The characteristics of high-performing
education systems: Lessons from
international comparisons
Barry McGaw
Melbourne Graduate School of Education, University of Melbourne
Revolutions, Revelations & Reality
PDN School Leaders’ Conference 2009
Gold Coast, 7 August 2009
There is a rising demand for high-level
skills
Changed demand for skills in the US
65
60
The dilemma for schools:
The skills that are easiest to teach and
test are also the ones that are easiest
to digitise, automate and outsource.
55
50
40
1960
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45
1970
1980
Routine manual
Nonroutine manual
Nonroutine analytic
Nonroutine interactive
1990
2002
Routine cognitive
Autor, D., Levy, F. and Murnane, R. J., (2003) The skill content of recent technical change, Quarterly Journal of Economics 118, M.I.T. Press, Cambridge,
pp.1279-1334.
Levy, F. and Murnane, R.J. (2006), “How Computerized Work and Globalization Shape Human Skill Demands”, working paper, available at:
http://web.mit.edu/flevy/www/computers_offshoring_and_skills.pdf.
3
The storyline so far…
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There is a growing labour market demand for higher level skills.
4
How good is Australian school
education?
Using international comparisons
Making international comparisons of
achievement requires decisions about...
whom to assess.
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what to assess,
7
Deciding what to assess...
looking back at what they were expected to
have learned
OECD/PISA chose the latter.
IEA studies have chosen the former.
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OR
looking ahead to what they can do with what
they have learned.
NAEP intention was the latter (as for PISA);
but it became more curriculum-oriented (as for IEA)
8
PISA defines science performance
in 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 sciencerelated issues
Awareness of how science and technology shape
our material, intellectual and cultural environments
Willingness to engage with science-related issues
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Understanding of the characteristic features of
science as a form of human knowledge and enquiry
For example
When reading
about a health
issue, can
students
separate
scientific from
non-scientific
aspects of the
text, apply
knowledge and
justify personal
decisions?
9
PISA defines science performance
in 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 sciencerelated issues
Awareness of how science and technology shape
our material, intellectual and cultural environments
Willingness to engage with science-related issues
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Understanding of the characteristic features of
science as a form of human knowledge and enquiry
For example
Can students
distinguish
between
evidence-based
explanations
and personal
opinions?
10
PISA defines science performance
in 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 sciencerelated issues
Awareness of how science and technology shape
our material, intellectual and cultural environments
Willingness to engage with science-related issues
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Understanding of the characteristic features of
science as a form of human knowledge and enquiry
For example
Can 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 of11
PISA defines science performance
in 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 sciencerelated issues
Awareness of how science and technology shape
our material, intellectual and cultural environments
Willingness to engage with science-related issues
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Understanding of the characteristic features of
science as a form of human knowledge and enquiry
Interest in
science, support
for scientific
enquiry,
responsibility for
the environment
This 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. 12
Mimi and Dean wondered which sunscreen product
provides the best protection for their skin. Sunscreen
products have a Sun Protection Factor (SPF) that shows
how well each product absorbs the ultraviolet radiation
component of sunlight. A high SPF sunscreen protects
skin for longer than a low SPF sunscreen.
Mimi thought of a way to compare some different
sunscreen products. She and Dean collected the
following:
• two sheets of clear plastic that do not absorb sunlight;
• one sheet of light-sensitive paper;
• mineral oil (M) and a cream containing zinc oxide
(ZnO); and
• four different sunscreens that they called S1, S2, S3,
and S4.
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Example question: Sunscreens
13
Example question: Sunscreens
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Mimi and Dean included mineral oil because it lets most
of the sunlight through, and zinc oxide because it almost
completely blocks sunlight.
Dean placed a drop of each substance inside a circle
marked on one sheet of plastic, then put the second
plastic sheet over the top. He placed a large book on top
of both sheets and pressed down.
Mimi then put the plastic sheets on top of the sheet of
light-sensitive paper. Light-sensitive paper changes from
dark grey to white (or very light grey), depending on how
long it is exposed to sunlight.
Finally, Dean placed the sheets in a sunny place.
14
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Question:
Which one of these statements is a scientific description
of the role of the mineral oil and the zinc oxide in
comparing the effectiveness of the sunscreens?
A. Mineral oil and zinc oxide are both factors being
tested.
B. Mineral oil is a factor being tested and zinc oxide is a
reference substance.
C. Mineral oil is a reference substance and zinc oxide is
a factor being tested.
D. Mineral oil and zinc oxide are both reference
substances.
15
Question:
The light-sensitive paper is a dark grey and fades to a
lighter grey when it is exposed to some sunlight, and to
white when exposed to a lot of sunlight. Which one of
these diagrams shows a pattern that might occur?
Explain why you chose it.
A. ZnO has blocked the sunlight as it should and M has let it
through.
I chose A because the mineral oil needs to be the lightest shade
while the zinc oxide is the darkest.
Partial Credit: A. Gives a correct explanation for either the ZnO
spot or the M spot, but not both.
A. Mineral oil provides the lowest resistance against UVL. So with
other substances the paper would not be white.
A. Zinc oxide absorbs practically all rays and the diagram shows
this.
A because ZnO blocks the light and M absorbs it.
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Full Credit: A. With explanation that the ZnO spot has
stayed dark grey (because it blocks sunlight) and the M
spot has gone white (because mineral oil absorbs very
little sunlight).
A
B
C
D
16
Deciding whom to assess...
grade-based sample
OR
age-based sample
differences in school starting age
differences in grade retention/promotion policies.
IEA studies have chosen grade-based.
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OECD/PISA chose the age-based
NAEP started as age-based (as for PISA)
became grade-based in 1980s (as for IEA)
17
Problem of age-based sample (IEA/PIRLS)
570
Sweden
EnglandNetherlands
550
Canada(O,Q)
540
Italy
530
520
Hungary
United States
Germany
Czech Republic
Scotland
Greece
New Zealand
France
Slovak Republic
Iceland
510
500
R = 0.55
R2 = 0.30
Norway
490
9.6
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Mean score in reading
560
Countries that perform best are
those that test older students.
9.8
10.0
10.2
10.4
10.6
10.8
11.0
Mean age of students tested
18
OECD’s PISA assessment of the knowledge
and skills of 15-year-olds
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Coverage of world economy
83%
81%
77%
87%
86%
85%
19
What do international comparisons tell us?
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550
350
300
Finland
Canada
New Zealand
Australia
Ireland
Hong Kong-China
Korea
United Kingdom
Japan
Sweden
Austria
Belgium
Iceland
Norway
France
United States
Denmark
Switzerland
Spain
Czech Republic
Italy
Germany
Liechtenstein
Hungary
Poland
Greece
Portugal
Russian Federation
Latvia
Israel
Luxembourg
Thailand
Bulgaria
Romania
Mexico
Argentina
Chile
Brazil
FYR Macedonia
Indonesia
Albania
Peru
Mean reading results (PISA 2000)
600
Australia tied for 2nd
with 8 others
among 42 countries.
500
450
400
OECD (2003), Literacy skills for the world of tomorrow: Further results from PISA 2000, Fig. 2.5, p.76.
21
Australia’s ranking in OECD/PISA Reading

