andreas schleicher, oecd directorate for education, 2003 organisation for economic co-operation and...
TRANSCRIPT
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3 Organisation for Economic Co-Operation and
Development
Literacy Skills for the World of
Tomorrow Results from the OECD Programme
for International Student Assessment (PISA)1 July 2003
Andreas SchleicherHead, Indicators and Analysis Division
Directorate for Education
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What PISA provides A comprehensive assessment of the yield
of education systems including and beyond the curriculum
Comparable skill measures that can guide policy decisions
Insights into the mix of factors which contribute to the development of knowledge and skills
and how these factors operate similarly or differently across countries
A strong substantive and multicultural core for defining performance targets
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3
0
10
20
30
40
50
60
70
80
90
100U
nite
d S
tate
s
Ger
man
y
Can
ada
Jap
an
Uni
ted K
ingd
om
Fin
land
OECD
ave
rage
Fra
nce
Kor
ea
Arg
enti
na
Chile
Peru
Ital
y
Spa
in
Bra
zil
Mex
ico
Indon
esia
Thai
land
55-64 45-54 35-44 25-34
Rise in baseline qualifications over one generation
Proportion of the population with completed upper secondary education by age group (37 countries)
10
14
4
11
1
24
37
34
9
131
26
26
28
29
29
34
32
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To analyse, compare, contrast, and evaluate
To think imaginatively
To apply knowledge in real-life situations
To communicate thoughts and ideas effectively
Literacy in PISAAbout the capacity of young adults to access,
manage, integrate, evaluate and reflect on written information
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Reading Literacy
Using, interpreting
and reflecting on written
material
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Mathematical literacy
Emphasis is on mathematical knowledge put into functional use in a multitude of different situations
in varied, reflective and insight-based ways
Reading Literacy
Using, interpreting
and reflecting on written
material
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Mathematical literacy
Emphasis is on mathematical knowledge put into functional use in a multitude of different situations
in varied, reflective and insight-based ways
Reading Literacy
Using, interpreting
and reflecting on written
material
Scientific Literacy
Using scientific knowledge, identifying scientific questions, and drawing evidence-based conclusions
to understand and make decisions about the natural world
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Literacy Skills for the World of Tomorrow
1.1. Where we are today What PISA shows about the
preparedness of students in non-OECD countries
2.2. Where we can be What the best performing countries
show can be achieved
3.3. How we might get there Some policy levers
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Below Level 1These students may be able to
read, but have not acquired the skills to use reading for
learning
Reading Literacy Level 1Recognise main theme on a familiar topic, make simple
connections
10%
22%
12%
6%
22%
29%
OECD Average
PISA Proficiency Levels in Reading Literacy
Reading Literacy Level 5Evaluating information and
building hypotheses Drawing on specialised
