This session

55
1 1 University of Minnesota March, 22 2009 Bringing Lessons from the World’s Top Performers to Minnesota This session 1. There is nowhere to hide Why the yardstick for educational success is no longer improvement by national standards but the best performing systems internationally 2. Benchmarking education internationally Where we are – and where we can be Where the US and other countries stand in terms of quality and equity of schooling outcomes What the best performing countries show can be achieved 3. How we can get there Some policy levers that emerge from

description

This session. 1 . There is nowhere to hide Why the yardstick for educational success is no longer improvement by national standards but the best performing systems internationally 2. Benchmarking education internationally Where we are – and where we can be - PowerPoint PPT Presentation

Transcript of This session

Page 1: This session

11U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

taThis session

1. There is nowhere to hide Why the yardstick for educational success is

no longer improvement by national standards but the best performing systems internationally

2. Benchmarking education internationally Where we are – and where we can be

– Where the US and other countries stand in terms of quality and equity of schooling outcomes

– What the best performing countries show can be achieved

3. How we can get there Some policy levers that emerge from

international comparisons

Page 2: This session

22U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta

There is nowhere to hideThe yardstick for success is no longer improvement by national

standards but the best performing education systems

Page 3: This session

AustraliaAustriaCzech RepublicDenmarkFinlandGermanyGreeceHungaryIcelandIrelandItalyJapanNetherlandsNew ZealandNorwayPolandPortugalSlovak RepublicSpainSwedenUnited KingdomUnited States

Expe

nditu

re p

er st

uden

t at t

ertia

ry le

vel (

USD

)

Tertiary-type A graduation rate

A world of change – college education

Graduate supply

Cost

per

st

uden

t

Page 4: This session

Expe

nditu

re p

er st

uden

t at t

ertia

ry le

vel (

USD

)

Tertiary-type A graduation rate

A world of change – college education

United States

Japan

Sweden

Graduate supply

Cost

per

st

uden

t

Germany

Page 5: This session

Expe

nditu

re p

er st

uden

t at t

ertia

ry le

vel (

USD

)

Tertiary-type A graduation rate

A world of change – college education

Australia

United States (2000)

United States (1995)

Page 6: This session

Expe

nditu

re p

er st

uden

t at t

ertia

ry le

vel (

USD

)

Tertiary-type A graduation rate

A world of change – college education

Page 7: This session

Expe

nditu

re p

er st

uden

t at t

ertia

ry le

vel (

USD

)

Tertiary-type A graduation rate

A world of change – college education

Page 8: This session

Expe

nditu

re p

er st

uden

t at t

ertia

ry le

vel (

USD

)

Tertiary-type A graduation rate

A world of change – college education

Page 9: This session

Expe

nditu

re p

er st

uden

t at t

ertia

ry le

vel (

USD

)

Tertiary-type A graduation rate

A world of change – college education

Page 10: This session

Expe

nditu

re p

er st

uden

t at t

ertia

ry le

vel (

USD

)

Tertiary-type A graduation rate

A world of change – college education

United States

Australia

Ireland

Sweden

Page 11: This session

Expe

nditu

re p

er st

uden

t at t

ertia

ry le

vel (

USD

)

Tertiary-type A graduation rate

A world of change – college education

United States

Page 12: This session

Expe

nditu

re p

er st

uden

t at t

ertia

ry le

vel (

USD

)

Tertiary-type A graduation rate

A world of change – college education

United States

Page 13: This session

Expe

nditu

re p

er st

uden

t at t

ertia

ry le

vel (

USD

)

Tertiary-type A graduation rate

A world of change – college education

United States

Page 14: This session

Expe

nditu

re p

er st

uden

t at t

ertia

ry le

vel (

USD

)

Tertiary-type A graduation rate

A world of change – college education

United States

Page 15: This session

Expe

nditu

re p

er st

uden

t at t

ertia

ry le

vel (

USD

)

Tertiary-type A graduation rate

A world of change – college education

United States

Page 16: This session

Expe

nditu

re p

er st

uden

t at t

ertia

ry le

vel (

USD

)

Tertiary-type A graduation rate

A world of change – college education

Page 17: This session

Expe

nditu

re p

er st

uden

t at t

ertia

ry le

vel (

USD

)

Tertiary-type A graduation rate

A world of change – college education

Australia

United States

Rising higher education qualifications seem generally not to have led to an “inflation” of the labour-market value of qualifications.