Reading ranks



PISA 2000: 4th but tied for 2nd
PISA 2003: 4th but tied for 2nd
PISA 2006: 7th but tied for 6th
PISA 2000
PISA 2003
PISA 2006
Finland
Finland
Finland
Korea
Canada
NZ
Hong Kong
Korea
Canada
NZ
Hong Kong
Korea
Canada
NZ
Same as
Australia
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Ahead of
Australia
Behind
Australia
Hong Kong
22
560
Trends in reading performance
Higher performers in Korea improved.
Korea
550
Finland
540
Lower performers
in HK improved.
Hong Kong
China
530
Canada
New
Zealand
Australia
510
Changes for Finland, Canada & New Zealand are not significant.
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520
500
PISA 2000
OECD (2007), PISA 2006: science competencies for
tomorrow’s world, Vol. 1 - analysis, Fig. 6.21, p.319.
PISA 2003
PISA 2006
23
Trends in Australian reading performances
700
95th %ile
650
90th %ile
600
75th %ile
550
Mean
25th %ile
450
400
10th %ile
5th %ile
350
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500
300
PISA 2000
PISA 2003
PISA 2006
OECD (2007), PISA 2006: science competencies for tomorrow’s world, Vol. 1 - analysis, Fig. 6.21, p.319.
24
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550
350
300
Hong Kong-China
Finland
Korea
Netherlands
Liechtenstein
Japan
Canada
Belgium
Macao-China
Switzerland
Australia
New Zealand
Czech Republic
Iceland
Denmark
France
Sweden
Austria
Germany
Ireland
Slovak Republic
Norway
Luxembourg
Poland
Hungary
Spain
Latvia
United States
Russian Federation
Portugal
Italy
Greece
Serbia
Turkey
Uruguay
Thailand
Mexico
Indonesia
Tunisia
Brazil
Mean mathematics results (PISA 2003)
600
Australia tied for 5th
with 8 others
among 40 countries.
500
450
400
OECD (2004), Learning for tomorrow’s world: first results from PISA 2003, Fig. 2.16b, p.92.
25
Australia’s ranking in OECD/PISA Mathematics

