How Peru Can Improve Student Performance in PISA Tests
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What do 15-year-olds know… …and what can they do with what they know? Students in Peru still perform at low levels, but significant gains in reading skills show that improvement is possible
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How Peru Can Improve Student Performance in PISA Tests
- 1. PISA 2012 Strong performers and successful reformers in education OECD EMPLOYER Lessons for Peru BRAND Playbook Andreas Schleicher Peru, February 2014 1
- 2. 2 PISA in brief • Over half a million students… – representing 28 million 15-year-olds in 65 countries/economies … took an internationally agreed 2-hour test… – Goes beyond testing whether students can reproduce what they were taught… … to assess students’ capacity to extrapolate from what they know and creatively apply their knowledge in novel situations – Mathematics, reading, science, problem-solving, financial literacy – Total of 390 minutes of assessment material … and responded to questions on… – their personal background, their schools and their engagement with learning and school • Parents, principals and system leaders provided data on… – school policies, practices, resources and institutional factors that help explain performance differences .
- 3. 3 What do 15-year-olds know… …and what can they do with what they know? Students in Peru still perform at low levels, but significant gains in reading skills show that improvement is possible
- 4. Change in performance between PISA 2003 and 2012 4 5 PISA 2003 performance above the OECD average PISA 2003 performance below the OECD average Mexico 3 Turkey Tunisia Portugal Italy Poland 2 1 Thailand Germany Russian Fed. Greece Hong Kong-China Macao-China Korea Improving performance Peru (R) Brazil 4 Latvia Switzerland Japan United States Austria Liechtenstein Spain Luxembourg OECD average Norway Ireland Indonesia Peru (M) 0 -1 Slovak Republic France Hungary Uruguay Denmark -2 Canada Belgium Iceland Netherlands Australia New Zealand Czech Republic -3 Finland Sweden Deteriorating performance Average annual mathematics score change Fig I.2.18 -4 350 400 450 500 Average mathematics performance in PISA 2003 550 600
- 5. 5 Performance of countries in a level playing field How the world would look if students around the world were living in similar social and economic conditions
- 6. 340 Shanghai-China Singapore Hong Kong-China Chinese Taipei Viet Nam Macao-China Korea Japan Liechtenstein Poland Switzerland Estonia Netherlands Germany Belgium Finland Canada Portugal Austria Czech Republic New Zealand Latvia France Slovenia Ireland Australia OECD average Turkey Slovak Republic Spain Hungary Luxembourg Italy Russian Federation United Kingdom Denmark Lithuania Croatia United States Norway Sweden Iceland Romania Israel Serbia Thailand Greece Bulgaria Chile Uruguay Malaysia Kazakhstan Cyprus5, 6 Mexico Costa Rica United Arab… Brazil Montenegro Tunisia Indonesia Peru Argentina Colombia Jordan Qatar Mean mathematics score 6 Mathematics performance in a level playing field Mean mathematics performance after accounting for socio-economic status Fig II.3.3 Mean score at the country level before adjusting for socio-economic status Mean score at the country level after adjusting for socio economic status 600 580 560 540 520 500 480 460 440 420 400 380 360
- 7. 7 The dream of social mobility In some countries it is close to a reality
- 8. 0.50 -1.50 Peru Costa Rica Mexico Brazil Indonesia Thailand Colombia New Zealand Turkey Argentina United States Uruguay Australia Chile Viet Nam Jordan Shanghai-China U.A.E. Romania Sweden Israel Bulgaria Chinese Taipei Malaysia Ireland Greece Tunisia Poland Canada Japan Macao-China OECD average Luxembourg Qatar Russian Fed. Iceland Belgium France Switzerland Portugal Hong Kong-China Spain Lithuania Denmark Kazakhstan Italy Czech Republic Netherlands Estonia Hungary Slovenia Austria Singapore Latvia Slovak Republic Montenegro Korea Germany Serbia United Kingdom Norway Croatia Finland Liechtenstein Albania Mean index difference Educational resources are more problematic in disadvantaged schools in most countries Fig IV.3.8 Difference between socio-economically disadvantaged and socio-economically advantaged schools Disadvantaged and public schools reported better educational resources 0.00 -0.50 -1.00 Advantaged and private schools reported better educational resources -2.00
- 9. Social background and school performance - Peru 9 Score Level 5 700 Private school Level 4 Public school in rural area Level 3 Public school in urban area Below level 1 Level 1 Level 2 494 200 -3 B -2 -1 0 1 PISA index of social, economic and cultural status 2 3
- 10. 2 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 10 Percentage of resilient students 12 % 10 8 More than 10 % resilient Fig II.2.4 20 18 16 14 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. 6 4 Between 5%-10% of resilient students Less than 5% 0
- 11. 11 It is not just about poor kids in poor neighbourhoods… …but about many kids in many neighbourhoods
- 12. 60 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 12 Variability in student mathematics performance between and within schools Fig II.2.7 100 80 Performance differences between schools 40 OECD average 20 0 Performance variation of students within schools 40 60 OECD average 100
- 13. 10 -40 Jordan Qatar Thailand Malaysia Iceland U.A.E. Latvia Singapore Finland Sweden Bulgaria Russian Fed. Albania Montenegro Lithuania Kazakhstan Norway Macao-China Slovenia Romania Poland Indonesia United States Estonia Chinese Taipei Shanghai-China Belgium Turkey Greece France Hungary Serbia Slovak Republic Vietnam Canada Netherlands OECD average Portugal Uruguay Croatia Israel Czech Republic Australia United Kingdom Switzerland Germany Argentina Denmark Mexico New Zealand Tunisia Ireland Hong Kong-China Spain Brazil Japan Korea Italy Peru Austria Liechtenstein Costa Rica Chile Luxembourg Colombia Score-point difference (boys-girls) 13 Gender differences in mathematics performance Fig I.2.25 30 20 Boys perform better than girls 0 -10 -20 -30 Girls perform better than boys -50
- 14. High impact on outcomes 14 14 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
- 15. High impact on outcomes 15 15 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
- 16. High impact on outcomes 16 16 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
- 17. 17 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 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
- 18. 18 Perceived self-responsibility for failure in mathematics Fig III.3.6 Percentage of students who reported "agree" or "strongly agree" with the following statements: Peru 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
- 19. 19 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.
