Bildung in die Zukunft steuern Wien, 15. April 2010 Prof. Andreas Schleicher Advisor of the OECD Secretary-General on Education Policy OECD Directorate for Education Some 10 years ago, we lived in a very different world in which education systems tended to be inward-looking , where schools and education systems typically considered themselves to be unique and to operate in a unique context that would not allow them to borrow on policies and practices developed elsewhere. Sort of, where practitioners and policy makers alike felt reluctant to take any medicine for which they had not themselves participated in its clinical trial. There were lots of walls between education systems. Some of these walls were “natural”, established by language or culture, but others result from poor knowledge management in education systems and because education often remains dominated by beliefs and traditions. International comparisons provide one way to break through some of these walls, and they have become a powerful instrument for policy reform and transformational change, by allowing education systems to look at themselves in the light of the intended, implemented and achieved policies elsewhere. When education ministers meet at the OECD these days, they begin almost any conversation with a comparative perspective. It seems that information feeding peer pressure and public accountability is now often more powerful than legislation, rules and regulations.

Neue Herausforderungen Gestern Heute Märkte Stabil Dynamisch Wettbewerb National Global Organisationsformen Hierarchisch Vernetzt Produktion Massenproduktion Flexible Produktion –embedded services Wachstumsimpulse Mechanisierung Digitalisierung, Miniaturisierung Wettbewerbsvorteil „Economies of scale“ Innovation, Zeitnähe Firmenmodell Einzelbetrieb „Co-petition” – Allianzen Politische Ziele Vollbeschäftigung „Employability” Berufsprofile Klare Identität im berufsspezifischen Kontext Konvergenz und Transformation Kompetenzen Berufsspezifisch Multi-dimensional Bildung Formale Qualifikation Lebensbegleitendes Lernen

There is nowhere to hide And policy makers do this because in this world where all work that can be digitised, automated or outsourced can now be done anywhere in the world by those who are best prepared, the yardstick for success is no longer improvement by national standards, but the best performing education systems internationally. I will begin my presentation this evening by showing how the global talent pool has changed, in response to the forces of globalisation and technological change Then examine what international comparisons can tell us about this. I will show you where we see the United States and try to contrast this with the best performing education systems, that give you a sense of what is possible in education, terms of the quality of educational outcomes and equity in the distribution of educational opportunities. And I will conclude with tying the results to some of the policy levers that emerge from international comparisons. There is nowhere to hide Why the yardstick for success is no longer improvement by national educational standards

Spitzenqualifikationen Expenditure per student at tertiary level (USD) Cost per student The pace of change is most clearly visible in higher education, and I want to bring two more dimensions into the picture here. Each dot on this chart represents one country. The horizontal axis shows you the college graduation rate, the proportion of an age group that comes out of the system with a college degree. The vertical axis shows you how much it costs to educate a graduate per year. Graduate supply Tertiary-type A graduation rate

Spitzenqualifikationen Expenditure per student at tertiary level (USD) United States Cost per student Austria Finland *Lets now add where the money comes from into the picture, the larger the dot, the larger the share of private spending on college education, such as tuition. The chart shows the US as the country with the highest college graduation rate, and the highest level of spending per student. The US is also among the countries with the largest share of resources generated through the private sector. That allows the US to spend roughly twice as much per student as Europe. US, Finland The only thing I have not highlighted so far is that this was the situation in 1995. And now watch this closely as you see how this changed between 1995 and 2005. Graduate supply Tertiary-type A graduation rate

Spitzenqualifikationen Expenditure per student at tertiary level (USD) Australia United Kingdom Finland You see that in 2000, five years, later, the picture looked very different. While in 1995 the US was well ahead of any other country – you see that marked by the dotted circle, in 2000 several other countries had reached out to this frontier. Look at Australia, in pink. Poland Tertiary-type A graduation rate

Spitzenqualifikationen Expenditure per student at tertiary level (USD) Tertiary-type A graduation rate

Spitzenqualifikationen Expenditure per student at tertiary level (USD) Tertiary-type A graduation rate

Spitzenqualifikationen Expenditure per student at tertiary level (USD) Tertiary-type A graduation rate