Mathematics ranks



PISA 2000: 6th but tied for 3rd
PISA 2003: 11th but tied for 5th
PISA 2006: 13th but tied for 9th
PISA 2000
Hong Kong
Finland
Hong Kong
Korea
Netherlands
Japan
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Ahead of
Australia
PISA 2003
Same as
Australia
Finland
Korea
Switzerland
Canada
Switzerland
Canada
Macao
Japan
PISA 2006
Taiwan
Finland
Hong Kong
Korea
Netherlands
Switzerland
Canada
Macao
Japan
26
None of those that moved ahead of Australia in
mathematics from 2003 to 2006 improved significantly.
Australia did not move significantly from 2003 to 2006.
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Australia’s significant shift in ranking is a consequence of
cumulative non-significant shifts in different directions.
27
Trends in Australian mathematics performances
700
95th %ile
650
90th %ile
600
75th %ile
550
Mean
25th %ile
450
10th %ile
400
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500
5th %ile
350
PISA 2003
PISA 2006
OECD (2007), PISA 2006: science competencies for tomorrow’s world, Vol. 1 - analysis, Fig. 6.21, p.319.
28
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550
350
300
Finland
Hong Kong-China
Canada
Chinese Taipei
Estonia
Japan
New Zealand
Australia
Netherlands
Liechtenstein
Korea
Slovenia
Germany
United Kingdom
Czech Republic
Switzerland
Macao-China
Austria
Belgium
Ireland
Hungary
Sweden
Poland
Denmark
France
Croatia
Iceland
Latvia
United States
Slovak Republic
Spain
Lithuania
Norway
Luxembourg
Russian Federation
Italy
Portugal
Greece
Israel
Chile
Serbia
Bulgaria
Uruguay
Turkey
Jordan
Thailand
Romania
Montenegro
Mexico
Indonesia
Argentina
Brazil
Colombia
Tunisia
Azerbaijan
Qatar
Kyrgyzstan
Mean science results (PISA 2006)
600
Australia tied for 4th
with 7 others
among 57 countries.
500
450
400
OECD (2007), PISA 2006: science competencies for tomorrow’s world, Vol. 1 - analysis, Fig. 2.11b, pp.56-57.
29
Australia’s ranking in OECD/PISA Science

