ICT Role in 21st Century Education & its Challenges.pptx
Strong performers and successful reformers - lessons from PISA for Turkey
1. Strong performers and
successful reformers
Lessons from PISA for Turkey
OECD EMPLOYER
BRAND
Playbook
Andreas Schleicher
Istanbul, 15 February 2014
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. Changes in the demand for skills
3
Trends in different tasks in occupations (United States)
Mean task input in percentiles of 1960 task distribution
70
65
Routine manual
60
Nonroutine manual
Routine cognitive
55
Nonroutine analytic
Nonroutine interpersonal
50
45
40
35
1960
1970
1980
1990
2000
2006
2009
Source: Autor, David H. and Brendan M. Price. 2013. "The Changing Task Composition of the US Labor Market: An Update of Autor, Levy, and Murnane (
2003)." MIT Mimeograph, June.
5. High mathematics performance
Mean score … Shanghai-China performs above this line (613)
580
Singapore
570
560
Chinese Taipei
Korea
550
540
Macao-China
Japan Liechtenstein
Switzerland
530
520
510
500
490
480
470
Hong Kong-China
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
460
450
Greece
Serbia Turkey
Romania
440
430
420
410
Chile
… 12 countries perform below this line
Bulgaria
U.A.E.
Kazakhstan
Thailand
Malaysia
Mexico
Low mathematics performance
Average performance
of 15-year-olds in
Mathematics
Fig I.2.13
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
11. 11
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
12. 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
12
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
13. 13
The dream of social mobility
In some countries it is close to a reality
14. Percentage of resilient students
14
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
15. 15
It is not just about poor kids
in poor neighbourhoods…
…but about many kids in many neighbourhoods
16. B
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
16
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
17. High impact on outcomes
22
22
Quick wins
Lessons from high performers
Must haves
Catching up with the top-performers
Low feasibility
High feasibility
Money pits
Low hanging fruits
Low impact on outcomes
18. High impact on outcomes
23
23
Quick wins
Must haves
Lessons from high performers
Commitment to universal achievement
Capacity
at point of delivery
Resources
where they yield most
Gateways, instructional
systems
Coherence
A learning system
Low feasibility
High feasibility
Incentive structures and
accountability
Money pits
Low hanging fruits
Low impact on outcomes
19. High impact on outcomes
24
24
Lessons from high performers
Quick
Must to education and the belief that wins
A commitmenthaves
Commitment to universal therefore
competencies can be learned andachievementall
children can achieve
Capacity
personalization as
at Universal educational standards andResources
point of delivery
the approach to heterogeneitywhere they yield most
in the student body…
… as opposed to a belief that students have different
Gateways, instructional
destinations to be met with different expectations, and
systems
selection/stratification as the approach to
Coherence
heterogeneity
A learning system
Clear articulation who is responsible for ensuring
Low feasibility
High feasibility
student success and to whom
Incentive structures and
accountability
Money pits
Low hanging fruits
Low impact on outcomes
20. 25
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
21. 26
Perceived self-responsibility for failure
in mathematics
Fig III.3.6
Percentage of students who reported "agree" or "strongly agree" with the following statements:
Turkey
Shanghai-China
OECD average
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
100
22. High impact on outcomes
30
30
Quick wins
Must haves
Lessons from high performers
Commitment to universal achievement
Clear ambitious goals that are shared across the
Capacity
system and aligned with high stakes gateways and
Resources
at point of delivery
where
instructional systemsthey yield most
Coherence
Low feasibility
Well established delivery chain through which
Gateways, instructional
curricular goals translate into instructional systems,
systems
instructional practices and student learning (intended,
implemented andlearning system
A achieved)
High level of metacognitive content of instruction …
High feasibility
Incentive structures and
accountability
Money pits
Low hanging fruits
Low impact on outcomes
23. 31
High impact on outcomes
31
Capacity at
Lessons from high performers
the point of delivery
Quick wins
Must haves
Attracting, developing and retaining high quality
Commitment a universal achievement
teachers and school leaders andto work organisation in
which they can use their potential
Capacity
Instructional leadership and human resource
Resources
at point of delivery
management in schools
where they yield most
Keeping teaching an attractive profession
Gateways, instructional
System-wide career development …
systems
Coherence
A learning system
Low feasibility
High feasibility
Incentive structures and
accountability
Money pits
Low hanging fruits
Low impact on outcomes
25. High impact on outcomes
33
33
Lessons from high performers
Quick wins
Must haves
Incentives, accountability, knowledge management
Commitment to universal achievement
Aligned incentive structures
For students
Capacity
Resources
How gateways
at point of delivery affect the strength, direction, clarity and nature of the
incentives operating on students at each stage of their education
where they yield most
Degree to which students have incentives to take tough courses and study hard
Gateways,
Opportunity costs for staying in school and performing well instructional
For teachers
Coherenceinnovations in pedagogy and/or organisation
Make
A learning system
Low feasibility
Improve their own performance
and the performance of their colleagues
Pursue professional development opportunities
that lead to stronger pedagogical practices
systems
High feasibility
Incentive structures and
A balance between vertical and lateral accountability
accountability
Effective instruments to manage and share knowledge and spread
innovation – communication within the system and with
stakeholders around it
Money pits
Low hanging
A capable centre with authority and legitimacy to act fruits
Low impact on outcomes
26. 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
27. 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
28. 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
29. 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
30. 38
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:
Singapore
OECD average
Implementation of a standardised policy for
mathematics
Regular consultation with one or more experts over a
period of at least six months with the aim of improving…
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…
Written specification of student-performance standards
Written specification of the school's curriculum and
educational goals
0
20
40
%
60
80
100
31. 39
The issue is not how many charter schools
a country has…
…but how countries enable every school
to assume charter type autonomy
32. High impact on outcomes
40
40
Quick wins
Lessons from high performers
Must haves
Commitment to universal achievement
Investing resources where they can
make most
of
Capacity a difference
Resources
Alignment of resources with key challenges (e.g.
