Lessons for Sweden from PISA 2012 performance
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This document provides an overview and analysis of PISA 2012 test results for Sweden and other countries. Some key points: - 15-year-old Swedish students' performance declined compared to 40 other countries that improved in at least one subject. - Shanghai-China, Singapore, Hong Kong-China, Chinese Taipei, Korea, and Japan had the highest student performance. - Socioeconomic factors strongly influence student performance across countries. High-performing education systems promote equitable access to learning opportunities regardless of student background.
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Lessons for Sweden from PISA 2012 performance
- 1. Strong performers and successful reformers in PISA 2012 OECD EMPLOYER Lessons for Sweden BRAND Playbook Andreas Schleicher Stockholm, 18 February 2014 1
- 2. 3 What do 15-year-old Swedes know… …and what can they do with what they know? Of the 65 countries in PISA 40 improved at least in one of the three subjects – Sweden saw a decline
- 3. High student performance 2012 Shanghai-China Singapore Hong Kong-China Chinese Taipei Korea Macao-China Japan Switzerland Liechtenstein Estonia Netherlands Poland Canada Belgium Finland Viet Nam Germany Strong socio-economic Austria Australia impact on student New Zealand Denmark Slovenia Ireland Iceland Czech Rep. performance 22France 26 24 20 18 16 14 12 10 8 6 UK Latvia Luxembourg Norway Portugal Italy Russian Fed. US Spain Lithuania Sweden Slovak Rep. Hungary Croatia Israel Romania Bulgaria Greece Turkey Serbia United Arab Emirates Kazakhstan Thailand Chile Malaysia Low student performance Mexico Socially equitable distribution of learning opportunities 4 2 0
- 4. Australia Austria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel socio-economic Strong Italy impact on student Japan performance Korea Luxembourg Mexico Slovak Rep. Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US 2012 Korea Japan Switzerland Netherlands Poland Belgium Germany Estonia Canada Finland Socially equitable Austria Australia New Zealand Denmark Ireland Slovenia distribution of learning Iceland Czech Rep. opportunities France UK Luxembourg Norway Portugal Italy US Spain Sweden Hungary Israel Greece Turkey Chile Mexico
- 5. Australia Austria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Slovak Rep. Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US Korea Japan Switzerland Netherlands Poland Belgium Germany Estonia Canada Finland Austria Australia New Zealand Denmark Ireland Slovenia Iceland Czech Rep. France UK Luxembourg Norway Portugal Italy US Spain Sweden Hungary Israel Greece Turkey Chile Mexico
- 6. Contribution of various factors to upper secondary teacher compensation costs, per student as a percentage of GDP per capita (2004) Salary as % of GDP/capita Instruction time 1/teaching time 1/class size Difference with OECD average 15 Percentage points 10 5 0 -5 Slovak Republic Poland United States Sweden Finland Mexico Ireland Iceland Norway Hungary Czech Republic Austria Italy Denmark Netherlands France New Zealand United Kingdom Australia Japan Greece Germany Luxembourg Korea Belgium Switzerland Spain Portugal -10
- 7. EU/U S Slovak Republic Iceland Czech Republic Hungary Italy Austria Estonia United States Norway Chile Poland Scotland France Slovenia Sweden Ireland Belgium (Fr.) Netherlands EU21 average OECD average Belgium (Fl.) Denmark Australia England Israel Finland Germany Canada New Zealand Portugal Luxembourg Korea Spain Ratio of teachers' salary to earnings for full-time, full-year workers with tertiary education aged 25-64 (2011 or latest available year) Ratio 1.5 1.0 0.5 0.0
- 8. Australia Austria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Slovak Rep. Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US Korea Japan Switzerland Netherlands Poland Belgium Germany Estonia Canada Finland Austria Australia New Zealand Denmark Ireland Slovenia Iceland Czech Rep. France UK Luxembourg Norway Portugal Italy US Spain Sweden Hungary Israel Greece Turkey Chile Mexico
- 9. Australia Austria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Slovak Rep. Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US Shanghai 2003 - 2012 Singapore Singapore Korea Japan Switzerland Netherlands Poland Belgium Germany Estonia Canada Finland Austria Australia New Zealand Denmark Ireland Slovenia Iceland Czech Rep. France UK Luxembourg Norway Portugal Italy US Spain Sweden Hungary Israel Greece Turkey Chile Mexico