In all but three of the 20 countries with available data, the earnings benefit increased between 1997 and 2003, in Germany, Italy and Hungary by between 20% and 40%

Page 18: This session

1919U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta Moving targetsFuture supply of high school graduates

0

2,000,000

4,000,000

6,000,000

8,000,000

10,000,000

12,000,000

14,000,000

China EU India US

200320102015

Page 19: This session

2020U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

3,500,000

4,000,000

4,500,000

5,000,000

China EU India US

200320102015

Future supply of high school graduates

0

2 , 0 0 0 , 0 0 0

4 , 0 0 0 , 0 0 0

6 , 0 0 0 , 0 0 0

8 , 0 0 0 , 0 0 0

10 , 0 0 0 , 0 0 0

12 , 0 0 0 , 0 0 0

14 , 0 0 0 , 0 0 0

China EU India US

200320102015

Future supply of college graduates

Page 20: This session

2121U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

taHow the demand for skills has changed

Economy-wide measures of routine and non-routine task input (US)

1960 1970 1980 1990 200240

45

50

55

60

65 Routine manual

Nonroutine manual

Routine cognitive

Nonroutine analytic

Nonroutine inter-active

(Levy and Murnane)

Mea

n ta

sk in

put a

s per

cent

iles o

f th

e 19

60 ta

sk d

istrib

utio

n

The dilemma of schools:The skills that are easiest to teach and test are also the ones that are easiest to digitise, automate and outsource

Page 21: This session

2222U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta

Coverage of world economy 77%81%83%85%86%87%

OECD’s PISA assessment of the knowledge and skills of 15-year-olds

Page 22: This session

2323U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

taPISA defines science performancein terms of a student’s:

Scientific knowledge and use/extrapolation of that knowledge to…

… identify scientific issues, … explain scientific phenomena, and … draw evidence-based conclusions about

science-related issues

Understanding of the characteristic features of science as a form of human knowledge and enquiry

Awareness of how science and technology shape our material, intellectual and cultural environments

Willingness to engage with science-related issues

For exampleWhen reading about a health issue, can students separate scientific from non-scientific aspects of the text, apply knowledge and justify personal decisions ?

Page 23: This session

2424U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

taPISA defines science performancein terms of a student’s:

Scientific knowledge and use/extrapolation of that knowledge to…

… identify scientific issues, … explain scientific phenomena, and … draw evidence-based conclusions about

science-related issues

Understanding of the characteristic features of science as a form of human knowledge and enquiry

Awareness of how science and technology shape our material, intellectual and cultural environments

Willingness to engage with science-related issues

For exampleCan students distinguish between evidence-based explanations and personal opinions ?

Page 24: This session

2525U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

taPISA defines science performancein terms of a student’s:

Scientific knowledge and use/extrapolation of that knowledge to…

… identify scientific issues, … explain scientific phenomena, and … draw evidence-based conclusions about

science-related issues

Understanding of the characteristic features of science as a form of human knowledge and enquiry

Awareness of how science and technology shape our material, intellectual and cultural environments

Willingness to engage with science-related issues

For exampleCan individuals recognise and explain the role of technologies as they influence a nation’s economy ? Or are they aware of environmental changes and the effects of those changes on economic/social stability ?

Page 25: This session

2626U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

taPISA defines science performancein terms of a student’s:

Scientific knowledge and use/extrapolation of that knowledge to…

… identify scientific issues, … explain scientific phenomena, and … draw evidence-based conclusions about

science-related issues

Understanding of the characteristic features of science as a form of human knowledge and enquiry

Awareness of how science and technology shape our material, intellectual and cultural environments

Willingness to engage with science-related issues

Interest in science, support for scientific enquiry, responsibility for the environmentThis addresses the value students place on science, both in terms of topics and in terms of the scientific approach to understanding the world and solving problems

Page 26: This session

2727U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta Context- Personal

- Social/public- Global

Competencies- Identify scientific issues- Explain phenomena scientifically- Use scientific evidence

Knowledge- Knowledge of science- Knowledge about science

Attitudes-Interest in science-Support for scientific enquiry-Responsibility

IdentifyingRecognising issues that can be investigated scientificallyIdentifying keywords in a scientific investigationRecognising the key features of a scientific investigation

