Over half a million students representing 28 million 15-year-olds in 65 countries/economies took an internationally agreed 2-hour test and responded to questions on their personal background, their schools and their engagement with learning and school

1. OECD EMPLOYER
BRAND
Playbook
1
Insights from PISA
for Schools and
Local Educators
Programme for
International Student
Assessment (PISA)
Alejandro Gomez Palma
Policy Analyst
Organisation for Economic
Co-operation and Development
(OECD)
Presentation for Local Educators
from the USA
1 April 2014

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 2012 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 – e.g. PISA for Schools
• Productive feedback to fuel improvement at every level of the system .

4. Math teaching and learning ≠ math
teaching and learning
PISA = reason mathematically and understand, formulate, employ
and interpret mathematical concepts, facts and procedures (not curriculum-
based but content is important)
4

5. 5
The real world The world of mathematics
A real situation
Mathematical model
Results of the
mathematical
procedure
Real results
Understanding the
situation, structuring
and simplifying it
Transforming the problem to
be dealt with mathematics
Interpreting the
mathematical results
Employing
mathematical
tools to solve a
problem
Validating the results
PISA = competencies, skills and content = reason mathematically and use
mathematical concepts, procedures, facts and tools
A model from
reality

6. 6
Climbing Mount Fuji
Mount Fuji is a famous dormant volcano
in Japan.
Mount Fuji is only open to the public for
climbing from 1 July to 27 August each
year. About 200 000 people climb
Mount Fuji during this time.
On average, about how many people
climb Mount Fuji each day?
A. 340 (answer code: pisa1a)
B. 710 (answer code: pisa1b)
C. 3400 (answer code: pisa1c)
D. 7100 (answer code: pisa1d)
E. 7400 (answer code: pisa1e)
PISA 2012 Sample Question

7. 7
Climbing Mount Fuji
Correct Answer: C. 3400
This item belongs to the quantity category. The notion of quantity may be the most
pervasive and essential mathematical aspect of engaging with, and functioning in, our
world. It incorporates the quantification of attributes of objects, relationships, situations
and entities in the world, understanding various representations of those
quantifications, and judging interpretations and arguments based on quantity.
SCORING:
Description: Identify an average daily rate given a total number and a
specific time period (dates provided)
Mathematical
content area:
Quantity
Context: Societal
Process: Formulate
PISA 2012 Sample Question 1

8. 9
Helen the Cyclist
Helen has just got a new bike. It has a speedometer which
sits on the handlebar. The speedometer can tell Helen the
distance she travels and her average speed for a trip.
Helen rode 6 km to her aunt’s house. Her speedometer
showed that she had averaged 18 km/h for the whole trip.
Which one of the following statements is correct?
A. It took Helen 20 minutes to get to her aunt’s house. (answer code: pisa2a)
B. It took Helen 30 minutes to get to her aunt’s house. (answer code: pisa2b)
C. It took Helen 3 hours to get to her aunt’s house. (answer code: pisa2c)
D. It is not possible to tell how long it took Helen
to get to her aunt’s house. (answer code: pisa2d)
PISA 2012 Sample Question 2

9. 10
Correct Answer: A. It took Helen 20 minutes to get to her aunt’s house.
This item belongs to the change and relationships category. This involves understanding
fundamental types of change and recognising when they occur in order to use suitable
mathematical models to describe and predict change.
SCORING:
Description: Calculate time travelled given average speed and distance
travelled
Mathematical
content area:
Change and relationships
Context: Personal
Process: Employ
Helen the Cyclist
PISA 2012 Sample Question 2

10. 11
Percent of 15-year-olds who scored Level 3 or Above
Shanghai-China
Singapore
HongKong-China
Korea
ChineseTaipei
Macao-China
Japan
Liechtenstein
Switzerland
Estonia
Netherlands
Finland
Canada
Poland
Vietnam
Germany
Belgium
Austria
Ireland
Denmark
Australia
CzechRepublic
Slovenia
NewZealand
France
UnitedKingdom
Iceland
OECDaverage
Latvia
Norway
Luxembourg
Portugal
Spain
Italy
RussianFederation
SlovakRepublic
Sweden
Lithuania
UnitedStates
Hungary
Israel
Croatia
Greece
Serbia
Turkey
Bulgaria
Romania
UnitedArabEmirates
Kazakhstan
Chile
Thailand
Malaysia
Uruguay
Montenegro
Mexico
Albania
Qatar
CostaRica
Brazil
Argentina
Tunisia
Jordan
Peru
Colombia
Indonesia
0
10
20
30
40
50
60
70
80
90
100
PISA 2012 Sample Question 2