- 10. 14 Math teaching ≠ math teaching PISA = reason mathematically and understand, formulate, employ and interpret mathematical concepts, facts and procedures
- 11. 1.50 1.00 Viet Nam Macao-China Shanghai-China Turkey Uruguay Greece Hong Kong-China Chinese Taipei Portugal Brazil Serbia Bulgaria Singapore Netherlands Japan Argentina Costa Rica Lithuania Tunisia New Zealand Czech Republic Israel Korea Latvia Qatar Italy United States Estonia Ireland Australia Mexico United Arab Emirates Norway Malaysia Kazakhstan United Kingdom Romania OECD average Albania Colombia Indonesia Sweden Belgium Peru Thailand Denmark Russian Federation Canada Slovak Republic Hungary Germany Croatia Luxembourg Montenegro Chile Poland Finland Austria Slovenia France Switzerland Jordan Liechtenstein Spain Iceland Index of exposure to word problems 15 Students' exposure to word problems Fig I.3.1a 2.50 2.00 Formal math situated in a word problem, where it is obvious to students what mathematical knowledge and skills are needed 0.50 0.00
- 12. Sweden Iceland Tunisia Argentina Switzerland Brazil Luxembourg Ireland Netherlands New Zealand Costa Rica Austria Liechtenstein Malaysia Indonesia Denmark United Kingdom Uruguay Lithuania Germany Australia Chile OECD average Slovak Republic Thailand Qatar Finland Portugal Colombia Mexico Peru Czech Republic Israel Italy Belgium Hong Kong-China Poland France Spain Montenegro Greece Turkey Slovenia Viet Nam Hungary Bulgaria Kazakhstan Chinese Taipei Canada United States Estonia Romania Latvia Serbia Japan Korea Croatia Albania Russian Federation United Arab Emirates Jordan Macao-China Singapore Shanghai-China Iceland Index of exposure to formal mathematics 16 Students' exposure to conceptual understanding Fig I.3.1b 2.50 2.00 1.50 1.00 0.50 0.00
- 13. Czech Republic Macao-China Shanghai-China Viet Nam Uruguay Finland Costa Rica Sweden Japan Chinese Taipei Italy Israel Norway Estonia Hong Kong-China Austria Serbia Korea Croatia Latvia Slovak Republic Greece United Kingdom Ireland Luxembourg Belgium Montenegro Argentina Slovenia Bulgaria OECD average Lithuania Hungary Switzerland New Zealand Germany Turkey Denmark Russian Federation Singapore Iceland United States Spain Qatar Liechtenstein Poland Australia France Brazil Malaysia Peru Canada Chile United Arab Emirates Romania Tunisia Netherlands Portugal Colombia Albania Kazakhstan Jordan Mexico Indonesia Thailand Index of exposure to applied mathematics 17 Students' exposure to applied mathematics Fig I.3.1c 2.50 2.00 1.50 1.00 0.50 0.00
- 14. Relationship between mathematics performance and students' exposure to applied mathematics 18 Fig I.3.2 Mean score in mathematics 510 490 470 450 430 0.0 never 0.5 1.0 rarely 1.5 2.0 sometimes Index of exposure to applied mathematics 2.5 3.0 frequently
- 15. 19 The dream of social mobility In some countries it is close to a reality
- 16. 10 Shanghai-China Hong Kong-China Macao-China Viet Nam Singapore Korea Chinese Taipei Japan Liechtenstein Switzerland Estonia Netherlands Poland Canada Finland Belgium Portugal Germany Turkey OECD average Italy Spain Latvia Ireland Australia Thailand Austria Luxembourg Czech Republic Slovenia United Kingdom Lithuania France Norway Iceland New Zealand Russian Fed. United States Croatia Denmark Sweden Hungary Slovak Republic Mexico Serbia Greece Israel Tunisia Romania Malaysia Indonesia Bulgaria Kazakhstan Uruguay Brazil Costa Rica Chile Colombia Montenegro U.A.E. Argentina Jordan Peru Qatar 20 Percentage of resilient students % 40 30 More than 40 % resilient Fig II.2.4 80 70 60 50 Socio-economically disadvantaged students not only score lower in mathematics, they also report lower levels of engagement, drive, motivation and self-beliefs. Resilient students break this link and share many characteristics of advantaged highachievers. 20 Between 20%-40% of resilient students Less than 20% 0
- 17. 21 The share of immigrant students in OECD countries increased from 9% in 2003 to 12% in 2012… …while the performance disadvantage of immigrant students shrank by 11 score points during the same period (after accounting for socio-economic factors)
- 18. Finland Mexico France Change between 2003 and 2012 in immigrant students' mathematics performance – before accounting for students’ socio-economic status Denmark Switzerland - Belgium - Austria Sweden Netherlands Brazil Germany - Spain Iceland Greece 80 Liechtenstein 2012 Italy + Norway Portugal Luxembourg OECD average 2003 - Czech Republic Russian Federation Thailand United States United Kingdom Hong Kong-China Latvia Canada Ireland New Zealand - Turkey -20 Slovak Republic - Macao-China Australia - Hungary - Score point difference (without-with immig.) 23 Fig II.3.5 2003 100 Students without an immigrant background perform better 60 40 20 0 Students with an immigrant background perform better -40
