1 National Conference on Student Assessment How the U.S. and Other Countries Compare: Lessons Learned International Data CCSSO San Diego June 22, 2015 Andreas Schleicher
Increased likelihood of positive outcomes among adults with higher literacy skills (scoring at Level 4/5 compared with those scoring at Level 1 or below) Odds ratio 4.5 United States 4.0 3.5 3.0 2.5 2.0 1.5 1.0 Being Employed High wages Good to excellent health Participation in volunteer activities High levels of political efficacy High levels of trust 2
5 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.
Mean score 580 570 560 550 High mathematics performance Shanghai-China performs above this line (613) Chinese Taipei Singapore Hong Kong-China Korea Average performance of 15-year-olds in Mathematics (PISA) Fig I.2.13 540 530 520 510 500 490 480 470 460 450 440 430 420 410 Massachusetts Poland Belgium Germany Austria Slovenia New Zealand Denmark Czech Republic France LuxembourgLatvia Portugal Spain Slovak Republic United States Hungary Israel Greece Romania Chile Macao-China Japan Liechtenstein Switzerland Netherlands Estonia Finland Canada Viet Nam Australia Ireland United Kingdom Iceland Norway Italy Russian Fed. Lithuania Sweden Croatia Serbia Turkey Bulgaria U.A.E. Kazakhstan Thailand Malaysia Mexico Low mathematics performance 26% of American 15-year-olds do not reach PISA Level 2 (OECD average 23%, Shanghai 4%, Japan 11%, Canada 14%) Below PISA Level 2
420 410 400 390 380 370 Low mathematics performance Iran* Costa Rica Montenegro BrazilArgentina Tunisia Saudi Arabia* Indonesia Peru Uruguay Bahrain* Georgia* Albania Jordan Macedonia Colombia Qatar Botswana* Oman* 360 350 Morocco* 340 330 320 310 Honduras* South Africa* 300 290 Ghana* 280 270 260 * Substituted from TIMSS
420 410 400 390 380 370 751% GDP 23,841 bn$ Low mathematics performance Iran* Costa Rica Montenegro BrazilArgentina Tunisia Saudi Arabia* Indonesia Peru Uruguay Bahrain* Georgia* Albania Jordan Macedonia Colombia Qatar Botswana* Oman* 360 350 Morocco* 340 330 320 310 Honduras* South Africa* 300 290 280 Ghana* 3880% GDP 4,526 bn$ 270 260 * Substituted from TIMSS
High mathematics performance Chinese Taipei Singapore Hong Kong-China Korea 86% GDP 402 bn$ Poland Belgium Germany Austria Slovenia New Zealand Denmark Czech Republic France LuxembourgLatvia Portugal Spain Slovak 153% Republic GDP United States Hungary 27,929 bn$ Israel Macao-China Japan Liechtenstein Switzerland Netherlands Estonia Finland Canada Viet Nam Australia Ireland United Kingdom Iceland Norway Italy Russian Fed. Lithuania Sweden Croatia Greece Romania Chile Serbia Turkey Bulgaria U.A.E. Kazakhstan Thailand Malaysia Mexico Low mathematics performance
High mathematics performance Chinese Taipei Singapore Hong Kong-China Korea Average performance of 15-year-olds in mathematics Strong socio-economic impact on student performance Poland Belgium Germany Austria Slovenia New Zealand Denmark Czech Republic France LuxembourgLatvia Portugal Spain Slovak Republic United States Hungary Israel Macao-China Japan Liechtenstein Switzerland Netherlands Estonia Finland Canada Viet Nam Australia Ireland United Kingdom Iceland Norway Italy Russian Fed. Lithuania Sweden Croatia Socially equitable distribution of learning opportunities Greece Romania Chile Serbia Turkey Bulgaria U.A.E. Kazakhstan Thailand Malaysia Mexico Low mathematics performance
High mathematics performance 2012 Singapore Chinese Taipei Korea Hong Kong-China Strong socio-economic impact on student performance 26 Slovak Rep. Japan Switzerland Liechtenstein Netherlands Estonia Poland Belgium Canada Finland Germany Viet Nam Denmark Austria New Zealand Australia Slovenia Ireland Czech Rep. Iceland 22France 20 18 16 14 12 10 8 6 4 UK Luxembourg Latvia Norway Portugal Italy US Russian Fed. Spain Lithuania Sweden Hungary Croatia Israel Massachusetts 24 Macao-China Socially equitable distribution of learning 2opportunities 0 Chile Bulgaria Romania Greece Turkey Serbia United Arab Emirates Malaysia Kazakhstan Thailand Mexico Low mathematics performance
High mathematics performance 2012 Korea Strong socio-economic impact on student performance Slovak Rep. Switzerland Japan Netherlands Estonia Poland Belgium Canada Finland Germany Denmark Austria New Zealand Australia Slovenia Ireland Czech Rep. Iceland France UK Luxembourg Norway Portugal Italy US Spain Sweden Hungary Socially equitable distribution of learning opportunities Israel Greece Turkey Chile Low mathematics performance Mexico