11. Singapore
Hong Kong-ChinaChinese Taipei
Korea
Macao-China
Japan Liechtenstein
Switzerland
Netherlands
Estonia Finland
Canada
Poland
Belgium
Germany Viet Nam
Austria Australia
IrelandSlovenia
DenmarkNew Zealand
Czech Republic France
United Kingdom
Iceland
LatviaLuxembourg Norway
Portugal ItalySpain
Russian Fed.Slovak Republic United States
LithuaniaSwedenHungary
Croatia
Israel
Greece
SerbiaTurkey
Romania
Bulgaria
U.A.E.
Kazakhstan
Thailand
Chile Malaysia
Mexico
410
420
430
440
450
460
470
480
490
500
510
520
530
540
550
560
570
580
Mean score
High mathematics performance
Low mathematics performance
… Shanghai-China performs above this line (613)
… 12 countries perform below this line
Average performance
of 15-year-olds in
Mathematics
Fig I.2.13
US
Massachusetts
Connecticut
Florida
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 )

12. Socially equitable
distribution of learning
opportunities
High mathematics performance
Low mathematics performance
Average performance
of 15-year-olds in
mathematics
Strong socio-economic
impact on student
performance
Singapore
Hong Kong-ChinaChinese Taipei
Korea
Macao-China
Japan Liechtenstein
Switzerland
Netherlands
Estonia Finland
Canada
Poland
Belgium
Germany Viet Nam
Austria Australia
IrelandSlovenia
DenmarkNew Zealand
Czech Republic France
United Kingdom
Iceland
LatviaLuxembourg Norway
Portugal ItalySpain
Russian Fed.Slovak Republic United States
LithuaniaSwedenHungary
Croatia
Israel
Greece
SerbiaTurkey
Romania
Bulgaria
U.A.E.
Kazakhstan
Thailand
Chile Malaysia
Mexico

13. AustraliaAustria
Belgium Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain Sweden
Switzerland
Turkey
UK
US
Singapore
Hong Kong-ChinaChinese Taipei
Macao-China
Liechtenstein
Viet Nam
Latvia
Russian Fed.
Lithuania
Croatia
Serbia
Romania
Bulgaria United Arab Emirates
Kazakhstan
Thailand
Malaysia
02468101214161820222426
2012
Shanghai-China
Socially equitable
distribution of learning
opportunities
Strong socio-economic
impact on student
performance

14. AustraliaAustria
Belgium Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain Sweden
Switzerland
Turkey
UK
US
Australia
Austria
Belgium
Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain
Sweden
Switzerland
Turkey
UK
US
2012
Socially equitable
distribution of learning
opportunities
Strong socio-economic
impact on student
performance

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

16. AustraliaAustria
Belgium Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain Sweden
Switzerland
Turkey
UK
US
Australia
Austria
Belgium
Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain
Sweden
Switzerland
Turkey
UK
US
Singapore
Shanghai
Singapore
2003 - 2012

17. AustraliaAustria
Belgium Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain Sweden
Switzerland
Turkey
UK
US
Australia
Austria
Belgium
Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain
Sweden
Switzerland
Turkey
UK
US
Singapore
2003 - 2012

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

19. AustraliaAustria
Belgium Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain Sweden
Switzerland
Turkey
UK
US
Australia
Austria
Belgium
Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain
Sweden
Switzerland
Turkey
UK
US
Singapore
2003 - 2012
Norway, the United States and
Switzerland improved equity
between 2003 and 2012

20. Of the 65 countries…
…45 improved in at least one subject
22

21. Mathematics, reading and science Israel, Poland, Portugal, Turkey, Brazil,
Dubai (UAE), Hong Kong-China,
Macao-China, Qatar, Singapore, Tunisia
Mathematics and reading
Chile, Germany, Mexico, Albania, Montenegro,
Serbia, Shanghai-China
Mathematics and science
Italy, Kazakhstan, Romania
Reading and science
Japan, Korea, Latvia, Thailand
Mathematics only
Greece, Bulgaria, Malaysia,
United Arab Emirates (ex. Dubai)
Reading only Estonia, Hungary, Luxembourg, Switzerland,
Colombia, Indonesia, Liechtenstein, Peru,
Russian Federation, Chinese Taipei
Science only
Ireland
Improvement in mathematics, reading or science23

