei* 6.9Hungary 6.7Estonia 6.4
Slovak Republic 6.3Korea 6.0Latvia 5.4
Czech Republic 5.3
Girls Boys
Proportion of boys and girls
planning a career in health
services (excluding nursing)
Percentage of all students who plan a career in health
services
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17 17 P
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1 The Gender Gap in Motivation
Australia
AustriaBelgium
Canada
Czech Republic
Denmark
Finland
FranceGermany
Greece
Hungary Ireland
Italy
Korea
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Spain
Sweden
Switzerland
Turkey
United States
Brazil
10
15
20
25
30
35
40
45
-0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
Fem
ales
gra
duat
ion
rate
s in
mat
hem
atic
s/co
mpu
ting
Motivation gap (boys - girls)
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18 18 P
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1 Summary
Gender gaps in schools are more evident when looking at top performers in mathematics and low performers in reading. Policy decisions should aim at encouraging talented girls to study mathematics and science at the most advanced levels.
Lack of reading skills among low performing boys is worrying. Policies aiming at helping boys to acquire reading skills are especially needed among those with basic reading problems.
Career preferences and motivation seems to be more important than achievement for future choices of students. Even top-skilled girls at age 15 rarely opt for engineering or computing.
Achievement-focused policies will not change the relative disadvantage of women in labour markets.
School level policies aimed at attracting girls to mathematics and science as future career options should be part of more general policies that try to change traditional views on the role of women as professionals.
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19 19 P
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1 The OECD Gender Initiative
Recognising the importance of gender equality, the OECD has embarked on a Horizontal Project in Gender Equality in three areas key to economic opportunity: Education, Employment and Entrepreneurship
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20 20 P
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ISA
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1 The OECD Gender Initiative
develop more detailed knowledge on KEY barriers in the “three Es”
Establish standard indicators to measure progress in closing gender gaps
Collect better and more comparable data on gender gaps in entrepreneurship – expected outcome OECD database
Promote an exchange of best practices and policy transferability between OECD countries and emerging economies
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21 21 P
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Pro
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Ass
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n ab
out t
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er g
ap fr
om P
ISA
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1
Thank you !
Find out more about PISA at… OECD www.pisa.oecd.org
Email: [email protected]