- 19. 25 It is not just about poor kids in poor neighbourhoods… …but about many kids in many neighbourhoods
- 20. 60 40 20 20 80 Albania Finland Iceland Sweden Norway Denmark Estonia Ireland Spain Canada Poland Latvia Kazakhstan United States Mexico Colombia Costa Rica Russian Fed. Malaysia Jordan New Zealand Lithuania Greece Montenegro United Kingdom Argentina Australia Brazil Portugal Indonesia Chile Thailand Romania Tunisia Switzerland Peru Uruguay Croatia U.A.E. Macao-China Serbia Viet Nam Korea ong Kong-China Singapore Austria Italy Luxembourg Czech Republic Japan Bulgaria Israel Qatar Shanghai-China Germany Slovenia Slovak Republic Turkey Belgium Hungary Liechtenstein Netherlands Chinese Taipei Variation in student performance as % of OECD average variation 26 Variability in student mathematics performance between and within schools Fig II.2.7 100 80 Performance differences Between-school differences are still small in between schools Sweden, but they increased from 831 index OECD average points in 2003 to 1042 index points in 2012 58% of between-school differences are explained by social factors 0 Performance variation of students within schools 40 60 OECD average 100
- 21. % 30 Hong Kong-China Korea + Liechtenstein Macao-China + Japan Switzerland Belgium Netherlands Germany Poland + Canada Finland New Zealand Australia Austria OECD average 2003 France Czech Republic Luxembourg Iceland Slovak Republic Ireland Portugal + Denmark Italy + Norway Hungary United States Sweden Spain Latvia Russian Federation Turkey Greece Thailand Uruguay Tunisia Brazil Mexico Indonesia 28 Percentage of top performers in mathematics in 2003 and 2012 2012 Fig I.2.23 2003 40 Across OECD, 13% of students are top performers (Level 5 or 6). They can develop and work with models for complex situations, and work strategically with advanced thinking and reasoning skills 20 10 0
- 22. Excellence matters 30 % • Evolution of employment in occupational groups defined by 20 problem-solving skills 25 medium-low level of problem-solving 15 10 5 0 Low level of problem-solving -5 -10 -15 -20 Medium-high level of problem-solving
- 23. High impact on outcomes 31 31 Quick wins Lessons from high performers Must haves Catching up with the top-performers Low feasibility High feasibility Money pits Low hanging fruits Low impact on outcomes
- 24. High impact on outcomes 32 32 Quick wins Must haves Lessons from high performers Commitment to universal achievement Capacity at point of delivery Resources where they yield most Gateways, instructional systems Coherence A learning system Low feasibility High feasibility Incentive structures and accountability Money pits Low hanging fruits Low impact on outcomes
- 25. High impact on outcomes 33 33 Lessons from high performers Quick Must to education and the belief that wins A commitmenthaves Commitment to universal therefore competencies can be learned andachievementall children can achieve Capacity personalization as at Universal educational standards andResources point of delivery the approach to heterogeneitywhere they yield most in the student body… … as opposed to a belief that students have different Gateways, instructional destinations to be met with different expectations, and systems selection/stratification as the approach to Coherence heterogeneity A learning system Clear articulation who is responsible for ensuring Low feasibility High feasibility student success and to whom Incentive structures and accountability Money pits Low hanging fruits Low impact on outcomes
- 26. 34 Countries where students have stronger beliefs in their abilities perform better in mathematics Fig III.4.5 OECD average 650 Mean mathematics performance 600 550 500 450 400 350 300 -0.60 Shanghai-China Singapore Hong Kong-China Korea R² = Chinese Taipei Macao-China Japan Switzerland Netherlands Estonia Canada Liechtenstein Finland Germany Poland Belgium Viet Nam Slovenia Denmark New Zealand Latvia Sweden Portugal Italy Austria Australia Russian Fed. Hungary Luxembourg Spain Croatia Slovak Republic Greece Norway Turkey Israel Sweden Serbia Czech Republic Lithuania U.A.E. Iceland Romania United Kingdom Malaysia Thailand United States Ireland Bulgaria Kazakhstan Chile Montenegro France Costa Rica Mexico Uruguay Albania Brazil Argentina Tunisia Colombia Qatar Jordan Indonesia Peru -0.40 -0.20 0.00 0.20 0.40 0.60 Mean index of mathematics self-efficacy 0.80 0.36 1.00 1.20