High mathematics performance Korea Strong socio-economic impact on student performance Slovak Rep. Switzerland Japan Netherlands Estonia Poland Belgium Canada Finland Germany Denmark Austria New Zealand Australia Slovenia Ireland Czech Rep. Iceland France UK Luxembourg Norway Portugal Italy US Spain Sweden Hungary Socially equitable distribution of learning opportunities Israel Greece Turkey Chile Low mathematics performance Mexico
Portugal Contribution of various factors to upper secondary teacher compensation costs, per student as a percentage of GDP per capita (2004) Spain Switzerland Belgium Korea Luxembourg Germany Greece Japan Australia United Kingdom New Zealand France Netherlands Denmark Italy Austria Czech Republic Hungary Norway Iceland Ireland Mexico Finland Sweden United States Poland Slovak Republic Salary as % of GDP/capita Instruction time 1/teaching time 1/class size Difference with OECD average 15 Percentage points 10 5 0-5 -10
15 or less 16-20 21-25 26-30 31-35 36 or more None 1% to 10% 11% to 30% 31% or more Teacher job satisfaction (level) Teacher job satisfaction (level) 20 Behavioural issues equate to lower job satisfaction, class size doesn t Mean mathematics performance, by school location, after acc ounting for socio-economic status Teachers' job satisfaction level following the number of students in the classroom in relation to the percentage of students with behavioural problems Fig II.3.3 13.0 Average 13.0 Average 12.5 12.5 12.0 12.0 11.5 11.5 11.0 11.0 10.5 10.5 10.0 10.0 Class size (number of students) Students with behavioural problems
High mathematics performance Korea Strong socio-economic impact on student performance Slovak Rep. Switzerland Japan Netherlands Estonia Poland Belgium Canada Finland Germany Denmark Austria New Zealand Australia Slovenia Ireland Czech Rep. Iceland France UK Luxembourg Norway Portugal Italy US Spain Sweden Hungary Socially equitable distribution of learning opportunities Israel Greece Turkey Chile Low mathematics performance Mexico
High mathematics Shanghaiperformance 2003-2012 Singapore Singapore Korea Strong socio-economic impact on student performance Slovak Rep. Switzerland Japan Netherlands Estonia Poland Belgium Canada Finland Germany Denmark Austria New Zealand Australia Slovenia Ireland Czech Rep. Iceland France UK Luxembourg Norway Portugal Italy US Spain Sweden Hungary Socially equitable distribution of learning opportunities Israel Greece Turkey Chile Turkey 2003 Chile 2003 Low mathematics performance Mexico
24 Why poverty need not be destiny It s not just about poor kids in poor neighborhoods but about many kids in many neighborhoods The country where students go to class matters more than what social class students come from
Mexico Chile Greece Norway Sweden Iceland Israel Italy United States Spain Denmark Luxembourg Australia Ireland United Kingdom Hungary Canada Finland Austria Turkey Liechtenstein Czech Republic Estonia Portugal Slovenia Slovak Republic New Zealand Germany Netherlands France Switzerland Poland Belgium Japan Macao-China Hong Kong-China Korea Singapore Chinese Taipei Shanghai-China 300 325 350 375 400 425 450 475 500 525 550 575 600 625 650 675 25 PISA mathematics performance by decile of social background Source: PISA 2012
% students from disadvantaged backgrounds the percentage of students with a value of ESCS lower than -1 Social background principal and students 60 Brazil Mexico 50 Size of bullet represents impact of social background on student performance Portugal Malaysia 40 Chile 30 Serbia Spain Latvia Bulgaria Romania 20 10 0 Singapore Italy Poland Slovak Republic Japan Korea Estonia Netherlands Norway Iceland Australia France Israel United States 0 10 20 30 40 50 60 70 % principals who reported that more than 30% of their students are from socioeconomically disadvantaged homes
