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PISA 2012
Evaluating school systems
to improve education
Embargo until
3 December
OECD EMPLOYER Paris time
11:00
BRAND

Playbook

Andreas Schleicher

1
2

PISA in brief
• Over half a million students…
– representing 28 million 15-year-olds in 65 countries/economies

… took an internationally agreed 2-hour test…
– Goes beyond testing whether students can
reproduce what they were taught…
… to assess students’ capacity to extrapolate from what they know
and creatively apply their knowledge in novel situations
– Mathematics, reading, science, problem-solving, financial literacy
– Total of 390 minutes of assessment material

… and responded to questions on…
– their personal background, their schools
and their engagement with learning and school

• Parents, principals and system leaders provided data on…
– school policies, practices, resources and institutional factors that
help explain performance differences .
3

PISA in brief
• Key principles
– ‘Crowd sourcing’ and collaboration
• PISA draws together leading expertise and institutions from participating
countries to develop instruments and methodologies…
… guided by governments on the basis of shared policy interests

– Cross-national relevance and transferability of policy experiences
• Emphasis on validity across cultures, languages and systems
• Frameworks built on well-structured conceptual understanding
of academic disciplines and contextual factors

– Triangulation across different stakeholder perspectives
• Systematic integration of insights from students, parents,
school principals and system-leaders

– Advanced methods with different grain sizes
• A range of methods to adequately measure constructs with different grain sizes
to serve different decision-making needs
• Productive feedback, at appropriate levels of detail, to fuel improvement at
every level of the system .
4

Each year OECD countries spend 200bn$ on math education in school

What do 15-year-olds know…
…and what can they do with what they know?
Mathematics (2012)
High mathematics performance
Mean score … Shanghai-China performs above this line (613)

Average performance
of 15-year-olds in
Mathematics

580

Singapore

570
560

Chinese Taipei

540

Macao-China
Japan Liechtenstein
Switzerland

530

510

500
490
480
470

Fig I.2.13

Korea

550

520

Hong Kong-China

Poland
Belgium
Germany
Austria
Slovenia
New Zealand Denmark
France
Czech Republic
Latvia
Luxembourg
Portugal Spain
Slovak Republic United States
Connecticut
Hungary

Massachusetts

Florida

Netherlands
Estonia Finland
Canada
Viet Nam
Australia
Ireland
United Kingdom
Iceland
Norway
Italy
Russian Fed.
Lithuania Sweden
Croatia

Israel

460
450

Greece

Serbia Turkey

Romania
440
430
420
410

US

Chile
… 12 countries perform below this line

Bulgaria
U.A.E.
Kazakhstan
Thailand
Malaysia
Mexico

Low mathematics performance

26% of American 15-year-olds
do not reach PISA Level 2
(OECD average 23%, Shanghai
4%, Japan 11%, Canada 14%, Some
estimate long-term economic cost to be US$72
trillion )
High mathematics performance

Singapore
Chinese Taipei

Hong Kong-China

Average performance
of 15-year-olds in
mathematics

Korea
Macao-China
Japan Liechtenstein
Switzerland

Strong socio-economic
impact on student
performance

Poland
Belgium
Germany
Austria
Slovenia
New Zealand Denmark
France
Czech Republic
Latvia
Luxembourg
Portugal Spain
Slovak Republic United States
Hungary

Netherlands
Estonia Finland
Canada
Viet Nam
Australia
Ireland
United Kingdom
Iceland
Norway
Italy
Russian Fed.
Lithuania Sweden
Croatia

Israel
Greece

Serbia Turkey

Romania

Chile

Bulgaria
U.A.E.
Kazakhstan
Thailand
Malaysia
Mexico

Low mathematics performance

Socially equitable
distribution of learning
opportunities
2012

Shanghai-China
Singapore
Hong Kong-China

Chinese Taipei
Korea

Macao-China

Japan
Switzerland

Liechtenstein
Estonia

Netherlands
Poland

Canada
Belgium
Finland
Viet Nam
Germany
Strong socio-economic
Austria
Australia
impact on student New Zealand Denmark
Slovenia Ireland
Iceland
Czech Rep.
performance 22France
26
24
20
18
16
14
12
10
8
6
UK
Latvia
Luxembourg
Norway
Portugal
Italy
Russian Fed.
US
Spain
Lithuania
Sweden
Slovak Rep.
Hungary
Croatia
Israel

Romania
Bulgaria

Greece
Turkey

Serbia

United Arab Emirates
Kazakhstan
Thailand

Chile

Malaysia
Mexico

Socially equitable
distribution of learning
opportunities
4
2
0
Australia
Austria
Belgium
Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel socio-economic
Strong
Italy
impact on student
Japan
performance
Korea
Luxembourg
Mexico
Slovak Rep.
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain
Sweden
Switzerland
Turkey
UK
US

2012

Korea

Japan
Switzerland
Netherlands
Poland

Belgium

Germany

Estonia
Canada
Finland

Socially equitable

Austria
Australia
New Zealand Denmark
Ireland
Slovenia
distribution of learning
Iceland
Czech Rep.
opportunities
France
UK
Luxembourg
Norway
Portugal
Italy
US
Spain
Sweden
Hungary
Israel

Greece
Turkey

Chile
Mexico
Australia
Austria
Belgium
Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Luxembourg
Mexico
Slovak Rep.
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain
Sweden
Switzerland
Turkey
UK
US

Korea

Japan
Switzerland
Netherlands
Poland

Belgium

Germany

Estonia
Canada
Finland

Austria
Australia
New Zealand Denmark
Ireland
Slovenia
Iceland
Czech Rep.
France
UK
Luxembourg
Norway
Portugal
Italy
US
Spain
Sweden
Hungary
Israel

Greece
Turkey

Chile
Mexico
Australia
Austria
Belgium
Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Luxembourg
Mexico
Slovak Rep.
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain
Sweden
Switzerland
Turkey
UK
US

Shanghai

2003 - 2012

Singapore
Singapore
Korea

Japan
Switzerland
Netherlands
Poland

Belgium

Germany

Estonia
Canada
Finland

Austria
Australia
New Zealand Denmark
Ireland
Slovenia
Iceland
Czech Rep.
France
UK
Luxembourg
Norway
Portugal
Italy
US
Spain
Sweden
Hungary
Israel

Greece
Turkey

Chile
Mexico
Australia
Austria
Belgium
Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Luxembourg
Mexico
Slovak Rep.
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain
Sweden
Switzerland
Turkey
UK
US

2003 - 2012
Singapore

Korea

Japan
Switzerland
Netherlands
Poland

Belgium

Germany

Estonia
Canada
Finland

Austria
Australia
New Zealand Denmark
Ireland
Slovenia
Iceland
Czech Rep.
France
UK
Luxembourg
Norway
Portugal
Italy
US
Spain
Sweden
Hungary
Israel

Greece
Turkey

Chile
Mexico
Australia
Austria
Belgium
Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Luxembourg
Mexico
Slovak Rep.
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain
Sweden
Switzerland
Turkey
UK
US

2003 - 2012
Singapore

Korea

Japan
Switzerland

Brazil, Italy, MacaoEstonia
Netherlands
Poland
China, Poland, Portugal, Canada
Belgium
Finland
Germany
Russian
Austria
Australia
New Zealand Denmark
Federation, Thailand
Ireland
Slovenia
Iceland
Czech Rep.
France
and Tunisia saw
UK
Luxembourg
Norway
Portugal
Italy
significant
US
Spain
improvements in math Sweden
Hungary
performance between
Israel
2003 and 2012
(adding countries with more recent
Greece
Turkey
trends results in 25 countries with
improvements in math)

Chile
Mexico
Australia
Austria
Belgium
Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Luxembourg
Mexico
Slovak Rep.
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain
Sweden
Switzerland
Turkey
UK
US

2003 - 2012
Singapore

Korea

Japan
Switzerland

Estonia

Netherlands
Poland

Belgium

Canada
Finland

Germany
Norway, the United States and
Austria
Australia
New Zealand Denmark
Ireland
Switzerland improved equity
Slovenia
Czech Rep.
France
UK
between Luxembourg 2012
2003 and
Portugal

Iceland

Italy
US

Spain
Hungary

Sweden

Israel

Greece
Turkey

Chile
Mexico

Norway
26

Of the 65 countries…
…45 improved at least in one subject
28

Performance of countries
in a level playing field
How the world would look if students around the world
were living in similar social and economic conditions
340

Shanghai-China
Singapore
Hong Kong-China
Chinese Taipei
Viet Nam
Macao-China
Korea
Japan
Liechtenstein
Poland
Switzerland
Estonia
Netherlands
Germany
Belgium
Finland
Canada
Portugal
Austria
Czech Republic
New Zealand
Latvia
France
Slovenia
Ireland
Australia
OECD average
Turkey
Slovak Republic
Spain
Hungary
Luxembourg
Italy
Russian Federation
United Kingdom
Denmark
Lithuania
Croatia
United States
Norway
Sweden
Iceland
Romania
Israel
Serbia
Thailand
Greece
Bulgaria
Chile
Uruguay
Malaysia
Kazakhstan
Cyprus5, 6
Mexico
Costa Rica
United Arab…
Brazil
Montenegro
Tunisia
Indonesia
Peru
Argentina
Colombia
Jordan
Qatar

Mean mathematics score

29
Mathematics performance in a level playing field

Mean mathematics performance after accounting for socio-economic status

Fig II.3.3

Mean score at the country level before adjusting for socio-economic status
Mean score at the country level after adjusting for socio economic status

600

580

560

540

520

500

480

460

440

420

400

380

360
31

It is not just about poor kids
in poor neighbourhoods…
…but about many kids in many neighbourhoods
%

30

Hong Kong-China
Korea +
Liechtenstein
Macao-China +
Japan
Switzerland
Belgium Netherlands Germany
Poland +
Canada Finland New Zealand Australia Austria
OECD average 2003 France
Czech Republic Luxembourg
Iceland Slovak Republic
Ireland
Portugal +
Denmark Italy +
Norway Hungary
United States
Sweden Spain
Latvia
Russian Federation
Turkey
Greece
Thailand
Uruguay Tunisia
Brazil
Mexico
Indonesia

38
Percentage of top performers in mathematics
in 2003 and 2012

2012

Fig I.2.23

2003

40

Across OECD, 13% of students are top
performers (Level 5 or 6). They can develop
and work with models for complex
situations, and work strategically with
advanced thinking and reasoning skills

20

10

0
40

Gender differences remain
10

-40

Jordan
Qatar
Thailand
Malaysia
Iceland
U.A.E.
Latvia
Singapore
Finland
Sweden
Bulgaria
Russian Fed.
Albania
Montenegro
Lithuania
Kazakhstan
Norway
Macao-China
Slovenia
Romania
Poland
Indonesia
United States
Estonia
Chinese Taipei
Shanghai-China
Belgium
Turkey
Greece
France
Hungary
Serbia
Slovak Republic
Vietnam
Canada
Netherlands
OECD average
Portugal
Uruguay
Croatia
Israel
Czech Republic
Australia
United Kingdom
Switzerland
Germany
Argentina
Denmark
Mexico
New Zealand
Tunisia
Ireland
Hong Kong-China
Spain
Brazil
Japan
Korea
Italy
Peru
Austria
Liechtenstein
Costa Rica
Chile
Luxembourg
Colombia

Score-point difference (boys-girls)

41

Gender differences in mathematics performance
Fig I.2.25

30

20

Boys perform better than girls

0

-10

-20

-30

Girls perform better than boys

-50
10

-40

Jordan
Qatar
U.A.E.
Bulgaria
Thailand
Montenegro
Finland
Latvia
Lithuania
Greece
Malaysia
Turkey
Slovenia
Kazakhstan
Sweden
Albania
Argentina
Russian Fed.
Romania
Serbia
Norway
Indonesia
Iceland
Poland
France
Estonia
Croatia
Portugal
United States
Macao-China
Uruguay
Israel
Singapore
Germany
Belgium
Czech Republic
Chinese Taipei
Tunisia
Viet Nam
OECD average
Brazil
Italy
Canada
Hungary
Netherlands
Korea
Ireland
New Zealand
Australia
Shanghai-China
Peru
Switzerland
Mexico
Hong Kong-China
Chile
Slovak Republic
Spain
Austria
Denmark
Japan
Costa Rica
United Kingdom
Luxembourg
Liechtenstein
Colombia

Score-point difference (boys-girls)

42

Gender differences in science performance
Fig I.5.12

30

20

Boys perform better than girls

0

-10

-20

-30

Girls perform better than boys

-50
Jordan
Qatar
Bulgaria
Montenegro
Finland
Slovenia
U.A.E.
Lithuania
Thailand
Latvia
Sweden
Iceland
Greece
Croatia
Norway
Serbia
Turkey
Germany
Israel
France
Estonia
Poland
Romania
Malaysia
Russian Fed.
Hungary
Slovak Republic
Portugal
Italy
Czech Republic
Argentina
OECD average
Austria
Kazakhstan
Switzerland
Macao-China
Uruguay
Canada
Australia
New Zealand
Chinese Taipei
Singapore
Belgium
Viet Nam
United States
Denmark
Tunisia
Brazil
Luxembourg
Spain
Ireland
Indonesia
Netherlands
Hong Kong-China
Costa Rica
United Kingdom
Liechtenstein
Japan
Shanghai-China
Mexico
Korea
Chile
Peru
Colombia
Albania

Score-point difference (boys-girls)

43

Gender differences in reading performance
Fig I.4.12

0

-10

-20

-30

-40

-50

In all countries and economies
girls perform better than boys

-60

-70

-80
44

Math teaching ≠ math teaching
PISA = reason mathematically and understand, formulate, employ
and interpret mathematical concepts, facts and procedures
1.50

1.00

Viet Nam
Macao-China
Shanghai-China
Turkey
Uruguay
Greece
Hong Kong-China
Chinese Taipei
Portugal
Brazil
Serbia
Bulgaria
Singapore
Netherlands
Japan
Argentina
Costa Rica
Lithuania
Tunisia
New Zealand
Czech Republic
Israel
Korea
Latvia
Qatar
Italy
United States
Estonia
Ireland
Australia
Mexico
United Arab Emirates
Norway
Malaysia
Kazakhstan
United Kingdom
Romania
OECD average
Albania
Colombia
Indonesia
Sweden
Belgium
Peru
Thailand
Denmark
Russian Federation
Canada
Slovak Republic
Hungary
Germany
Croatia
Luxembourg
Montenegro
Chile
Poland
Finland
Austria
Slovenia
France
Switzerland
Jordan
Liechtenstein
Spain
Iceland

Index of exposure to word problems

45

Students' exposure to word problems
Fig I.3.1a

2.50

2.00

Formal math situated in a word
problem, where it is obvious to
students what mathematical
knowledge and skills are needed

0.50

0.00
Sweden
Iceland
Tunisia
Argentina
Switzerland
Brazil
Luxembourg
Ireland
Netherlands
New Zealand
Costa Rica
Austria
Liechtenstein
Malaysia
Indonesia
Denmark
United Kingdom
Uruguay
Lithuania
Germany
Australia
Chile
OECD average
Slovak Republic
Thailand
Qatar
Finland
Portugal
Colombia
Mexico
Peru
Czech Republic
Israel
Italy
Belgium
Hong Kong-China
Poland
France
Spain
Montenegro
Greece
Turkey
Slovenia
Viet Nam
Hungary
Bulgaria
Kazakhstan
Chinese Taipei
Canada
United States
Estonia
Romania
Latvia
Serbia
Japan
Korea
Croatia
Albania
Russian Federation
United Arab Emirates
Jordan
Macao-China
Singapore
Shanghai-China
Iceland

Index of exposure to formal mathematics

46

Students' exposure to formal mathematics
Fig I.3.1b

2.50

2.00

1.50

1.00

0.50

0.00
Czech Republic
Macao-China
Shanghai-China
Viet Nam
Uruguay
Finland
Costa Rica
Sweden
Japan
Chinese Taipei
Italy
Israel
Norway
Estonia
Hong Kong-China
Austria
Serbia
Korea
Croatia
Latvia
Slovak Republic
Greece
United Kingdom
Ireland
Luxembourg
Belgium
Montenegro
Argentina
Slovenia
Bulgaria
OECD average
Lithuania
Hungary
Switzerland
New Zealand
Germany
Turkey
Denmark
Russian Federation
Singapore
Iceland
United States
Spain
Qatar
Liechtenstein
Poland
Australia
France
Brazil
Malaysia
Peru
Canada
Chile
United Arab Emirates
Romania
Tunisia
Netherlands
Portugal
Colombia
Albania
Kazakhstan
Jordan
Mexico
Indonesia
Thailand

Index of exposure to applied mathematics

47

Students' exposure to applied mathematics
Fig I.3.1c

2.50

2.00

1.50

1.00

0.50

0.00
Relationship between mathematics performance
and students' exposure to applied mathematics

48

Fig I.3.2

Mean score in mathematics

510

490

470

OECD countries
All participating countries and economies
450

430
0.0

never

0.5

1.0

rarely

1.5

2.0

sometimes

Index of exposure to applied mathematics

2.5

3.0

frequently
52

The share of immigrant students in OECD countries
increased from 9% in 2003 to 12% in 2012…
…while the performance disadvantage of immigrant students
shrank by 11 score points during the same period (after
accounting for socio-economic factors)
Finland

Mexico

France

Change between 2003 and 2012 in immigrant students' mathematics
performance – before accounting for students’ socio-economic status

Denmark

Switzerland -

Belgium -

Austria

Sweden

Netherlands

Brazil

Germany -

Spain

Iceland

Greece

80

Liechtenstein

2012

Italy +

Norway

Portugal

Luxembourg

OECD average 2003 -

Czech Republic

Russian Federation

Thailand

United States

United Kingdom

Hong Kong-China

Latvia

Canada

Ireland

New Zealand -

Turkey

-20

Slovak Republic -

Macao-China

Australia -

Hungary -

Score point difference (without-with immig.)