- 20. Parents’ expectations for their child have a strong influence on students’ behaviour towards school 20 Fig III.6.11 Percentage-point change in arriving late for school that is associated with parents expecting the child to complete a university degree 4 2 -2 -4 -6 -8 -10 -12 -14 Hungary Korea Croatia Hong Kong-China Macao-China Italy Portugal Chile Mexico Belgium (Flemish) -16 Germany Percentage-point change 0
- 21. Parents’ high expectations can nurture students’ enjoyment in learning mathematics 21 Fig III.6.11 Change in the index of intrinsic motivation to learn mathematics that is associated with parents expecting the child to complete a university degree 0.50 0.45 0.35 0.30 0.25 0.20 0.15 0.10 0.05 Germany Mexico Macao-China Croatia Hungary Portugal Chile Hong Kong-China Italy Korea 0.00 Belgium (Flemish) Mean index change 0.40
- 22. Parents’ high expectations can foster perseverance in their child 22 Fig III.6.11 Change in the index of perseverance that is associated with parents expecting the child to complete a university degree 0.35 0.25 0.20 0.15 0.10 0.05 Macao-China Korea Croatia Germany Hong Kong-China Chile Hungary Mexico Belgium (Flemish) Italy 0.00 Portugal Mean index change 0.30
- 23. High impact on outcomes 23 23 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
- 24. Grade repetition is negatively related to equity Fig IV.1.4 Adjusted by per capita GDP Greater equity 2 Variation in mathematics performance explained by socioeconomic status (%) 4 Macao-China 6 Kazakhstan Hong Kong-China Estonia Jordan Indonesia Norway Qatar Thailand Iceland Mexico Finland Canada Tunisia Japan Korea Italy UAE Serbia Croatia Russian Fed. Sweden Montenegro Lithuania Viet Nam Australia Turkey Argentina Latvia Switzerland Netherlands UK Brazil Greece Colombia Belgium Slovenia Ireland USA Shanghai-China Poland Czech Rep. Spain Singapore Israel Austria R2=0.05 Denmark Costa Rica Romania Germany New Zealand Chinese Taipei R2=0.07 Portugal 8 10 12 14 16 18 20 Bulgaria 22 Chile Peru Luxembourg Hungary France Slovak Rep. 24 Uruguay 26 -5 Less equity 0 5 10 15 20 25 30 Percentage of students who have repeated at least one grade 35 40 45
- 25. Belgium Netherlands France Spain Germany Portugal Italy Austria United States Ireland Canada Australia Slovak Republic New Zealand Denmark Finland Sweden Korea Czech Republic Poland Slovenia United Kingdom Israel Iceland Estonia Norway Japan USD, PPPs Grade repetition is an expensive policy Fig IV.1.5 Total cost per repeater (one grade year) Total annual cost, relative to total expenditure on primary and secondary education (%) 60000 14 50000 12 10 40000 8 30000 % 6 20000 4 10000 2 0 0
- 26. 26 High impact on outcomes 26 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 … FIN systems Coherence A learning system Low feasibility High feasibility Incentive structures and accountability Money pits Low hanging fruits Low impact on outcomes
- 27. Luxembourg Jordan Thailand Turkey Shanghai-China Israel Colombia Peru Chile Netherlands Mexico Germany Viet Nam Russian Fed. Uruguay Norway Kazakhstan Indonesia Belgium Italy Malaysia Australia Brazil Iceland U.A.E. Singapore New Zealand Korea Switzerland Estonia Macao-China Costa Rica OECD average Sweden Argentina Tunisia Austria Qatar Ireland Chinese Taipei France Denmark United Kingdom Hong Kong-China Albania Japan Canada Slovak Republic Latvia Greece United States Czech Republic Croatia Finland Montenegro Romania Hungary Lithuania Slovenia Spain Serbia Portugal Bulgaria Poland Mean index Teacher shortage Mean index Top quarter of this index Fig IV.3.5 Bottom quarter of this index 3 2.5 2 1.5 1 0.5 0 -0.5 -1 -1.5
- 28. Singapore Qatar Australia Chinese Taipei Switzerland United Kingdom Hong Kong-China Japan Slovenia France United States U.A.E. Poland Macao-China Belgium Canada Austria Romania New Zealand Netherlands Hungary Portugal Lithuania Shanghai-China Uruguay Ireland Germany Korea OECD average Sweden Czech Republic Italy Luxembourg Latvia Spain Bulgaria Denmark Estonia Norway Finland Malaysia Iceland Greece Israel Chile Turkey Albania Jordan Russian Fed. Viet Nam Montenegro Croatia Brazil Argentina Slovak Republic Serbia Thailand Kazakhstan Indonesia Mexico Costa Rica Peru Tunisia Colombia Mean index Adequacy of educational resources Mean index Top quarter of this index Fig IV.3.8 Bottom quarter of this index 3.00 2.00 1.00 0.00 -1.00 -2.00 -3.00 -4.00