- 27. 35 Motivation to learn mathematics Fig III.3.9 Percentage of students who reported "agree" or "strongly agree" with the following statements: Sweden Shanghai-China OECD average I am interested in the things I learn in mathematics I do mathematics because I enjoy it I look forward to my mathematics lessons I enjoy reading about mathematics 0 B UK 10 20 30 40 % 50 60 70
- 28. 36 Perceived self-responsibility for failure in mathematics Fig III.3.6 Percentage of students who reported "agree" or "strongly agree" with the following statements: Sweden Shanghai-China OECD average Sometimes I am just unlucky The teacher did not get students interested in the material Sometimes the course material is too hard This week I made bad guesses on the quiz My teacher did not explain the concepts well this week I’m not very good at solving mathematics problems 0 B US 20 40 60 % 80 100
- 29. 37 The parent factor Students whose parents have high educational expectations for them tend to report more perseverance, greater intrinsic motivation to learn mathematics, and more confidence in their own ability to solve mathematics problems than students of similar background and academic performance, whose parents hold less ambitious expectations for them.
- 30. High impact on outcomes 41 41 Quick wins Must haves Lessons from high performers Commitment to universal achievement Clear ambitious goals that are shared across the Capacity system and aligned with high stakes gateways and Resources at point of delivery where instructional systemsthey yield most Coherence Low feasibility Well established delivery chain through which Gateways, instructional curricular goals translate into instructional systems, systems instructional practices and student learning (intended, implemented andlearning system A achieved) High level of metacognitive content of instruction … High feasibility Incentive structures and accountability Money pits Low hanging fruits Low impact on outcomes
- 31. B Netherlands Croatia ong Kong-China Japan Thailand Serbia Viet Nam Hungary Singapore Bulgaria Liechtenstein Macao-China Switzerland Luxembourg Austria U.A.E. Korea Indonesia Italy Germany Albania Montenegro New Zealand Czech Republic Israel Malaysia Slovak Republic Shanghai-China Costa Rica Mexico Tunisia Qatar Chinese Taipei Kazakhstan Australia OECD average Turkey Colombia Canada Chile Estonia Portugal Jordan United States Romania France Peru Slovenia Latvia United Kingdom Uruguay Belgium Ireland Russian Fed. Iceland Brazil Lithuania Poland Argentina Denmark Sweden Greece Norway Spain Finland Most schools look at students’ past academic performance when considering admission Fig IV.1.6 Students in schools whose principals reported that "students' records of academic performance" or "recommendations of feeder schools" is always considered for admission 100 90 80 70 % 60 50 40 30 20 10 0
- 32. 43 High impact on outcomes 43 Capacity at Lessons from high performers the point of delivery Quick wins Must haves Attracting, developing and retaining high quality Commitment a universal achievement teachers and school leaders andto work organisation in which they can use their potential Capacity Instructional leadership and human resource Resources at point of delivery management in schools where they yield most Keeping teaching an attractive profession Gateways, instructional System-wide career development … systems Coherence A learning system Low feasibility High feasibility Incentive structures and accountability Money pits Low hanging fruits Low impact on outcomes
- 33. 1.3 -0.1 -0.3 B Korea Estonia Israel Kazakhstan Latvia Malaysia Slovenia Italy Poland Singapore Argentina Costa Rica Netherlands Portugal Colombia Bulgaria France Finland Tunisia Lithuania Qatar Macao-China Thailand Spain Greece Switzerland Romania Norway Russian Fed. Japan Austria Montenegro Croatia Canada U.A.E. OECD average Germany Denmark Hungary United Kingdom Luxembourg Hong Kong-China Belgium Iceland Jordan Peru Viet Nam Ireland United States Chile Czech Republic Serbia Turkey Mexico Indonesia Uruguay Shanghai-China Slovak Republic Sweden Brazil New Zealand Australia Chinese Taipei Albania Mean index difference Teacher shortage is more of concern in disadvantaged schools Fig IV.3.5 Difference between socio-economically disadvantaged and socio-economically advantaged schools 1.5 Disadvantaged and public schools reported more teacher shortage 1.1 0.9 0.7 0.5 0.3 0.1 Advantaged and private schools reported more teacher shortage -0.5