54
Fig II.3.5

2003

100

Students without an immigrant
background perform better

60

40

20

0

Students with an immigrant
background perform better

-40
20

65
46
52
35
55
21
29
26
24
16
15
16
15
23
09
13
13
11
09
11
18
11
18
12
10
10
09
11
07
09
13
08
06
03
07
04
03
06
05
03
01
01
02
01
01
01
02
01
02
01
01
00
01
00
00
01
00
00
00
00
00
00

%

Macao-China
Luxembourg
Qatar
Hong Kong-China
Ù.A.E.
United States
Canada
New Zealand
Switzerland
Kazakhstan
Belgium
Austria
Sweden
Australia
Norway
United Kingdom
Germany
Greece
Denmark
Netherlands
Israel
OECD average
Singapore
Croatia
Ireland
Spain
Slovenia
Russian Fed.
Italy
Serbia
Jordan
Estonia
Costa Rica
Iceland
Portugal
Argentina
Finland
Montenegro
Latvia
Czech Republic
Shanghai-China
Mexico
Malaysia
Thailand
Turkey
Peru
Hungary
Slovak Republic
Lithuania
Chile
Chinese Taipei
Japan
Brazil
Colombia
Tunisia
Bulgaria
Uruguay
Romania
Indonesia
Poland
Viet Nam
Korea

56
Proportion of immigrant students in socio-economically
disadvantaged, average and advantaged schools

Socio-economically disadvantaged schools

Fig II.3.9

Socio-economically advantaged schools

80

70

60

50

40

30

Percentage of immigrant
students

10

0
Percentage of resilient students

59

Fig II.2.4

20

18

A resilient student is situated in the bottom quarter of
the PISA index of economic, social and cultural
status (ESCS) in the country of assessment and
performs in the top quarter of students among all
countries, after accounting for socio-economic status.

16

14

12

Socio-economically disadvantaged students not
only score lower in mathematics, they also report
lower levels of engagement, drive, motivation and
self-beliefs. Resilient students break this link and
share many characteristics of advantaged highachievers.

% 10
8

6

4

2

More than 10
% resilient

Between 5%-10% of resilient students

Less than 5%

Shanghai-China
Hong Kong-China
Macao-China
Viet Nam
Singapore
Korea
Chinese Taipei
Japan
Liechtenstein
Switzerland
Estonia
Netherlands
Poland
Canada
Finland
Belgium
Portugal
Germany
Turkey
OECD average
Italy
Spain
Latvia
Ireland
Australia
Thailand
Austria
Luxembourg
Czech Republic
Slovenia
United Kingdom
Lithuania
France
Norway
Iceland
New Zealand
Russian Fed.
United States
Croatia
Denmark
Sweden
Hungary
Slovak Republic
Mexico
Serbia
Greece
Israel
Tunisia
Romania
Malaysia
Indonesia
Bulgaria
Kazakhstan
Uruguay
Brazil
Costa Rica
Chile
Colombia
Montenegro
U.A.E.
Argentina
Jordan
Peru
Qatar

0
60

20

80

Albania
Finland
Iceland
Sweden
Norway
Denmark
Estonia
Ireland
Spain
Canada
Poland
Latvia
Kazakhstan
United States
Mexico
Colombia
Costa Rica
Russian Fed.
Malaysia
Jordan
New Zealand
Lithuania
Greece
Montenegro
United Kingdom
Argentina
Australia
Brazil
Portugal
Indonesia
Chile
Thailand
Romania
Tunisia
Switzerland
Peru
Uruguay
Croatia
U.A.E.
Macao-China
Serbia
Viet Nam
Korea
ong Kong-China
Singapore
Austria
Italy
Luxembourg
Czech Republic
Japan
Bulgaria
Israel
Qatar
Shanghai-China
Germany
Slovenia
Slovak Republic
Turkey
Belgium
Hungary
Liechtenstein
Netherlands
Chinese Taipei

Variation in student performance as % of OECD average variation

61
Variability in student mathematics performance
between and within schools
Fig II.2.7

100

80

Performance differences
between schools

40

OECD average

20

0

Performance variation of
students within schools

40

60

OECD average

100
62

Disciplinary climate improved
Teacher-student relations improved between 2003 and 2012 in all but
one country; and disciplinary climate also improved during the
period, on average across OECD countries and in 27 individual countries
-0.2

Tunisia
Germany
Finland
France
Latvia
Sweden
Uruguay
Australia
New Zealand
Ireland
Hungary
Russian Federation
Netherlands
Slovak Republic
Greece
United States
Brazil
Switzerland
OECD average 2003
Spain
Poland
Portugal
Canada
Belgium
Turkey
Macao-China
Austria
Italy
Liechtenstein
Denmark
Mexico
Thailand
Indonesia
Korea
Iceland
Czech Republic
Norway
Luxembourg
Hong Kong-China
Japan

Mean index change

In most countries and economies, the disciplinary
climate in schools improved between 2003 and 2012

0.4

0.3

Fig IV.5.13

Change between 2003 and 2012 in disciplinary climate in schools

0.5

Disciplinary climate
improved

0.2

0.1

0

-0.1

Disciplinary climate
declined

-0.3
Norway
Jordan
Portugal
Iceland
Estonia
Argentina
Switzerland
Latvia
Mexico
Finland
Peru
Costa Rica
Russian Fed.
Hong Kong-China
Liechtenstein
Thailand
Poland
Colombia
Brazil
Macao-China
Canada
Luxembourg
Chile
Viet Nam
Netherlands
Spain
United Kingdom
Israel
Germany
Kazakhstan
Montenegro
Malaysia
Indonesia
Lithuania
Czech Republic
Uruguay
Ireland
Tunisia
Qatar
OECD average
Denmark
U.A.E.
Sweden
Australia
Bulgaria
Austria
Italy
Belgium
Turkey
Korea
Slovak Republic
Serbia
Greece
Romania
Shanghai-China
New Zealand
United States
Singapore
Japan
Croatia
Hungary
Slovenia
Chinese Taipei

64
Differences in disciplinary climate explained by
students' and schools' socio-economic profile
Fig II.4.9

Proportion of variation explained by students' socio-economic status

Proportion of variation explained by students' and schools' socio-economic status

%

35

30

25

20

15

10

5

0
Countries with large proportions of truants
perform worse in mathematics

Fig IV.1.22

Adjusted by per capita GDP
650

Shanghai-China

Mathematics performance (score points)

600

Viet Nam
Chinese Taipei
Hong Kong-China
Korea Japan
Poland
Singapore
R² = 0.16
Estonia
Netherlands
Latvia
Belgium
Finland
Slovenia
Czech Rep. Germany SwitzerlandNew Zealand
Canada
Lithuania
500
France
Russian Fed.
Austria
Australia
UK
Portugal
Hungary
Spain
Bulgaria
Romania
Italy
USA
Thailand
Norway
Sweden
Malaysia
Turkey
Greece
450
Kazakhstan
Uruguay
Montenegro
Chile
Mexico
Brazil
Costa Rica
Albania
Jordan
Tunisia
Colombia
400
Indonesia
Luxembourg
UAE
Argentina
Peru
550

350

Qatar
300
0

10

20

30

40

50

60

Percentage of students in schools who skipped at least one day of school in the two weeks prior to
the PISA test

70
72

Social and emotional dimensions matter too
73

Motivation to learn mathematics

Fig III.3.9

Percentage of students who reported "agree" or "strongly agree" with the following statements:
United Kingdom

Shanghai-China

I am interested in the things I learn
in mathematics

I do mathematics because I enjoy it

I look forward to my mathematics
lessons

I enjoy reading about mathematics
0

10

20

30

40

%

50

60

70
75

Countries where students have stronger beliefs
in their abilities perform better in mathematics

Fig III.4.5

OECD average

650

Mean mathematics performance

600

550

500

450

400

350

300
-0.60

Shanghai-China

Singapore
Hong Kong-China
Korea
R² =
Chinese Taipei
Macao-China
Japan
Switzerland
Netherlands Estonia Canada
Liechtenstein
Finland
Germany
Poland
Belgium
Viet Nam
Slovenia
Denmark
New Zealand
Latvia
Portugal
Italy
Austria
Australia
Russian Fed.
Hungary
Luxembourg Spain
Croatia
Slovak Republic
Greece
Norway
Turkey Israel
Sweden
Serbia
Czech Republic
Lithuania
U.A.E.
Iceland
Romania
United Kingdom
Malaysia
Thailand
United States
Ireland
Bulgaria Kazakhstan
Chile
Montenegro
France
Costa Rica
Mexico
Uruguay
Albania
Brazil
Argentina
Tunisia
Colombia
Qatar
Jordan
Indonesia
Peru

-0.40

-0.20

0.00

0.20

0.40

0.60

Mean index of mathematics self-efficacy

0.80

0.36

1.00

1.20
40

Colombia
Costa Rica
Peru
Israel
Luxembourg
Chile
Tunisia
Slovak Republic
Liechtenstein
Italy
Korea
Spain
Argentina
Brazil
Portugal
Greece
Japan
Austria
Uruguay
Mexico
Hong Kong-China
Bulgaria
Turkey
Indonesia
Hungary
Viet Nam
United States
Romania
U.A.E.
Chinese Taipei
Canada
Ireland
Belgium
Kazakhstan
Czech Republic
OECD average
Croatia
France
Shanghai-China
Montenegro
Poland
Serbia
Malaysia
Estonia
Qatar
Macao-China
Netherlands
New Zealand
Norway
Lithuania
Slovenia
Denmark
Jordan
Switzerland
Australia
Germany
Latvia
Russian Fed.
Sweden
Singapore
United Kingdom
Thailand
Finland
Iceland

Score-point difference (boys-girls)

77
Greater self-efficacy among girls could shrink the gender gap in mathematics
performance, particularly among the highest-performing students
Fig III.7.12

Gender gap among the highest-achieving students (90th percentile)
Gender gap adjusted for differences in mathematics self-efficacy between boys and girls
Gender gap

30

20

10

0

-10

-20
78

Openness to problem solving

Fig III.3.4

Percentage of students who reported "agree" or "strongly agree" with the following statements:
United Kingdom

United States

I like to solve complex
problems
I can easily link facts together

I seek explanation for things

I am quick to understand things

I can handle a lot of information
0

10

20

30

40

%

50

60

70
79

Perceived self-responsibility for failure
in mathematics

Fig III.3.6

Percentage of students who reported "agree" or "strongly agree" with the following statements:
United Kingdom

United States

Sometimes I am just unlucky
The teacher did not get students interested in
the material
Sometimes the course material is too hard

This week I made bad guesses on the quiz
My teacher did not explain the concepts well
this week
I’m not very good at solving mathematics
problems
0

20

40

%

60

80
Students open to problem solving perform better

80

Fig III.3.5

Score-point difference in mathematics associated with
Students who feel that they can handle a lot of
one unit of the index of students' openness to problem solving information, seek explanations for things, can

Average student
60

easily link facts together, and like to solve
complex problems – score 30 points higher in
mathematics, on average

Change in performance per one unit of the index among lowest-achieving students

50

40

30

20

10

0

-10

Korea
New Zealand
Australia
United Kingdom
Finland
Canada
Czech Republic
Sweden
Lithuania
Ireland
Denmark
Chinese Taipei
Norway
France
Austria
Spain
Estonia
Portugal
OECD average
United States
Latvia
Macao-China
Liechtenstein
Shanghai-China
Iceland
Hong Kong-China
Greece
Slovenia
Switzerland
Hungary
Japan
Germany
Luxembourg
Chile
Poland
Viet Nam
Slovak Republic
Singapore
Russian Fed.
Italy
Mexico
Belgium
Netherlands
Costa Rica
Uruguay
Croatia
Turkey
Israel
Peru
U.A.E.
Serbia
Tunisia
Romania
Jordan
Argentina
Bulgaria
Malaysia
Brazil
Qatar
Thailand
Kazakhstan
Indonesia
Colombia
Montenegro
Albania

Score-point difference

Change in performance per one unit of the index among highest-achieving students
Korea
Chinese Taipei
Norway
Finland
Japan
Hong Kong-China
Denmark
Sweden
Iceland
Greece
Poland
Australia
Czech Republic
United Kingdom
Portugal
Macao-China
Estonia
Canada
Ireland
France
Shanghai-China
Malaysia
Viet Nam
OECD average
Spain
Netherlands
Liechtenstein
Germany
Italy
Latvia
Slovenia
Russian Fed.
Austria
Belgium
Luxembourg
New Zealand
Hungary
Lithuania
Switzerland
United States
Chile
Croatia
Jordan
Turkey
Qatar
Tunisia
Slovak Republic
Singapore
U.A.E.
Serbia
Thailand
Mexico
Montenegro
Kazakhstan
Costa Rica
Uruguay
Albania
Israel
Colombia
Argentina
Bulgaria
Brazil
Indonesia
Romania
Peru

Score-point difference

81
Students who enjoy learning mathematics perform better
Fig III.3.13

Score-point difference in mathematics associated with
one unit of the index of intrinsic motivation to learn mathematics
Average student
Change in performance per one unit of the index among lowest-achieving students
Change in performance per one unit of the index among highest-achieving students

50

40

30

20

10

0

-10

-20

-30
Korea
Chinese Taipei
Norway
Finland
Poland
Japan
Portugal
Iceland
Denmark
Hong Kong-China
Canada
Sweden
Australia
New Zealand
Spain
Greece
Qatar
Malaysia
Viet Nam
Netherlands
OECD average
Estonia
Belgium
Lithuania
United States
France
Luxembourg
Jordan
Thailand
Tunisia
Slovenia
Hungary
Shanghai-China
Germany
Italy
Latvia
Ireland
Czech Republic
Macao-China
Croatia
United Kingdom
U.A.E.
Russian Fed.
Turkey
Chile
Slovak Republic
Israel
Mexico
Switzerland
Austria
Bulgaria
Serbia
Montenegro
Indonesia
Kazakhstan
Peru
Argentina
Costa Rica
Brazil
Uruguay
Albania
Singapore
Colombia
Liechtenstein
Romania

Score-point difference

82
Students who believe that learning mathematics
is useful perform better
Fig III.3.17

Score-point difference in mathematics associated with one unit of the index of
instrumental motivation to learn mathematics
Average student
Change in performance per one unit of the index among lowest-achieving students
Change in performance per one unit of the index among highest-achieving students

40

30

20

10

0

-10

-20
85

Students' sense of belonging

Fig III.2.12

Percentage of students who agree/disagree with the following statements:
Liechtenstein

OECD average

Agree: I am satisfied with my school

Agree: Things are ideal in my school

Agree: I feel happy at school

Disagree: I feel lonely at school

Agree: I feel like I belong at school

0

20

40

60

%

80

100
86

Students' sense of belonging

Fig III.2.12

Percentage of students who agree/disagree with the following statements:
Liechtenstein

OECD average

Agree: I am satisfied with my school

Agree: Things are ideal in my school

Agree: I feel happy at school

Disagree: I feel lonely at school

Agree: Other students seem to like me

Disagree: I feel awkward and out of place in my school

Agree: I feel like I belong at school

Agree: I make friends easily at school

Disagree: I feel like an outsider (or left out of things) at school
0

20

40

60

%

80

100
87

Students’ attitudes towards school:
Learning outcomes

Fig III.2.15

Percentage of students who agree/disagree with the following statements:
Malaysia

