PISA 2012 is the programme’s 5th survey. It assessed the competencies of 15-year-olds in reading, mathematics and science (with a focus on mathematics) in 65 countries and economies.
Around 510 000 students between the ages of 15 years 3 months and 16 years 2 months participated in the assessment, representing about 28 million 15-year-olds globally.
The students took a paper-based test that lasted 2 hours. The tests were a mixture of open-ended and multiple-choice questions that were organised in groups based on a passage setting out a real-life situation. A total of about 390 minutes of test items were covered. Students took different combinations of different tests. They and their school principals also answered questionnaires to provide information about the students' backgrounds, schools and learning experiences and about the broader school system and learning environment.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
Figure I.2.15
Figure I.2.15
Figure I.2.15
Figure I.2.15
(Fig. II.4.5)
(Fig. II.4.5)
(Fig. II.4.5)
(Fig. II.4.5)
(Fig. II.4.5)
(Fig. II.4.5)
(Fig. II.4.5)
Shows OECD average – chart can be adapted, to show further countries This is a selection. Next slide contains all items for this index
Shows OECD average – chart can be adapted, to show further countries