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Organisation for Economic Cooperation and Development (OECD)
Programme for International
Student Assessment - PISA
Origins of PISA
2
 OECD
work on education statistics
and indicators

major development commenced in late
1980s
 Network
on educational outcomes
 Council decision in 1997
3
PISA 2000 country participation
OECD Partner countries (4)
OECD countries (28)
4
PISA 2003 country participation
OECD Partner countries (11)
OECD countries (30)
5
PISA 2006 country participation
OECD Partner countries (28)
OECD countries (30)
6
Making international comparisons of
achievement requires decisions about...
what to assess,
whom to assess.
7
Deciding what to assess...
looking back at what they were expected
to have learned
OR
looking ahead to what they can do with
what they have learned.
For PISA, the OECD countries chose the latter.
8
PISA assessments



Reading literacy
 Using, interpreting and reflecting on written
material.
Mathematical literacy
 Recognising problems that can be solved
mathematically, representing them mathematically,
solving them.
Scientific literacy
 Identifying scientific questions, recognising what
counts as scientific evidence, using evidence to draw
conclusions about the natural world.
9
Development of the PISA tests
Development of assessments
10


Frameworks by international experts
Assessment materials






submitted by countries
developed by research consortium
screened for cultural bias
translated into English & French originals
trialled to check items working consistently in all countries
Final tests


items shown in trial to be culturally biased removed
best items chosen for final tests
– balanced to reflect framework
– range of difficulties
– range of item types
11
Measuring mathematical literacy in
PISA 2003
12
Mathematical literacy in PISA
The real world
The mathematical World
Making the problem amenable
to mathematical treatment
A model of reality
Understanding,
structuring and
simplifying the
situation
A mathematical
model
Using relevant
mathematical
tools to solve
the problem
A real situation
Validating
the results
Mathematical
results
Real results
Interpreting
the mathematical results
Mathematical literacy in PISA
13

The capacity to:


identify, understand and engage in mathematics;
make well-founded judgements about the role
that mathematics plays in an individual’s current
and future:
–
–
–
–

private life
occupational life
social life with peers and relatives
life as a constructive, concerned and reflective citizen.
Seen as depending on…



mathematical knowledge and skills,
ability to think and work mathematically,
ability to apply the knowledge in a wide variety
of contexts.
14 Measuring mathematical literacy in
PISA 2003

Content




Space and shape
Change and relationships Quantity
Uncertainty
Process skills



Reproduction: use of practised knowledge, routine procedures…
Connections: somewhat familiar but not routine…
Reflection: insight, creativity in choosing mathematical
concepts…
15
Deciding whom to assess...
grade-based sample
OR
age-based sample
For PISA, the OECD countries chose the latter, selecting
15-year-olds in school as the population.
PISA sampling requirements
16


Population: all 15-year-olds in school
Sample




minimum of 150 schools per country
two random samples: schools and replacement schools
if school declines, replacement school is invited
stringent requirements set by countries (85% of
selected schools, 80% of selected students within
schools)
Key features of PISA 2003 assessment
17

Information collected

each student
– 2 hours on paper-and-pencil tasks (subset of all
questions)
– ½ hour for questionnaire on background, learning
habits, learning environment, engagement and
motivation


school principals
– questionnaire (school demography, learning
environment quality)
Sample