ExplainingApplying knowledge of science in a situationDescribing or interpreting phenomena scientifically or predicting change

Using evidenceInterpreting scientific evidence and drawing conclusionsIdentifying the assumptions, evidence and reasoning behind conclusions

Knowledge of sciencePhysical systems (structure of matter, properties of matter, chemical changes of matter, motions and forces, energy and its transformations, energy and matter)Living systems (cells, humans, populations, ecosystems, biosphere)Earth and space (structures of the earth system, energy in the earth system, change in the earth system, earth’s history, space)Technology systems (Concepts and principles, science and technology)Knowledge about scienceScientific enquiry (purpose, experiments, data, measurement, characteristics of results)Scientific explanations (types, rules, outcomes)

Interest scienceIndicate curiosity in science and science-related issues and endeavoursDemonstrate willingness to acquire additional scientific knowledge and skills, using variety of resources and methodsDemonstrate willingness to seek information and have an interest in science, including consideration of science-related careers Support for scienceAcknowledge the importance of considering different scientific perspectives and argumentsSupport the use of factual information and rational explanationLogical and careful processes in drawing conclusions

Page 27: This session

2929U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

taAverage performanceof 15-year-olds in science – extrapolate and apply

High science performance

Low science performance… 18 countries perform below this line

I srael

I talyPortugal Greece

Russian FederationLuxembourgSlovak Republic,Spain,

Iceland LatviaCroatia

SwedenDenmarkFrancePolandHungary

AustriaBelgiumIrelandCzech Republic SwitzerlandMacao- China

GermanyUnited Kingdom

Korea

J apanAustralia

SloveniaNetherlandsLiechtenstein

New ZealandChinese Taipei

Hong Kong- China

Finland

CanadaEstonia

United States LithuaniaNorway

445

465

485

505

525

545

565

616

Page 28: This session

3030U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta Context- Personal

- Social/public- Global

Competencies- Identify scientific issues- Explain phenomena scientifically- Use scientific evidence

Knowledge- Knowledge of science- Knowledge about science

Attitudes-Interest in science-Support for scientific enquiry-Responsibility

IdentifyingRecognising issues that can be investigated scientificallyIdentifying keywords in a scientific investigationRecognising the key features of a scientific investigation

ExplainingApplying knowledge of science in a situationDescribing or interpreting phenomena scientifically or predicting change

Using evidenceInterpreting scientific evidence and drawing conclusionsIdentifying the assumptions, evidence and reasoning behind conclusions

OECD Level 6

OECD Level 2 Students can demonstrate

ability to understand and articulate the complex modelling inherent in the design of an investigation.

Students can determine ifscientific measurement can be applied to a given variable in an investigation. Students can appreciate the relationship between a simple model and the phenomenon it is modelling.

Students can draw ona range of abstract scientific knowledge and concepts andthe relationships between these in developing explanations ofprocesses

Students can recall anappropriate, tangible, scientific fact applicable in a simple and straightforward context and can use it to explain or predict an outcome.

Students demonstrateability to compare and differentiate among competing explanations byexamining supporting evidence. They can formulate arguments by synthesising evidence from multiplesources.

Students can point to an obvious feature in a simple table in support of a given statement. They are able to recognise if a set of given characteristics apply to the function of everydayartifacts.

Page 29: This session

3131U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta

New

Zea

land

Finl

and

Unite

d Ki

ngdo

m

Aust

ralia

Japa

n

Cana

da

OECD

ave

rage

Portu

gal

Italy

Turk

ey

Mex

ico

Unite

d St

ates

Kore

a

60

40

20

0

20

40

60

80

100

Level 6 Level 5 Level 4 Level 3 Level 2 Below Level 1%

530 563 515 527 531 534 500 474 475 424 410 489 522

Large proportion of top performers

Top and bottom performers in science

Large prop. of poor perf.