- 34. High impact on outcomes 45 45 Lessons from high performers Quick wins Must haves Incentives, accountability, knowledge management Commitment to universal achievement Aligned incentive structures For students Capacity Resources How gateways at point of delivery affect the strength, direction, clarity and nature of the incentives operating on students at each stage of their education where they yield most Degree to which students have incentives to take tough courses and study hard Gateways, Opportunity costs for staying in school and performing well instructional For teachers Coherenceinnovations in pedagogy and/or organisation Make A learning system Low feasibility Improve their own performance and the performance of their colleagues Pursue professional development opportunities that lead to stronger pedagogical practices systems High feasibility Incentive structures and A balance between vertical and lateral accountability accountability Effective instruments to manage and share knowledge and spread innovation – communication within the system and with stakeholders around it Money pits Low hanging A capable centre with authority and legitimacy to act fruits Low impact on outcomes
- 35. Schools with more autonomy perform better than schools with less autonomy in systems with standardised math policies Fig IV.1.16 School autonomy for curriculum and assessment x system's extent of implementing a standardised math policy (e.g. curriculum and instructional materials) Score points 485 480 475 470 465 460 Standardised math policy 455 No standardised math policy Less school autonomy More school autonomy
- 36. Schools with more autonomy perform better than schools with less autonomy in systems with more collaboration School autonomy for resource allocation x System's level of teachers participating in school management Across all participating countries and economies Score points 485 480 475 470 465 460 Teachers participate in management 455 Teachers don't participate in management Less school autonomy More school autonomy Fig IV.1.17
- 37. Schools with more autonomy perform better than schools with less autonomy in systems with more accountability arrangements Fig IV.1.16 School autonomy for curriculum and assessment x system's level of posting achievement data publicly Score points 478 476 474 472 470 468 466 School data public 464 School data not public Less school autonomy More school autonomy
- 38. % 0 Finland Uruguay Greece + Switzerland + Ireland + Belgium + Sweden + Japan + Germany + Norway + Italy + Hungary + Slovak Republic Tunisia Denmark + OECD average 2003… Spain Australia + Luxembourg + Liechtenstein + Netherlands + Latvia Korea + New Zealand + Iceland + Brazil + United States Macao-China + Austria + Indonesia Turkey + Czech Republic + Mexico Hong Kong-China + Thailand + Portugal + Russian Federation + Poland Change between 2003 and 2012 in using student assessment data to monitor teachers 2012 Fig IV.4.19 Percentage of students in schools that use assessment data to monitor teachers: 2003 100 90 80 70 60 50 40 30 20 10
- 39. 51 Quality assurance and school improvement Fig IV.4.14 Percentage of students in schools whose principal reported that their schools have the following for quality assurance and improvement: Sweden Singapore OECD average Implementation of a standardised policy for mathematics Regular consultation with one or more experts over a period of at least six months with the aim of improving… Teacher mentoring Written feedback from students (e.g. regarding lessons, teachers or resources) External evaluation Internal evaluation/self-evaluation Systematic recording of data, including teacher and student attendance and graduation rates, test results… Written specification of student-performance standards Written specification of the school's curriculum and educational goals 0 20 40 % 60 80 100
- 40. High impact on outcomes 52 52 Quick wins Lessons from high performers Must haves Commitment to universal achievement Investing resources where they can make most of Capacity a difference Resources Alignment of resources with key challenges (e.g. at point of delivery where they teachers attracting the most talentedyield mostto the most challenging classrooms) Gateways, instructional Effective spending choices that prioritise high quality systems teachers over smaller classes Coherence A learning system Low feasibility High feasibility Incentive structures and accountability Money pits Low hanging fruits Low impact on outcomes