275,000 students
41 participating countries
18
Results from PISA 2003
19
PISA provides five key benchmarks for the
quality of education systems
1. Overall performance of education systems
2. Equity in the distribution of learning
opportunities
3. Consistency of performance standards
across schools
4. Gender differences
5. Foundations for lifelong learning
20
Mean mathematics scores – selected
countries
300
350
400
450
500
550
600
Finland
Korea
Netherlands
Japan
Canada
Belgium
Switzerland
Australia
New Zealand
Czech Rep.
Iceland
Denmark
France
Sweden
Austria
Germany
Ireland
Slovak Rep.
Norway
Poland
Hungary
Spain
USA
Portugal
Italy
Greece
Turkey
Mexico
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Table 2.5c, p.356.
21
What students can do in mathematics
OECD
Level 6
4%
Level 5
10
%
Level 4
18
%
Level 3
22
%
Level 2
21
%
Level 1
15
%
Below
Level 1
11
%
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Table 2.5a, p.354.
Level 6
Level 1
Below Level 1
100%
0%
Level 5
20%
Level 4
40%
60%
Level 3
Level 2
80%
Greece
Portugal
Italy
United States
Spain
Poland
Hungary
Norway
Slovak Republic
Germany
Ireland
Austria
Sweden
France
Czech Republic
Denmark
Iceland
New Zealand
Australia
Belgium
Switzerland
Japan
Netherlands
Canada
Korea
Finland
22
Percentage of students at each of the
proficiency levels on the mathematics scale
23
What students can do in reading
10%
Level 5
22%
Level 4
29%
Level 3
22%
12%
Level 2
Level 1
OECD
Average
6
%
Below Level 1
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Table 6.1, p.443.
100%
Mexico
Turkey
Slovak Republic
Greece
Italy
Portugal
Hungary
Spain
Czech Republic
Austria
Iceland
Germany
United States
Denmark
Poland
France
Japan
Norway
Switzerland
Belgium
Netherlands
Sweden
New Zealand
Ireland
Australia
Canada
Korea
Finland
24 Percentage of students at each of the
proficiency levels in reading
0%
20%
40%
60%
80%
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Table 6.1, p.443.
Performance in all domains
25
Hong Kong
Finland
Korea
Netherlands
Japan
Canada
Belgium
Macao
Switzerland
Australia
New
Zealand
Czech Rep.
Iceland
Denmark
France
Sweden
Austria
Germany
Ireland
Slovak Rep.
Norway
Luxembourg
Poland
Hungary
Spain
United
States
Portugal
Italy
Greece
Turkey
Mexico
Mathematics
Reading
Science
Problem Solving
26
Securing an equitable distribution of
learning opportunities
Measured by the impact students’ and schools’
socio-economic background has on performance –
not merely by the distribution of learning
outcomes
27
Social background and student performance
Student performance
High
On average, there is a 45
point change in
mathematics score for a
one standard deviation
change in social
background
Low
-3
Disadvantage
-2
-1
0
1
PISA Index of social background
2
3
Advantage
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Figure 4.8, p.176.
School performance and schools’ socioeconomic background - Sweden
28
Student performance
700
Student performance and student SES
School proportional to size
500
300
-3
Disadvantage
-2
-1
0
1
PISA Index of social background
2
Advantage
3
29
High performance
Hong Kong-China
High performance
Korea
Low social equity
Netherlands
Liechtenstein
High social equity540
Macao-China
Switzerland
Australia
New Zealand
Germany
Hungary
520
Czech Republic
Denmark
France
Sweden
Austria
Ireland
Slovak Republic
Poland
Portugal
Iceland
500
Norway
Luxembourg
United States

High performance
Japan
Canada
Belgium

Finland
Spain
Latvia
480
Russian Federation
Italy
Low performance
Low performance
Low social equity
High social equity
460
Greece
Strong 30
impact of social
background
20
Low Performance
10
440
0
Moderate impact of
social background
30
Student performance and spending per student
600
Performance in mathematics
550
Korea
Czech republic
Ireland
500
Slovak republic
Poland
Finland
Japan
Netherlands
Belgium
Canada
Australia
Iceland
Sweden
Germany
France
Hungary
Spain
Portugal
Switzerland
Denmark
Austria
Norway
United States
Italy
450
Spending
per student is positively associated
with average student performance…
… but
400 not a guarantee for high outcomes

Greece
Mexico
Australia, Belgium,
Canada, the Czech Republic,
Finland, Japan, Korea and the Netherlands do well R2 = 0.28
350in terms of “value for money”…
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
90,000
100,000
… while some of the big spenders perform
Cumulative expenditure (US$)
below-average

31
Ensuring consistent performance
standards across schools
Between and within-school variation in
performance
Iceland
Finland
Norway
Sweden
Poland
Denmark
Ireland
Canada
Spain
New Zealand
Australia
United States
Mexico
Portugal
Luxembourg
Switzerland
Greece
Slovak Republic
Korea
Czech Republic
Netherlands
Austria
Germany
Italy
Belgium
Japan
Hungary
Turkey
32
Is it all innate ability?
Variation in student performance
140
120
100
80
60
40
20
0
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Table 4.1a, p.383.
Is it all innate ability?
33
Variation in student performance in mathematics
100
Variation of
performance within
schools
80
60
40
20
0
-20
-40
Variation of
performance between
schools
-60
Iceland
Finland
Norway
Sweden
Poland
Denmark
Ireland
Canada
Spain
New Zealand
Australia
United States
Mexico
Portugal
Luxembourg
Switzerland
Greece
Slovak Republic
Korea
Czech Republic
Netherlands
Austria
Germany
Italy
Belgium
Japan
Hungary
Turkey
-80
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Table 4.1a, p.383.
34
Bridging the gender gap
Performance, attitudes and motivation
35
Gender differences
 In