knowledge, Accommodating concepts contrary to expectations
Level 5
Level 4
Level 3
Level 2
Level 1
Below Level 1
23%
22%
Non-OECD average
OECD avera
ge
25%
19%
9%
2%
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1910 10
3 4 2 1 1 1 0 0 0 0
32
3122
13 149 9 5 5 3 2 1 0 1
29
33
29
27 25
22 2021 17
13 11 8 6 5
1417
22
29 26
27 26 3730
2824
21 2515
5 712
1918
2221
27
2833
28
2738
26
2 3 6 9 13 18 2310
20 2335
4431
54
20%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Fin
land
Hon
g Kon
g-Chi
na
OECD
Ave
rage
Rus
sian
Fed
erat
ion
Latv
ia
Bul
gari
a
Arg
enti
na
Tha
iland
Chi
le
Bra
zil
FYR M
aced
onia
Alb
ania
Indo
nesi
a
Peru
Percentage of students at each of the proficiency levels in reading literacy
Level 2
Level 1
Below Level 1
Level 5
Level 4
Level 3
1 628
41
35
32
36
37
38
40
39
29
33
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-30
-10
10
30
50
70
90
110
130
150
170A
rgen
tina
Bul
gari
a
Peru
Isra
el
Chi
le
Alb
ania
FYR M
aced
onia
Hon
g Kon
g-Chi
na
OECD
ave
rage
Bra
zil
Latv
ia
Rus
sian
Fed
erat
ion
Indo
nesi
a
Tha
iland
Kor
ea
Fin
land
Variation in reading literacy performance
1728
41
35
32
36
37
38
40
39
29
33
630
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-80
-60
-40
-20
0
20
40
60
80
100
Arg
enti
na
Bul
gari
a
Peru
Isra
el
Chi
le
Alb
ania
FYR M
aced
onia
Hon
g Kon
g-Chi
na
OECD
ave
rage
Bra
zil
Latv
ia
Rus
sian
Fed
erat
ion
Indo
nesi
a
Tha
iland
Kor
ea
Fin
land
Variation in reading literacy performance
1728
41
35
32
36
37
38
40
39
29
33
630
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-80
-60
-40
-20
0
20
40
60
80
100
Arg
enti
na
Bul
gari
a
Peru
Isra
el
Chi
le
Alb
ania
FYR M
aced
onia
Hon
g Kon
g-Chi
na
OECD
ave
rage
Bra
zil
Latv
ia
Rus
sian
Fed
erat
ion
Indo
nesi
a
Tha
iland
Kor
ea
Fin
land
Variation of performance
between schools
Variation of performance within
schools
Variation in reading literacy performance
1728
41
35
32
36
37
38
40
39
29
33
630
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Low Performan
ce
HighPerforman
ce
Low performance
Low social equity
High performance
Low social equity
Low performance
High social equity
High performance
High social equityLow
Social equityHigh
Social equity
Thailand
Peru
Liechtenstein
Russian Fed.Latvia
Israel
FYR MacedoniaIndonesia
Hong Kong-China/
Chile
Bulgaria
Albania
Brazil
Argentina
Finland
KoreaJ apan
Iceland
Canada
Ireland
Sweden
SpainI taly
PolandGreecePortugal
Luxembourg
Mexico
Denmark
AustriaNorway
New ZealandAustralia
United Kingdom
Belgium/FranceUnited States
SwitzerlandCzech Republik
HungaryGermany
325
350
375
400
425
450
475
500
525
550
-25 -20 -15 -10 -5 0 5 10 15 20 25
1717
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Low Performan
ce
HighPerforman
ce
Low performance
Low social equity
High performance
Low social equity
Low performance
High social equity
High performance
High social equityLow
Social equityHigh
Social equity
Thailand
Peru
Liechtenstein
Russian Fed.
LatviaIsrael
FYR Macedonia
Indonesia
Hong Kong-China
Chile
Bulgaria
Albania
Brazil
Argentina
Finland
KoreaJ apan
Iceland
CanadaIreland
Sweden
SpainI taly
PolandGreece
Portugal
Luxembourg
Mexico
Denmark
AustriaNorway
New Zealand
AustraliaUnited Kingdom
BelgiumFranceUnited States
SwitzerlandCzech Republik
Hungary
Germany
325
350
375
400
425
450
475
500
525
550
-25 -20 -15 -10 -5 0 5 10 15 20 25