These students often confuse key features of a scientific investigation, apply incorrect information, mix personal beliefs with facts in support of a position…

These students can consistently identify, explain and apply scientific knowledge, link different information sources and explanations and use evidence from these to justify decisions, demonstrate advanced scientific thinking in unfamiliar situations…

Page 30: This session

3232U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

taIncreased likelihood of postsec. particip. at age 19 associated with reading proficiency at age

15 (Canada)after accounting for school engagement, gender, mother

tongue, place of residence, parental, education and family income (reference group Level 1)

02468

101214161820

Level 2 Level 3 Level 4 Level 5

Page 31: This session

3333U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta

France=495

- 35 - 25 - 15 - 5 5 15 25 35

Overall science score

I dentifying scientific issues

Explaining phenomena scientifically

Using scientific evidence

Knowledge about science

Earth and space

Living systems

Physical systems

Strengths and weaknesses of countries in science relative to their overall performance

France

OECD (2007), PISA 2006 – Science Competencies for Tomorrow’s World, Figure 2.13

Science competencies

Science knowledge

Page 32: This session

3434U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta

France=495 Czech Republic=512

- 35 - 25 - 15 - 5 5 15 25 35

Overall science score

I dentifying scientific issues

Explaining phenomena scientifically

Using scientific evidence

Knowledge about science

Earth and space

Living systems

Physical systems

Strengths and weaknesses of countries in science relative to their overall performance

Czech Republic

OECD (2007), PISA 2006 – Science Competencies for Tomorrow’s World, Figure 2.13

Scientific competencies

Scientific knowledge

20

Page 33: This session

3535U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta

United States=489

- 35 - 25 - 15 - 5 5 15 25 35

Overall science score

I dentifying scientific issues

Explaining phenomena scientifically

Using scientific evidence

Knowledge about science

Earth and space

Living systems

Physical systems

Strengths and weaknesses of countries in science relative to their overall performance

United States

OECD (2007), PISA 2006 – Science Competencies for Tomorrow’s World, Figure 2.13

Science competencies

Science knowledge

Page 34: This session

3636U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

taAverage performanceof 15-year-olds in science – extrapolate and apply

Low average performanceLarge socio-economic disparities

High average performanceLarge socio-economic disparities

Low average performanceHigh social equity

High average performanceHigh social equity

Strong socio-economic impact on

student performance

Socially equitable distribution of

learning opportunities

High science performance

Low science performance

I srael

I talyPortugal Greece

Russian FederationLuxembourgSlovak Republic,Spain,

Iceland LatviaCroatia

SwedenDenmarkFrancePolandHungary

AustriaBelgiumIrelandCzech Republic SwitzerlandMacao- China

GermanyUnited Kingdom

Korea

J apanAustralia

SloveniaNetherlandsLiechtenstein

New ZealandChinese Taipei

Hong Kong- China

Finland

CanadaEstonia

United States LithuaniaNorway

445

465

485

505

525

545

565

616

Page 35: This session

3737U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta Durchschnittliche Schülerleistungen im Bereich Mathematik

Low average performanceLarge socio-economic disparities

High average performanceLarge socio-economic disparities

Low average performanceHigh social equity

High average performanceHigh social equity

Strong socio-economic impact on

student performance

Socially equitable distribution of

learning opportunities

High science performance

Low science performance

I srael

GreecePortugal I talyRussian Federation

LuxembourgSlovak Republic SpainIcelandLatviaCroatia

Sweden

DenmarkFrancePoland

HungaryAustriaBelgium Ireland

Czech Republic Switzerland Macao- ChinaGermany United Kingdom

Korea

J apanAustralia

SloveniaNetherlandsLiechtenstein

New ZealandChinese Taipei

Hong Kong- China

Finland

CanadaEstonai

United States Lithuania Norway

440

460

480

500

520

540

560

2122215

Page 36: This session

4242P

ISA

OE

CD

Pro

gram

me

for

Inte

rnat

iona

l Stu

dent

Ass

essm

ent

Brie

fing

of C

ounc

il14

Nov

embe

r 200

7

How to get thereSome policy levers that emerge from

international comparisons

Page 37: This session

4343U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta Some myths US coverage of the sampled population

is more comprehensive than in other countries

US covered 96% of 15-year-olds enrolled (OECD 97%) US covered 86% of all 15-year-olds (OECD 89%) No impact on mean performance

No relationship between size of countries and average performance

No relationship between proportion of immigrants and average performance

Few difference in students’ reported test motivation

Limited impact of national item preferences .