reading, girls are far ahead
In all countries, girls significantly
outperform boys in reading
 In
mathematics, boys tend to be
somewhat ahead in most countries
…However …
Gender differences
36
Females perform
better
-60
-40
-20
Males perform
better
0
20
Liechtenstein
Korea
Macao-China
Greece
Slovak Republic
Italy
Luxembourg
Switzerland
Denmark
Brazil
Turkey
Czech Republic
Ireland
New Zealand
Portugal
Tunisia
Uruguay
Canada
Mexico
Russian Federation
Germany
Spain
France
Japan
Hungary
Austria
Belgium
Finland
Sweden
United States
Norway
Poland
Australia
Netherlands
Hong Kong-China
Indonesia
Latvia
Serbia
Thailand
Iceland
40
Performance in mathematics
-60
Females perform
better
-40
-20
Males perform
better
0
20
Performance in reading
40
OECD (2004), Learning for tomorrow’s world: First results from PISA 2003, Tables 2.5c, 6.3, pp.356, 445.
37
Governance of the school system

In many of the best performing countries



Decentralised decision-making is combined with
devices to ensure a fair distribution of
substantive educational opportunities
The provision of standards and curricula at
national/subnational levels is combined with
advanced evaluation systems
Process-oriented assessments and/or
centralised final examinations are complemented
with individual reports and feed-back
mechanisms on student learning progress
38
Support systems and professional
teacher development

In the best performing countries





Effective support systems are located at
individual school level or in specialised support
institutions
Teacher training schemes are selective
The training of pre-school personnel is closely
integrated with the professional development of
teachers
Continuing professional development is a
constitutive part of the system
Special attention is paid to the professional
development of school management personnel
39
Student approaches to learning

The ability to manage one’s learning is both an
important outcome of education and a contributor
to student literacy skills at school


Different aspects of students’ learning
approaches are closely related


Well-motivated and self-confident students tend to
invest in effective learning strategies and this
contributes to their literacy skills
Immigrant students tend to be weaker
performers
…

Learning strategies, motivation, self-related beliefs,
preferred learning styles
but they do not have weaker characteristics as learners
Boys and girls each have distinctive strengths and
weaknesses as learners


Girls stronger in relation to motivation and selfconfidence in reading
Boys believing more than girls in their own efficacy as
learners and in their mathematical abilities
40
Thematic Reports
 To
complement the initial report.
 In different areas of interest often
based on options parts of the
questionnaire
 Two of particular interest:


Where Immigrant Students Succeed
Are Students Ready for a Technology Rich
World
Key Issues
41
Policy attention is shifting from managing and
containing migration inflows to addressing
challenges of integration
 Schools can play a central role in integration
processes
 Preparation for school-work transitions
 Overcoming language barriers
 Transmission of norms and values
 PISA provides first-time comparative data on
cognitive and non-cognitive learning outcomes
of immigrant students…
 Comparison with native peers
 Comparison with immigrant student

42
 The
report compares three student
populations…



Native students are students who were born
in the country of assessment or who had at
least one parent born in that country
Second-generation immigrant students are
students who were born in the country of
assessment, but whose parents were born in
another country, i.e. students who have
followed their entire school career in the
country of assessment
First-generation immigrant students are
students who were not born in the country
of assessment and whose parents were also
born in another country
43
 Key