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0
10
20
30
40
50
60
70
80
90
OE
CD
ave
rag
e
Bu
lga
ria
Isra
el
Pe
ru
FY
R M
ace
do
nia
Arg
en
tina
Ru
ssia
nF
ed
era
tion
La
tvia
Ch
ile
Bra
zil
Ind
on
esi
a
Ho
ng
Ko
ng
-C
hin
a
Th
aila
nd
Eff ect of students' economic, social and cultural statusEff ect of schools' mean economic, social and cultural status
Effects of students’ and schools’ socio-economic background on student performance
(Effects associated with half a standard deviation on the socio-economic index)
1919
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Place of birth and student performance
0
5
10
15
20
25
30
35
40
45
50H
ong
Kon
g-Chi
na
Luxem
bou
rg
Isra
el
Aus
tral
ia
Latv
ia
Sw
itze
rlan
d
Liec
hten
stei
n
Can
ada
New
Zea
land
Ger
man
y
Rus
sian
Fed
erat
ion
FYR M
aced
onia
Irel
and
Arg
enti
na
Spa
in
Alb
ania
Tha
iland
Bul
gari
a
Indo
nesi
a
Peru
Chi
le
250
300
350
400
450
500
550
600
650
Percentage of non-native and first-generation students
Performance of non-native, first-generation students on the combined
reading literacy scale
First-generation studentsNon-native students
First-generation students
Native students
2020
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Gender differences- 60 - 40 - 20 0 20 40
Favouring girls
Favouring boysReadin
g literacy
Mathematical literacy
Scientific literacy
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Percentage of students at or below Level 1 in Reading Literacy
%
81
7275
51 5054 53
81
3741
35
22
12
60
32
2428
8
1317 18
54
13
20 20
13
3
52
0
20
40
60
80
100A
lban
ia
FYR M
aced
onia
Indon
esia
Thai
land
Bul
gari
a
Chile
Arg
enti
na
Peru
Isra
el
Latv
ia
Rus
sian
Fed
erat
ion
OECD
ave
rage
Hon
g Kon
g-Chin
a
Bra
zil
Males Females
2222
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Reading literacy, reading engagement and gender
516
464
494
442
400
420
440
460
480
500
520
540
High engagement in reading Low engagement in reading
Perf
orm
ance
on
com
bin
ed
read
ing
litera
cy s
cale
Females
Males
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Job-expectations of 15-year-olds at age 30
100
80
60
40
20
0
20
40
60
80
100
Bra
zil
Mex
ico
Peru
Kor
ea
Uni
ted S
tate
s
Arg
enti
na
FYR M
aced
onia
Port
ugal
Indon
esia
Ital
y
Alb
ania
Hon
g Kon
g-Chin
a
Chile
Latv
ia
Isra
el
Uni
ted K
ingd
om
Fin
land
Hun
gary
Ger
man
y
Bul
gari
a
Liec
hte
nste
in
Sw
itze
rlan
d
Cze
ch R
epub
lic
Fra
nce
Rus
sian
Fed
erat
ion
Jap
an
Thai
land
Males, White-Collar High-Skilled Males, White-Collar Low-Skilled
Females, White-Collar High-Skilled Females, White-Collar Low-Skilled
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Low Social equity
HighSocial equity
HighPerforman
ce
Low Performan
ce
E.g. Learning environment and course offering
High degree of autonomy
Low degree of autonomy
% Variance between schools
Thailand
Peru
Liechtenstein
Russian Fed.
LatviaIsrael
FYR Macedonia
Indonesia
Hong Kong-China
Chile
Bulgaria
Albania
Brazil
Argentina
Finland
KoreaJ apan
Iceland
CanadaIreland
Sweden
SpainI taly
PolandGreece
Portugal
Luxembourg
Mexico
Denmark
AustriaNorway
New Zealand
AustraliaUnited Kingdom
BelgiumFranceUnited States
SwitzerlandCzech Republik
Hungary
Germany
325
350
375
400
425
450
475
500
525
550
-25 -20 -15 -10 -5 0 5 10 15 20 25
2525
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Thailand
Peru
Liechtenstein
Russian Fed.