Albania

OECD average

Agree: School has taught me things which could
be useful in a job

Agree: School has helped give me confidence to
make decisions

Disagree: School has been a waste of time

Disagree: School has done little to prepare me for
adult life when I leave school

0

20

40

60

%

80

100

120
88

Students and perseverance

Fig III.3.2

Percentage of students who reported that the following statements describe someone "very
much like me" or "mostly like me" (*) or "not much like me" or "not at all like me" (**)
Kazakhstan

OECD average

Agree: I continue working on tasks until
everything is perfect

Agree: I remain interested in the tasks that
I start

Disagree: I put off difficult problems

Disagree: When confronted with a
problem, I give up easily

0

20

40

60

80

100
89

Students’ attitudes towards school:
Learning outcomes

Fig III.2.15

Percentage of students who agree/disagree with the following statements:
Malaysia

Albania

OECD average

Agree: School has taught me things which could
be useful in a job

Agree: School has helped give me confidence to
make decisions

Disagree: School has been a waste of time

Disagree: School has done little to prepare me for
adult life when I leave school

0

20

40

60

%

80

100

120
90

Students’ intrinsic motivation to learn mathematics

Fig III.3.9

Percentage of students who reported "agree" or "strongly agree" with the following statements:
Albania

OECD average

I am interested in the things I learn in mathematics

I do mathematics because I enjoy it

I look forward to my mathematics lessons

I enjoy reading about mathematics

0

20

40

60

%

80

100
91

Students’ instrumental motivation to learn mathematics

Fig III.3.14

Percentage of students who reported "agree" or "strongly agree" with the following statements:
Peru

OECD average

I will learn many things in mathematics that will
help me get a job

Mathematics is an important subject for me
because I need it for what I want to study later on

Learning mathematics is worthwhile for me
because it will improve my career prospects and
chances

Making an effort in mathematics is worth it
because it will help me in the work that I want to
do later on

0

20

40

60

%

80

100
92

Students’ mathematics self-efficacy

Fig III.4.2

Percentage of students who feel very confident or confident about having to do the foll
owing tasks in mathematics:
Shanghai-China
OECD average
Calculating the petrol-consumption rate of a car

Solving an equation like 2(x+3)=(x+3)(x-3)
Finding the actual distance between two places on
a map with a 1:10 000 scale
Solving an equation like 3x+5=17

Understanding graphs presented in newspapers
Calculating how many square metres of tiles you
need to cover a floor
Calculating how much cheaper a TV would be
after a 30% discount
Using a <train timetable> to work out how long it
would take to get from one place to another
50

60

70

80

%

90

100
93

Students' mathematics self-concept

Fig III.4.7

Percentage of students who agree*/disagree** with the following statements:
United Arab Emirates

OECD average

Agree: In my mathematics class, I understand
even the most difficult work

Agree: I have always believed that mathematics is
one of my best subjects

Agree: I learn mathematics quickly

Agree: I get good <grades> in mathematics

Disagree: I am just not good at mathematics

0

20

40

60
%

80

100
94

Students’ mathematics anxiety

Fig III.4.10

Percentage of students who reported "agree" or "strongly agree" with the following statements:
Tunisia

OECD average

I worry that I will get poor <grades> in
mathematics

I feel helpless when doing a mathematics problem

I get very nervous doing mathematics problems

I get very tense when I have to do mathematics
homework

I often worry that it will be difficult for me in
mathematics classes

0

20

40

60

%

80

100
95

Students' participation in mathematics-related activities

Fig III.4.16

Percentage of students who reported "agree" or "strongly agree" with the following statements:
Jordan

OECD average

I participate in a mathematics club

I programme computers

I play chess
I do mathematics more than 2 hours a day
outside of school
I take part in mathematics competitions

I do mathematics as an <extracurricular> activity

I help my friends with mathematics
I talk about mathematics problems with my
friends
0

10

20

30

40

%

50

60

70
Fig III.2.15

96

Malaysia

Albania

OECD average

Agree: School has taught me things which could
be useful in a job

Agree: School has helped give me confidence to
make decisions

Disagree: School has been a waste of time

Disagree: School has done little to prepare me for
adult life when I leave school

0

20

40

60

%

80

100

120
97

Also worth noting
o 85% of advantaged students but only 78% of disadvantaged
students say feel they belong at school
o More than one in three students in OECD countries say they had
arrived late for school in the two weeks prior to the PISA test;
and more than one in four students reported that they had
skipped a class or a day of school during this period
o Better teacher-student relations are strongly associated with
greater student engagement at school
o Even when girls perform as well as boys in mathematics, they
tend to report less perseverance, less openness to problem
solving, less motivation to learn mathematics, less self-belief in
their ability to learn mathematics and more anxiety about
mathematics than boys, on average; they are also more likely
than boys to attribute failure in mathematics to themselves .
98

The parent factor
Students whose parents have high educational expectations for
them tend to report more perseverance, greater intrinsic
motivation to learn mathematics, and more confidence in their
own ability to solve mathematics problems than students of
similar background and academic performance, whose parents
hold less ambitious expectations for them.
Parents’ expectations for their child have a strong
influence on students’ behaviour towards school

100

Fig III.6.11

Percentage-point change in arriving late for school that is associated with parents
expecting the child to complete a university degree
4

2

-2
-4
-6
-8
-10
-12
-14

Hungary

Korea

Croatia

Hong Kong-China

Macao-China

Italy

Portugal

Chile

Mexico

Belgium (Flemish)

-16

Germany

Percentage-point change

0
Parents’ high expectations can nurture
students’ enjoyment in learning mathematics

101

Fig III.6.11

Change in the index of intrinsic motivation to learn mathematics that is associated
with parents expecting the child to complete a university degree

0.50
0.45

0.35
0.30
0.25
0.20
0.15

0.10
0.05

Germany

Mexico

Macao-China

Croatia

Hungary

Portugal

Chile

Hong Kong-China

Italy

Korea

0.00

Belgium (Flemish)

Mean index change

0.40
Parents’ high expectations can foster
perseverance in their child

102

Fig III.6.11

Change in the index of perseverance that is associated with parents expecting the
child to complete a university degree

0.35

0.25

0.20

0.15

0.10

0.05

Macao-China

Korea

Croatia

Germany

Hong Kong-China

Chile

Hungary

Mexico

Belgium (Flemish)

Italy

0.00

Portugal

Mean index change

0.30
10
3

Schools make a difference
Grade repetition is negatively related to equity

Fig IV.1.4

Adjusted by per capita GDP

Greater equity
2

Variation in mathematics performance explained by socioeconomic status (%)

4

Macao-China

6

Kazakhstan
Hong Kong-China
Estonia Jordan
Indonesia
Norway
Qatar
Thailand
Iceland
Mexico
Finland
Canada
Tunisia
Japan
Korea
Italy
UAE
Serbia
Croatia
Russian Fed. Sweden
Montenegro Lithuania
Viet Nam
Australia
Turkey
Argentina
Latvia
Switzerland
Netherlands
UK
Brazil
Greece
Colombia
Belgium
Slovenia
Ireland USA
Shanghai-China
Poland Czech Rep.
Spain
Singapore
Israel
Austria
R2=0.05
Denmark
Costa Rica
Romania
Germany
New Zealand
Chinese Taipei
R2=0.07
Portugal

8
10

12
14
16
18
20

Bulgaria

22

Chile Peru Luxembourg

Hungary

France

Slovak Rep.

24

Uruguay

26
-5

Less equity

0

5

10

15

20

25

30

Percentage of students who have repeated at least one grade

35

40

45
Japan
Norway
Iceland
Russian Federation
Thailand +
Korea +
Finland +
Sweden
Poland
Greece Denmark
Czech Republic +
New Zealand
Australia Slovak Republic +
Canada Latvia
Ireland Hungary
Austria
United States
OECD average 2003 Turkey Mexico Indonesia
Hong Kong-China
Italy Liechtenstein
Switzerland
Germany
Netherlands
France Spain +
Portugal
Luxembourg Brazil
Belgium +
Uruguay
Tunisia Macao-China -

Percentage of repeaters in 2003 and 2012
2012

Tab IV.2.18

70

2003

60

50

40

%
30

20

10

0
Belgium

Netherlands

France

Spain

Germany

Portugal

Italy

Austria

United States

Ireland

Canada

Australia

Slovak Republic

New Zealand

Denmark

Finland

Sweden

Korea

Czech Republic

Poland

Slovenia

United Kingdom

Israel

Iceland

Estonia

Norway

Japan

USD, PPPs

Grade repetition is an expensive policy
Fig IV.1.5

Total cost per repeater (one grade year)
Total annual cost, relative to total expenditure on primary and secondary education (%)

60000

14

50000

12

10

40000

8

30000

%

6

20000

4

10000

2

0

0
In most countries, disadvantaged students are more likely
to have repeated a grade than advantaged students

Fig IV.2.3

Socio-economically disadvantaged student (ESCS=-1)
Socio-economically average student (ESCS = 0 )

Socio-economically advantaged student (ESCS = 1 )

Probability of repeating a grade

0.50
0.45
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
300

350

400

Mathematics score (score points)

450

500
80

70

Greece
Austria
Czech Republic
Poland +
Liechtenstein +
Portugal
Japan Finland Macao-China Luxembourg Germany Slovak Republic
Mexico +
OECD average 2003 Indonesia
Turkey
Denmark Italy Thailand
Hungary Belgium Brazil
Latvia +
Tunisia Sweden +
Switzerland
Iceland Korea Hong Kong-China
Uruguay Spain
Canada +
Netherlands
United States
Russian Fed.
Australia
New Zealand
Ireland

Change between 2003 and 2012 in ability grouping

2012

Fig IV.2.11

2003

%

90

+ 2012 higher than 2003
- 2012 lower than 2003

60

50

40

30

20

10

0
113

Also worth noting
o Stratification in school systems (e.g. grade repetition
and selecting students at a young age for different
“tracks” or types of schools) is negatively related to
equity; and students in highly stratified systems tend to
be less motivated than those in less-stratified systems
11
4

Money makes a difference…
…but only up to a point
Spending per student from the age of 6 to 15 and
mathematics performance in PISA 2012

Fig IV.1.8

650

Cumulative expenditure per student less than USD 50 000
Mathematics performance (score points)

Shanghai-China

Cumulative expenditure per student USD 50 000 or more

600

Singapore
Korea
550

Japan
Switzerland
PolandCanada
Finland Netherlands
Viet Nam
Estonia
Belgium
Germany
Czech Republic
Australia Austria
New Zealand
Slovenia Ireland
Denmark
Latvia
France
UK
Norway
Portugal
Iceland
Lithuania
Slovak Republic
Croatia
Italy Sweden United States
Israel
Hungary
Spain
Turkey

500

R² = 0.01
Luxembourg

450

Bulgaria

Thailand

Chile
Mexico
Montenegro
Uruguay

Malaysia
400

Tunisia Brazil
Jordan
Colombia
Peru

350

R² = 0.37
300
0

20 000

40 000

60 000

80 000

100 000

120 000

140 000

160 000

Average spending per student from the age of 6 to 15 (USD, PPPs)

180 000

200 000
Among high-income countries
high-performers pay teachers more

Fig IV.1.10

Mathematics performance (score points)

650

Per capita GDP less than USD 20 000

In 33 countries schools where a higher
600 share of principals reported that
teacher shortages hinder learning tend
to show lower performance
550

Shanghai-China

Per capita GDP over USD 20 000
Singapore
Hong Kong-China
Korea

Macao-China

Japan

R² = 0.09
Netherlands
Finland
Canada
Belgium
Austria Australia
Germany
Czech Rep.
Iceland
Ireland
Latvia
France
Denmark
New Zealand
Slovenia UK
Slovak Rep.
Norway
Italy Luxembourg
Portugal
Spain
USA
Hungary
Croatia
Israel Sweden Lithuania
Romania
Greece
Bulgaria Thailand
Malaysia
Uruguay
Chile
Tunisia
Montenegro
Qatar
Indonesia
Colombia
Argentina Peru
Jordan
Estonia

500

450

400

Poland

Among low-income countries a
host of other resources are the
principal barriers

350

R² = 0.05

300
20

40

60

80

100

120

140

Teachers' salaries relative to per capita GDP (%)

160

180

200

220
0

Chinese Taipei
Greece
Japan
Korea
Thailand
Hong Kong-…
Montenegro
Turkey
Shanghai-China
Viet Nam
Romania
Macao-China
Tunisia
Croatia
Hungary
Malaysia
New Zealand
Ireland
Liechtenstein
Costa Rica
Czech Republic
Australia
Bulgaria
Netherlands
Jordan
Belgium
Latvia
Spain
Argentina
OECD average
Indonesia
Singapore
Russian Fed.
Austria
Iceland
France
Brazil
Uruguay
Lithuania
Israel
Qatar
Slovak Republic
Canada
Estonia
Germany
U.A.E.
Slovenia
Serbia
Italy
Finland
Colombia
Chile
United Kingdom
Switzerland
Luxembourg
United States
Sweden
Kazakhstan
Portugal
Peru
Poland
Denmark
Norway
Mexico

In many countries, more advantaged than disadvantaged
students attend after-school lessons
Fig IV.3.11

Percentage of all students participating in after-school lessons
Students in the bottom quarter of socio-economic status
Students in the top quarter of socio-economic status

100

90

80

70

60

% 50

40

30

20

10
118

Teacher shortage

Fig IV.3.5

Percentage of students in schools whose principals reported that
the following phenomena hindered student learning "to some
extent" or "a lot":
Slovenia

OECD average

Lack of qualified science teachers

Lack of qualified mathematics teachers

Lack of qualified language-of-instruction teachers

Lack of qualified teachers of other subjects

0

5

10

15

%

20

25
Luxembourg
Jordan
Thailand
Turkey
Shanghai-China
Israel
Colombia
Peru
Chile
Netherlands
Mexico
Germany
Viet Nam
Russian Fed.
Uruguay
Norway
Kazakhstan
Indonesia
Belgium
Italy
Malaysia
Australia
Brazil
Iceland
U.A.E.
Singapore
New Zealand
Korea
Switzerland
Estonia
Macao-China
Costa Rica
OECD average
Sweden
Argentina
Tunisia
Austria
Qatar
Ireland
Chinese Taipei
France
Denmark
United Kingdom
Hong Kong-China
Albania
Japan
Canada
Slovak Republic
Latvia
Greece
United States
Czech Republic
Croatia
Finland
Montenegro
Romania
Hungary
Lithuania
Slovenia
Spain
Serbia
Portugal
Bulgaria
Poland

Mean index

Teacher shortage
Mean index
Top quarter of this index

Fig IV.3.5

Bottom quarter of this index

3

2.5

2

1.5

1

0.5

0

-0.5

-1

-1.5
-0.5

Korea
Estonia
Israel
Kazakhstan
Latvia
Malaysia
Slovenia
Italy
Poland
Singapore
Argentina
Costa Rica
Netherlands
Portugal
Colombia
Bulgaria
France
Finland
Tunisia
Lithuania
Qatar
Macao-China
Thailand
Spain
Greece
Switzerland
Romania
Norway
Russian Fed.
Japan
Austria
Montenegro
Croatia
Canada
U.A.E.
OECD average
Germany
Denmark
Hungary
United Kingdom
Luxembourg
Hong Kong-China
Belgium
Iceland
Jordan
Peru
Viet Nam
Ireland
United States
Chile
Czech Republic
Serbia
Turkey
Mexico
Indonesia
Uruguay
Shanghai-China
Slovak Republic
Sweden
Brazil
New Zealand
Australia
Chinese Taipei
Albania

Mean index difference

Teacher shortage is more of concern in disadvantaged
schools also in public schools, in most countries
Fig IV.3.5

Difference between socio-economically disadvantaged and socio-economically advantaged schools
Difference between public and private advantaged schools

1.5

Disadvantaged and public schools
reported more teacher shortage

1

0.5

0

Advantaged and private schools r
eported more teacher shortage

-1
121

Adequacy of educational resources

Fig IV.3.8

Percentage of students in schools whose principals reported
that the following phenomena hindered student learning "not at
all" or "very little“:
Singapore

OECD average

Shortage or inadequacy of science laboratory
equipment

Shortage or inadequacy of instructional
materials (e.g. textbooks)

