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Bringing lessons from the world

Bringing lessons from the world. 23 March 2009 Prof. Andreas Schleicher Head, Indicators and Analysis Division OECD Directorate for Education. This session. 1 . There is nowhere to hide

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Bringing lessons from the world

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  1. Bringing lessons from the world 23 March 2009 Prof. Andreas SchleicherHead, Indicators and Analysis DivisionOECD Directorate for Education

  2. 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 international comparisons

  3. There is nowhere to hide The yardstick for success is no longer improvement by national standards but the best performing education systems

  4. A world of change in baseline qualificationsApproximated by percentage of persons with high school or equivalent qualfications in the age groups 55-64, 45-55, 45-44 und 25-34 years % 1 13 1 27 1. Excluding ISCED 3C short programmes 2. Year of reference 2004 3. Including some ISCED 3C short programmes 3. Year of reference 2003.

  5. A world of change – collegeeducation Expenditure per student at tertiary level (USD) Cost per student Graduate supply Tertiary-type A graduation rate

  6. A world of change – collegeeducation Expenditure per student at tertiary level (USD) United States Cost per student Sweden Germany Japan Graduate supply Tertiary-type A graduation rate

  7. A world of change – collegeeducation Expenditure per student at tertiary level (USD) United States (2000) United States (1995) Australia Tertiary-type A graduation rate

  8. A world of change – collegeeducation Expenditure per student at tertiary level (USD) Tertiary-type A graduation rate

  9. A world of change – collegeeducation Expenditure per student at tertiary level (USD) Tertiary-type A graduation rate

  10. A world of change – collegeeducation Expenditure per student at tertiary level (USD) Tertiary-type A graduation rate

  11. A world of change – collegeeducation Expenditure per student at tertiary level (USD) Tertiary-type A graduation rate

  12. A world of change – collegeeducation Expenditure per student at tertiary level (USD) United States Sweden Australia Ireland Tertiary-type A graduation rate

  13. A world of change – collegeeducation Expenditure per student at tertiary level (USD) United States Tertiary-type A graduation rate

  14. A world of change – collegeeducation Expenditure per student at tertiary level (USD) United States Tertiary-type A graduation rate

  15. A world of change – collegeeducation Expenditure per student at tertiary level (USD) United States Tertiary-type A graduation rate

  16. A world of change – collegeeducation Expenditure per student at tertiary level (USD) United States Tertiary-type A graduation rate

  17. A world of change – collegeeducation Expenditure per student at tertiary level (USD) United States Tertiary-type A graduation rate

  18. A world of change – collegeeducation Expenditure per student at tertiary level (USD) Tertiary-type A graduation rate

  19. A world of change – collegeeducation • 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% Expenditure per student at tertiary level (USD) United States Australia Tertiary-type A graduation rate

  20. Cumulated streams of costs and benefits The IRR is the discount rate at which the Net Present Value=0. Given a stream of assumed costs and benefits over 25-to-64-years-old, the IRR represents the rate of return on investment expressed as an interest rate.

  21. Moving targetsFuture supply of high school graduates

  22. Future supply of high school graduates Future supply of college graduates

  23. How the demand for skills has changedEconomy-wide measures of routine and non-routine task input (US) Mean task input as percentiles of the 1960 task distribution 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 (Levy and Murnane)

  24. Deciding 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 the PISA assessment of the knowledge and skills of 15-year-olds, OECD governments chose the latter

  25. OECD’s PISA assessment of the knowledge and skills of 15-year-olds Coverage of world economy 83% 77% 81% 85% 86% 87%

  26. High science performance Average performanceof 15-year-olds in science – extrapolate and apply … 18 countries perform below this line Low science performance

  27. Increased 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)

  28. Strengths and weaknesses of countries in science relative to their overall performanceFrance Science competencies Science knowledge OECD (2007), PISA 2006 – Science Competencies for Tomorrow’s World, Figure 2.13

  29. Strengths and weaknesses of countries in science relative to their overall performanceCzech Republic Scientific competencies Scientific knowledge 20 OECD (2007), PISA 2006 – Science Competencies for Tomorrow’s World, Figure 2.13

  30. Strengths and weaknesses of countries in science relative to their overall performanceUnited States Science competencies Science knowledge OECD (2007), PISA 2006 – Science Competencies for Tomorrow’s World, Figure 2.13

  31. High science performance Average performanceof 15-year-olds in science – extrapolate and apply 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

  32. 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 15 Low science performance

  33. Student performance PISA Index of socio-economic background Disadvantage Advantage School performance and socio-economic background Germany Student performance and students’ socio-economic background withinschools School performance and schools’ socio-economic background Student performance and students’ socio-economic background Schools proportional to size

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

  35. Student performance PISA Index of socio-economic background Disadvantage Advantage 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 Schools proportional to size

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

  37. How to get there Some policy levers that emerge from international comparisons

  38. 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 .

  39. High ambitions and universal standards Rigor, focus and coherence Great systems attract great teachers and provide access to best practice and quality professional development

  40. Challenge and support Strong support Poor performance Improvements idiosyncratic Strong performance Systemic improvement Lowchallenge Highchallenge Poor performance Stagnation Conflict Demoralisation Weak support

  41. High ambitions Devolved responsibility,the school as the centre of action Accountability and intervention in inverse proportion to success Access to best practice and quality professional development

  42. School autonomy, standards-based examinations and science performanceSchool autonomy in selecting teachers for hire PISA score in science

  43. Local responsibility and national prescription Towards system-wide sustainable reform National prescription Schools today The industrial model, detailed prescription of what schools do Schools tomorrow? Building capacity Finland today Every school an effective school Schools leading reform

  44. Public and private schools % Score point difference Public schools perform better Private schools perform better

  45. Pooled international dataset, effects of selected school/system factors on science 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

  46. Strong ambitions Devolvedresponsibility,the school as the centre of action Integrated educational opportunities From prescribed forms of teaching and assessment towards personalised learning Accountability Access to best practice and quality professional development

  47. 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 • Early selection and institutional differentiation • High degree of stratification • Low degree of stratification Low average performance Large socio-economic disparities Low average performance High social equity 6 Low science performance

  48. Money matters - but other things do too

  49. Spending choices on secondary schoolsContribution of various factors to upper secondary teacher compensation costsper student as a percentage of GDP per capita (2004) Percentage points

  50. Paradigm shifts The old bureaucratic education system The modern enabling education system Universal high standards Hit & miss Uniformity Embracing diversity Provision Outcomes Bureaucratic – look up Devolved – look outwards Talk equity Deliver equity Received wisdom Data and best practice Prescription Informed profession Demarcation Collaboration

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