22. 340
360
380
400
420
440
460
480
500
520
540
560
580
600
Shanghai-China
Singapore
HongKong-China
ChineseTaipei
VietNam
Macao-China
Korea
Japan
Liechtenstein
Poland
Switzerland
Estonia
Netherlands
Germany
Belgium
Finland
Canada
Portugal
Austria
CzechRepublic
NewZealand
Latvia
France
Slovenia
Ireland
Australia
OECDaverage
Turkey
SlovakRepublic
Spain
Hungary
Luxembourg
Italy
RussianFederation
UnitedKingdom
Denmark
Lithuania
Croatia
UnitedStates
Norway
Sweden
Iceland
Romania
Israel
Serbia
Thailand
Greece
Bulgaria
Chile
Uruguay
Malaysia
Kazakhstan
Cyprus5,6
Mexico
CostaRica
UnitedArab…
Brazil
Montenegro
Tunisia
Indonesia
Peru
Argentina
Colombia
Jordan
Qatar
Meanmathematicsscore
Mean score at the country level before adjusting for socio-economic status
Mean score at the country level after adjusting for socio economic status
Mathematics performance in a level playing field
Mean mathematics performance after accounting for socio-economic status
Fig II.3.3
24

23. 0
2
4
6
8
10
12
14
16
18
20
Shanghai-China
HongKong-China
Macao-China
VietNam
Singapore
Korea
ChineseTaipei
Japan
Liechtenstein
Switzerland
Estonia
Netherlands
Poland
Canada
Finland
Belgium
Portugal
Germany
Turkey
OECDaverage
Italy
Spain
Latvia
Ireland
Australia
Thailand
Austria
Luxembourg
CzechRepublic
Slovenia
UnitedKingdom
Lithuania
France
Norway
Iceland
NewZealand
RussianFed.
UnitedStates
Croatia
Denmark
Sweden
Hungary
SlovakRepublic
Mexico
Serbia
Greece
Israel
Tunisia
Romania
Malaysia
Indonesia
Bulgaria
Kazakhstan
Uruguay
Brazil
CostaRica
Chile
Colombia
Montenegro
U.A.E.
Argentina
Jordan
Peru
Qatar
%
Percentage of resilient students
More than 10
% resilient Between 5%-10% of resilient students Less than 5%
Fig II.2.4
25
A resilient student is situated in the bottom quarter of
the PISA index of economic, social and cultural
status (ESCS) in their own country and yet
performs in the top quarter of students among all
countries, after accounting for socio-economic status.
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
high-achievers.

24. Comparisons of performance Table I.2.3b
Peru 22 years vs Indonesia 45 yearsQatar 13 years vs Tunisia 35 yearsBrazil 42 years vs Kazakhstan 9 years
0
100
200
300
400
500
600
700
800
2003
2005
2007
2009
2011
2013
2015
2017
2019
2021
2023
2025
2027
2029
2031
2033
2035
2037
2039
2041
2043
2045
2047
MeanPerformanceinMathematics
Catching up to the OECD Average in Mathematics
Qatar
Tunisia
OECD
0
100
200
300
400
500
600
700
800
900
2006
2009
2012
2015
2018
2021
2024
2027
2030
2033
2036
2039
2042
2045
2048
2051
2054
MeanPerformanceinScience
Catching up to the OECD Average in Science
Brazil
Kazakhsta
n
0
100
200
300
400
500
600
700
2000
2003
2006
2009
2012
2015
2018
2021
2024
2027
2030
2033
2036
2039
2042
2045
2048
2051
2054
2057
MeanPerformanceinReading
Catching up to the OECD Average in Reading
Peru
Indonesia
OECD
26

25. Studentperformance
AdvantagePISA Index of socio-economic backgroundDisadvantage
700
200
493
-3 -2 -1 0 1 2 3
School performance and socio-economic background: United States
27
Student performance and students’ socio-economic background
School performance and schools’ socio-economic background
Private school
Public school in rural area
Public school in urban area
Student performance and students’ socio-economic background within schools
Schools with similiar socio-economic backgrounds