Spitzenqualifikationen Expenditure per student at tertiary level (USD) Tertiary-type A graduation rate

Spitzenqualifikationen Expenditure per student at tertiary level (USD) That was all very quick, let us go through this development once again Tertiary-type A graduation rate

Spitzenqualifikationen Expenditure per student at tertiary level (USD) United States Australia Austria Finland Tertiary-type A graduation rate

Veränderungen in der Nachfrage nach Kompetenzen Economy-wide measures of routine and non-routine task input (US) Mean task input as percentiles of the 1960 task distribution Levy and Murnane show how the composition of the US work force has changed. What they show is that, between 1970 and 2000, work involving routine manual input, the jobs of the typical factory worker, was down significantly. Non-routine manual work, things we do with our hands, but in ways that are not so easily put into formal algorithms, was down too, albeit with much less change over recent years – and that is easy to understand because you cannot easily computerise the bus driver or outsource your hairdresser. All that is not surprising, but here is where the interesting story begins: Among the skill categories represented here, routine cognitive input, that is cognitive work that you can easily put into the form of algorithms and scripts saw the sharpest decline in demand over the last couple of decades, with a decline by almost 8% in the share of jobs. So those middle class white collar jobs that involve the application of routine knowledge, are most at threat today. And that is where schools still put a lot of their focus and what we value in multiple choice accountability systems. The point here is, that the skills that are easiest to teach and test are also the skills that are easiest to digitise, automatise and offshore. If that is all what we do in school, we are putting our youngsters right up for competition with computers, because those are the things computers can do better than humans, and our kids are going to loose out before they even started. Where are the winners in this process? These are those who engage in expert thinking – the new literacy of the 21st century, up 8% - and complex communication, up almost 14%. 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)

Latin America then… GDP/pop 1960 Years schooling Asia 1891 4 Sub-Saharan Africa 2304 3.3 MENA 2599 2.7 Latin America 4152 4.7 Europe 7469 7.4 Orig. OECD 11252 9.5 Let us go back to the 1960s. The chart shows you the wealth of world regions and the average years of schooling in these regions, which is the most traditional measure of human capital. Have a look at Latin America, it ranked third in wealth and third in years of schooling, so in the 1960s the world seemed pretty much in order. Hanushek 2009

Latin America then and now… GDP/pop 1960 Years schooling Growth 1960-2000 GDP/pop 2000 Asia 1891 4 4.5 13571 Sub-Saharan Africa 2304 3.3 1.4 3792 MENA 2599 2.7 8415 Latin America 4152 4.7 1.8 8063 Europe 7469 7.4 2.9 21752 Orig. OECD 11252 9.5 2.1 26147 But when you look at economic growth between 1960 and 2000, you see that something went wrong. Despite the fact that Latin America did well in terms of years of schooling, only Sub-Saharan Africa did worse in terms of economic growth. So in 2000, Latin America had fallen back considerably in terms of GDP per capita. You can draw two conclusions from this: Either education is not as important for economic growth as we thought, or we have for a long time been measuring the wrong thing. Hanushek 2009

Latin America then and now… Why quality is the key GDP/pop 1960 Years schooling Growth 1960-2000 GDP/pop 2000 Test score Asia 1891 4 4.5 13571 480 Sub-Saharan Africa 2304 3.3 1.4 3792 360 MENA 2599 2.7 8415 412 Latin America 4152 4.7 1.8 8063 388 Europe 7469 7.4 2.9 21752 492 Orig. OECD 11252 9.5 2.1 26147 500 Now let me add one additional element, and that is a measure of the quality of education, in the form of the score of the different world regions on international tests like PISA or TIMSS. And you see now that the world looks in order again, there seems a close relationship between test scores and economic growth. You can see that even more clearly when you put this into graphical form. This is one of the charts produced by Professor Hanushek. And, as Professor Hanushek will explain, the relationship holds even when you account for other factors, it even holds when you compare growth in economies with growth in learning outcomes, which is the closest we can come to examining causality. So what this tells you is that it is not simply years of schooling or the number of graduates we produce, but indeed the quality of learning outcomes that counts. Hanushek 2009