600
550 
500
450
Mathematics
performance
On average across the 17 countries, 15-
Native studentsfirst-generation
Second-generation students
First-generationscore
students
year-old
immigrants
in mathematics more
than oneOECD
school
year
Native students
average = 500
behind their native counterparts
Second-generation students
The performance disadvantageFirst-generation
varies widely
students
across countries from negligible amounts
to…
…more than 90 score points in Belgium and Sweden
for first-generation students
…more than 90 score points in Belgium and
Germany for second-generation students
The performance of immigrant students also
varies in absolute terms
Ko
ng
-C
N
hi
et
na
he
rl
an
ds
Be
Sw lgiu
m
it
ze
rl
an
d
Ca
N
na
ew
da
Ze
al
M
an
ac
d
ao
-C
hi
na
A
us
tr
al
Ge i a
rm
an
y
Fr
an
ce
D
en
m
ar
k
Sw
ed
en
A
us
tr
Lu
ia
xe
m
bo
ur
g
N
U
or
ni
wa
te
Ru
y
d
ss
St
ia
at
n
Fe
es
de
ra
ti
on
400 
findings
H
on
g
…with second-generation immigrants in Canada
outperforming their German counterparts by 111
score points
Where immigrant students succeed – A comparative review of performance and engagement in PISA 2003: Figure 2.2a.
Unemployment rates by immigration background
%
Native-born (2003)
Foreign-born (2003)
20
15
10
5
er
m
an
y
Fr
an
ce
Be
U
lg
ni
iu
te
m
d
S
ta
te
s
A
us
tr
al
ia
Ca
na
da
S
w
ed
en
A
us
tr
ia
D
en
m
ar
k
N
or
w
Lu
ay
xe
m
bo
N
ur
et
g
he
rl
an
S
ds
w
it
ze
rl
an
d
0
G
44
Where immigrant students succeed – A comparative review of performance and engagement in PISA 2003: Table 1.4.
Larger immigrant populations do not imply lower
overall performance
560
Hong Kong-China
550
Netherlands
540
Mathematics performance
45
Canada
Switzerland
Australia
New Zealand
Belgium
530
520
Macao-China
Denmark
510
Sweden
500
France
Austria
Germany
Norway
490
Luxembourg
United States
480
r = 0.30, p=0.25
Russian
470
Federation
460
0
20
40
60
80
Percentage of immigrant students in the country
100
46
Mathematics performance by proficiency levels
In PISA Level 2 demonstrates an essential foundation of mathematics skills
Percentage of native students
in
N
a
et
he
rl
an
ds
Level 3
H
on
g
Ko
ng
-C
h
da
Ca
na
us
tr
al
ia
Ge
rm
an
y
Be
lg
iu
M
m
ac
ao
-C
hi
na
Sw
it
ze
rl
an
d
A
an
d
Ze
al
Percentage of first-generation immigrant students
Level 2
Level 1
in
N
a
et
he
rl
an
ds
H
on
g
Ko
ng
-C
h
da
Ca
na
us
tr
al
ia
Ge
rm
an
y
Be
lg
iu
M
m
ac
ao
-C
hi
na
Sw
it
ze
rl
an
d
A
an
d
Ze
al
ce
Below 1
N
ew
Fe
de
ra
ti
U
on
ni
te
d
St
at
es
N
or
wa
Lu
y
xe
m
bo
ur
g
A
us
tr
ia
Sw
ed
en
De
nm
ar
k
Ru
ss
ia
n
N
ew
Fr
an
ce
Level 4
Fr
an
Ru
ss
ia
n
100
80
60
40
20
0
-20
-40
-60
PISA
Proficiency
Levels
Levels
5 and 6
Fe
de
ra
ti
U
on
ni
te
d
St
at
es
N
or
wa
Lu
y
xe
m
bo
ur
g
A
us
tr
ia
Sw
ed
en
De
nm
ar
k
100
80
60
40
20
0
-20
-40
-60
Where immigrant students succeed – A comparative review of performance and engagement in PISA 2003: Figure 2.4a.
47 Students’ interest in and enjoyment
of mathematics (OECD average)
Native
students
Secondgeneration
immigrant
students
Firstgeneration
immigrant
students
I enjoy reading about
mathematics.
28
35
41
I look forward to my
mathematics lessons.
31
40
47
I do mathematics because
I enjoy it.
38
43
48
I am interested in the
things I learn in
mathematics.
52
59
64
Stronger in 9 countries
Effect size 0.16
Stronger in 14
countries
Effect size 0.32
Where immigrant students succeed – A comparative review of performance and engagement in PISA 2003: Figures 4.2 and 4.9.
49
Are students ready for a technology-rich world?