26. 200
494
-3 -2 -1 0 1 2 3
School performance and socio-economic background:
Viet Nam28
AdvantagePISA Index of socio-economic backgroundDisadvantage
Student performance and students’ socio-economic background
School performance and schools’ socio-economic background
Private school
Public school in rural area
Public school in urban area
Student performance and students’ socio-economic background within schools
Studentperformance
700

27. -2.00
-1.50
-1.00
-0.50
0.00
0.50
Peru
CostaRica
Mexico
Brazil
Indonesia
Thailand
Colombia
NewZealand
Turkey
Argentina
UnitedStates
Uruguay
Australia
Chile
VietNam
Jordan
Shanghai-China
U.A.E.
Romania
Sweden
Israel
Bulgaria
ChineseTaipei
Malaysia
Ireland
Greece
Tunisia
Poland
Canada
Japan
Macao-China
OECDaverage
Luxembourg
Qatar
RussianFed.
Iceland
Belgium
France
Switzerland
Portugal
HongKong-China
Spain
Lithuania
Denmark
Kazakhstan
Italy
CzechRepublic
Netherlands
Estonia
Hungary
Slovenia
Austria
Singapore
Latvia
SlovakRepublic
Montenegro
Korea
Germany
Serbia
UnitedKingdom
Norway
Croatia
Finland
Liechtenstein
Albania
Meanindexdifference
Difference between socio-economically disadvantaged and socio-economically advantaged schools
Educational resources are more problematic in disadvantaged
schools, also in public schools in most countries
Advantaged and private schools
reported better educational
resources
Disadvantaged and public schools
reported better educational
resources
Fig IV.3.8
29

28. 0
10
20
30
40
HongKong-China
Korea+
Liechtenstein
Macao-China+
Japan
Switzerland
Belgium-
Netherlands-
Germany
Poland+
Canada-
Finland-
NewZealand-
Australia-
Austria
OECDaverage2003-
France
CzechRepublic-
Luxembourg
Iceland-
SlovakRepublic
Ireland
Portugal+
Denmark-
Italy+
Norway-
Hungary
UnitedStates
Sweden-
Spain
Latvia
RussianFederation
Turkey
Greece
Thailand
Uruguay-
Tunisia
Brazil
Mexico
Indonesia
%
2012 2003
Percentage of top performers in mathematics
in 2003 and 2012
Fig I.2.23
30
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

29. Gender differences in reading performance
-80
-70
-60
-50
-40
-30
-20
-10
0
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
RussianFed.
Hungary
SlovakRepublic
Portugal
Italy
CzechRepublic
Argentina
OECDaverage
Austria
Kazakhstan
Switzerland
Macao-China
Uruguay
Canada
Australia
NewZealand
ChineseTaipei
Singapore
Belgium
VietNam
UnitedStates
Denmark
Tunisia
Brazil
Luxembourg
Spain
Ireland
Indonesia
Netherlands
HongKong-China
CostaRica
UnitedKingdom
Liechtenstein
Japan
Shanghai-China
Mexico
Korea
Chile
Peru
Colombia
Albania
Score-pointdifference(boys-girls)
In all countries and economies
girls perform better than boys
Fig I.4.12
31

30. 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)
32

31. -40
-20
0
20
40
60
80
100
Hungary-
Australia-
Macao-China
SlovakRepublic-
Turkey
NewZealand-
Ireland
Canada
Latvia
HongKong-China
UnitedKingdom
UnitedStates
Thailand
RussianFederation
CzechRepublic
OECDaverage2003-
Luxembourg
Portugal
Norway
Italy+
Liechtenstein
Greece
Iceland
Spain
Germany-
Brazil
Netherlands
Sweden
Austria
Belgium-
Switzerland-
Denmark
France
Mexico
Finland
Scorepointdifference(without-withimmig.)
2012 2003
Students without an immigrant
background perform better
Students with an immigrant
background perform better
Change between 2003 and 2012 in immigrant students' mathematics
performance – before accounting for students’ socio-economic status
Fig II.3.5
33