LatviaIsrael
FYR Macedonia
Indonesia
Hong Kong-China
Chile
Bulgaria
Albania
Brazil
Argentina
Finland
KoreaJ apan
Iceland
CanadaIreland
Sweden
SpainI taly
PolandGreece
Portugal
Luxembourg
Mexico
Denmark
AustriaNorway
New Zealand
AustraliaUnited Kingdom
BelgiumFranceUnited States
SwitzerlandCzech Republik
Hungary
Germany
325
350
375
400
425
450
475
500
525
550
-25 -20 -15 -10 -5 0 5 10 15 20 25
Low Social equity
HighSocial equity
HighPerforman
ce
Low Performan
ce
Early selection and institutional stratification
Low degree of stratification
High degree of stratification
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Summing up Building student engagement with reading…
…may help lift overall performance and counter social disadvantage
Many of the high performing countries have shifted the focus of policy and practice…… from the control over resources to the
management of results– High performance expectations– Strong learning climate and teacher-student relations– Schools with greater freedom to decide on curricular
offerings, establish their learning environment, manage their resources
… from the institutions to learning and the learner
– Individual teacher support and open pathways
PISA cannot provide conclusive answers but can help to ask the right questions
2727
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Further information
www.oecd.org www.pisa.oecd.org email: [email protected]
…and remember:
Without data, you are just another person with an opinion
2828
Supplementary slides
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3 MEX
GRC
PRT
LUX
ITA
DEU
NOR
USA
ESPPOL HUN
CZE
KOR NZLJ PN
FIN
GBRAUSCAN
FRA
SWE
BELDNK
IRLAUTISLCHE
300
350
400
450
500
550
0 10000 20000 30000 40000 50000
GDP per capita (US$converted using PPPs)
Ave
rage
per
form
ance
(re
adin
g, m
athe
mat
ical
and
scie
ntifi
c lit
erac
y)
Student performance and national income
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PER
BRA
IDN
ALB
MKD
ARGCHLMEX
THABGR
ISR
GRC
PRT
LUX
ITA
DEU
NOR
USA
ESP
LVA RUS
POL HUNCZE
KOR NZLHKG
J PN
FIN
GBRAUSCAN
FRA
SWE
BELDNK
IRLAUTISLCHE
300
350
400
450
500
550
0 10000 20000 30000 40000 50000
GDP per capita (US$converted using PPPs)
Ave
rage
per
form
ance
(re
adin
g, m
athe
mat
ical
and
scie
ntifi
c lit
erac
y)
Student performance and national income
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Gender differences-60 -40 -20 0 20 40
Favouring girls
Favouring boysReadin
g literacy
Mathematical literacy
Scientific literacy
3232
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423
467
540
583
506
463
548
540
491
400
420
440
460
480
500
520
540
560
580
600
Low engagement Medium engagement High engagement
Rea
din
g Li
tera
cy P
erfo
rman
ce
Low socio- economic backgroundMedium socio- economic backgroundHigh socio- economic background
Reading literacy proficiency by levels of engagement and social background
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Engagement with School
-2 -1 0 1 2Socioeconomic Status
0
10
20
30
40
50
60
Pre
vale
nce
Truant Students
Non-Academic Students
Disaffected Students
Engaged Students
Top Students
Highly engaged and high
performing students
Highly engaged but moderately
performing students
Truant and low performing students
Disengaged but high performing
students
Disengaged and low-performing but not truant
3434
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300
350
400
450
500
550
600
-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8
Index of interest in reading
Perf
orm
ance
on
the
com
bin
ed r
eadin
g
lite
racy
sca
le
Interest in reading and performance on reading literacy
Males
Females
Low interest in reading High interest in reading
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300
350
400
450
500
550
600
- 0.8 - 0.6 - 0.4 - 0.2 0 0.2 0.4 0.6 0.8
Index of interest in reading
Perf
orm
ance
on
the
com
bin
ed
read
ing
lite
racy
sca
le
Interest in mathematics and performance on mathematical
literacy
MalesFemale
s
Low interest in mathematicsHigh interest in mathematics
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Job-expectations of 15-year-olds at age 30
0
25
50
75
100
0 25 50 75 100
Percentage of females
Percentage of males
White collar
Blue collar