- 29. High impact on outcomes 29 29 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
- 30. Countries that grant schools autonomy over curricula and assessments tend to perform better in mathematics 650 Fig IV.1.15 Shanghai-China Mathematics performance (score points) 600 Chinese Taipei Viet Nam 550 500 450 400 Korea Estonia Singapore Hong Kong-China Japan Poland Latvia Slovenia Belgium Czech Rep. Switzerland Canada Germany Finland New Zealand Lithuania Netherlands Portugal Hungary Austria Croatia Italy Spain France Australia Serbia UK Macao-China Turkey Norway Iceland Denmark R² = 0.13 Slovak Rep. Bulgaria Thailand Greece Romania Kazakhstan Israel Malaysia Chile Uruguay USA Sweden Jordan Costa Rica Indonesia Brazil Albania Luxembourg Tunisia Colombia UAE Argentina Peru 350 Qatar 300 -1.5 -1 -0.5 0 0.5 Index of school responsibility for curriculum and assessment (index points) 1 1.5
- 31. 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
- 32. 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
- 33. % 0 Finland Belgium Shanghai-China Japan Austria Switzerland Argentina Macao-China Uruguay Peru Germany Costa Rica Spain Luxembourg Chinese Taipei Tunisia Ireland Jordan Indonesia Albania Croatia Greece Iceland Lithuania Latvia Hong Kong-… Liechtenstein Estonia Malaysia Denmark Italy Brazil Mexico Czech Republic OECD average France U.A.E. Poland Israel Hungary Qatar Singapore Colombia Portugal Slovenia Norway Bulgaria Serbia Canada Chile Turkey Romania Australia Korea Viet Nam Thailand Slovak Republic Russian Fed. Kazakhstan Montenegro New Zealand Sweden United Kingdom Netherlands United States Use of achievement data for accountability Fig IV.4.13 Percentage of students in schools that use achievement data in the following ways: Post publicly 100 90 80 70 60 50 40 30 20 10
- 34. 34 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: 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 SIN 0 20 40 % 60 80 100
- 35. 35 The issue is not how many charter schools a country has… …but how countries enable every school to assume charter type autonomy
- 36. 100 -50 Chinese Taipei Hong Kong-China Thailand Viet Nam Luxembourg Switzerland Indonesia Italy Kazakhstan Japan Czech Republic Netherlands Estonia Albania Ireland United States Hungary Sweden Korea United Kingdom Finland Denmark OECD average France Shanghai-China Australia Spain Slovak Republic Mexico Germany Austria Colombia Chile Canada Poland Jordan Argentina United Arab Emirates Portugal Peru Costa Rica Brazil New Zealand Malaysia Slovenia Uruguay Qatar Score-point difference Differences in mathematics performance between private and public schools shrink considerably after accounting for socio-economic status 50 Fig IV.1.19 Observed performance difference After accounting for students’ and schools’ socio-economic status 75 Performance advantage of public schools 25 0 -25 Performance advantage of private schools -75 -100 -125
- 37. High impact on outcomes 37 37 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
- 38. 38 Money makes a difference… …but only up to a point
- 39. Spending per student from the age of 6 to 15 and mathematics performance in PISA 2012 Fig IV.1.8 650 Cumulative expenditure per student less than USD 50 000 Mathematics performance (score points) Shanghai-China Cumulative expenditure per student USD 50 000 or more 600 Singapore Korea 550 Japan Switzerland PolandCanada Finland Netherlands 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
- 40. 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 Shanghai-China 600 550 500 450 Mexico Costa Rica 400 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 SHA 1 Less equity 0.5 Equity in resource allocation (index points) 0 -0.5 Greater equity
- 41. High impact on outcomes 41 41 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
- 42. High impact on outcomes 42 42 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
- 43. What it all means 43 43 Lessons from high performers The old bureaucratic system The modern enabling system 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
- 44. 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
Hinweis der Redaktion
- Figure I.2.15
- (Fig. II.4.5)
- (Fig. II.4.5)
- (Fig. II.4.5)
- 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.