- 41. Money makes a difference – but only up to a point 650 Cumulative expenditure per student less than USD 50 000 Shanghai-China Mathematics performance (score points) Fig IV.1.8 Cumulative expenditure per student USD 50 000 or more 600 Singapore Korea 550 Japan Switzerland Netherlands PolandCanada Finland Viet Nam Estonia Belgium Germany Czech Republic Australia Austria New Zealand Slovenia Ireland Denmark Latvia France UK Norway Portugal Iceland Lithuania Slovak Republic Croatia Italy Sweden United States Israel Hungary Spain Turkey 500 R² = 0.01 Luxembourg 450 Bulgaria Thailand Chile Mexico Montenegro Uruguay Malaysia 400 Tunisia Brazil Jordan Colombia Peru 350 R² = 0.37 300 0 20 000 40 000 60 000 80 000 100 000 120 000 140 000 160 000 Average spending per student from the age of 6 to 15 (USD, PPPs) 180 000 200 000
- 42. Among high-income countries high-performers pay teachers more Fig IV.1.10 Mathematics performance (score points) 650 Per capita GDP less than USD 20 000 In 33 countries schools where a higher 600 share of principals reported that teacher shortages hinder learning tend to show lower performance 550 Shanghai-China Per capita GDP over USD 20 000 Singapore Hong Kong-China Korea Macao-China Japan R² = 0.09 Netherlands Finland Canada Belgium Austria Australia Germany Czech Rep. Iceland Ireland Latvia France Denmark New Zealand Slovenia UK Slovak Rep. Norway Italy Luxembourg Portugal Spain USA Hungary Croatia Israel Sweden Lithuania Romania Greece Bulgaria Thailand Malaysia Uruguay Chile Tunisia Montenegro Qatar Indonesia Colombia Argentina Peru Jordan Estonia 500 450 400 Poland Among low-income countries a host of other resources are the principal barriers 350 R² = 0.05 300 20 40 60 80 100 120 140 Teachers' salaries relative to per capita GDP (%) 160 180 200 220
- 43. Countries with better performance in mathematics tend to allocate educational resources more equitably 700 Adjusted by per capita GDP 650 Mathematics performance (score points) Fig IV.1.11 30% of the variation in math performance across OECD countries is 600 explained by the degree of similarity of educational resources between advantaged and disadvantaged schools 550 500 450 Mexico Costa Rica 400 Shanghai-China Chinese Taipei Korea R² = 0.19 Viet Nam Singapore Hong Kong-China Estonia Japan Poland Slovenia Switzerland Latvia Finland Canada Belgium Germany Macao-China Slovak Rep. New Zealand UK IrelandIceland France DenmarkSpain Austria Australia Croatia Hungary Israel Romania Portugal Sweden Bulgaria Turkey USA Greece Norway Italy Serbia Thailand Malaysia Chile Kazakhstan Uruguay Jordan Brazil Indonesia UAE Montenegro Colombia Tunisia Argentina Luxembourg Peru 350 Qatar 300 1.5 1 Less equity 0.5 OECD countries tend to allocate at least an equal, if not a larger, number of teachers per student to disadvantaged schools; but disadvantaged schools tend to have great difficulty in attracting 0 -0.5 qualified teachers. Equity in resource allocation (index points) Greater equity
- 44. High impact on outcomes 57 57 Quick wins Must haves Lessons from high performers Commitment to universal achievement Capacity at point of delivery Coherence of policies and practices Alignment of policies across all aspects of the system Coherence Coherence of policies over sustained periods of time LowConsistency of implementation feasibility Fidelity of implementation (without excessive control) Money pits CAN Resources where they yield most Gateways, instructional systems A learning system High feasibility Incentive structures and accountability Low hanging fruits Low impact on outcomes
- 45. High impact on outcomes 58 58 Quick wins Must haves Lessons from high performers Commitment to universal achievement Capacity at point of delivery Resources where they yield most Gateways, instructional systems Coherence A learning system Low feasibility High feasibility Incentive structures and accountability Money pits Low hanging fruits Low impact on outcomes
- 46. What it all means 59 59 Lessons from high performers Average education systems High performers Student inclusion Some students learn at high levels All students need to learn at high levels Curriculum, instruction and assessment Routine cognitive skills, rote learning Learning to learn, complex ways of thinking, ways of working Teacher quality Few years more than secondary High-level professional knowledge workers Work organisation ‘Tayloristic’, hierarchical Flat, collegial Accountability Primarily to authorities Primarily to peers and stakeholders