Increased likelihood of tertiary particip Increased likelihood of tertiary particip. at age 19/21 associated with PISA reading proficiency at age 15 (Canada) after accounting for school engagement, gender, mother tongue, place of residence, parental, education and family income (reference group PISA Level 1) Increased chance of successful tertiary participation The best way to find out whether what students have learned at school matters for their life is to actually watch what happens to them after they leave school. This is exactly what we have done that with around 30,000 students in Canada. We tested them in the year 2000 when they were 15 years old in reading, math and science, and since then we are following up with them each year on what choices they make and how successful they are in their transition from school to higher education and work. The horizontal axis shows you the PISA level which 15-year-old Canadians had scored in 2000. Level 2 is the baseline level on the PISA reading test and Level 5 the top level in reading. The red bar shows you how many times more successful someone who scored Level 2 at age 15 was at age 19 to have made a successful transition to university, as compared to someone who did not make it to the baseline PISA level 1. And to ensure that what you see here is not simply a reflection of social background, gender, immigration or school engagement, we have already statistically accounted for all of these factors. The orange bar. … How would you expect the picture to be like at age 21? We are talking about test scores here, but for a moment, lets go back to the judgements schools make on young people, for example through school marks. You can do the same thing here, you can see how well school marks at age 15 predict the subsequent success of youths. You see that there is some relationship as well, but that it is much less pronounced than when we use the direct measure of skills. School marks at age 15 PISA performance at age 15

Some policy levers that emerge from international comparisons International comparisons demonstrate what can be done with a combination of the right strategy and courageous, sustained leadership. Let us look at what’s behind the success of some of these countries. Handlungsfelder Some policy levers that emerge from international comparisons

Hohe Erwartungen und anspruchsvolle Standards Zugang zu guter Praxis und berufliche Weiterentwicklung als integraler Bestandteil des Berufsfeldes

Standards und Unterstützung Gute Unterstützung der Einrichtungen Schwache Leistungen Verbesserungen bleiben Einzelfall Starke Leistungen Systemische Verbesserungen Unklare Anforderungen Anspruchsvolle Standards Schwache Leistungen Stagnation Konflikt Demoralisierung Geringe Unterstützung

Hohe Erwartungen und anspruchsvolle Standards Freiräume und Handlungsfähigkeit der Bildungs-einrichtungen Evaluation, motivierende Leistungsrückmeldungen und Intervention invers zum Erfolg Zugang zu guter Praxis und berufliche Weiterentwicklung als integraler Bestandteil des Berufsfeldes

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

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 But the balance between national prescription and schools leading reform is not an all-or-nothing. In fact, most school systems have started out with highly prescriptive education systems. But gradually the have moved towards building capacity and enabling schools to assume greater responsibility. Schools leading reform

Hohe Erwartungen und anspruchsvolle Standards Freiräume und Handlungsfähigkeit der Schulen Individualisierung von Lernen Evaluation, motivierende Leistungsrückmeldungen und Intervention invers zum Erfolg Offene und vernetzte Bildungswege statt früher Selektion Qualifikationsrahmen Zugang zu guter Praxis und berufliche Weiterentwicklung als integraler Bestandteil des Berufsfeldes

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 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 Low science performance

Hohe Erwartungen und anspruchsvolle Standards Freiräume und Handlungsfähigkeit der Schulen Individulalisierung von Lernen Evaluation und Intervention invers zum Erfolg Offene und integrierte Bildungswege Zugang zu guter Praxis und berufliche Weiterentwicklung als integraler Bestandteil des Berufsfeldes

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

Paradigm shifts Hit and miss  Universal high standards Uniformity The old bureaucratic system The modern enabling system Hit and miss  Universal high standards Uniformity Embracing diversity Provision Outcomes Bureaucratic look-up Devolved – look outwards Talk equity Deliver equity Prescription Informed profession Conformity Ingenious Curriculum-centred Learner-centred Interactive Participative Individualised Community-centred Delivered wisdom User-generated wisdom Management Leadership Public vs private Public with private Culture as obstacle Culture as capital

Thank you ! www.oecd.org; 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 Thank you !