Science ranks



PISA 2000: 8th but tied for 3rd
PISA 2003: 6th but tied for 4th
PISA 2006: 8th but tied for 4th
PISA 2000
Same as
Australia
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Ahead of
Australia
PISA 2003
PISA 2006
Finland
Finland
Hong Kong
Canada
Japan
Korea
Japan
Korea
Finland
Hong Kong
Canada
Hong Kong
Canada
Japan
Korea
30
The storyline so far…
There is a growing labour market demand for higher level skills.
International comparisons on quality in education show that:
• Australian students are relatively high performing.
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• The competition is not standing still.
31
The impact of raising expectations of low
performers
Variation of performance
within schools
OECD, UNESCO (2003), Literacy skills for tomorrow’s world: further results from PISA 2000, Table 7.1a, p.357.
Iceland
Sweden
Finland
Norway
Spain
Ireland
Canada
Denmark
Korea
New Zealand
Australia
United Kingdom
Luxembourg
United States
Portugal
Mexico
Switzerland
Italy
Czech Republic
Greece
Poland
Austria
Hungary
Germany
Variation of performance
between schools
Belgium
110
100
90
80
70
60
50
40
30
20
10
0
-10
-20
-30
-40
-50
-60
-70
-80
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Variation in reading performance (PISA 2000)
33
OECD (2004), Learning for tomorrow’s world, Table 4.1a, p.383.
Iceland
Finland
Norway
Sweden
Poland
Denmark
Ireland
Canada
-80
Spain
-60
New Zealand
Australia
United States
Mexico
Portugal
Luxembourg
Switzerland
Greece
Slovak Republic
Korea
Czech Republic
Netherlands
Austria
Germany
Italy
Belgium
80
Japan
100
Hungary
Turkey
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Variation in mathematics performance (PISA 2003)
Variation of performance
within schools
60
40
20
0
-20
-40
Variation of performance
between schools
34
560
Trends in reading performance
Korea
550
Finland
540
Hong Kong
China
530
Canada
New
Zealand
520
Australia
Poland
510
490
Lower and higher
performers in
Poland improved.
Lower performers in
Poland improved.
480
Changes for Finland, Canada & New Zealand are not significant.
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500
470
PISA 2000
OECD (2007), PISA 2006: science competencies for
tomorrow’s world, Vol. 1 - analysis, Fig. 6.21, p.319.
PISA 2003
PISA 2006
35
The storyline so far…
There is a growing labour market demand for higher level skills.
International comparisons on quality in education show that:
• Australian students are relatively high performing.
• The competition is not standing still.
International comparisons on equity in education show that:
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• Setting high expectations for all can improve low performers.
36
Elite student achievement is important too.
Scientific excellence of 15-year-olds and countries’ research
intensity
Number of researchers per 1000 employed,
FTE
Finland
16
14
12
Sweden
Japan
10
New Zealand
Denmark
United States
Australia
France
Belgium
Canada
Korea Germany
Luxembourg
Switzerland
Austria
Spain
United Kingdom
Ireland
Slovak Republic
Portugal
Poland
Netherlands
Greece
Hungary
Italy
Norway
8
6
4
2
R2 = 0.70
Turkey
Mexico
0
0
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18
2
4
6
8
10
12
14
16
18
20
22
Percentage of students at levels 5 & 6 in PISA 2006 science
OECD (2007), PISA 2006: Science Competencies for Tomorrow’s World, Vol. 1, p.51.
38
Equity matters too.
% at each reading proficiency level: PISA 2000
Korea has relatively high mean but with few very
high performers and very few low performers.
100
90
Level 5
80
70
Australia’s mean is high because of its relatively high
percentage of very high-performing students.
Level 4
60
50
40
Level 3
30
20
Level 2
10
0
Level 1
-20
-30
Australia has somewhat more low performing students
than some high-performing countries around it.
Peru
Brazil
Chile
Argentina
Mexico
Romania
Bulgaria
Thailand
-100
Source: OECD, UNESCO (2003) Literacy skills for the world of tomorrow, Table 2.1a, p.274
Luxembourg
Israel
Latvia
Russian Federation
Portugal
Greece
Poland
Hungary
Liechtenstein
Germany
Italy
Czech Republic
Spain
Switzerland
Denmark
United States
Norway
France
Iceland
Belgium
Austria
Sweden
Japan
United Kingdom
Korea
Ireland
Australia
Canada
-90
Finland
-80
New Zealand
-70
Hong Kong-China
-60
Albania
Below
Level 1
Indonesia
-50
FYR Macedonia
-40
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-10
40
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100
80
60
40
10
-40
-50
-60
-70
-80
-90
-100
Finland
Hong Kong-China
Canada
Chinese Taipei
Estonia
Japan
New Zealand
Australia
Netherlands
Liechtenstein
Korea
Slovenia
Germany
United Kingdom
Czech Republic
Switzerland
Macao-China
Austria
Belgium
Ireland
Hungary
Sweden
Poland
Denmark
France
Croatia
Iceland
Latvia
United States
Slovak Republic
Spain
Lithuania
Norway
Luxembourg
Russian Federation
Italy
Portugal
Greece
Israel
Chile
Serbia
Bulgaria
Uruguay
Turkey
Jordan
Thailand
Romania
Montenegro
Mexico
Indonesia
Argentina
Brazil
Colombia
Tunisia
Azerbaijan
Qatar
Kyrgyzstan
% at each science proficiency level: PISA 2006
Level 6
90
Level 5
70
Level 4
50
Level 3
30
20
Level 2
0
-10
-20
Level 1
-30
Australia’s percentage of low performing
students is similar to those in other relatively
high performing countries around it.
OECD (2007), PISA 2006: science competencies for tomorrow’s world, Vol. 1 - analysis, Fig. 2.11a, p.49.
Below
Level 1
41
Socioeconomic status & reading literacy (PISA 2000)
Reading literacy
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High
Two indices of relationship:
Social gradient
Correlation or variance accounted for
Social gradient:
Magnitude of increment in
achievement associated with an
increment in social background