Shanghai-China Singapore Chinese Taipei Hong Kong-China Korea Liechtenstein Macao-China Japan Switzerland Belgium Netherlands Germany Poland Canada Finland New Zealand Australia Estonia Austria Slovenia Viet Nam France Czech Republic OECD average United Kingdom Luxembourg Iceland Slovak Republic Ireland Portugal Denmark Italy Norway Israel Hungary United States Lithuania Sweden Spain Latvia Russian Federation Croatia Turkey Serbia Bulgaria Greece United Arab Emirates Romania Thailand Qatar Chile Uruguay Malaysia Montenegro Kazakhstan Albania Tunisia Brazil Mexico Peru Costa Rica Jordan Colombia Indonesia Argentina 27 % 60 Percentage of top performers in mathematics Tab I.2.1a 50 40 30 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 Massachusetts Connecticut Florida 0
28 Why care about advanced skills? % 25 Evolution of employment in occupational groups defined by PIAAC problem-solving skills 20 15 10 Employment of workers with advanced problem-solving skills 5 0-5 -10-15 Employment of workers with medium-low problem-solving skills (PIAAC) Employment of workers with poor problem-solving skills -20 Source:PIAAC 2011
29 Math teaching math teaching PISA = reason mathematically and understand, formulate, employ and interpret mathematical concepts, facts and procedures
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 30 Focus on word problems Fig I.3.1a 2.50 2.00 1.50 1.00 Formal math situated in a word problem, where it is obvious to students what mathematical knowledge and skills are needed 0.50 0.00
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 Index of exposure to formal mathematics 31 Focus on conceptual understanding Fig I.3.1b 2.50 2.00 1.50 1.00 0.50 0.00
Lessons from high performers Low impact on outcomes 32 Must haves High impact on outcomes Quick wins Catching up with the top-performers Low feasibility High feasibility Money pits Low hanging fruits
Lessons from high performers Low impact on outcomes 33 Must haves High impact on outcomes Commitment to universal achievement Quick wins Capacity at point of delivery Low feasibility Coherence Resources where they yield most A learning system Gateways, instructional systems High feasibility Incentive structures and accountability Money pits Low hanging fruits
Lessons from high performers Low impact on outcomes 34 Low feasibility High impact on outcomes A commitment Must haves to education and the belief that Quick wins Commitment to universal achievement competencies can be learned and therefore all children can achieve Capacity at point Universal of delivery educational standards and Resources personalization as the approach to heterogeneity where in the they student yield body most 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 heterogeneity Coherence A learning system Clear articulation who is responsible for ensuring student success and to whom High feasibility Incentive structures and accountability Money pits Low hanging fruits
Countries where students have stronger beliefs Fig III.4.5 35 in their abilities perform better in mathematics Mean mathematics performance OECD average Mean index of mathematics self-efficacy 650 Shanghai-China 600 550 500 450 400 350 Singapore Hong Kong-China Korea Chinese Taipei Japan Macao-China Switzerland NetherlandsEstonia Finland Canada Liechtenstein Belgium Poland Germany Viet Nam Denmark Slovenia New Zealand Latvia Italy Portugal Austria Australia Russian Fed. Hungary Croatia Luxembourg Greece Slovak Republic Spain Turkey Israel Sweden Norway Serbia Lithuania Czech Republic U.A.E. United Kingdom Thailand Malaysia Romania Iceland Chile Bulgaria Kazakhstan Ireland United States Montenegro France Costa Rica Brazil Uruguay Mexico Albania Argentina Tunisia Colombia Qatar Jordan Indonesia Peru R² = 0.36 300-0.60-0.40-0.20 0.00 0.20 0.40 0.60 0.80 1.00 1.20
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: France 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 20 40 60 80 100 %
Colombia Costa Rica Peru Israel Luxembourg Chile Tunisia Slovak Republic Liechtenstein Italy Korea Spain Argentina Brazil Portugal Greece Japan Austria Uruguay Mexico Hong Kong-China Bulgaria Turkey Indonesia Hungary Viet Nam United States Romania U.A.E. Chinese Taipei Canada Ireland Belgium Kazakhstan Czech Republic OECD average Croatia France Shanghai-China Montenegro Poland Serbia Malaysia Estonia Qatar Macao-China Netherlands New Zealand Norway Lithuania Slovenia Denmark Jordan Switzerland Australia Germany Latvia Russian Fed. Sweden Singapore United Kingdom Thailand Finland Iceland Score-point difference (boys-girls) Greater self-efficacy among girls could shrink the gender gap in mathematics Fig III.7.12 37 performance, particularly among the highest-performing students Gender gap among the highest-achieving students (90th percentile) 40 Gender gap adjusted for differences in mathematics self-efficacy between boys and girls Gender gap 30 Boys do better 20 10 0-10 Girls do better -20