32. -0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
Japan
HongKong-China
Luxembourg
Norway
CzechRepublic
Iceland
Korea
Indonesia
Thailand
Mexico
Denmark
Liechtenstein
Italy
Austria
Macao-China
Turkey
Belgium
Canada
Portugal
Poland
Spain
OECDaverage2003
Switzerland
Brazil
UnitedStates
Greece
SlovakRepublic
Netherlands
RussianFederation
Hungary
Ireland
NewZealand
Australia
Uruguay
Sweden
Latvia
France
Finland
Germany
Tunisia
Meanindexchange
Change between 2003 and 2012 in disciplinary climate in schools
In most countries and economies, the disciplinary
climate in schools improved between 2003 and 2012
Disciplinary climate
declined
Disciplinary climate
improved
Fig IV.5.13

33. Motivation to learn mathematics
Percentage of students who reported "agree" or "strongly agree" with the following statements:
0 10 20 30 40 50 60 70
I enjoy reading about mathematics
I look forward to my mathematics
lessons
I do mathematics because I enjoy it
I am interested in the things I learn
in mathematics
%
United States Shanghai-China
Fig III.3.9
35

34. United States
Poland
Hong Kong-China
Brazil
New Zealand
Greece
Uruguay
United Kingdom
Estonia
Finland
Albania
Croatia
Latvia
Slovak Republic
Luxembourg
Germany
Lithuania
Austria
Czech Republic
Chinese Taipei
France
Thailand
Japan
Turkey Sweden
Hungary
Australia
Israel
Canada
IrelandBulgaria
Jordan
Chile
Macao-China
U.A.E.
Belgium
Netherlands
Spain
Argentina
Indonesia
Denmark
Kazakhstan
Peru
Costa Rica
Switzerland
Montenegro
Tunisia
Iceland
Slovenia
Qatar
Singapore
Portugal
Norway
Colombia
Malaysia
Mexico
Liechtenstein
Korea
Serbia
Russian Fed.
Romania
Viet Nam
Italy
Shanghai-China
R² = 0.36
300
350
400
450
500
550
600
650
-0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00 1.20
Meanmathematicsperformance
Mean index of mathematics self-efficacy
OECDaverage
Countries where students have stronger beliefs
in their abilities perform better in mathematics36 Fig III.4.5

35. Schools with more autonomy perform better than schools with
less autonomy in systems with more accountability arrangements
School data not public
School data public
464
466
468
470
472
474
476
478
Less school autonomy
More school autonomy
Score points
School autonomy for curriculum and assessment
x system's level of posting achievement data publicly
Fig IV.1.16
37

36. No mathematics
standards
Central
mathematics…455
460
465
470
475
480
485
Less school autonomy
More school autonomy
Schools with more autonomy perform better than schools with
less autonomy in systems with more accountability arrangements
Score points
School autonomy for curriculum and assessment x System's extent of implementing
a standardised policy
Fig IV.1.16

37. Attract
• Attract the best students to the teaching
profession (Examples:
Brazil, Korea, Israel, United Kingdom)
• Create incentives to encourage
experienced teachers to work in
disadvantaged schools (Examples:
Brazil, Estonia, Shanghai)
Train
• Provide quality training that combines
acquiring knowledge and skills
(Examples: Finland, Japan, Turkey)
• Prepare teachers to address specific
problems of students, assess and use
appropriate remedial methods
(Examples: Germany, Poland, Canada)
Accompany
• Provide mentoring programs for young
teachers (Examples: Germany, Singapore)
• Give young teachers the opportunity early in
their career to return to university and improve
their skills (Examples: Finland, Germany)
Retain
• Develop continuous professional
development, which is as important, if
not more than initial training
(Examples:
Brazil, Canada, Mexico, Singapore)
• Provide career advancement
opportunities (Examples:
Quebec, Portugal)
39
Summary of insights regarding teachers from countries with high
performance and equity in PISA:

38.  Provides information on the
competencies, knowledge, skills and
engagement of students, and the learning
environment at the school  comparable to
PISA scales
 Tool in support of research and the
benchmarking efforts for improvement
 Can be used by schools, networks of schools
and districts …To support local
improvement
OECD Test for Schools (based on PISA)
Uses of the assessment tool

39. Is not…
• A mandated standardised test
• Intended to influence – in of itself – everyday
teaching practices
• An alternative to national, regional PISA
participation
• Intended to align completely with the content and
curricular standards of a specific country, although
there is overlap
• A tool for “rankings” or “league tables”
OECD Test for Schools (based on PISA)
Uses of the assessment tool