Page 38: This session

4545U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta

High ambitions and universal

standardsRigor, focus and

coherence

Great systems attract great teachers and

provide access to best practice and quality

professional development

Page 39: This session

4646U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta Challenge and support

Weak support

Strong support

Lowchallenge

Highchallenge

Strong performanceSystemic improvement

Poor performanceImprovements idiosyncratic

ConflictDemoralisation

Poor performanceStagnation

Page 40: This session

4747U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta

High ambitions

Access to best practice and quality professional development

Accountability and intervention in

inverse proportion to success

Devolved responsibility,

the school as the centre of action

Page 41: This session

4848U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta

NoYes

0

10

20

30

40

50

60

70

No

Yes0

41

46

63

Standards based external

examinations School autonomyin selecting teachers for hire

PISA score in science

School autonomy, standards-based examinations and science performance

School autonomy in selecting teachers for hire

Page 42: This session

4949U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

taLocal responsibility and national

prescription

National prescription

Schools leading reform

Schools todayThe industrial

model, detailed prescription of

what schools do

Schools tomorrow?

Building capacity

Finland todayEvery school an effective school

Towards system-wide sustainable reform

Page 43: This session

5050U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

taPublic and private schools

0 20 40 60 80 100

LuxembourgJ apanI taly

SwitzerlandFinland

DenmarkCzech Republic

SwedenHungaryAustria

PortugalUnited States

NetherlandsSlovak Republic

KoreaI reland

SpainCanadaMexico

New ZealandGermany

OECDUnited Kingdom

Government schoolsGovernment dependent privateGovernment independent private

- 150 - 100 - 50 0 50 100

Observed perf ormance diff erence

Diff erence af ter accounting f or socio-economic background of students and schools

Private schools perform better

Public schools perform better

%Score point difference

Page 44: This session

5151U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

taPooled international dataset, effects of selected

school/system factors on science performance after accounting for all other factors in the model

OECD (2007), PISA 2006 – Science Competencies from Tomorrow’s World, Table 6.1a

Gross Net30

20

10

0

10

20

30

40

50

60

70

80

90

100

Approx. one school year

Scor

e po

int d

iffer

ence

in s

cienc

e

Schools practicing ability grouping (gross and net)

Academically selective schools (gross and net)

but no system-wide effect

School results posted publicly (gross and net)

One additional hour of science learning at

school (gross and net)

One additional hour of out-of-school lessons

(gross and net)

One additional hour of self-study or homework

(gross and net)

School activities to promote science

learning(gross and net)

Schools with greater autonomy (resources)

(gross and net)

Each additional 10% of public funding(gross only)

Schools with more competing schools

(gross only)

School principal’s perception that lack of

qualified teachers hinders instruction

(gross only)

School principal’s positive evaluation of quality of educational

materials(gross only)

Measured effectEffect after accounting for the socio-economic

background of students, schools and countries

Page 45: This session

5252U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta

Strong ambitions

Access to best practice and quality professional development

Accountability

Devolvedresponsibility,

the school as the centre of action

Integrated educational

opportunities From prescribed

forms of teaching and assessment towards personalised learning

Page 46: This session

5353U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta Durchschnittliche Schülerleistungen im Bereich Mathematik

Low average performanceLarge socio-economic disparities

High average performanceLarge socio-economic disparities

Low average performanceHigh social equity

High average performanceHigh social equity

Strong socio-economic impact on

student performance

Socially equitable distribution of

learning opportunities

High science performance

Low science performanceTurkey

AustraliaJ apan

Finland

CanadaNew Zealand

KoreaCzech Republic United Kingdom

AustriaGermany

Netherlands

SwitzerlandIrelandBelgium

PolandSwedenHungary

IcelandFrance Denmark

United States SpainLuxembourg NorwaySlovak Republic

I talyGreecePortugal

420

440

460

480

500

520

540

560

580

21222

Early selection and institutional differentiation

High degree of stratificationLow degree of stratification

6

Page 47: This session

5454U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

taMoney matters - but other things do too

0 10000 20000 30000 40000 50000 60000 70000 80000 90000 100000400

425

450

475

500

525

550

575

495

410

488

f(x) = 0.000612701270434402 x + 462.612736410929R² = 0.19035445894851

Scienceperformance

Cumulative expenditure (US$ converted using PPPs)