Turkey Jordan * Costa Rica * Thailand Kazakhstan * Iceland Shanghai-China * Viet Nam Albania * United Arab Emirates * Qatar Malaysia * Norway Israel Cyprus Indonesia * Portugal * Colombia Japan Netherlands Croatia Latvia Uruguay Argentina Denmark Peru Mexico Tunisia Estonia Chile Liechtenstein Macao-China Poland Luxembourg France Spain Italy Sweden Belgium United States Czech Republic Chinese Taipei Singapore OECD average Slovenia Canada Greece Lithuania Bulgaria Switzerland Finland United Kingdom Slovak Republic Romania Russian Federation Austria Montenegro Brazil Ireland Germany Hong Kong-China Australia New Zealand Serbia Korea Hungary Percentage of girls and boys who intend to take additional mathematics, rather than language, courses after they leave school % 90 80 70 60 50 40 30 20 10 0 Girls Boys
Lessons from high performers Low impact on outcomes 39 Capacity at point of delivery Low feasibility Coherence High impact on outcomes Must haves Quick wins Commitment to universal achievement Clear ambitious goals that are shared across the system and aligned with Resources high stakes gateways and instructional systems where they yield most Well established delivery chain Gateways, through instructional which curricular goals translate into instructional systems systems, instructional practices and student learning (intended, implemented and A learning achieved) system High level of metacognitive content of instruction High feasibility Incentive structures and accountability Money pits Low hanging fruits
Lessons from high performers Low impact on outcomes 40 Capacity at the point of delivery Must haves High impact on outcomes Quick wins Attracting, developing and retaining high quality teachers and school Commitment leaders and to a work universal organisation achievement in which they can use their potential Capacity Instructional leadership and human resource at point of delivery Resources 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
Mean mathematics performance, by school location, after acc 41 Capacity at ounting the for point socio-economic of delivery status Improve the societal view of teaching as a profession Recruit top candidates into the profession Developing Teaching as a profession Retain and recognise effective teachers path for growth Support teachers in continued development of practice
Malaysia Singapore Korea Abu Dhabi (UAE) Finland Mexico Alberta (Canada) Flanders (Belgium) Netherlands Australia England (UK) Romania Israel United States Chile Average Norway Japan Latvia Serbia Bulgaria Denmark Poland Iceland Estonia Brazil Italy Czech Republic Portugal Croatia Spain Sweden France Slovak Republic Percentage of teachers 42 Mean mathematics performance, by school location, after accounting for socio-economic status 42 Teachers' perceptions of the value of teaching Fig II.3.3 Percentage of lower secondary teachers who "agree" or "strongly agree" that teaching profession is a valued profession in society 100 90 80 70 60 50 40 30 20 10 0
Share of mathematics top performers 43 Countries Mean mathematics where teachers performance, believe by school their profession location, is valued show after higher accounting levels of for student socio-economic achievement status Fig II.3.3 Relationship between lower secondary teachers' views on the value of their profession in society and the country s share of top mathematics performers in PISA 2012 45 40 Singapore 35 30 Korea 25 Japan Flanders (Belgium) R 2 = 0.24 r= 0.49 20 15 10 5 0 Poland Netherlands Estonia France Australia Czech Republic England (UK) Slovak Republic Italy Iceland Portugal Norway Israel Sweden Spain Denmark Latvia United States Croatia Serbia Bulgaria Romania Chile Brazil Alberta (Canada) Finland Mexico 0 10 20 30 40 50 60 70 80 Percentage of teachers who agree that teaching is valued in society