Shortage or inadequacy of computers for
instruction

Lack or inadequacy of Internet connectivity

Shortage or inadequacy of computer software
for instruction

Shortage or inadequacy of library materials

50

60

70

80

90

%

100

110
Singapore
Qatar
Australia
Chinese Taipei
Switzerland
United Kingdom
Hong Kong-China
Japan
Slovenia
France
United States
U.A.E.
Poland
Macao-China
Belgium
Canada
Austria
Romania
New Zealand
Netherlands
Hungary
Portugal
Lithuania
Shanghai-China
Uruguay
Ireland
Germany
Korea
OECD average
Sweden
Czech Republic
Italy
Luxembourg
Latvia
Spain
Bulgaria
Denmark
Estonia
Norway
Finland
Malaysia
Iceland
Greece
Israel
Chile
Turkey
Albania
Jordan
Russian Fed.
Viet Nam
Montenegro
Croatia
Brazil
Argentina
Slovak Republic
Serbia
Thailand
Kazakhstan
Indonesia
Mexico
Costa Rica
Peru
Tunisia
Colombia

Mean index

Adequacy of educational resources
Mean index
Top quarter of this index

Fig IV.3.8

Bottom quarter of this index

3.00

2.00

1.00

0.00

-1.00

-2.00

-3.00

-4.00
0.50

-1.50

Peru
Costa Rica
Mexico
Brazil
Indonesia
Thailand
Colombia
New Zealand
Turkey
Argentina
United States
Uruguay
Australia
Chile
Viet Nam
Jordan
Shanghai-China
U.A.E.
Romania
Sweden
Israel
Bulgaria
Chinese Taipei
Malaysia
Ireland
Greece
Tunisia
Poland
Canada
Japan
Macao-China
OECD average
Luxembourg
Qatar
Russian Fed.
Iceland
Belgium
France
Switzerland
Portugal
Hong Kong-China
Spain
Lithuania
Denmark
Kazakhstan
Italy
Czech Republic
Netherlands
Estonia
Hungary
Slovenia
Austria
Singapore
Latvia
Slovak Republic
Montenegro
Korea
Germany
Serbia
United Kingdom
Norway
Croatia
Finland
Liechtenstein
Albania

Mean index difference

Educational resources are more problematic in disadvantaged
schools, also in public schools in most countries
Fig IV.3.8

Difference between socio-economically disadvantaged and socio-economically advantaged schools
Difference between public and private advantaged schools
Disadvantaged and public schools
reported better educational
resources

0.00

-0.50

-1.00

Advantaged and private schools
reported better educational
resources

-2.00
124

Quality assurance and school improvement

Fig IV.4.14

Percentage of students in schools whose principal reported that their schools
have the following for quality assurance and improvement:
Shanghai-China

OECD average

Implementation of a standardised policy for mathematics (i.e.
school curriculum with shared instructional materials
accompanied by staff development and training)
Regular consultation with one or more experts over a period
of at least six months with the aim of improving the school
Teacher mentoring
Written feedback from students (e.g. regarding
lessons, teachers or resources)
External evaluation

Internal evaluation/self-evaluation
Systematic recording of data, including teacher and student
attendance and graduation rates, test results and
professional development of teachers
Written specification of student-performance standards
Written specification of the school's curriculum and
educational goals

0

20

40

60

%

80

100

120
125

Students' views of how conducive
classrooms are to learning

Fig IV.5.4

Percentage of students who reported that the following
phenomena occur "never or hardly ever" or "in some lessons”:
Japan

OECD average

Students don’t listen to what the teacher says

There is noise and disorder

The teacher has to wait a long time for students
to quiet down.

Students cannot work well

Students don’t start working for a long time after
the lesson begins

0

20

40

60

%

80

100
120

Shanghai-China
Hong Kong-China
France
Slovak Republic
Macao-China
Italy
Switzerland
Qatar
Czech Republic
Israel
Thailand
Argentina
Denmark
Belgium
Viet Nam
Germany
U.A.E.
United Kingdom
Greece
Indonesia
Spain
Chinese Taipei
Singapore
Japan
Finland
Uruguay
Poland
Sweden
Australia
New Zealand
OECD average
Netherlands
Malaysia
Austria
Luxembourg
Bulgaria
Mexico
Jordan
Peru
Iceland
Portugal
Brazil
Turkey
Romania
Canada
Norway
Tunisia
Lithuania
Chile
Serbia
Korea
United States
Russian Fed.
Costa Rica
Kazakhstan
Montenegro
Colombia
Croatia
Slovenia
Ireland
Latvia
Estonia

Score point difference

126

Difference in mathematics
performance, by attendance at preprimary school
before accounting for students' socio-economic status

Fig III.4.12

after accounting for students' socio-economic status

140

Students who attended pre-primary
school perform better

100

80

60

40

20

0

-20
127

Also worth noting

o Educational resources relate to student performance
– 33% of the variation in math performance is explained by differences
in principal’s responses to questions about the adequacy of science
laboratory equipment, instructional material, ICT and libraries (GDP
adjusted)

o Adequacy of physical infrastructure unrelated to performance
o Within countries, class time relates positively to performance
– Holds also after accounting for socio-economic and demographic
factors, but does not hold when pooling data across countries
(learning outcomes are the product of quantity and quality)
– The proportion of students in schools with after-school mathematics
lessons is unrelated to system performance
– Homework relates positively to school performance
128

Also worth noting
o Most countries and economies with comparable data
between 2003 and 2012 have moved towards betterstaffed and better-equipped schools
o Students in 2012 were more likely than their
counterparts in 2003 to have attended at least one year
of pre-primary education
– yet many of the students who reported that they had not
attended pre-primary school are disadvantaged
12
9

High performers spend resources where
they are needed most
Countries with better performance in mathematics tend
to allocate educational resources more equitably
700

Adjusted by per capita GDP

650

Mathematics performance (score points)

Fig IV.1.11

30% of the variation in math
performance across OECD countries is
600
explained by the degree of similarity of
educational resources between
advantaged and disadvantaged schools
550
500

450

Mexico
Costa Rica

400

Shanghai-China

Chinese Taipei
Korea
R² = 0.19
Viet Nam Singapore
Hong Kong-China
Estonia
Japan Poland
Slovenia
Switzerland
Latvia
Finland
Canada
Belgium
Germany
Macao-China
Slovak Rep.
New Zealand
UK
IrelandIceland France
DenmarkSpain Austria
Australia
Croatia
Hungary
Israel
Romania Portugal
Sweden
Bulgaria
Turkey
USA
Greece
Norway
Italy
Serbia
Thailand
Malaysia
Chile
Kazakhstan
Uruguay
Jordan
Brazil
Indonesia UAE
Montenegro
Colombia
Tunisia
Argentina
Luxembourg

Peru
350

Qatar
300
1.5

1

Less
equity

0.5

OECD countries tend to allocate at least
an equal, if not a larger, number of
teachers per student to disadvantaged
schools; but disadvantaged schools tend
to have great difficulty in attracting
0
-0.5
qualified teachers.

Equity in resource allocation
(index points)

Greater
equity
13
2

Governance matters
Schools with more autonomy over curricula and assessments tend to
perform better than schools with less autonomy where they are part of
school systems with more accountability arrangements and greater
teacher-principal collaboration in school management
Countries that grant schools autonomy over curricula and
assessments tend to perform better in mathematics

650

Fig IV.1.15

Shanghai-China

Mathematics performance (score points)

600

Chinese Taipei

Viet Nam
550

500

450

400

Korea

Estonia

Singapore

Hong Kong-China
Japan

Poland
Latvia
Slovenia Belgium
Czech Rep.
Switzerland Canada Germany
Finland New Zealand
Lithuania Netherlands
Portugal
Hungary
Austria
Croatia
Italy
Spain France Australia
Serbia
UK
Macao-China
Turkey
Norway
Iceland
Denmark
R² = 0.13
Slovak Rep.
Bulgaria
Thailand
Greece
Romania
Kazakhstan
Israel
Malaysia
Chile
Uruguay
USA Sweden
Jordan
Costa Rica
Indonesia
Brazil Albania
Luxembourg
Tunisia
Colombia
UAE Argentina
Peru

350

Qatar
300
-1.5

-1

-0.5

0

0.5

Index of school responsibility for curriculum and assessment
(index points)

1

1.5
Schools with more autonomy perform better than schools with
less autonomy in systems with more collaboration

School autonomy for resource allocation x System's level of teachers
participating in school management
Across all participating countries and economies
Score points
485

480

475

470

465

460

Teachers participate in
management

455

Teachers don't participate
in management

Less school autonomy
More school autonomy

Fig IV.1.17
Schools with more autonomy perform better than schools with
less autonomy in systems with standardised math policies

Fig IV.1.16

School autonomy for curriculum and assessment
x system's extent of implementing a standardised math policy (e.g. curriculum and
instructional materials)

Score points
485

480

475

470

465

460

Standardised math
policy

455

No standardised
math policy

Less school autonomy
More school autonomy
Schools with more autonomy perform better than schools with
less autonomy in systems with more accountability arrangements

Fig IV.1.16

School autonomy for curriculum and assessment
x system's level of posting achievement data publicly

Score points
478

476

474
472
470
468
466

School data public
464

School data not public
Less school autonomy
More school autonomy
%

0

Finland
Belgium
Shanghai-China
Japan
Austria
Switzerland
Argentina
Macao-China
Uruguay
Peru
Germany
Costa Rica
Spain
Luxembourg
Chinese Taipei
Tunisia
Ireland
Jordan
Indonesia
Albania
Croatia
Greece
Iceland
Lithuania
Latvia
Hong Kong-…
Liechtenstein
Estonia
Malaysia
Denmark
Italy
Brazil
Mexico
Czech Republic
OECD average
France
U.A.E.
Poland
Israel
Hungary
Qatar
Singapore
Colombia
Portugal
Slovenia
Norway
Bulgaria
Serbia
Canada
Chile
Turkey
Romania
Australia
Korea
Viet Nam
Thailand
Slovak Republic
Russian Fed.
Kazakhstan
Montenegro
New Zealand
Sweden
United Kingdom
Netherlands
United States

Use of achievement data for accountability

Post publicly

Fig IV.4.13

Percentage of students in schools that use achievement data in the following ways:
Track over time by an administrative authority

100

90

80

70

60

50

40

30

20

10
90

80

%

0

Finland
Uruguay
Greece +
Switzerland +
Ireland +
Belgium +
Sweden +
Japan +
Germany +
Norway +
Italy +
Hungary +
Slovak Republic
Tunisia
Denmark +
OECD average 2003…
Spain
Australia +
Luxembourg +
Liechtenstein +
Netherlands +
Latvia Korea +
New Zealand +
Iceland +
Brazil +
United States
Macao-China +
Austria +
Indonesia
Turkey +
Czech Republic +
Mexico
Hong Kong-China +
Thailand +
Portugal +
Russian Federation +
Poland

Change between 2003 and 2012 in using student
assessment data to monitor teachers

2012

Fig IV.4.19

Percentage of students in schools that use assessment data to monitor teachers:

2003

100

+ 2012 higher than 2003
- 2012 lower than 2003

70

60

50

40

30

20

10
14
1

The issue is not how many charter schools
a country has…
…but how countries enable every school
to assume charter type autonomy
%

Hong Kong-China
Netherlands
Chile
Ireland
Korea
U.A.E.
United Kingdom
Indonesia
Australia
Qatar
Chinese Taipei
Argentina
Spain
Japan
Denmark
OECD average
France
Uruguay
Jordan
Thailand
Hungary
Luxembourg
Peru
Colombia
Sweden
Brazil
Costa Rica
Portugal
Shanghai-China
Mexico
Slovak Republic
Austria
Albania
Czech Republic
Canada
Viet Nam
Switzerland
Germany
New Zealand
United States
Italy
Malaysia
Finland
Poland
Kazakhstan
Estonia
Slovenia

What type of school do most students attend?
Fig IV.1.22

Fig IV.1.22

Percentage of students attending
Government-independent private schools
Government-dependent private schools
Government or public schools

100

90

80

70

60

50

40

30

20

10

0
100

-50

Chinese Taipei
Hong Kong-China
Thailand
Viet Nam
Luxembourg
Switzerland
Indonesia
Italy
Kazakhstan
Japan
Czech Republic
Netherlands
Estonia
Albania
Ireland
United States
Hungary
Sweden
Korea
United Kingdom
Finland
Denmark
OECD average
France
Shanghai-China
Australia
Spain
Slovak Republic
Mexico
Germany
Austria
Colombia
Chile
Canada
Poland
Jordan
Argentina
United Arab Emirates
Portugal
Peru
Costa Rica
Brazil
New Zealand
Malaysia
Slovenia
Uruguay
Qatar

Score-point difference

Differences in mathematics performance between private and public
schools shrink considerably after accounting for socio-economic status

50

Fig IV.1.19

Observed performance difference

After accounting for students’ and schools’ socio-economic status

75

Performance advantage of public schools

25

0

-25

Performance advantage of private schools

-75

-100

-125
14
5

How the theory of school choice squares
with the reality in families
If offered a choice of schools for their child, parents consider criteria as
“a safe school environment” and “a school’s good reputation” more
important than “high academic achievement of students in the school”.
School competition and mathematics performance

Fig IV.1.18

Adjusted by per capita GDP
650
Shanghai-China

There is no relationship between
the prevalence of competition and
overall performance level

Mathematics performance (score points)

600

Korea

Viet Nam
550
Poland
Switzerland

Finland

500

Lithuania
France

Iceland

450

Montenegro

400

R² = 0.030

Japan
Netherlands
Czech Rep.
Slovak Rep.

Hong Kong-China
Singapore
Latvia
Belgium
New Zealand

Spain
Serbia
Macao-China
Ireland
Hungary
Romania
Austria
UK
Bulgaria
Sweden
USA
Australia
Turkey
Thailand
Greece
Chile
Uruguay Kazakhstan
Malaysia
Jordan
Costa Rica
Mexico
Argentina
Albania
Brazil
Tunisia
Indonesia
UAE
Luxembourg
Colombia
Peru
Italy

Norway

Estonia
Germany
Slovenia
Portugal

Chinese Taipei

350

Qatar
300
30

40

50

60

70

80

Percentage of students in schools that compete with at least one other school

90

100
A school’s particular approach to teaching is not a determining
factor when parents choose a school for their child

Fig IV.4.5

Percentage of parents who reported that a particular approach to pedagogy is a very
important criterion when choosing a school for their child
All parents
Parents in the bottom quarter of socio-economic status
Parents in the top quarter of socio-economic status
80
70
60
50

% 40
30
20
10

Hungary

Belgium (Fl. Comm.)

Germany

Italy

Portugal

Hong Kong-China

Korea

Chile

Macao-China

Mexico

0
Expenses associated with schooling are a concern among
disadvantaged families

Fig IV.4.5

Percentage of parents who reported that expenses such as tuition, books, and room
and board, are very important criteria when choosing a school for their child
All parents
Parents in the bottom quarter of socio-economic status
Parents in the top quarter of socio-economic status
80
70
60
50

% 40
30
20
10

Belgium (Fl. Comm.)

Germany

Hong Kong-China

Italy

Hungary

Macao-China

Korea

Croatia

Portugal

Mexico

Chile

0
Financial aid for school is a greater concern among
disadvantaged parents

Fig IV.4.5

Percentage of parents who reported that the availability of financial aid, such as a school
loan, scholarship or grant, is a very important criterion when choosing a school for their child
All parents
Parents in the bottom quarter of socio-economic status
Parents in the top quarter of socio-economic status
80
70
60
50

% 40
30
20
10

Belgium (Fl. Comm.)

Germany

Hungary

Hong Kong-China

Croatia

Macao-China

Korea

Portugal

Mexico

Chile

0
For disadvantaged families, physical access
to school is a significant concern

Fig IV.4.5

Percentage of parents who reported that the school’s distance from home is
a very important criterion when choosing a school for their child
All parents
Parents in the bottom quarter of socio-economic status
Parents in the top quarter of socio-economic status
80
70
60
50

% 40
30

20
10

Italy

Hong Kong-China

Macao-China

Belgium (Fl. Comm.)

Croatia

Hungary

Germany

Korea

Chile

Mexico

Portugal

0
Advantaged families tend to seek out schools whose students
are high achievers

Fig IV.4.5

Percentage of parents who reported that students’ high academic achievement is a very
important criterion in choosing a school for their child
All parents
Parents in the bottom quarter of socio-economic status
Parents in the top quarter of socio-economic status
80
70
60
50

% 40
30
20
10

Belgium (Fl. Comm.)

Hungary

Italy

Germany

Hong Kong-China

Croatia

Macao-China

Mexico

Portugal

Chile

Korea

0
A school’s reputation is a very important
consideration among advantaged families

Fig IV.4.5

Percentage of parents who reported that a school’s good reputation is
a very important criterion when choosing a school for their child
All parents
Parents in the bottom quarter of socio-economic status
Parents in the top quarter of socio-economic status
80
70
60
50
40
30
20
10

Croatia

Hungary

Macao-China

Italy

Korea

Germany

Belgium (Fl. Comm.)