(on average)
Correlation:
How well the regression
line summarises the
relationship
Low
PISA Index of social background
Source: OECD (2001) Knowledge and skills for life, Appendix B1, Table 8.1, p.308
Social
Advantage
42
Social gradients for reading literacy (PISA 2000)
High
600
Reading literacy
Finland
500
Canada
450
Australia
This gap is in the order
of 3 years of schooling.
400
Germany
350
Steeper slope = less equitable results
300
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550
-2
Low
-1.5
-1
-0.5
0
0.5
1
1.5
2
Social
PISA Index of social background
Source: OECD (2001) Knowledge and skills for life, Appendix B1, Table 8.1, p.308
Advantage
43
Social gradients for reading literacy (PISA 2000)
550
High quality
540 Low equity
Finland
New Zealand
Australia
United Kingdom
530
Reading literacy
500
490
Germany
Hungary
Korea
Japan
Sweden
Belgium
Austria
France
Norway
United States
Denmark
Switzerland
Czech Republic
510
480
Canada
Ireland
Iceland
Spain
Italy
Poland
Greece
Portugal
470
460
450
Luxembourg
440
430
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520
High quality
High equity
420
-25
Low quality
Low equity
-20
Low quality
High equity
Mexico
-15
-10
-5
0
5
10
15
Social equity (OECD regression slope - country regression slope)
Source: OECD (2001) Knowledge and skills for life, Table 2.3a, p.253.
20
25
44
Social gradients for science literacy (PISA 2006)
575
High quality
FinlandHigh equity
High quality
Low equity
550
New Zealand
United Kingdom
Czech Republic
500
France
Germany
Switzerland
Austria
Belgium
Hungary
Poland
United States
Slovak Republic
Korea
Ireland
Sweden
Denmark
Luxembourg
475
Norway
Greece
Spain
Italy
Iceland
Portugal
450
425
Turkey
Low quality
Low equity
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Science literacy
525
Canada
Japan
Australia
Netherlands
400
-15.0
-10.0
Low quality
Mexico
High equity
-5.0
0.0
5.0
10.0
15.0
Social equity (OECD regression slope - country regression slope
OECD (2007) PISA 2006: science competencies for tomorrow’s world, Vol 1 – analysis, Figure 4.6, p.184.
45
575
SES-science literacy correlations (PISA 2006)
High quality
High quality
Low equity
Finland
High equity
550
New Zealand
Australia
Netherlands
United Kingdom
Germany Czech Republic
Switzerland
Belgium
Ireland
Austria
Hungary
Sweden
Poland
Denmark
France
United States
Spain
Luxembourg Slovak Republic
Italy
Portugal Greece
Science literacy
525
500
475
Korea
Norway
Iceland
450
425
Turkey
Low quality
Low equity
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Canada
Japan
400
-10.0
-8.0
Low quality
High equity
Mexico
-6.0
-4.0
-2.0
0.0
2.0
4.0
6.0
8.0
10.0
Social equity (% variation accounted for: OECD-country)
OECD (2007) PISA 2006: science competencies for tomorrow’s world, Vol 1 – analysis, Figure 4.6, p.184.
46
The storyline so far…
There is a growing labour market demand for higher level skills.
International comparisons on quality in education show that:
• Australian students are relatively high performing.
• The competition is not standing still.
International comparisons on equity in education show that:
• Setting high expectations for all can improve low performers.
• The disadvantaged are over-represented among low performers.
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• Low performers are not left further behind than in other high-performing
countries except to some extent in reading.
47
What do international comparisons tell us
about Australian students’ engagement?
Australian students’ engagement with science learning
Rank among 57 countries
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Aspect of engagement
Level of
engagement
Difference in
achievement
associated with 1
unit difference in
engagement
General value of science
41st
2nd
Personal value of science
37th
1st
General interest in science
54th
13th
Enjoyment of science
45th
2nd
Self efficacy in science
13th
4th
Self concept in science
43rd
1st
Instrumental motivation to learn
32nd
3rd
Future-oriented motivation to learn
42nd
3rd
Involvement in science-related activities
53rd
2nd
OECD (2007) PISA 2006: science competencies for tomorrow’s world, Vol 1 – analysis, Chapter 3, pp.122-163.
49
The storyline so far…
There is a growing labour market demand for higher level skills.
International comparisons on quality in education show that:
• Australian students are relatively high performing.
• The competition is not standing still.
International comparisons on equity in education show that:
• Setting high expectations for all can improve low performers.
• The disadvantaged are over-represented among low performers.
Australian students’ engagement with (science) learning:
• They think they are good at science, as they are.
• They don’t like it, don’t see the value of it, and don’t engage outside school.
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• Low performers are not left further behind than in other high-performing
countries except to some extent in reading.
50
Characteristics of the best performing
systems
Autonomy and standards
70
63
PISA science
50
41
40
46
30
Yes
20
10
Standards-based
No
external
examinations
0
0
No
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60
Yes
School autonomy (in teacher selection)
52
Characteristics of Finland

High-quality teachers



Schools responsible for all their students



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No grade repetition
No school differentiation (before age 15)
Early intervention for students needing it

mcgaw group pty ltd
More difficult to enrol in teacher education than medicine
All 6-year trained with Masters on entry
Largest % of students given extra support is in Grade 1
53
bmcgaw@unimelb.edu.au