40. OECD Test for Schools (based on PISA)
What does the actual assessment look like?
 Experience for students similar to that of the main PISA
tests: ~ 3.25 hours (with breaks and student
questionnaire)
 Three areas (domains) equally represented (over 90
minutes of assessment items)
 Student sample size per school (target): 75 (some
schools tested over 100 students)
 Contextual information  questionnaires for students
and school authorities
 Paper and pencil for first phase…

41. Content of school reports provided
I. Introduction: Understanding your school’s results
II. What students at Your School Know and Can Do
in Reading, Mathematics and Science
III. Student Engagement and the Learning
Environment at Your School
IV. Your School Compared with Similar Schools in
Your Country
V. Your School’s Results in an International Context
Annexes School name
School District
State
United States
How your school compares
internationally
OECD Test for Schools
Pilot Trial 2012
OECD Test for Schools (based on PISA)
Overview of school reports

42. School-specific results provided
 Performance on PISA scales
 Relative performance based on
background of students
(socio-economic status - ESCS)
 Learning environment at school
OECD Test for Schools (based on PISA)
Overview of school reports
• Teacher-student relations
• Disciplinary climate in English and
Mathematics lessons
• Student confidence and attitudes towards
mathematics and science
http://youtu.be/tnhLrGM81eI?t=1m58s

43. PerformanceonPISAscale
OECD Test for Schools (based on PISA)
Overview of results (from the pilot)
300
400
500
600
700
Schools in the
United States
Schools in the
Shanghai-China
Schools in
Mexico
PISA 2009 Results
North Star Academy
300
400
500
600
700 Pilot Results
10% above
25% above
50% above/below
25% below
10% below
10% above
25% above
50% above/below
25% below
10% below
10% above
25% above
50% above/below
25% below
10% below
Reading
300
400
500
600
700
300
400
500
600
700
300
400
500
600
700
Woodson HS
300
400
500
600
700
BASIS Scottsdale
300
400
500
600
700
Langley High School
300
400
500
600
700
Oakton High School
300
400
500
600
700
BASIS Tucson
300
400
500
600
700

44. OECD Test for Schools (based on PISA)
Overview of results (from the pilot)
What does the same mean mean?
0%20%40%60%80%100%
Brazil
Mexico
United States
OECD average
United Kingdom
Germany
Poland
Singapore
Japan
Canada
Korea
Finland
Shanghai-China
Langley High school
Oakton High School
0% 20% 40% 60% 80% 100%
Brazil
Mexico
United States
OECD average
United Kingdom
Germany
Poland
Singapore
Japan
Canada
Korea
Finland
Shanghai-China
Langley High school
Oakton High School
543 and 543
Reading
Level 1 and be`low Level 2 Level 3 Level 4 Level 5 Level 6

45. OECD Test for Schools
School Reports
Disciplinary climate and reading performancce

46. http://youtu.be/tnhLrGM81eI?t=1m36s
Disciplinary climate and reading performancce

47. Disciplinary climate and mathematics lessons

48. Quality of teacher-student relations
http://youtu.be/1MzGhxJ5HOg?t=3m17s

49. Performance and teacher-student relations

50. Motivation of students to learn science

51. Self-belief of students in science

52. Instrumental motivation and self-efficacy of students and performance at your
school

53. OECD Test for Schools
School Reports

54.  Performance needs to be considered not in absolute
terms but in terms of equity and relative
effectiveness of schools
 International benchmarking supported by the
assessment is a process – the “real work” begins
after receiving the results…
 Performance should also be considered in the context
of the quality of the learning environment at schools
 Importance of peer-to-peer learning opportunities –
– and the opportunity to share good practices to help
identify “what works”
OECD Test for Schools (based on PISA)
What now? Current cycle of testing in the USA

55.  America Achieves – key partners in the USA
 EdLeader21 – key partners in the USA
 CTB/McGraw-Hill – currently accredited service
provider
 Spain has finished pilot in four official languages
(224 schools)
 In UK: England, Wales and Norther Ireland
 International Learning Network – Australia….
OECD Test for Schools (based on PISA)
Availability in the United States and Internationally

56. OECD EMPLOYER
BRAND
Playbook
58
PISA Insights for
Schools and Local
Educators
Thank you very much
www.pisa.oecd.org
• All national and international
publications
• The complete micro-level
database
• Documents and Presentations
of PISA for Development