Hong Kong-China

Mexico

Chile

0

Portugal

%
Advantaged parents tend to seek out schools with an active and
pleasant climate

Fig IV.4.5

Percentage of parents who reported that an active and pleasant climate is a very
important criterion when choosing a school for their child
All parents
Parents in the bottom quarter of socio-economic status
Parents in the top quarter of socio-economic status
80
70
60
50

% 40
30
20
10

Hungary

Belgium (Fl. Comm.)

Croatia

Italy

Macao-China

Hong Kong-China

Mexico

Germany

Portugal

Korea

Chile

0
Parents everywhere look for a safe school environment
for their child

Fig IV.4.5

Percentage of parents who reported that a safe school environment is a very
important criterion in choosing a school for their child
All parents
Parents in the bottom quarter of socio-economic status
Parents in the top quarter of socio-economic status
80
70
60
50

% 40
30
20
10

Belgium (Fl. Comm.)

Hungary

Germany

Italy

Croatia

Mexico

Macao-China

Hong Kong-China

Chile

Korea

Portugal

0
15
9

PISA 2012 Sample Question 4

Revolving Door
Correct Answer: in the range from 103 to 105.
Accept answers calculated as 1/6th of the circumference (100π/3). Also accept an answer
of 100 only if it is clear that this response resulted from using π =3.
Note: Answer of 100 without supporting working could be obtained by a simple guess that it
is the same as the radius (length of a single wing).
This item belongs to the space and shape category. Space and shape encompasses a wide
range of phenomena that are encountered everywhere in our visual and physical world:
patterns, properties of objects, positions and orientations, representations of objects,
decoding and encoding of visual information, navigation and dynamic interaction with real
shapes as well as with representations.

SCORING:
Description:

Interpret a geometrical model of a real life situation to calculate the
length of an arc

Mathematical
content area:

Space and shape

Context:

Scientific

Process:

Formulate
15

10

5

0
Hong Kong-China
Korea
Japan
Macao-China
Liechtenstein
Switzerland
Belgium
Poland
Germany
New Zealand
Netherlands
Canada
Australia
Estonia
Finland
Vietnam
Slovenia
OECD average
Austria
Czech Republic
France
Slovak Republic
United Kingdom
Luxembourg
Iceland
United States
Israel
Ireland
Italy
Hungary
Portugal
Norway
Denmark
Croatia
Sweden
Latvia
Russian Federation
Lithuania
Spain
Turkey
Serbia
Bulgaria
Greece
Romania
United Arab Emirates
Thailand

25
Shanghai-China

30

Singapore
Chinese Taipei

16
0
PISA 2012 Sample Question 4

Percent of 15-year-olds who scored Level 6 or Above

20
Find out more about PISA at www.pisa.oecd.org
• All national and international publications
• The complete micro-level database

Thank you !

Email: Andreas.Schleicher@OECD.org
Twitter: SchleicherEDU

and remember:
Without data, you are just another person with an opinion
Do you have an idea on how to use this data to
improve education in your country?
Would you like to work with us
to develop that idea?
Apply to the
Thomas J. Alexander
fellowship programme!
http://www.oecd.org/edu/thomasjalexanderfellowship.htm
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PISA 2012 Evaluating school systems to improve education