Page 48: This session

5555U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta

Portu

gal

Spain

Switz

erlan

d

Turk

ey

Belg

ium

Kore

a

Luxe

mbo

urg

Germ

any

Gree

ce

Japa

n

Aust

ralia

Unite

d Ki

ngdo

m

New

Zeala

nd

Fran

ce

Neth

erlan

ds

Denm

ark

Italy

Aust

ria

Czec

h Re

publ

ic

Hung

ary

Norw

ay

Icela

nd

Irelan

d

Mexic

o

Finlan

d

Swed

en

Unite

d St

ates

Polan

d

Slov

ak R

epub

lic

-10

-5

0

5

10

15

Salary as % of GDP/capita Instruction time 1/teaching time 1/class sizePo

rtuga

l

Spain

Switz

erlan

d

Turk

ey

Belg

ium

Kore

a

Luxe

mbo

urg

Germ

any

Gree

ce

Japa

n

Aust

ralia

Unite

d Ki

ngdo

m

New

Zeala

nd

Fran

ce

Neth

erlan

ds

Denm

ark

Italy

Aust

ria

Czec

h Re

publ

ic

Hung

ary

Norw

ay

Icela

nd

Irelan

d

Mexic

o

Finlan

d

Swed

en

Unite

d St

ates

Polan

d

Slov

ak R

epub

lic

-10

-5

0

5

10

15

Difference with OECD average

Spending choices on secondary schoolsContribution of various factors to upper secondary teacher compensation costs

per student as a percentage of GDP per capita (2004)

Percentage points

Page 49: This session

5656U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta Paradigm shifts

Prescription Informed profession

Uniformity Embracing diversity

Demarcation Collaboration

Provision Outcomes

Bureaucratic – look up Devolved – look outwards

Talk equity Deliver equity

Hit & miss Universal high standards

Received wisdom Data and best practice

The old bureaucratic education system The modern enabling education system

Page 50: This session

5757U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta

Towards next generation of global benchmarks

Challenges to the instrumentsChallenges to the approach

Page 51: This session

5858U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta

Low policy value

High policy value

Low feasibility High feasibility

Money pits

Must haves

Low-hanging fruits

Quick wins

Examine individual, institutional and systemic

factors associated with high performance

Establish the relative standing of countries in terms of quality and equity in basic

school subjects

Extending the range of competencies through which quality is assessed (including ICT)

Measuring growth in learning

Bridging gap between formative and summative

assessment .

Monitor educational progress

Page 52: This session

5959U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta Why care? Progress

Concerns about skill barriers to economic growth, productivity growth and rates of technological innovation– One additional year of education equals to between

3 and 6% of GDP– Rising tertiary level qualifications seem generally not

to have led to an “inflation” of the labour-market value of qualifications (in all but three of the 20 countries with available data, the earnings benefit increased between 1997 and 2003, in Germany, Italy and Hungary by between 20% and 40%)

Fairness Concerns about the role of skills in creating

social inequity in economic outcomes– Both average and distribution of skill matter

to long-term growth (high percentages of low skill impede growth)

Value for money Concerns about the demand for, and efficiency

and effectiveness of, investments in public goods

Page 53: This session

6060U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta

0

10

20

30

40

1989

1994

1999

2004

2014

2019

2024

2029

2034

2039

2044

2049

2054

2059

2064

The cost of inactionImproved GDP from achieving the goal of being first in the world by 2000

Note: *K-12 education expenitures are assumed to be constant at the level attained in 2005. These data show that economic benefits from a 1989 reform that raised the U.S. to the highest levels of test performance would cover the cost of K-12 education by 2015

Source:Eric Hanushek

Percent addition to GDP

10-year reform20-year reform30-year reformTotal U.S. K-12 spending

Page 54: This session

6161U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta

Page 55: This session

6262U

nive

rsity

of M

inne

sota

Mar

ch, 2

2 20

09B

ringi

ng L

esso

ns fr

om th

e W

orld

’s T

op P

erfo

rmer

s to

Min

neso

ta

Thank you !

www.oecd.org; www.pisa.oecd.org– All national and international publications– The complete micro-level database

email: [email protected]

[email protected]

…and remember:Without data, you are just another person with an opinion