Schleicher

1111

Seeing US education through the prism of international

comparisons

Organisation for Economic Cooperation and Development (OECD)

Alliance for excellent education, Washington, 4 October 2007Prof. Andreas Schleicher

Head, Indicators and Analysis DivisionOECD Directorate for Education

2222 Agenda

11.. Why we need to care A world of change in the demand for skills

and the global talent pool

2.2. Where we are – and where we can be Quality, equity and efficiency in education in

the best performing countries

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

international comparisons

4444

%

1. Excluding ISCED 3C short programmes 2. Year of reference 20043. Including some ISCED 3C short programmes 3. Year of reference 2003.

Growth in baseline qualificationsA world of change

Approximated by percentage of persons with high school or equivalent qualfications in the age groups 55-64, 45-55, 45-44 und 25-34 years

13

1

1

27

6666 High school completion ratesPercentage of graduates to the population at the typical age of graduation

%

7777 College-level graduation ratesPercentage of tertiary type A graduates to the population at the typical age of graduation

%

A3.1

15

2

Decline of the relative position of the US from 1995 to 2005

Rising college-degrees have not 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%

Growing benefits in many of the countries with the steepest attainment growth .

12121212 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

2003

2010

2015

13131313Future 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 I ndia US

2003

2010

2015

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

2003

2010

2015

Future supply of college graduates

14141414 Percentage of science graduates

0

10

20

30

40

50

60

70

80

90

100

Korea J apan EU United States

15151515

Getting the fundamentals right.

What the top-performers achieve in terms of quality, equity and

efficiency in schooling outcomes

17171717Coverage of world economy 77%81%83%85%86%87%

PISA - OECD’s global assessment of what students know and can do with their

knowledge

18181818Deciding what to assess...

looking back at what students were expected to have learned

…or…

looking ahead to how well they can extrapolate from what they have

learned and apply their knowledge and skills in novel settings.

For PISA, the OECD countries chose the latter.

19191919 Average performanceof 15-year-olds in mathematics – extrapolate and apply

High mathematics performance

Low mathematics performanceGreece

Russian Federation

Liechtenstein

Korea

Hong Kong- China

Finland

Netherlands

Canada

Macao- China Switzerland

New Zealand

Belgium

J apan

Australia

I celandCzech Republic

SwedenFranceDenmark

I reland GermanyAustria

Slovak Republic

LuxembourgPoland Hungary

Norway

SpainUnited StatesLatvia

PortugalI taly

440

460

480

500

520

540

61626

20202020

400

450

500

550

600

Hong

Kong

-China

Nethe

rland

s

Belgi

um

Switz

erland

Cana

da

New Z

ealan

d

Mac

ao-C

hina

Australi

a

Germ

any

Fran

ce

Denmar

k

Swed

en

Austria

Luxe

mbour

g

Norwa

y

United

Sta

tes

Russian Fe

dera

tion

Native students First- generation students Second- generation students

OECD average = 500

Math performance of immigrant students

Native students

Second-generation students

First-generation students

Where immigrant students succeed – A comparative review of performance and engagement in PISA 2003: Figure 2.2a.

21212121Strengths and weaknesses in

mathThe real world The mathematical World

A real situation

A model of reality A mathematical model

Mathematical results

Real results

Understanding, structuring and simplifying the situation

Making the problem amenable to mathematical

treatment

Interpreting the mathematical results

Using relevant mathematical tools to solve the problemValidating

the results

22222222 How the demand for skills has changedEconomy-wide measures of routine and non-routine task input

(US)

(Levy and Murnane)