  • 1. PISA 2012 Evaluating school systems to improve education Embargo until 3 December OECD EMPLOYER Paris time 11:00 BRAND Playbook Andreas Schleicher 1
  • 2. 2 PISA in brief • Over half a million students… – representing 28 million 15-year-olds in 65 countries/economies … took an internationally agreed 2-hour test… – Goes beyond testing whether students can reproduce what they were taught… … to assess students’ capacity to extrapolate from what they know and creatively apply their knowledge in novel situations – Mathematics, reading, science, problem-solving, financial literacy – Total of 390 minutes of assessment material … and responded to questions on… – their personal background, their schools and their engagement with learning and school • Parents, principals and system leaders provided data on… – school policies, practices, resources and institutional factors that help explain performance differences .
  • 3. 3 PISA in brief • Key principles – ‘Crowd sourcing’ and collaboration • PISA draws together leading expertise and institutions from participating countries to develop instruments and methodologies… … guided by governments on the basis of shared policy interests – Cross-national relevance and transferability of policy experiences • Emphasis on validity across cultures, languages and systems • Frameworks built on well-structured conceptual understanding of academic disciplines and contextual factors – Triangulation across different stakeholder perspectives • Systematic integration of insights from students, parents, school principals and system-leaders – Advanced methods with different grain sizes • A range of methods to adequately measure constructs with different grain sizes to serve different decision-making needs • Productive feedback, at appropriate levels of detail, to fuel improvement at every level of the system .
  • 4. 4 Each year OECD countries spend 200bn$ on math education in school What do 15-year-olds know… …and what can they do with what they know? Mathematics (2012)
  • 5. High mathematics performance Mean score … Shanghai-China performs above this line (613) Average performance of 15-year-olds in Mathematics 580 Singapore 570 560 Chinese Taipei 540 Macao-China Japan Liechtenstein Switzerland 530 510 500 490 480 470 Fig I.2.13 Korea 550 520 Hong Kong-China Poland Belgium Germany Austria Slovenia New Zealand Denmark France Czech Republic Latvia Luxembourg Portugal Spain Slovak Republic United States Connecticut Hungary Massachusetts Florida Netherlands Estonia Finland Canada Viet Nam Australia Ireland United Kingdom Iceland Norway Italy Russian Fed. Lithuania Sweden Croatia Israel 460 450 Greece Serbia Turkey Romania 440 430 420 410 US Chile … 12 countries perform below this line Bulgaria U.A.E. Kazakhstan Thailand Malaysia Mexico Low mathematics performance 26% of American 15-year-olds do not reach PISA Level 2 (OECD average 23%, Shanghai 4%, Japan 11%, Canada 14%, Some estimate long-term economic cost to be US$72 trillion )
  • 6. High mathematics performance Singapore Chinese Taipei Hong Kong-China Average performance of 15-year-olds in mathematics Korea Macao-China Japan Liechtenstein Switzerland Strong socio-economic impact on student performance Poland Belgium Germany Austria Slovenia New Zealand Denmark France Czech Republic Latvia Luxembourg Portugal Spain Slovak Republic United States Hungary Netherlands Estonia Finland Canada Viet Nam Australia Ireland United Kingdom Iceland Norway Italy Russian Fed. Lithuania Sweden Croatia Israel Greece Serbia Turkey Romania Chile Bulgaria U.A.E. Kazakhstan Thailand Malaysia Mexico Low mathematics performance Socially equitable distribution of learning opportunities
  • 7. 2012 Shanghai-China Singapore Hong Kong-China Chinese Taipei Korea Macao-China Japan Switzerland Liechtenstein Estonia Netherlands Poland Canada Belgium Finland Viet Nam Germany Strong socio-economic Austria Australia impact on student New Zealand Denmark Slovenia Ireland Iceland Czech Rep. performance 22France 26 24 20 18 16 14 12 10 8 6 UK Latvia Luxembourg Norway Portugal Italy Russian Fed. US Spain Lithuania Sweden Slovak Rep. Hungary Croatia Israel Romania Bulgaria Greece Turkey Serbia United Arab Emirates Kazakhstan Thailand Chile Malaysia Mexico Socially equitable distribution of learning opportunities 4 2 0
  • 8. Australia Austria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel socio-economic Strong Italy impact on student Japan performance Korea Luxembourg Mexico Slovak Rep. Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US 2012 Korea Japan Switzerland Netherlands Poland Belgium Germany Estonia Canada Finland Socially equitable Austria Australia New Zealand Denmark Ireland Slovenia distribution of learning Iceland Czech Rep. opportunities France UK Luxembourg Norway Portugal Italy US Spain Sweden Hungary Israel Greece Turkey Chile Mexico
  • 9. Australia Austria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Slovak Rep. Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US Korea Japan Switzerland Netherlands Poland Belgium Germany Estonia Canada Finland Austria Australia New Zealand Denmark Ireland Slovenia Iceland Czech Rep. France UK Luxembourg Norway Portugal Italy US Spain Sweden Hungary Israel Greece Turkey Chile Mexico
  • 10. Australia Austria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Slovak Rep. Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US Shanghai 2003 - 2012 Singapore Singapore Korea Japan Switzerland Netherlands Poland Belgium Germany Estonia Canada Finland Austria Australia New Zealand Denmark Ireland Slovenia Iceland Czech Rep. France UK Luxembourg Norway Portugal Italy US Spain Sweden Hungary Israel Greece Turkey Chile Mexico
  • 11. Australia Austria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Slovak Rep. Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US 2003 - 2012 Singapore Korea Japan Switzerland Netherlands Poland Belgium Germany Estonia Canada Finland Austria Australia New Zealand Denmark Ireland Slovenia Iceland Czech Rep. France UK Luxembourg Norway Portugal Italy US Spain Sweden Hungary Israel Greece Turkey Chile Mexico
  • 12. Australia Austria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Slovak Rep. Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US 2003 - 2012 Singapore Korea Japan Switzerland Brazil, Italy, MacaoEstonia Netherlands Poland China, Poland, Portugal, Canada Belgium Finland Germany Russian Austria Australia New Zealand Denmark Federation, Thailand Ireland Slovenia Iceland Czech Rep. France and Tunisia saw UK Luxembourg Norway Portugal Italy significant US Spain improvements in math Sweden Hungary performance between Israel 2003 and 2012 (adding countries with more recent Greece Turkey trends results in 25 countries with improvements in math) Chile Mexico
  • 13. Australia Austria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Slovak Rep. Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US 2003 - 2012 Singapore Korea Japan Switzerland Estonia Netherlands Poland Belgium Canada Finland Germany Norway, the United States and Austria Australia New Zealand Denmark Ireland Switzerland improved equity Slovenia Czech Rep. France UK between Luxembourg 2012 2003 and Portugal Iceland Italy US Spain Hungary Sweden Israel Greece Turkey Chile Mexico Norway
  • 14. 26 Of the 65 countries… …45 improved at least in one subject
  • 15. 28 Performance of countries in a level playing field How the world would look if students around the world were living in similar social and economic conditions
  • 16. 340 Shanghai-China Singapore Hong Kong-China Chinese Taipei Viet Nam Macao-China Korea Japan Liechtenstein Poland Switzerland Estonia Netherlands Germany Belgium Finland Canada Portugal Austria Czech Republic New Zealand Latvia France Slovenia Ireland Australia OECD average Turkey Slovak Republic Spain Hungary Luxembourg Italy Russian Federation United Kingdom Denmark Lithuania Croatia United States Norway Sweden Iceland Romania Israel Serbia Thailand Greece Bulgaria Chile Uruguay Malaysia Kazakhstan Cyprus5, 6 Mexico Costa Rica United Arab… Brazil Montenegro Tunisia Indonesia Peru Argentina Colombia Jordan Qatar Mean mathematics score 29 Mathematics performance in a level playing field Mean mathematics performance after accounting for socio-economic status Fig II.3.3 Mean score at the country level before adjusting for socio-economic status Mean score at the country level after adjusting for socio economic status 600 580 560 540 520 500 480 460 440 420 400 380 360
  • 17. 31 It is not just about poor kids in poor neighbourhoods… …but about many kids in many neighbourhoods
  • 18. % 30 Hong Kong-China Korea + Liechtenstein Macao-China + Japan Switzerland Belgium Netherlands Germany Poland + Canada Finland New Zealand Australia Austria OECD average 2003 France Czech Republic Luxembourg Iceland Slovak Republic Ireland Portugal + Denmark Italy + Norway Hungary United States Sweden Spain Latvia Russian Federation Turkey Greece Thailand Uruguay Tunisia Brazil Mexico Indonesia 38 Percentage of top performers in mathematics in 2003 and 2012 2012 Fig I.2.23 2003 40 Across OECD, 13% of students are top performers (Level 5 or 6). They can develop and work with models for complex situations, and work strategically with advanced thinking and reasoning skills 20 10 0
  • 20. 10 -40 Jordan Qatar Thailand Malaysia Iceland U.A.E. Latvia Singapore Finland Sweden Bulgaria Russian Fed. Albania Montenegro Lithuania Kazakhstan Norway Macao-China Slovenia Romania Poland Indonesia United States Estonia Chinese Taipei Shanghai-China Belgium Turkey Greece France Hungary Serbia Slovak Republic Vietnam Canada Netherlands OECD average Portugal Uruguay Croatia Israel Czech Republic Australia United Kingdom Switzerland Germany Argentina Denmark Mexico New Zealand Tunisia Ireland Hong Kong-China Spain Brazil Japan Korea Italy Peru Austria Liechtenstein Costa Rica Chile Luxembourg Colombia Score-point difference (boys-girls) 41 Gender differences in mathematics performance Fig I.2.25 30 20 Boys perform better than girls 0 -10 -20 -30 Girls perform better than boys -50
  • 21. 10 -40 Jordan Qatar U.A.E. Bulgaria Thailand Montenegro Finland Latvia Lithuania Greece Malaysia Turkey Slovenia Kazakhstan Sweden Albania Argentina Russian Fed. Romania Serbia Norway Indonesia Iceland Poland France Estonia Croatia Portugal United States Macao-China Uruguay Israel Singapore Germany Belgium Czech Republic Chinese Taipei Tunisia Viet Nam OECD average Brazil Italy Canada Hungary Netherlands Korea Ireland New Zealand Australia Shanghai-China Peru Switzerland Mexico Hong Kong-China Chile Slovak Republic Spain Austria Denmark Japan Costa Rica United Kingdom Luxembourg Liechtenstein Colombia Score-point difference (boys-girls) 42 Gender differences in science performance Fig I.5.12 30 20 Boys perform better than girls 0 -10 -20 -30 Girls perform better than boys -50
  • 22. Jordan Qatar Bulgaria Montenegro Finland Slovenia U.A.E. Lithuania Thailand Latvia Sweden Iceland Greece Croatia Norway Serbia Turkey Germany Israel France Estonia Poland Romania Malaysia Russian Fed. Hungary Slovak Republic Portugal Italy Czech Republic Argentina OECD average Austria Kazakhstan Switzerland Macao-China Uruguay Canada Australia New Zealand Chinese Taipei Singapore Belgium Viet Nam United States Denmark Tunisia Brazil Luxembourg Spain Ireland Indonesia Netherlands Hong Kong-China Costa Rica United Kingdom Liechtenstein Japan Shanghai-China Mexico Korea Chile Peru Colombia Albania Score-point difference (boys-girls) 43 Gender differences in reading performance Fig I.4.12 0 -10 -20 -30 -40 -50 In all countries and economies girls perform better than boys -60 -70 -80
  • 23. 44 Math teaching ≠ math teaching PISA = reason mathematically and understand, formulate, employ and interpret mathematical concepts, facts and procedures
  • 24. 1.50 1.00 Viet Nam Macao-China Shanghai-China Turkey Uruguay Greece Hong Kong-China Chinese Taipei Portugal Brazil Serbia Bulgaria Singapore Netherlands Japan Argentina Costa Rica Lithuania Tunisia New Zealand Czech Republic Israel Korea Latvia Qatar Italy United States Estonia Ireland Australia Mexico United Arab Emirates Norway Malaysia Kazakhstan United Kingdom Romania OECD average Albania Colombia Indonesia Sweden Belgium Peru Thailand Denmark Russian Federation Canada Slovak Republic Hungary Germany Croatia Luxembourg Montenegro Chile Poland Finland Austria Slovenia France Switzerland Jordan Liechtenstein Spain Iceland Index of exposure to word problems 45 Students' exposure to word problems Fig I.3.1a 2.50 2.00 Formal math situated in a word problem, where it is obvious to students what mathematical knowledge and skills are needed 0.50 0.00
  • 25. Sweden Iceland Tunisia Argentina Switzerland Brazil Luxembourg Ireland Netherlands New Zealand Costa Rica Austria Liechtenstein Malaysia Indonesia Denmark United Kingdom Uruguay Lithuania Germany Australia Chile OECD average Slovak Republic Thailand Qatar Finland Portugal Colombia Mexico Peru Czech Republic Israel Italy Belgium Hong Kong-China Poland France Spain Montenegro Greece Turkey Slovenia Viet Nam Hungary Bulgaria Kazakhstan Chinese Taipei Canada United States Estonia Romania Latvia Serbia Japan Korea Croatia Albania Russian Federation United Arab Emirates Jordan Macao-China Singapore Shanghai-China Iceland Index of exposure to formal mathematics 46 Students' exposure to formal mathematics Fig I.3.1b 2.50 2.00 1.50 1.00 0.50 0.00
  • 26. Czech Republic Macao-China Shanghai-China Viet Nam Uruguay Finland Costa Rica Sweden Japan Chinese Taipei Italy Israel Norway Estonia Hong Kong-China Austria Serbia Korea Croatia Latvia Slovak Republic Greece United Kingdom Ireland Luxembourg Belgium Montenegro Argentina Slovenia Bulgaria OECD average Lithuania Hungary Switzerland New Zealand Germany Turkey Denmark Russian Federation Singapore Iceland United States Spain Qatar Liechtenstein Poland Australia France Brazil Malaysia Peru Canada Chile United Arab Emirates Romania Tunisia Netherlands Portugal Colombia Albania Kazakhstan Jordan Mexico Indonesia Thailand Index of exposure to applied mathematics 47 Students' exposure to applied mathematics Fig I.3.1c 2.50 2.00 1.50 1.00 0.50 0.00
  • 27. Relationship between mathematics performance and students' exposure to applied mathematics 48 Fig I.3.2 Mean score in mathematics 510 490 470 OECD countries All participating countries and economies 450 430 0.0 never 0.5 1.0 rarely 1.5 2.0 sometimes Index of exposure to applied mathematics 2.5 3.0 frequently
  • 28. 52 The share of immigrant students in OECD countries increased from 9% in 2003 to 12% in 2012… …while the performance disadvantage of immigrant students shrank by 11 score points during the same period (after accounting for socio-economic factors)
  • 29. Finland Mexico France Change between 2003 and 2012 in immigrant students' mathematics performance – before accounting for students’ socio-economic status Denmark Switzerland - Belgium - Austria Sweden Netherlands Brazil Germany - Spain Iceland Greece 80 Liechtenstein 2012 Italy + Norway Portugal Luxembourg OECD average 2003 - Czech Republic Russian Federation Thailand United States United Kingdom Hong Kong-China Latvia Canada Ireland New Zealand - Turkey -20 Slovak Republic - Macao-China Australia - Hungary - Score point difference (without-with immig.) 54 Fig II.3.5 2003 100 Students without an immigrant background perform better 60 40 20 0 Students with an immigrant background perform better -40
  • 30. 20 65 46 52 35 55 21 29 26 24 16 15 16 15 23 09 13 13 11 09 11 18 11 18 12 10 10 09 11 07 09 13 08 06 03 07 04 03 06 05 03 01 01 02 01 01 01 02 01 02 01 01 00 01 00 00 01 00 00 00 00 00 00 % Macao-China Luxembourg Qatar Hong Kong-China Ù.A.E. United States Canada New Zealand Switzerland Kazakhstan Belgium Austria Sweden Australia Norway United Kingdom Germany Greece Denmark Netherlands Israel OECD average Singapore Croatia Ireland Spain Slovenia Russian Fed. Italy Serbia Jordan Estonia Costa Rica Iceland Portugal Argentina Finland Montenegro Latvia Czech Republic Shanghai-China Mexico Malaysia Thailand Turkey Peru Hungary Slovak Republic Lithuania Chile Chinese Taipei Japan Brazil Colombia Tunisia Bulgaria Uruguay Romania Indonesia Poland Viet Nam Korea 56 Proportion of immigrant students in socio-economically disadvantaged, average and advantaged schools Socio-economically disadvantaged schools Fig II.3.9 Socio-economically advantaged schools 80 70 60 50 40 30 Percentage of immigrant students 10 0
  • 31. Percentage of resilient students 59 Fig II.2.4 20 18 A resilient student is situated in the bottom quarter of the PISA index of economic, social and cultural status (ESCS) in the country of assessment and performs in the top quarter of students among all countries, after accounting for socio-economic status. 16 14 12 Socio-economically disadvantaged students not only score lower in mathematics, they also report lower levels of engagement, drive, motivation and self-beliefs. Resilient students break this link and share many characteristics of advantaged highachievers. % 10 8 6 4 2 More than 10 % resilient Between 5%-10% of resilient students Less than 5% Shanghai-China Hong Kong-China Macao-China Viet Nam Singapore Korea Chinese Taipei Japan Liechtenstein Switzerland Estonia Netherlands Poland Canada Finland Belgium Portugal Germany Turkey OECD average Italy Spain Latvia Ireland Australia Thailand Austria Luxembourg Czech Republic Slovenia United Kingdom Lithuania France Norway Iceland New Zealand Russian Fed. United States Croatia Denmark Sweden Hungary Slovak Republic Mexico Serbia Greece Israel Tunisia Romania Malaysia Indonesia Bulgaria Kazakhstan Uruguay Brazil Costa Rica Chile Colombia Montenegro U.A.E. Argentina Jordan Peru Qatar 0
  • 32. 60 20 80 Albania Finland Iceland Sweden Norway Denmark Estonia Ireland Spain Canada Poland Latvia Kazakhstan United States Mexico Colombia Costa Rica Russian Fed. Malaysia Jordan New Zealand Lithuania Greece Montenegro United Kingdom Argentina Australia Brazil Portugal Indonesia Chile Thailand Romania Tunisia Switzerland Peru Uruguay Croatia U.A.E. Macao-China Serbia Viet Nam Korea ong Kong-China Singapore Austria Italy Luxembourg Czech Republic Japan Bulgaria Israel Qatar Shanghai-China Germany Slovenia Slovak Republic Turkey Belgium Hungary Liechtenstein Netherlands Chinese Taipei Variation in student performance as % of OECD average variation 61 Variability in student mathematics performance between and within schools Fig II.2.7 100 80 Performance differences between schools 40 OECD average 20 0 Performance variation of students within schools 40 60 OECD average 100
  • 33. 62 Disciplinary climate improved Teacher-student relations improved between 2003 and 2012 in all but one country; and disciplinary climate also improved during the period, on average across OECD countries and in 27 individual countries
  • 34. -0.2 Tunisia Germany Finland France Latvia Sweden Uruguay Australia New Zealand Ireland Hungary Russian Federation Netherlands Slovak Republic Greece United States Brazil Switzerland OECD average 2003 Spain Poland Portugal Canada Belgium Turkey Macao-China Austria Italy Liechtenstein Denmark Mexico Thailand Indonesia Korea Iceland Czech Republic Norway Luxembourg Hong Kong-China Japan Mean index change In most countries and economies, the disciplinary climate in schools improved between 2003 and 2012 0.4 0.3 Fig IV.5.13 Change between 2003 and 2012 in disciplinary climate in schools 0.5 Disciplinary climate improved 0.2 0.1 0 -0.1 Disciplinary climate declined -0.3
  • 35. Norway Jordan Portugal Iceland Estonia Argentina Switzerland Latvia Mexico Finland Peru Costa Rica Russian Fed. Hong Kong-China Liechtenstein Thailand Poland Colombia Brazil Macao-China Canada Luxembourg Chile Viet Nam Netherlands Spain United Kingdom Israel Germany Kazakhstan Montenegro Malaysia Indonesia Lithuania Czech Republic Uruguay Ireland Tunisia Qatar OECD average Denmark U.A.E. Sweden Australia Bulgaria Austria Italy Belgium Turkey Korea Slovak Republic Serbia Greece Romania Shanghai-China New Zealand United States Singapore Japan Croatia Hungary Slovenia Chinese Taipei 64 Differences in disciplinary climate explained by students' and schools' socio-economic profile Fig II.4.9 Proportion of variation explained by students' socio-economic status Proportion of variation explained by students' and schools' socio-economic status % 35 30 25 20 15 10 5 0
  • 36. Countries with large proportions of truants perform worse in mathematics Fig IV.1.22 Adjusted by per capita GDP 650 Shanghai-China Mathematics performance (score points) 600 Viet Nam Chinese Taipei Hong Kong-China Korea Japan Poland Singapore R² = 0.16 Estonia Netherlands Latvia Belgium Finland Slovenia Czech Rep. Germany SwitzerlandNew Zealand Canada Lithuania 500 France Russian Fed. Austria Australia UK Portugal Hungary Spain Bulgaria Romania Italy USA Thailand Norway Sweden Malaysia Turkey Greece 450 Kazakhstan Uruguay Montenegro Chile Mexico Brazil Costa Rica Albania Jordan Tunisia Colombia 400 Indonesia Luxembourg UAE Argentina Peru 550 350 Qatar 300 0 10 20 30 40 50 60 Percentage of students in schools who skipped at least one day of school in the two weeks prior to the PISA test 70
  • 37. 72 Social and emotional dimensions matter too
  • 38. 73 Motivation to learn mathematics Fig III.3.9 Percentage of students who reported "agree" or "strongly agree" with the following statements: United Kingdom Shanghai-China I am interested in the things I learn in mathematics I do mathematics because I enjoy it I look forward to my mathematics lessons I enjoy reading about mathematics 0 10 20 30 40 % 50 60 70