- 47. Find out more about PISA at www.pisa.oecd.org • All national and international publications • The complete micro-level database Thank you ! Email: Andreas.Schleicher@OECD.org Twitter: SchleicherEDU and remember: Without data, you are just another person with an opinion
Notas del editor
- The red dot indicates classroom spending per student, relative to the spending capacity of countries, the higher the dot, the more of its GDP a country invests. High salaries are an obvious cost driver. You see Korea paying their teachers very well, the green bar goes up a lot. Korea also has long school days, another cost driver, marked here by the white bar going up. Last but not least, Korea provides their teachers with lots of time for other things than teaching such as teacher collaboration and professional development, which costs money as well. So how does Korea finances all of this? They do this with large classes, the blue bar pulls costs down. If you go to the next country on the list, Luxembourg, you see that the red dot is about where it is for Korea, so Luxembourg spends roughly the same per student as Korea. But parents and teachers in Luxembourg mainly care about small classes, so policy makers have invested mainly into reducing class size, you see the blue bar as the main cost driver. But even Luxembourg can only spend its money once, and the result is that school days are short, teacher salaries are average at best and teachers have little time for anything else than teaching. Finland and the US are a similar contrast.Countries make quite different spending choices. But when you look at this these data long enough, you see that many of the high performing education systems tend to prioritise the quality of teachers over the size of classes.
- (9) Does this matter? Yes, it does. When you look at the evolution of employment by those problem-solving skills, you can see that there has been a significant decline in employment by people with basic problem-solving skills. There has been little change in employment among the low-skilled. But there has been significant growth in employment among great problem-solvers. What you see here is the hollowing out of labour-markets. Those who have great skills are fine, and will be better and better off. The people most at risk are not the poorly-skilled but white-collar workers with so-so-problem-solving skills, because their skills can increasingly be digitised, automated or outsourced. Those at the low end of the spectrum keep their jobs but are seeing declining wages. That's because you cannot digitise your bus driver or outsource your hairdresser to India.
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- I want to conclude with what we have learned about successful reform trajectories In the past when you only needed a small slice of well-educated people it was efficient for governments to invest a large sum in a small elite to lead the country. But the social and economic cost of low educational performance has risen substantially and all young people now need to leave school with strong foundation skills.When you could still assume that what you learn in school will last for a lifetime, teaching content and routine cognitive skills was at the centre of education. Today, where you can access content on Google, where routine cognitive skills are being digitised or outsourced, and where jobs are changing rapidly, the focus is on enabling people to become lifelong learners, to manage complex ways of thinking and complex ways of working that computers cannot take over easily.In the past, teachers had sometimes only a few years more education than the students they taught. When teacher quality is so low, governments tend to tell their teachers exactly what to do and exactly how they want it done and they tend to use Tayloristic methods of administrative control and accountability to get the results they want. Today the challenge is to make teaching a profession of high-level knowledge workers. But such people will not work in schools organised as Tayloristic workplaces using administrative forms of accountability and bureaucratic command and control systems to direct their work. To attract the people they need, successful education systems have transformed the form of work organisation in their schools to a professional form of work organisation in which professional norms of control complement bureaucratic and administrative forms of control.