1. OECD Programme for International Student Assessment (PISA)
Launch of PISA 2006
London, 4 December 2007
Barbara Ischinger
Director
Directorate for Education, OECD

2. A three-yearly global assessment that…
PISA
A three-yearly global assessment that…
… examines the performance of 15-year-olds in key subject areas as well as a wider range of educational outcomes
Including students attitudes to learning, their beliefs about themselves, and their learning strategies
… collects contextual data from students schools, parents and systems to identify policy levers
Coverage
Representative samples of between 3,500 and 50, year-old students drawn in each country
Most federal countries also draw regional samples
PISA covers roughly 90% of the world economy .

3. PISA countries in
2006
1998
2003
2009
2000
2001
Coverage of world economy
86%
85%
87%
81%
77%
83%

4. How PISA works
A strong international network of expertise among the participating countries…
From establishing the assessment frameworks…
The PISA assessments include tasks from more than 40 countries
… developing the instruments…
Cross-national and cross-cultural validity
… to analysing and interpreting the results
National, regional and international analyses and reports
In-depths country peer reviews
… supported by a consortium of the leading research institutions…
ACER, CITO, ETS, NIER, WESTAT
… co-ordinated through the OECD in collaboration with other international organisations .

5. Science in PISA 2006 PISA defines scientific literacy in terms of an individual’s:
Scientific knowledge and use 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 .

6. Quality in educational outcomes
High science performance
Average performance of 15-year-olds in science – extrapolate and apply
Quality in educational outcomes
… 18 countries perform below this line
Low science performance

7. Mean science scores – OECD countries
OECD (2007), PISA 2006 – Science Competencies for Tomorrow’s World, Table 2.1c

8. Comparison of performance on the different scales in science (UK)
Scientific competencies
Scientific knowledge
OECD (2007), PISA 2006 – Science Competencies for Tomorrow’s World, Figure 2.13

9. Gender differences in science performance (UK)
OECD (2007), PISA 2006 – Science Competencies for Tomorrow’s World, Tables 2.1c, 2.2c, 2.3c, 2.4c, 2.7, 2.8, 2.9, 2.10

10. PISA Proficiency Levels in Science
OECD UK
OECD
Science Level 6
Student can consistently identify, explain and apply scientific knowledge and knowledge about science in a variety of complex life situations 1% 3%
Level 6
Level 5 8%
11%
20%
22%
Level 4
27%
26%
Science Level 1 Student have such a limited scientific knowledge that it can only be applied to a few, familiar situations
Level 3
24%
22%
Level 2
14%
12%
Level 1
Below Level 1 Unable to use scientific skills in ways required by easiest PISA tasks.
Below Level 1 5% 5%
OECD (2007), PISA 2006 – Science Competencies for Tomorrow’s World, Table 2.1a

11. Top and bottom performers
Large proportion of top performers
Large prop. of poor perf. 20
OECD (2007), Learning for tomorrow’s world: First results from PISA 2006, Table 2.1a

12. Investments and outcomes
Since 2000, expenditure per primary and secondary student increased across OECD countries by 39% (in real terms) …
… while PISA outcomes generally remained flat…
… but there are notable exceptions…

13. Between PISA 2000 and 2003 Poland delayed the separation of students into different school types beyond the age of 15 years
Poland raised its reading performance by 28 PISA points, equivalent to ¾ of a school year - What happened?
In 2003, performance variation among schools had fallen from 51% to 16% of the variation of student performance
But did this lead to genuine improvements of school performance?
Between 2000 and 2003 showed the second-largest increase in reading (17 points) and a further 11 point increase since 2003
Most of that increase resulted from smaller proportions at the bottom level (23% in 2000, and three-quarters in vocational tracks, 17%in 2003)
Did this harm the better performers? 20
OECD (2007), Learning for tomorrow’s world: First results from PISA 2006, Table 6.1a

14. Mean reading scores – OECD countries
OECD (2007), PISA 2006 – Science Competencies for Tomorrow’s World, Table 6.1c

15. Mean mathematics scores – OECD countries
OECD (2007), PISA 2006 – Science Competencies for Tomorrow’s World, Table 6.2c