at point of delivery
where they teachers
attracting the most talentedyield mostto the most
challenging classrooms)
Gateways, instructional
Effective spending choices that prioritise high quality
systems
teachers over smaller classes
Coherence
A learning system
Low feasibility
High feasibility
Incentive structures and
accountability
Money pits
Low hanging fruits
Low impact on outcomes
34. 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
35. 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
Shanghai-China
600
550
500
450
Mexico
Costa Rica
400
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
SHA
1
Less
equity
0.5
Equity in resource allocation
(index points)
0
-0.5
Greater
equity
36. High impact on outcomes
44
44
Quick wins
Must haves
Lessons from high performers
Commitment to universal achievement
Capacity
at point of delivery
Coherence of policies and practices
Alignment of policies
across all aspects of the system
Coherence
Coherence of policies
over sustained periods of time
LowConsistency of implementation
feasibility
Fidelity of implementation
(without excessive control)
Money pits
CAN
Resources
where they yield most
Gateways, instructional
systems
A learning system
High feasibility
Incentive structures and
accountability
Low hanging fruits
Low impact on outcomes
37. High impact on outcomes
45
45
Quick wins
Must haves
Lessons from high performers
Commitment to universal achievement
Capacity
at point of delivery
Resources
where they yield most
Gateways, instructional
systems
Coherence
A learning system
Low feasibility
High feasibility
Incentive structures and
accountability
Money pits
Low hanging fruits
Low impact on outcomes
38. What it all means
46
46
Lessons from high performers
The old bureaucratic system
The modern enabling system
Student inclusion
Some students learn at high levels
All students need to learn at high levels
Curriculum, instruction and assessment
Routine cognitive skills, rote learning
Learning to learn, complex ways of thinking, ways
of working
Teacher quality
Few years more than secondary
High-level professional knowledge workers
Work organisation
‘Tayloristic’, hierarchical
Flat, collegial
Accountability
Primarily to authorities
Primarily to peers and stakeholders
39. 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
40. Do you have an idea on how to use this data to
improve education in your country?
Would you like to work with us
to develop that idea?
Apply to the
Thomas J. Alexander
fellowship programme!
http://www.oecd.org/edu/thomasjalexanderfellowship.htm
Notas do Editor
Another way of looking at the evolution of demand for skills is provided by Autor, Levy and Murnane (2003), whoclassify jobs into routine and non-routine tasks. They argue that the share of non-routine analytic and interactive jobtasks (tasks that involve expert thinking and complex communication skills) performed by American workers hasincreased steadily since 1960. The share of routine cognitive and manual tasks began to decline in theearly 1970s and 1980s, respectively – coinciding with the introduction of computers and computerised productionprocesses. These are tasks that are more readily automated and put into formal algorithms. The share of non-routinemanual tasks also declined, but stabilised in the 1990s, possibly due to the fact that they cannot be easily computerisedor outsourced.
(Fig. II.4.5)
(Fig. II.4.5)
I want to conclude with what we have learned about successful reform trajectories In the past when you only needed a small slice of well-educated people it was efficient for governments to invest a large sum in a small elite to lead the country. But the social and economic cost of low educational performance has risen substantially and all young people now need to leave school with strong foundation skills.When you could still assume that what you learn in school will last for a lifetime, teaching content and routine cognitive skills was at the centre of education. Today, where you can access content on Google, where routine cognitive skills are being digitised or outsourced, and where jobs are changing rapidly, the focus is on enabling people to become lifelong learners, to manage complex ways of thinking and complex ways of working that computers cannot take over easily.In the past, teachers had sometimes only a few years more education than the students they taught. When teacher quality is so low, governments tend to tell their teachers exactly what to do and exactly how they want it done and they tend to use Tayloristic methods of administrative control and accountability to get the results they want. Today the challenge is to make teaching a profession of high-level knowledge workers. But such people will not work in schools organised as Tayloristic workplaces using administrative forms of accountability and bureaucratic command and control systems to direct their work. To attract the people they need, successful education systems have transformed the form of work organisation in their schools to a professional form of work organisation in which professional norms of control complement bureaucratic and administrative forms of control.