Organisation for Economic Cooperation and Development (OECD)

1. Organisation for Economic Cooperation and Development (OECD) Responsive Education Systems and Skills for the Knowledge EconomyUsing education as a lever to compete by working smarter, rather than working harder or cheaper Knowledge economy forum Andreas Schleicher Head, Indicators and Analysis Division OECD Directorate for Education

2. Key competencies for tomorrow’s world „The world is flat“ (Thomas Friedman)

3. Key competencies for tomorrow’s world • The personal computer enabled millions of individuals to become authors of their own content in digital form • The spread of the Internet and the emergence of the World Wide Web enabled more people than ever to be connected and to share their knowledge • The emergence of software standards meant that people were able to seamlessly work together and upload and globalise content

4. Economy-wide measures of routine and non-routine task input (Levy and Murnane, 2007)

5. Delivering high level skills. Quantity - A world of change.

6. Baseline qualifications – A world of changeApproximated by the percentage of persons with ISCED 3 qualfication born in the period shown below (2004) 1 11 23 1 14 24 A1.2a

7. Growth in university-level qualificationsApproximated by the percentage of persons with ISCED 5A/6 qualfication born in the period shown below (2004) 3 +3.7 +3.5 +2.9 22 12 20 A1.3a

8. The returns on high level qualificationsPrivate internal rates of return (RoR) for an individual obtaining a university-level degree (ISCED 5/6) from an upper secondary and post-secondary non-tertiary level of education (ISCED 3/4), MALES

9. The returns on high level qualificationsPrivate internal rates of return (RoR) for an individual obtaining a university-level degree (ISCED 5/6) from an upper secondary and post-secondary non-tertiary level of education (ISCED 3/4), MALES • 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% (UK 9%). • Growing benefits in many of the countries with the steepest attainment growth

10. Enhancements in human capital contribute to labour productivity growthAverage annual percentage change (1990-2000)

11. Delivering high level skills. Quality – Getting the fundamentals right

12. Who will be “safe” from outsourcing, digitalisation and automatisation? • The great collaborators and orchestrators • The more complex the globalised world becomes, the more individuals and companies need various forms of co-ordination and management • The great synthesisers • Conventionally, our approach to problems was breaking them down into manageable bits and pieces, today we create value by synthesising disparate bits together • The great explainers • The more content we can search and access, the more important the filters and explainers become

13. Who will be “safe” from outsourcing, digitalisation and automatisation? • The great versatilists • Specialists generally have deep skills and narrow scope, giving them expertise that is recognised by peers but not valued outside their domain • Generalists have broad scope but shallow skills • Versatilists apply depth of skill to a progressively widening scope of situations and experiences, gaining new competencies, building relationships, and assuming new roles. • They are capable not only of constantly adapting but also of constantly learning and growing • The great personalisers • A revival of interpersonal skills, skills that have atrhophied to some degree because of the industrial age and the Internet • The great localisers • Localising the global

14. High mathematics performance Average performanceof 15-year-olds in mathematics Low mathematics performance

15. Mathematical literacy in PISA The real world The mathematical World A mathematical model A model of reality A real situation Mathematical results Real results

16. Mathematical literacy in PISA The real world The mathematical World Making the problem amenable to mathematical treatment Understanding, structuring and simplifying the situation Using relevant mathematical tools to solve the problem Validating the results Interpreting the mathematical results

17. Mathematical literacy in PISA The real world The mathematical World • The educators’ challenge • The skills that are easiest to teach and test are also the skills that are easiest to digitise, automatise and offshore • Teaching and evaluating skills in a context of real-world complexity • “expert thinking” – the ability to structure a problem • “complex communication” – the ability to convey a particular interpretation of information

18. High mathematics performance Average performanceof 15-year-olds in mathematics 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 mathematics performance

19. High mathematics 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 mathematics performance

20. Using the potential. Equality in outcomes and equity in opportunities.

21. School performance and schools’ socio-economic background – Russian Federation Student performance PISA Index of social background Disadvantage Advantage OECD Student performance and student SES within schools OECD School performance and school SES OECD Student performance and student SES School proportional to size Figure 4.13

22. School performance and schools’ socio-economic background - Finland Student performance and student SES Student performance and student SES within schools School performance and school SES School proportional to size Student performance PISA Index of social background Disadvantage Advantage Figure 4.13

23. High ambitions and clear standards Access to best practice and quality professional development

24. Sympathy doesn’t raise standards – aspiration does • PISA suggests that students and schools perform better in a climate characterised by high expectations and the readiness to invest effort, the enjoyment of learning, a strong disciplinary climate, and good teacher-student relations • Among these aspects, students’ perception of teacher-student relations and classroom disciplinary climate display the strongest relationships

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

26. High mathematics 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 mathematics performance

27. High mathematics performance Durchschnittliche Schülerleistungen im Bereich Mathematik Strong socio-economic impact on student performance Socially equitable distribution of learning opportunities • School with responsibility for deciding which courses are offered • High degree of autonomy • Low degree of autonomy Low mathematics performance

28. High mathematics performance Durchschnittliche Schülerleistungen im Bereich Mathematik 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 mathematics performance

29. Strong ambitions Devolvedresponsibility,the school as the centre of action Integrated educational opportunities Accountability Individualisedlearning Accountability Access to best practice and quality professional development

30. High ambitions Devolved responsibility, the school as the centre of action Integrated educational opportunities Diagnostic knowledgeand intervention in inverse proportion to success Individualisedlearning Access to best practice and quality professional development

31. 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

32. Further information • www.pisa.oecd.org • All national and international publications • The complete micro-level database • email: pisa@oecd.org • Andreas.Schleicher@OECD.org … and remember: Without data, you are just another person with an opinion