Mean t

ask

inp

ut

as

perc

enti

les

of

th

e 1

960 t

ask

dis

trib

uti

on

24242424 Average performanceof 15-year-olds in mathematics

Low average performance

Large socio-economic disparities

High average performance



High social equity


High social equity

Strong socio-economic impact

on student performance

Socially equitable distribution of

learning opportunities



Russian Federation

Liechtenstein

Korea

Hong Kong- China

Finland

Netherlands

Canada

Macao- China Switzerland

New Zealand

Belgium

J apan

Australia


SwedenFranceDenmark

I reland GermanyAustria

Slovak Republic

LuxembourgPoland Hungary

Norway

SpainUnited StatesLatvia

PortugalI taly

440

460

480

500

520

540

61626

25252525 Durchschnittliche Schülerleistungen im Bereich Mathematik






High social equity


High social equity







Russian Federation

Liechtenstein

Korea

Hong Kong- China

Finland

Netherlands

Canada

Switzerland

New Zealand

Belgium

J apan

Australia


SwedenFrance

Denmark

I relandGermanyAustria

Slovak Republic

LuxembourgPolandHungary

Norway

SpainUnited States Latvia

Portugal I taly

440

460

480

500

520

540

61626

Watch out for new data on this on December 4 !

29292929

How can we get there?

Levers for policy that emerge from OECD’s international comparisons

30303030

350

400

450

500

550

600

0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 100,000

Money matters - but other things do too

Mexico

Greece

Portugal Italy

Spain

GermanyAustria

Ireland

United StatesNorway

Korea

Czech republic

Slovak republicPoland

Hungary

Finland

NetherlandsCanada Switzerland

IcelandDenmark

FranceSweden

BelgiumAustralia

Japan

R2 = 0.28

Cumulative expenditure (US$)

Perf

orm

an

ce in

math

em

ati

cs

31313131High ambitions and universal

standardsDefining what students should be able to do, not prescribing what teachers should teach

Access to best practice and quality

professional development

32323232 Challenge and support

Weak support

Strong support

Lowchallenge

Highchallenge

Strong performance

Systemic improvement

Poor performance

Improvements idiosyncratic

Conflict

Demoralisation

Poor performance

Stagnation

33333333High ambitions



Intelligent accountability

and intervention in inverse proportion

to success

Devolved responsibility,

the school as the centre of action

34343434

YesNo

No

Yes

36.4

32.5

0.00%0

5

10

15

20

25

30

35

40

Central

standards

Local autonomy

Woessmann, 2005

PISA math performance

School autonomy and central exams

Pooled international data

36363636Public and private schools

0 20 40 60 80 100

Luxembourg

J apan

I taly

Switzerland

Finland

Denmark

Czech Republic

Sweden

Hungary

Austria

Portugal

United States

Netherlands

Slovak Republic

Korea

I reland

Spain

Canada

Mexico

New Zealand

Germany

OECD

United Kingdom

Government schools

Government dependent private

Government independent private

-15

0

-10

0

-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

39393939Strong ambitions



Accountability

Devolvedresponsibility,


Integrated educational

opportunities

From prescribed forms of teaching and assessment

towards personalised

learning

40404040 Durchschnittliche Schülerleistungen im Bereich Mathematik






Low mathematics performance

Early selection and institutional differentiation

High degree of stratification

Low degree of stratification Greece

Russian Federation

Liechtenstein

Korea

Hong Kong- China

Finland

Netherlands

Canada

Switzerland

New Zealand

Belgium

J apan

Australia


SwedenFrance

Denmark

I relandGermanyAustria

Slovak Republic

LuxembourgPolandHungary

Norway

SpainUnited States Latvia

Portugal I taly

440

460

480

500

520

540

61626

41414141High ambitions



Accountabilityand intervention in inverse proportion

to success

Personalizedlearning

Devolved responsibility,


Integrated educational opportunities

42424242Creating a knowledge-rich profession in which schools and

teachers have the authority to act, the necessary knowledge to do so wisely, and access to effective support

systems

The tradition of education systems has been “knowledge poor”

(think of the assembly line in Detroit)

The best performing education systems are “knowledge rich”

(think of Silicon Valley)

National prescription

Professional judgement

Informed professional judgement, the teacher

as a “knowledge worker”

Informed prescription

Uninformed professional judgement, teachers working in isolation

Uninformed prescription,

teachers implement curricula

43434343 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

45454545 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

46464646

Thank you !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

Schleicher

Economy & Finance

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