  • 39. 75 Countries where students have stronger beliefs in their abilities perform better in mathematics Fig III.4.5 OECD average 650 Mean mathematics performance 600 550 500 450 400 350 300 -0.60 Shanghai-China Singapore Hong Kong-China Korea R² = Chinese Taipei Macao-China Japan Switzerland Netherlands Estonia Canada Liechtenstein Finland Germany Poland Belgium Viet Nam Slovenia Denmark New Zealand Latvia Portugal Italy Austria Australia Russian Fed. Hungary Luxembourg Spain Croatia Slovak Republic Greece Norway Turkey Israel Sweden Serbia Czech Republic Lithuania U.A.E. Iceland Romania United Kingdom Malaysia Thailand United States Ireland Bulgaria Kazakhstan Chile Montenegro France Costa Rica Mexico Uruguay Albania Brazil Argentina Tunisia Colombia Qatar Jordan Indonesia Peru -0.40 -0.20 0.00 0.20 0.40 0.60 Mean index of mathematics self-efficacy 0.80 0.36 1.00 1.20
  • 40. 40 Colombia Costa Rica Peru Israel Luxembourg Chile Tunisia Slovak Republic Liechtenstein Italy Korea Spain Argentina Brazil Portugal Greece Japan Austria Uruguay Mexico Hong Kong-China Bulgaria Turkey Indonesia Hungary Viet Nam United States Romania U.A.E. Chinese Taipei Canada Ireland Belgium Kazakhstan Czech Republic OECD average Croatia France Shanghai-China Montenegro Poland Serbia Malaysia Estonia Qatar Macao-China Netherlands New Zealand Norway Lithuania Slovenia Denmark Jordan Switzerland Australia Germany Latvia Russian Fed. Sweden Singapore United Kingdom Thailand Finland Iceland Score-point difference (boys-girls) 77 Greater self-efficacy among girls could shrink the gender gap in mathematics performance, particularly among the highest-performing students Fig III.7.12 Gender gap among the highest-achieving students (90th percentile) Gender gap adjusted for differences in mathematics self-efficacy between boys and girls Gender gap 30 20 10 0 -10 -20
  • 41. 78 Openness to problem solving Fig III.3.4 Percentage of students who reported "agree" or "strongly agree" with the following statements: United Kingdom United States I like to solve complex problems I can easily link facts together I seek explanation for things I am quick to understand things I can handle a lot of information 0 10 20 30 40 % 50 60 70
  • 42. 79 Perceived self-responsibility for failure in mathematics Fig III.3.6 Percentage of students who reported "agree" or "strongly agree" with the following statements: United Kingdom United States Sometimes I am just unlucky The teacher did not get students interested in the material Sometimes the course material is too hard This week I made bad guesses on the quiz My teacher did not explain the concepts well this week I’m not very good at solving mathematics problems 0 20 40 % 60 80
  • 43. Students open to problem solving perform better 80 Fig III.3.5 Score-point difference in mathematics associated with Students who feel that they can handle a lot of one unit of the index of students' openness to problem solving information, seek explanations for things, can Average student 60 easily link facts together, and like to solve complex problems – score 30 points higher in mathematics, on average Change in performance per one unit of the index among lowest-achieving students 50 40 30 20 10 0 -10 Korea New Zealand Australia United Kingdom Finland Canada Czech Republic Sweden Lithuania Ireland Denmark Chinese Taipei Norway France Austria Spain Estonia Portugal OECD average United States Latvia Macao-China Liechtenstein Shanghai-China Iceland Hong Kong-China Greece Slovenia Switzerland Hungary Japan Germany Luxembourg Chile Poland Viet Nam Slovak Republic Singapore Russian Fed. Italy Mexico Belgium Netherlands Costa Rica Uruguay Croatia Turkey Israel Peru U.A.E. Serbia Tunisia Romania Jordan Argentina Bulgaria Malaysia Brazil Qatar Thailand Kazakhstan Indonesia Colombia Montenegro Albania Score-point difference Change in performance per one unit of the index among highest-achieving students
  • 44. Korea Chinese Taipei Norway Finland Japan Hong Kong-China Denmark Sweden Iceland Greece Poland Australia Czech Republic United Kingdom Portugal Macao-China Estonia Canada Ireland France Shanghai-China Malaysia Viet Nam OECD average Spain Netherlands Liechtenstein Germany Italy Latvia Slovenia Russian Fed. Austria Belgium Luxembourg New Zealand Hungary Lithuania Switzerland United States Chile Croatia Jordan Turkey Qatar Tunisia Slovak Republic Singapore U.A.E. Serbia Thailand Mexico Montenegro Kazakhstan Costa Rica Uruguay Albania Israel Colombia Argentina Bulgaria Brazil Indonesia Romania Peru Score-point difference 81 Students who enjoy learning mathematics perform better Fig III.3.13 Score-point difference in mathematics associated with one unit of the index of intrinsic motivation to learn mathematics Average student Change in performance per one unit of the index among lowest-achieving students Change in performance per one unit of the index among highest-achieving students 50 40 30 20 10 0 -10 -20 -30
  • 45. Korea Chinese Taipei Norway Finland Poland Japan Portugal Iceland Denmark Hong Kong-China Canada Sweden Australia New Zealand Spain Greece Qatar Malaysia Viet Nam Netherlands OECD average Estonia Belgium Lithuania United States France Luxembourg Jordan Thailand Tunisia Slovenia Hungary Shanghai-China Germany Italy Latvia Ireland Czech Republic Macao-China Croatia United Kingdom U.A.E. Russian Fed. Turkey Chile Slovak Republic Israel Mexico Switzerland Austria Bulgaria Serbia Montenegro Indonesia Kazakhstan Peru Argentina Costa Rica Brazil Uruguay Albania Singapore Colombia Liechtenstein Romania Score-point difference 82 Students who believe that learning mathematics is useful perform better Fig III.3.17 Score-point difference in mathematics associated with one unit of the index of instrumental motivation to learn mathematics Average student Change in performance per one unit of the index among lowest-achieving students Change in performance per one unit of the index among highest-achieving students 40 30 20 10 0 -10 -20
  • 46. 85 Students' sense of belonging Fig III.2.12 Percentage of students who agree/disagree with the following statements: Liechtenstein OECD average Agree: I am satisfied with my school Agree: Things are ideal in my school Agree: I feel happy at school Disagree: I feel lonely at school Agree: I feel like I belong at school 0 20 40 60 % 80 100
  • 47. 86 Students' sense of belonging Fig III.2.12 Percentage of students who agree/disagree with the following statements: Liechtenstein OECD average Agree: I am satisfied with my school Agree: Things are ideal in my school Agree: I feel happy at school Disagree: I feel lonely at school Agree: Other students seem to like me Disagree: I feel awkward and out of place in my school Agree: I feel like I belong at school Agree: I make friends easily at school Disagree: I feel like an outsider (or left out of things) at school 0 20 40 60 % 80 100
  • 48. 87 Students’ attitudes towards school: Learning outcomes Fig III.2.15 Percentage of students who agree/disagree with the following statements: Malaysia Albania OECD average Agree: School has taught me things which could be useful in a job Agree: School has helped give me confidence to make decisions Disagree: School has been a waste of time Disagree: School has done little to prepare me for adult life when I leave school 0 20 40 60 % 80 100 120
  • 49. 88 Students and perseverance Fig III.3.2 Percentage of students who reported that the following statements describe someone "very much like me" or "mostly like me" (*) or "not much like me" or "not at all like me" (**) Kazakhstan OECD average Agree: I continue working on tasks until everything is perfect Agree: I remain interested in the tasks that I start Disagree: I put off difficult problems Disagree: When confronted with a problem, I give up easily 0 20 40 60 80 100
  • 50. 89 Students’ attitudes towards school: Learning outcomes Fig III.2.15 Percentage of students who agree/disagree with the following statements: Malaysia Albania OECD average Agree: School has taught me things which could be useful in a job Agree: School has helped give me confidence to make decisions Disagree: School has been a waste of time Disagree: School has done little to prepare me for adult life when I leave school 0 20 40 60 % 80 100 120
  • 51. 90 Students’ intrinsic motivation to learn mathematics Fig III.3.9 Percentage of students who reported "agree" or "strongly agree" with the following statements: Albania OECD average I am interested in the things I learn in mathematics I do mathematics because I enjoy it I look forward to my mathematics lessons I enjoy reading about mathematics 0 20 40 60 % 80 100
  • 52. 91 Students’ instrumental motivation to learn mathematics Fig III.3.14 Percentage of students who reported "agree" or "strongly agree" with the following statements: Peru OECD average I will learn many things in mathematics that will help me get a job Mathematics is an important subject for me because I need it for what I want to study later on Learning mathematics is worthwhile for me because it will improve my career prospects and chances Making an effort in mathematics is worth it because it will help me in the work that I want to do later on 0 20 40 60 % 80 100
  • 53. 92 Students’ mathematics self-efficacy Fig III.4.2 Percentage of students who feel very confident or confident about having to do the foll owing tasks in mathematics: Shanghai-China OECD average Calculating the petrol-consumption rate of a car Solving an equation like 2(x+3)=(x+3)(x-3) Finding the actual distance between two places on a map with a 1:10 000 scale Solving an equation like 3x+5=17 Understanding graphs presented in newspapers Calculating how many square metres of tiles you need to cover a floor Calculating how much cheaper a TV would be after a 30% discount Using a <train timetable> to work out how long it would take to get from one place to another 50 60 70 80 % 90 100
  • 54. 93 Students' mathematics self-concept Fig III.4.7 Percentage of students who agree*/disagree** with the following statements: United Arab Emirates OECD average Agree: In my mathematics class, I understand even the most difficult work Agree: I have always believed that mathematics is one of my best subjects Agree: I learn mathematics quickly Agree: I get good <grades> in mathematics Disagree: I am just not good at mathematics 0 20 40 60 % 80 100
  • 55. 94 Students’ mathematics anxiety Fig III.4.10 Percentage of students who reported "agree" or "strongly agree" with the following statements: Tunisia OECD average I worry that I will get poor <grades> in mathematics I feel helpless when doing a mathematics problem I get very nervous doing mathematics problems I get very tense when I have to do mathematics homework I often worry that it will be difficult for me in mathematics classes 0 20 40 60 % 80 100
  • 56. 95 Students' participation in mathematics-related activities Fig III.4.16 Percentage of students who reported "agree" or "strongly agree" with the following statements: Jordan OECD average I participate in a mathematics club I programme computers I play chess I do mathematics more than 2 hours a day outside of school I take part in mathematics competitions I do mathematics as an <extracurricular> activity I help my friends with mathematics I talk about mathematics problems with my friends 0 10 20 30 40 % 50 60 70
  • 57. Fig III.2.15 96 Malaysia Albania OECD average Agree: School has taught me things which could be useful in a job Agree: School has helped give me confidence to make decisions Disagree: School has been a waste of time Disagree: School has done little to prepare me for adult life when I leave school 0 20 40 60 % 80 100 120
  • 58. 97 Also worth noting o 85% of advantaged students but only 78% of disadvantaged students say feel they belong at school o More than one in three students in OECD countries say they had arrived late for school in the two weeks prior to the PISA test; and more than one in four students reported that they had skipped a class or a day of school during this period o Better teacher-student relations are strongly associated with greater student engagement at school o Even when girls perform as well as boys in mathematics, they tend to report less perseverance, less openness to problem solving, less motivation to learn mathematics, less self-belief in their ability to learn mathematics and more anxiety about mathematics than boys, on average; they are also more likely than boys to attribute failure in mathematics to themselves .
  • 59. 98 The parent factor Students whose parents have high educational expectations for them tend to report more perseverance, greater intrinsic motivation to learn mathematics, and more confidence in their own ability to solve mathematics problems than students of similar background and academic performance, whose parents hold less ambitious expectations for them.
  • 60. Parents’ expectations for their child have a strong influence on students’ behaviour towards school 100 Fig III.6.11 Percentage-point change in arriving late for school that is associated with parents expecting the child to complete a university degree 4 2 -2 -4 -6 -8 -10 -12 -14 Hungary Korea Croatia Hong Kong-China Macao-China Italy Portugal Chile Mexico Belgium (Flemish) -16 Germany Percentage-point change 0
  • 61. Parents’ high expectations can nurture students’ enjoyment in learning mathematics 101 Fig III.6.11 Change in the index of intrinsic motivation to learn mathematics that is associated with parents expecting the child to complete a university degree 0.50 0.45 0.35 0.30 0.25 0.20 0.15 0.10 0.05 Germany Mexico Macao-China Croatia Hungary Portugal Chile Hong Kong-China Italy Korea 0.00 Belgium (Flemish) Mean index change 0.40
  • 62. Parents’ high expectations can foster perseverance in their child 102 Fig III.6.11 Change in the index of perseverance that is associated with parents expecting the child to complete a university degree 0.35 0.25 0.20 0.15 0.10 0.05 Macao-China Korea Croatia Germany Hong Kong-China Chile Hungary Mexico Belgium (Flemish) Italy 0.00 Portugal Mean index change 0.30
  • 63. 10 3 Schools make a difference
  • 64. Grade repetition is negatively related to equity Fig IV.1.4 Adjusted by per capita GDP Greater equity 2 Variation in mathematics performance explained by socioeconomic status (%) 4 Macao-China 6 Kazakhstan Hong Kong-China Estonia Jordan Indonesia Norway Qatar Thailand Iceland Mexico Finland Canada Tunisia Japan Korea Italy UAE Serbia Croatia Russian Fed. Sweden Montenegro Lithuania Viet Nam Australia Turkey Argentina Latvia Switzerland Netherlands UK Brazil Greece Colombia Belgium Slovenia Ireland USA Shanghai-China Poland Czech Rep. Spain Singapore Israel Austria R2=0.05 Denmark Costa Rica Romania Germany New Zealand Chinese Taipei R2=0.07 Portugal 8 10 12 14 16 18 20 Bulgaria 22 Chile Peru Luxembourg Hungary France Slovak Rep. 24 Uruguay 26 -5 Less equity 0 5 10 15 20 25 30 Percentage of students who have repeated at least one grade 35 40 45
  • 65. Japan Norway Iceland Russian Federation Thailand + Korea + Finland + Sweden Poland Greece Denmark Czech Republic + New Zealand Australia Slovak Republic + Canada Latvia Ireland Hungary Austria United States OECD average 2003 Turkey Mexico Indonesia Hong Kong-China Italy Liechtenstein Switzerland Germany Netherlands France Spain + Portugal Luxembourg Brazil Belgium + Uruguay Tunisia Macao-China - Percentage of repeaters in 2003 and 2012 2012 Tab IV.2.18 70 2003 60 50 40 % 30 20 10 0
  • 66. Belgium Netherlands France Spain Germany Portugal Italy Austria United States Ireland Canada Australia Slovak Republic New Zealand Denmark Finland Sweden Korea Czech Republic Poland Slovenia United Kingdom Israel Iceland Estonia Norway Japan USD, PPPs Grade repetition is an expensive policy Fig IV.1.5 Total cost per repeater (one grade year) Total annual cost, relative to total expenditure on primary and secondary education (%) 60000 14 50000 12 10 40000 8 30000 % 6 20000 4 10000 2 0 0
  • 67. In most countries, disadvantaged students are more likely to have repeated a grade than advantaged students Fig IV.2.3 Socio-economically disadvantaged student (ESCS=-1) Socio-economically average student (ESCS = 0 ) Socio-economically advantaged student (ESCS = 1 ) Probability of repeating a grade 0.50 0.45 0.40 0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00 300 350 400 Mathematics score (score points) 450 500
  • 68. 80 70 Greece Austria Czech Republic Poland + Liechtenstein + Portugal Japan Finland Macao-China Luxembourg Germany Slovak Republic Mexico + OECD average 2003 Indonesia Turkey Denmark Italy Thailand Hungary Belgium Brazil Latvia + Tunisia Sweden + Switzerland Iceland Korea Hong Kong-China Uruguay Spain Canada + Netherlands United States Russian Fed. Australia New Zealand Ireland Change between 2003 and 2012 in ability grouping 2012 Fig IV.2.11 2003 % 90 + 2012 higher than 2003 - 2012 lower than 2003 60 50 40 30 20 10 0
  • 69. 113 Also worth noting o Stratification in school systems (e.g. grade repetition and selecting students at a young age for different “tracks” or types of schools) is negatively related to equity; and students in highly stratified systems tend to be less motivated than those in less-stratified systems
  • 70. 11 4 Money makes a difference… …but only up to a point
  • 71. Spending per student from the age of 6 to 15 and mathematics performance in PISA 2012 Fig IV.1.8 650 Cumulative expenditure per student less than USD 50 000 Mathematics performance (score points) Shanghai-China Cumulative expenditure per student USD 50 000 or more 600 Singapore Korea 550 Japan Switzerland PolandCanada Finland Netherlands Viet Nam Estonia Belgium Germany Czech Republic Australia Austria New Zealand Slovenia Ireland Denmark Latvia France UK Norway Portugal Iceland Lithuania Slovak Republic Croatia Italy Sweden United States Israel Hungary Spain Turkey 500 R² = 0.01 Luxembourg 450 Bulgaria Thailand Chile Mexico Montenegro Uruguay Malaysia 400 Tunisia Brazil Jordan Colombia Peru 350 R² = 0.37 300 0 20 000 40 000 60 000 80 000 100 000 120 000 140 000 160 000 Average spending per student from the age of 6 to 15 (USD, PPPs) 180 000 200 000
  • 72. Among high-income countries high-performers pay teachers more Fig IV.1.10 Mathematics performance (score points) 650 Per capita GDP less than USD 20 000 In 33 countries schools where a higher 600 share of principals reported that teacher shortages hinder learning tend to show lower performance 550 Shanghai-China Per capita GDP over USD 20 000 Singapore Hong Kong-China Korea Macao-China Japan R² = 0.09 Netherlands Finland Canada Belgium Austria Australia Germany Czech Rep. Iceland Ireland Latvia France Denmark New Zealand Slovenia UK Slovak Rep. Norway Italy Luxembourg Portugal Spain USA Hungary Croatia Israel Sweden Lithuania Romania Greece Bulgaria Thailand Malaysia Uruguay Chile Tunisia Montenegro Qatar Indonesia Colombia Argentina Peru Jordan Estonia 500 450 400 Poland Among low-income countries a host of other resources are the principal barriers 350 R² = 0.05 300 20 40 60 80 100 120 140 Teachers' salaries relative to per capita GDP (%) 160 180 200 220
  • 73. 0 Chinese Taipei Greece Japan Korea Thailand Hong Kong-… Montenegro Turkey Shanghai-China Viet Nam Romania Macao-China Tunisia Croatia Hungary Malaysia New Zealand Ireland Liechtenstein Costa Rica Czech Republic Australia Bulgaria Netherlands Jordan Belgium Latvia Spain Argentina OECD average Indonesia Singapore Russian Fed. Austria Iceland France Brazil Uruguay Lithuania Israel Qatar Slovak Republic Canada Estonia Germany U.A.E. Slovenia Serbia Italy Finland Colombia Chile United Kingdom Switzerland Luxembourg United States Sweden Kazakhstan Portugal Peru Poland Denmark Norway Mexico In many countries, more advantaged than disadvantaged students attend after-school lessons Fig IV.3.11 Percentage of all students participating in after-school lessons Students in the bottom quarter of socio-economic status Students in the top quarter of socio-economic status 100 90 80 70 60 % 50 40 30 20 10
  • 74. 118 Teacher shortage Fig IV.3.5 Percentage of students in schools whose principals reported that the following phenomena hindered student learning "to some extent" or "a lot": Slovenia OECD average Lack of qualified science teachers Lack of qualified mathematics teachers Lack of qualified language-of-instruction teachers Lack of qualified teachers of other subjects 0 5 10 15 % 20 25
  • 75. Luxembourg Jordan Thailand Turkey Shanghai-China Israel Colombia Peru Chile Netherlands Mexico Germany Viet Nam Russian Fed. Uruguay Norway Kazakhstan Indonesia Belgium Italy Malaysia Australia Brazil Iceland U.A.E. Singapore New Zealand Korea Switzerland Estonia Macao-China Costa Rica OECD average Sweden Argentina Tunisia Austria Qatar Ireland Chinese Taipei France Denmark United Kingdom Hong Kong-China Albania Japan Canada Slovak Republic Latvia Greece United States Czech Republic Croatia Finland Montenegro Romania Hungary Lithuania Slovenia Spain Serbia Portugal Bulgaria Poland Mean index Teacher shortage Mean index Top quarter of this index Fig IV.3.5 Bottom quarter of this index 3 2.5 2 1.5 1 0.5 0 -0.5 -1 -1.5