First internationally comparative data on:



The opportunities 15-year-old students
have for using computers at home and at
school
How they use computers and their
attitudes to them;
The relationship between computer use and
performance in key school subjects.
50
Access to computers at school has
increased rapidly between PISA 2000 and
PISA 2003…
51
…but in some countries students still have
only limited opportunity to use computers
at school.
0.0
Portugal
United Kingdom1
Tunisia
Brazil
Russian Federation
Serbia
Turkey
Indonesia
Uruguay
Thailand
Latvia
Poland
Slovak Republic
0.2
Germany
0.3
Spain
5 or
fewer
students
per
computer
Greece
Mexico
Ireland
Czech Republic
Macao-China
Italy
Netherlands
Belgium
Sweden
Finland
Switzerland
Norway
Iceland
Luxembourg
Denmark
Japan
Canada
Austria
Hong Kong-China
New Zealand
Hungary
Korea
Australia
0.4
United States
Liechtenstein
52
Number of computers per student
(PISA 2003)
More
than 10
students
per
computer
0.1
1. Response rate too low to ensure comparability.
Source: OECD (2005) Are students ready for a technology-rich world? What PISA studies tell us, Figure 2.8, p.27.
53
Access to computers at school is more
universal than access to computers at
home, but students report using
computers much more frequently at home.
54
Percentage of students using a computer at least
a few times each week
United Kingdom1
Thailand
Japan
100%
Percentage of students
reporting they useRussian Federation
computers “Almost
Turkey
every day” or “A few
times each week”:
Canada
Iceland
Sweden
Liechtenstein
Australia
Mexico
At home
Korea
Latvia
Denmark
Serbia
At school
Belgium
0%
Tunisia
United Sta
Greece
Germany
Uruguay
Switzerland
Poland
Austria
Ireland
Slovak Republic
Hungary
Czech Republic
1. Response rate too low to ensure comparability.
New Zealand
Italy
Finland
Portugal
Source: OECD (2005) Are students ready for a technology-rich world? What PISA studies tell us, Figure 3.2, p.37.
55
What do students use computers to do?

PISA asked students how often they used:













The Internet to look up information about people things or ideas
Games on a computer
Word processing (e.g. <Microsoft Word® or WordPerfect®>)
The Internet to collaborate with a group or team
Spreadsheets (e.g. <Lotus 1 2 3® or Microsoft Excel®>)
The Internet to download software (including games)
Drawing, painting or graphics programs on a computer
Educational software such as mathematics programs
The computer to help learn school material
The Internet to download music
The computer for programming
A computer for electronic communication (e.g. e-mail or “chat
rooms”)
Students could choose from the following answers:

Almost every day, A few times each week, Between once a week
and once a month, Less than once a month, Never
56
Students use computers for a wide range
of purposes and not just to play games…
57
Students' use of computers (1)
Percentage of students reporting they use the following “Almost every day” or “A
few times each week”:
The Internet to look up information about people, things or ideas.
Games on a computer.
Word processing (e.g. <Word® or WordPerfect®>)
80
60
40
United Kingdom1
Japan
Slovak Republic
Word processing
– 48% on
average
Source: OECD (2005) Are students ready for a technology-rich world? What PISA studies tell us,
Figures 3.3 and 3.4, pp.39 and 41.
Turkey
Ireland
Finland
Hungary
Poland
Greece
Mexico
Internet
Games – 53% on
research – 55%
average
1. Response rate
low to ensure comparability.
ontooaverage
Germany
Italy
Czech Republic
OECD average
Switzerland
Portugal
Korea
Belgium
Austria
Sweden
New Zealand
Denmark
Iceland
Australia
Canada
0
United States
20
58
… a minority of students frequently use
educational software on computers…
59
Students' use of computers (2)
Percentage of students reporting they use the following “Almost every day” or “A
few times each week”:
Educational software such as mathematics programs
The computer to help learn school material
80
60
40
Source: OECD (2005) Are students ready for a technology-rich world? What PISA studies tell us,
Figure 3.4, p.41.
Japan
Ireland
Finland
Korea
United Kingdom1
Educational
software - 13%
on average
Switzerland
Liechtenstein
Russian Federation
Greece
Sweden
Belgium
Latvia
Poland
Czech Republic
Germany
Serbia
Canada
OECD average
Hungary
Austria
New Zealand
To learn school
material - 30% on
1. Response rate too low to ensure comparability.
average
Slovak Republic
Turkey
Australia
United States
Thailand
Iceland
Tunisia
Italy
Mexico
Denmark
Uruguay
0
Portugal
20
60
In general, students are confident in
performing routine and Internet tasks on
computers.
61
Routine tasks on a computer –
percentage of students who are confident (OECD average)
I can do this…
With
help
By
myself
Open a file
90
7
Play computer games
90
7
Start a computer game
86
10
Save a computer document or file
88
8
Delete a computer document or file
88
8
Draw pictures using a mouse
85
10
Print a computer document or file
86
9
Scroll a document up and down a screen
87
8
Create/edit a document
80
13
Move files from one place to another on a computer
76
17
Copy a file from a floppy disk
75
16
Source: OECD (2005) Are students ready for a technology-rich world? What PISA studies tell us, Table 3.9, p.110.
62
Internet tasks on a computer –
percentage of students who are confident (OECD average)
I can do this…
By
myself
With
help
Get onto the Internet
88
7
Write and send e-mails
79
12
Copy or download files from the
Internet
70
19
Download music from the Internet
66
21
Attach a file to an e-mail message
58
24
At least 90% of students report confidence in these tasks in Australia,
Canada, Iceland, Korea, New Zealand, Sweden and the United States.
Source: OECD (2005) Are students ready for a technology-rich world? What PISA studies tell us, Table 3.11, p.112.
63
In general, 15-year-old boys report higher
confidence than girls do in performing
computing tasks and these differences are
particularly apparent for the more
demanding computing tasks...
64
High-level tasks on a computer –
percentage of students who are confident to perform
these tasks by themselves or with help (OECD average)
Boys
Girls
Use software to find and get rid of computer viruses
79
54
Create a multi-media presentation (with sound, pictures, video)
77
62
Create a computer program (e.g. in Logo, Pascal, Basic)
63
48
Construct a Web page
71
61
Create a presentation (e.g. using <Microsoft® PowerPoint® >
79
70
Use a spreadsheet to plot a graph
79
70
Use a database to produce a list of addresses
85
79
Source: OECD (2005) Are students ready for a technology-rich world? What PISA studies tell us, Table 3.14, p.115.
65
Students who are established computer
users perform better than students with
limited computing experience.
… and diminishes somewhat when socio-economic
background factors are taken into account
66
between students who reported using computers less than one year and those using computers more than five years
140
between students who reported using computers less than one year and those using computers three to five years
between students who reported using computers less than one year and those using computers one to three years
120
100
80
60
40
20
Ireland
Finland
Greece
Canada
Japan
Turkey
Slovak Republic
Czech Republic
Portugal
Poland
Australia
Mexico
Sweden
Hungary
Korea
Italy
Denmark
Austria
New Zealand
Germany
United States
Iceland
Belgium
Switzerland
0
67
If more experience counts, more frequent
use does not necessarily
Looking at a wide range of students’ use of
computers, moderate users perform
better than students who are either not
using computers/using them rarely or are
using computers very often…
68 Frequency of use of computer to perform a
wide range of tasks and student performance
Index of ICT Internet/entertainment use
Index of ICT program/software use
Reading performance
Mathematics performance
525
525
500
500
475
475
Bottom
Second
Third
Top
Bottom
Second
Third
Top
quarter
quarter
quarter
quarter
quarter
quarter
quarter
quarter
Students reporting a moderate use
of computers to perform a range of
tasks
Source: OECD (2005) Are students ready for a technology-rich world? What PISA studies tell us, Figure 4.6, p.65.
69
Other research
 “Northern
lights”
 Regional studies
 Longitudinal studies
 Science attitudes
 Reading engagement
 Mathematics anxiety
 Indigenous students
 Rural education
 Selection practices
70
Other research
 Social
background
 Teaching and learning strategies –
cumulative study (caution)
 Problem solving
71
Some country interests
Germany - social background, regional effects,
effect of tracking, migration
 Netherlands – social background, migration
 Australia – longitudinal, indigenous, rural,
regions
 Japan – attitudes to science,
 US – reading interest, difference in
performance of students in TIMSS and in
PISA
 Belgium – regions, social background
 Switzerland – grade sample

72
Some country interests
 Denmark
– longitudinal
 Luxembourg – language background
 Italy – regions
 Ireland – relationship of PISA with
National examinations
 Turkey – school variation
 Canada – longitudinal, province
differences
 Iceland – gender differences
73
Further information

www.pisa.oecd.org
– All national and international publications
– The complete database
– Data analysis manuals (SPSS, SAS)

email: [email protected]

[email protected]