16. Attitudes towards science
High science performance
Average performance of 15-year-olds in science – extrapolate and apply
Attitudes towards science
… 18 countries perform below this line
Low science performance

17. General value of science
OECD (2007), PISA 2006 – Science Competencies for Tomorrow’s World, Figure 3.2

18. Personal value of science
OECD (2007), PISA 2006 – Science Competencies for Tomorrow’s World, Figure 3.4

19. Student engagement with science
Students show strong support for scientific enquiry
93% said that science was important for understanding the natural world
92% said that advances in science and technology usually improved people’s living conditions
75% said that science helped them to understand things around them
57% said that science was very relevant to them personally
Students expressed confidence in be able to do scientific tasks, but more so for some tasks than others 20
76% said they could explain why earthquakes occurred more frequently in some areas than in others
64% said they could predict how changes to an environment would affect the survival of certain species
51% said they could discuss how new evidence could lead to a change in understanding about the possibility of life on Mars
OECD (2007), Learning for tomorrow’s world: First results from PISA 2006, Table 4.1a

20. Equity in educational opportunities
High science performance
Average performance of 15-year-olds in science – extrapolate and apply
High average performance
Large socio-economic disparities
High average performance
High social equity
Equity in educational opportunities
Strong socio-economic impact on student performance
Socially equitable distribution of learning opportunities
Low average performance
Large socio-economic disparities
Low average performance
High social equity
Low science performance

21. Durchschnittliche Schülerleistungen im Bereich Mathematik
High science performance
Durchschnittliche Schülerleistungen im Bereich Mathematik
High average performance
Large socio-economic disparities
High average performance
High social equity
Strong socio-economic impact on student performance
Socially equitable distribution of learning opportunities
Low average performance
Large socio-economic disparities
Low average performance
High social equity
Low science performance

22. School performance and socio-economic background Finland
Student performance and students’ socio-economic background within schools
School performance and schools’ socio-economic background
Student performance and students’ socio-economic background
Student performance
Schools proportional to size
Advantage
PISA Index of socio-economic background
Disadvantage

23. School performance and socio-economic background United Kingdom
Student performance and students’ socio-economic background within schools
School performance and schools’ socio-economic background
Student performance and students’ socio-economic background
Student performance
Schools proportional to size
Advantage
PISA Index of socio-economic background
Disadvantage

24. Student performance and migration
Native students
Second-generation students
OECD average = 500
First-generation students
PISA 2006: Science Competencies for Tomorrow’s World, Figure 4.2a.

25. Is it all innate ability? Variation in student performance
Performance variation across schools 20
OECD (2007), Learning for tomorrow’s world: First results from PISA 2006, Table 4.1a

26. Is it all innate ability? Variation in student performance
PISA 2006: Science Competencies for Tomorrow’s World, Figure 4.1a.

27. Is it all innate ability? Variation in student performance
Variation of performance within schools
Variation of performance between schools
PISA 2006: Science Competencies for Tomorrow’s World, Figure 4.1a.

28. Some school and system factors
Money matters - but other things do too
Some school and system factors

29. School autonomy and standards-based examination on science performance School autonomy in selecting teachers for hire
PISA score in science

30. Impact of selected student and school factors on school performance (after accounting for all other factors in the model)
School principal’s positive evaluation of quality of educational materials (gross only)
Schools with more competing schools (gross only)
Schools with greater autonomy (resources) (gross and net)
School activities to promote science learning (gross and net)
One additional hour of self-study or homework (gross and net)
One additional hour of science learning at school (gross and net)
School results posted publicly (gross and net)
Academically selective schools (gross and net) but no system-wide effect
Schools practicing ability grouping (gross and net)
One additional hour of out-of-school lessons (gross and net) 20
Each additional 10% of public funding (gross only)
School principal’s perception that lack of qualified teachers hinders instruction (gross only)
Effect after accounting for the socio-economic background of students, schools and countries
Measured effect
OECD (2007), PISA 2006 – Science Competencies from Tomorrow’s World, Table 6.1a

31. Thank you ! www.oecd.org; www.pisa.oecd.org
All national and international publications
The complete micro-level database (data from students, parents, schools and systems)
Thank you !