  • 76. -0.5 Korea Estonia Israel Kazakhstan Latvia Malaysia Slovenia Italy Poland Singapore Argentina Costa Rica Netherlands Portugal Colombia Bulgaria France Finland Tunisia Lithuania Qatar Macao-China Thailand Spain Greece Switzerland Romania Norway Russian Fed. Japan Austria Montenegro Croatia Canada U.A.E. OECD average Germany Denmark Hungary United Kingdom Luxembourg Hong Kong-China Belgium Iceland Jordan Peru Viet Nam Ireland United States Chile Czech Republic Serbia Turkey Mexico Indonesia Uruguay Shanghai-China Slovak Republic Sweden Brazil New Zealand Australia Chinese Taipei Albania Mean index difference Teacher shortage is more of concern in disadvantaged schools also in public schools, in most countries Fig IV.3.5 Difference between socio-economically disadvantaged and socio-economically advantaged schools Difference between public and private advantaged schools 1.5 Disadvantaged and public schools reported more teacher shortage 1 0.5 0 Advantaged and private schools r eported more teacher shortage -1
  • 77. 121 Adequacy of educational resources Fig IV.3.8 Percentage of students in schools whose principals reported that the following phenomena hindered student learning "not at all" or "very little“: Singapore OECD average Shortage or inadequacy of science laboratory equipment Shortage or inadequacy of instructional materials (e.g. textbooks) Shortage or inadequacy of computers for instruction Lack or inadequacy of Internet connectivity Shortage or inadequacy of computer software for instruction Shortage or inadequacy of library materials 50 60 70 80 90 % 100 110
  • 78. Singapore Qatar Australia Chinese Taipei Switzerland United Kingdom Hong Kong-China Japan Slovenia France United States U.A.E. Poland Macao-China Belgium Canada Austria Romania New Zealand Netherlands Hungary Portugal Lithuania Shanghai-China Uruguay Ireland Germany Korea OECD average Sweden Czech Republic Italy Luxembourg Latvia Spain Bulgaria Denmark Estonia Norway Finland Malaysia Iceland Greece Israel Chile Turkey Albania Jordan Russian Fed. Viet Nam Montenegro Croatia Brazil Argentina Slovak Republic Serbia Thailand Kazakhstan Indonesia Mexico Costa Rica Peru Tunisia Colombia Mean index Adequacy of educational resources Mean index Top quarter of this index Fig IV.3.8 Bottom quarter of this index 3.00 2.00 1.00 0.00 -1.00 -2.00 -3.00 -4.00
  • 79. 0.50 -1.50 Peru Costa Rica Mexico Brazil Indonesia Thailand Colombia New Zealand Turkey Argentina United States Uruguay Australia Chile Viet Nam Jordan Shanghai-China U.A.E. Romania Sweden Israel Bulgaria Chinese Taipei Malaysia Ireland Greece Tunisia Poland Canada Japan Macao-China OECD average Luxembourg Qatar Russian Fed. Iceland Belgium France Switzerland Portugal Hong Kong-China Spain Lithuania Denmark Kazakhstan Italy Czech Republic Netherlands Estonia Hungary Slovenia Austria Singapore Latvia Slovak Republic Montenegro Korea Germany Serbia United Kingdom Norway Croatia Finland Liechtenstein Albania Mean index difference Educational resources are more problematic in disadvantaged schools, also in public schools in most countries Fig IV.3.8 Difference between socio-economically disadvantaged and socio-economically advantaged schools Difference between public and private advantaged schools Disadvantaged and public schools reported better educational resources 0.00 -0.50 -1.00 Advantaged and private schools reported better educational resources -2.00
  • 80. 124 Quality assurance and school improvement Fig IV.4.14 Percentage of students in schools whose principal reported that their schools have the following for quality assurance and improvement: Shanghai-China OECD average Implementation of a standardised policy for mathematics (i.e. school curriculum with shared instructional materials accompanied by staff development and training) Regular consultation with one or more experts over a period of at least six months with the aim of improving the school Teacher mentoring Written feedback from students (e.g. regarding lessons, teachers or resources) External evaluation Internal evaluation/self-evaluation Systematic recording of data, including teacher and student attendance and graduation rates, test results and professional development of teachers Written specification of student-performance standards Written specification of the school's curriculum and educational goals 0 20 40 60 % 80 100 120
  • 81. 125 Students' views of how conducive classrooms are to learning Fig IV.5.4 Percentage of students who reported that the following phenomena occur "never or hardly ever" or "in some lessons”: Japan OECD average Students don’t listen to what the teacher says There is noise and disorder The teacher has to wait a long time for students to quiet down. Students cannot work well Students don’t start working for a long time after the lesson begins 0 20 40 60 % 80 100
  • 82. 120 Shanghai-China Hong Kong-China France Slovak Republic Macao-China Italy Switzerland Qatar Czech Republic Israel Thailand Argentina Denmark Belgium Viet Nam Germany U.A.E. United Kingdom Greece Indonesia Spain Chinese Taipei Singapore Japan Finland Uruguay Poland Sweden Australia New Zealand OECD average Netherlands Malaysia Austria Luxembourg Bulgaria Mexico Jordan Peru Iceland Portugal Brazil Turkey Romania Canada Norway Tunisia Lithuania Chile Serbia Korea United States Russian Fed. Costa Rica Kazakhstan Montenegro Colombia Croatia Slovenia Ireland Latvia Estonia Score point difference 126 Difference in mathematics performance, by attendance at preprimary school before accounting for students' socio-economic status Fig III.4.12 after accounting for students' socio-economic status 140 Students who attended pre-primary school perform better 100 80 60 40 20 0 -20
  • 83. 127 Also worth noting o Educational resources relate to student performance – 33% of the variation in math performance is explained by differences in principal’s responses to questions about the adequacy of science laboratory equipment, instructional material, ICT and libraries (GDP adjusted) o Adequacy of physical infrastructure unrelated to performance o Within countries, class time relates positively to performance – Holds also after accounting for socio-economic and demographic factors, but does not hold when pooling data across countries (learning outcomes are the product of quantity and quality) – The proportion of students in schools with after-school mathematics lessons is unrelated to system performance – Homework relates positively to school performance
  • 84. 128 Also worth noting o Most countries and economies with comparable data between 2003 and 2012 have moved towards betterstaffed and better-equipped schools o Students in 2012 were more likely than their counterparts in 2003 to have attended at least one year of pre-primary education – yet many of the students who reported that they had not attended pre-primary school are disadvantaged
  • 85. 12 9 High performers spend resources where they are needed most
  • 86. Countries with better performance in mathematics tend to allocate educational resources more equitably 700 Adjusted by per capita GDP 650 Mathematics performance (score points) Fig IV.1.11 30% of the variation in math performance across OECD countries is 600 explained by the degree of similarity of educational resources between advantaged and disadvantaged schools 550 500 450 Mexico Costa Rica 400 Shanghai-China Chinese Taipei Korea R² = 0.19 Viet Nam Singapore Hong Kong-China Estonia Japan Poland Slovenia Switzerland Latvia Finland Canada Belgium Germany Macao-China Slovak Rep. New Zealand UK IrelandIceland France DenmarkSpain Austria Australia Croatia Hungary Israel Romania Portugal Sweden Bulgaria Turkey USA Greece Norway Italy Serbia Thailand Malaysia Chile Kazakhstan Uruguay Jordan Brazil Indonesia UAE Montenegro Colombia Tunisia Argentina Luxembourg Peru 350 Qatar 300 1.5 1 Less equity 0.5 OECD countries tend to allocate at least an equal, if not a larger, number of teachers per student to disadvantaged schools; but disadvantaged schools tend to have great difficulty in attracting 0 -0.5 qualified teachers. Equity in resource allocation (index points) Greater equity
  • 87. 13 2 Governance matters Schools with more autonomy over curricula and assessments tend to perform better than schools with less autonomy where they are part of school systems with more accountability arrangements and greater teacher-principal collaboration in school management
  • 88. Countries that grant schools autonomy over curricula and assessments tend to perform better in mathematics 650 Fig IV.1.15 Shanghai-China Mathematics performance (score points) 600 Chinese Taipei Viet Nam 550 500 450 400 Korea Estonia Singapore Hong Kong-China Japan Poland Latvia Slovenia Belgium Czech Rep. Switzerland Canada Germany Finland New Zealand Lithuania Netherlands Portugal Hungary Austria Croatia Italy Spain France Australia Serbia UK Macao-China Turkey Norway Iceland Denmark R² = 0.13 Slovak Rep. Bulgaria Thailand Greece Romania Kazakhstan Israel Malaysia Chile Uruguay USA Sweden Jordan Costa Rica Indonesia Brazil Albania Luxembourg Tunisia Colombia UAE Argentina Peru 350 Qatar 300 -1.5 -1 -0.5 0 0.5 Index of school responsibility for curriculum and assessment (index points) 1 1.5
  • 89. Schools with more autonomy perform better than schools with less autonomy in systems with more collaboration School autonomy for resource allocation x System's level of teachers participating in school management Across all participating countries and economies Score points 485 480 475 470 465 460 Teachers participate in management 455 Teachers don't participate in management Less school autonomy More school autonomy Fig IV.1.17
  • 90. Schools with more autonomy perform better than schools with less autonomy in systems with standardised math policies Fig IV.1.16 School autonomy for curriculum and assessment x system's extent of implementing a standardised math policy (e.g. curriculum and instructional materials) Score points 485 480 475 470 465 460 Standardised math policy 455 No standardised math policy Less school autonomy More school autonomy
  • 91. Schools with more autonomy perform better than schools with less autonomy in systems with more accountability arrangements Fig IV.1.16 School autonomy for curriculum and assessment x system's level of posting achievement data publicly Score points 478 476 474 472 470 468 466 School data public 464 School data not public Less school autonomy More school autonomy
  • 92. % 0 Finland Belgium Shanghai-China Japan Austria Switzerland Argentina Macao-China Uruguay Peru Germany Costa Rica Spain Luxembourg Chinese Taipei Tunisia Ireland Jordan Indonesia Albania Croatia Greece Iceland Lithuania Latvia Hong Kong-… Liechtenstein Estonia Malaysia Denmark Italy Brazil Mexico Czech Republic OECD average France U.A.E. Poland Israel Hungary Qatar Singapore Colombia Portugal Slovenia Norway Bulgaria Serbia Canada Chile Turkey Romania Australia Korea Viet Nam Thailand Slovak Republic Russian Fed. Kazakhstan Montenegro New Zealand Sweden United Kingdom Netherlands United States Use of achievement data for accountability Post publicly Fig IV.4.13 Percentage of students in schools that use achievement data in the following ways: Track over time by an administrative authority 100 90 80 70 60 50 40 30 20 10
  • 93. 90 80 % 0 Finland Uruguay Greece + Switzerland + Ireland + Belgium + Sweden + Japan + Germany + Norway + Italy + Hungary + Slovak Republic Tunisia Denmark + OECD average 2003… Spain Australia + Luxembourg + Liechtenstein + Netherlands + Latvia Korea + New Zealand + Iceland + Brazil + United States Macao-China + Austria + Indonesia Turkey + Czech Republic + Mexico Hong Kong-China + Thailand + Portugal + Russian Federation + Poland Change between 2003 and 2012 in using student assessment data to monitor teachers 2012 Fig IV.4.19 Percentage of students in schools that use assessment data to monitor teachers: 2003 100 + 2012 higher than 2003 - 2012 lower than 2003 70 60 50 40 30 20 10
  • 94. 14 1 The issue is not how many charter schools a country has… …but how countries enable every school to assume charter type autonomy
  • 95. % Hong Kong-China Netherlands Chile Ireland Korea U.A.E. United Kingdom Indonesia Australia Qatar Chinese Taipei Argentina Spain Japan Denmark OECD average France Uruguay Jordan Thailand Hungary Luxembourg Peru Colombia Sweden Brazil Costa Rica Portugal Shanghai-China Mexico Slovak Republic Austria Albania Czech Republic Canada Viet Nam Switzerland Germany New Zealand United States Italy Malaysia Finland Poland Kazakhstan Estonia Slovenia What type of school do most students attend? Fig IV.1.22 Fig IV.1.22 Percentage of students attending Government-independent private schools Government-dependent private schools Government or public schools 100 90 80 70 60 50 40 30 20 10 0
  • 96. 100 -50 Chinese Taipei Hong Kong-China Thailand Viet Nam Luxembourg Switzerland Indonesia Italy Kazakhstan Japan Czech Republic Netherlands Estonia Albania Ireland United States Hungary Sweden Korea United Kingdom Finland Denmark OECD average France Shanghai-China Australia Spain Slovak Republic Mexico Germany Austria Colombia Chile Canada Poland Jordan Argentina United Arab Emirates Portugal Peru Costa Rica Brazil New Zealand Malaysia Slovenia Uruguay Qatar Score-point difference Differences in mathematics performance between private and public schools shrink considerably after accounting for socio-economic status 50 Fig IV.1.19 Observed performance difference After accounting for students’ and schools’ socio-economic status 75 Performance advantage of public schools 25 0 -25 Performance advantage of private schools -75 -100 -125
  • 97. 14 5 How the theory of school choice squares with the reality in families If offered a choice of schools for their child, parents consider criteria as “a safe school environment” and “a school’s good reputation” more important than “high academic achievement of students in the school”.
  • 98. School competition and mathematics performance Fig IV.1.18 Adjusted by per capita GDP 650 Shanghai-China There is no relationship between the prevalence of competition and overall performance level Mathematics performance (score points) 600 Korea Viet Nam 550 Poland Switzerland Finland 500 Lithuania France Iceland 450 Montenegro 400 R² = 0.030 Japan Netherlands Czech Rep. Slovak Rep. Hong Kong-China Singapore Latvia Belgium New Zealand Spain Serbia Macao-China Ireland Hungary Romania Austria UK Bulgaria Sweden USA Australia Turkey Thailand Greece Chile Uruguay Kazakhstan Malaysia Jordan Costa Rica Mexico Argentina Albania Brazil Tunisia Indonesia UAE Luxembourg Colombia Peru Italy Norway Estonia Germany Slovenia Portugal Chinese Taipei 350 Qatar 300 30 40 50 60 70 80 Percentage of students in schools that compete with at least one other school 90 100
  • 99. A school’s particular approach to teaching is not a determining factor when parents choose a school for their child Fig IV.4.5 Percentage of parents who reported that a particular approach to pedagogy is a very important criterion when choosing a school for their child All parents Parents in the bottom quarter of socio-economic status Parents in the top quarter of socio-economic status 80 70 60 50 % 40 30 20 10 Hungary Belgium (Fl. Comm.) Germany Italy Portugal Hong Kong-China Korea Chile Macao-China Mexico 0
  • 100. Expenses associated with schooling are a concern among disadvantaged families Fig IV.4.5 Percentage of parents who reported that expenses such as tuition, books, and room and board, are very important criteria when choosing a school for their child All parents Parents in the bottom quarter of socio-economic status Parents in the top quarter of socio-economic status 80 70 60 50 % 40 30 20 10 Belgium (Fl. Comm.) Germany Hong Kong-China Italy Hungary Macao-China Korea Croatia Portugal Mexico Chile 0
  • 101. Financial aid for school is a greater concern among disadvantaged parents Fig IV.4.5 Percentage of parents who reported that the availability of financial aid, such as a school loan, scholarship or grant, is a very important criterion when choosing a school for their child All parents Parents in the bottom quarter of socio-economic status Parents in the top quarter of socio-economic status 80 70 60 50 % 40 30 20 10 Belgium (Fl. Comm.) Germany Hungary Hong Kong-China Croatia Macao-China Korea Portugal Mexico Chile 0
  • 102. For disadvantaged families, physical access to school is a significant concern Fig IV.4.5 Percentage of parents who reported that the school’s distance from home is a very important criterion when choosing a school for their child All parents Parents in the bottom quarter of socio-economic status Parents in the top quarter of socio-economic status 80 70 60 50 % 40 30 20 10 Italy Hong Kong-China Macao-China Belgium (Fl. Comm.) Croatia Hungary Germany Korea Chile Mexico Portugal 0
  • 103. Advantaged families tend to seek out schools whose students are high achievers Fig IV.4.5 Percentage of parents who reported that students’ high academic achievement is a very important criterion in choosing a school for their child All parents Parents in the bottom quarter of socio-economic status Parents in the top quarter of socio-economic status 80 70 60 50 % 40 30 20 10 Belgium (Fl. Comm.) Hungary Italy Germany Hong Kong-China Croatia Macao-China Mexico Portugal Chile Korea 0
  • 104. A school’s reputation is a very important consideration among advantaged families Fig IV.4.5 Percentage of parents who reported that a school’s good reputation is a very important criterion when choosing a school for their child All parents Parents in the bottom quarter of socio-economic status Parents in the top quarter of socio-economic status 80 70 60 50 40 30 20 10 Croatia Hungary Macao-China Italy Korea Germany Belgium (Fl. Comm.) Hong Kong-China Mexico Chile 0 Portugal %
  • 105. Advantaged parents tend to seek out schools with an active and pleasant climate Fig IV.4.5 Percentage of parents who reported that an active and pleasant climate is a very important criterion when choosing a school for their child All parents Parents in the bottom quarter of socio-economic status Parents in the top quarter of socio-economic status 80 70 60 50 % 40 30 20 10 Hungary Belgium (Fl. Comm.) Croatia Italy Macao-China Hong Kong-China Mexico Germany Portugal Korea Chile 0
  • 106. Parents everywhere look for a safe school environment for their child Fig IV.4.5 Percentage of parents who reported that a safe school environment is a very important criterion in choosing a school for their child All parents Parents in the bottom quarter of socio-economic status Parents in the top quarter of socio-economic status 80 70 60 50 % 40 30 20 10 Belgium (Fl. Comm.) Hungary Germany Italy Croatia Mexico Macao-China Hong Kong-China Chile Korea Portugal 0
  • 107. 15 9 PISA 2012 Sample Question 4 Revolving Door Correct Answer: in the range from 103 to 105. Accept answers calculated as 1/6th of the circumference (100π/3). Also accept an answer of 100 only if it is clear that this response resulted from using π =3. Note: Answer of 100 without supporting working could be obtained by a simple guess that it is the same as the radius (length of a single wing). This item belongs to the space and shape category. Space and shape encompasses a wide range of phenomena that are encountered everywhere in our visual and physical world: patterns, properties of objects, positions and orientations, representations of objects, decoding and encoding of visual information, navigation and dynamic interaction with real shapes as well as with representations. SCORING: Description: Interpret a geometrical model of a real life situation to calculate the length of an arc Mathematical content area: Space and shape Context: Scientific Process: Formulate
  • 108. 15 10 5 0 Hong Kong-China Korea Japan Macao-China Liechtenstein Switzerland Belgium Poland Germany New Zealand Netherlands Canada Australia Estonia Finland Vietnam Slovenia OECD average Austria Czech Republic France Slovak Republic United Kingdom Luxembourg Iceland United States Israel Ireland Italy Hungary Portugal Norway Denmark Croatia Sweden Latvia Russian Federation Lithuania Spain Turkey Serbia Bulgaria Greece Romania United Arab Emirates Thailand 25 Shanghai-China 30 Singapore Chinese Taipei 16 0 PISA 2012 Sample Question 4 Percent of 15-year-olds who scored Level 6 or Above 20
  • 109. Find out more about PISA at www.pisa.oecd.org • All national and international publications • The complete micro-level database Thank you ! Email: Andreas.Schleicher@OECD.org Twitter: SchleicherEDU and remember: Without data, you are just another person with an opinion
  • 110. Do you have an idea on how to use this data to improve education in your country? Would you like to work with us to develop that idea? Apply to the Thomas J. Alexander fellowship programme! http://www.oecd.org/edu/thomasjalexanderfellowship.htm

Notas do Editor

  1. For AUT: manually delete the dot for 2009Annex B4 (volume 1)Instructions: Countries can appear in five possible figures, depending on the scale used (350-750, 300-700, 250-650, 200-600, 150-550). Please note that the right-hand axis (proficiency levels) is specific to the left-hand scale chosen, so be sure to use the corresponding graphSelect data to filter the country/economy that you wish to showFour countries and economies that began their participation after PISA 2003 the right part of the graph needs to be covered as missing data are assumed by the graph to be 0. Use the Blue rectangle with white lines for this purpose
  2. Figure I.2.15
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  6. (Fig. II.4.5)
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  13. Shows OECD average – chart can be adapted, to show further countries This is a selection. Next slide contains all items for this index
  14. Shows OECD average – chart can be adapted, to show further countries
  15. (Fig. II.4.5)
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  22. Answer
  23. Scores against 15-year-olds