Teacher skills and graduate skills (numeracy) Japan Finland Flanders (Belgium) Germany Norway Netherlands Austria Czech Republic Sweden Australia France Slovak Republic Northern Ireland (UK) Denmark England/N. Ireland (UK) England (UK) Korea Ireland Canada United States Estonia Poland Italy Middle half of the numeracy skill distribution of graduates (16-65 years) 230 250 270 290 310 330 350 PIAAC test scores (numeracy)
Teacher skills and graduate skills (numeracy) Japan Finland Flanders (Belgium) Germany Norway Netherlands Austria Czech Republic Sweden Australia France Slovak Republic Northern Ireland (UK) Denmark England/N. Ireland (UK) England (UK) Korea Ireland Canada United States Estonia Poland Italy Middle half of the numeracy skill distribution of graduates (16-65 years) Numeracy skills of teachers 230 250 270 290 310 330 350 PIAAC test scores (numeracy)
Never Once a year or less 2-4 times a year 5-10 times a year 1-3 times a month Once a week or more Teacher self-efficacy (level) 46 Mean mathematics performance, by school location, after accounting for socio-economic status 46 Teachers Self-Efficacy and Professional Collaboration Fig II.3.3 13.40 13.20 13.00 12.80 12.60 12.40 Teach jointly as a team in the same class Observe other teachers classes and provide feedback 12.20 12.00 11.80 11.60 11.40 Engage in joint activities across different classes Take part in collaborative professional learning
Discuss individual students Share resources Team conferences Collaborate for common standards Team teaching Collaborative PD Joint activities Classroom observations Percentage of teachers 47 Teacher co-operation Percentage of lower secondary teachers who report doing the following activities at least once per month 100 90 80 Exchange and co-ordination Average United States Professional collaboration 70 60 50 40 30 20 10 0
Mean mathematics performance, by school location, after acc ounting for socio-economic status 48 Teachers' needs for professional development Fig II.3.3 Percentage of lower secondary teachers indicating they have a high level of need for professional development in the following areas United States Average Teaching students with special needs ICT skills for teaching New technologies in the workplace Student behaviour and classroom management Teaching in a multicultural or multilingual setting Approaches to individualised learning Student career guidance and counselling Student evaluation and assessment practice Teaching cross-curricular skills Developing competencies for future work Pedagogical competencies School management and administration Knowledge of the subject field(s) Knowledge of the curriculum 0 5 10 15 20 25 30 35 40
Lessons from high performers Low impact on outcomes 49 Low feasibility Must haves Money pits High impact on outcomes Commitment to universal achievement Aligned incentive structures Capacity For students at point of delivery For teachers Coherence Resources where they yield most A learning system Quick wins Incentives, accountability, knowledge management How gateways affect the strength, direction, clarity and nature of the incentives operating on students at each stage of their education Degree to which students have incentives to take tough courses and study hard Opportunity costs for staying in school and performing well Make innovations in pedagogy and/or organisation Improve their own performance and the performance of their colleagues Pursue professional development opportunities that lead to stronger pedagogical practices Gateways, instructional systems Low hanging fruits 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 A capable centre with authority and legitimacy to act
Lessons from high performers 50 50 Aligning autonomy with accountability
Mathematics performance (score points) Lessons from high performers 51 51 Countries that grant schools autonomy over curricula and assessments tend to perform better in mathematics 650 Shanghai-China 600 550 500 450 400 Chinese Taipei Viet Nam Korea Singapore Estonia Hong Kong-China Japan Latvia Poland Slovenia Czech Rep. Switzerland Belgium Canada Portugal Germany Finland New Zealand Lithuania Croatia Austria Hungary Netherlands Serbia Spain France Australia Italy UK Turkey Norway Macao-China Greece Bulgaria Denmark Iceland Thailand Kazakhstan Romania Slovak Rep. R² = 0.13 Israel Malaysia Uruguay USA Sweden Chile Jordan Costa Rica Brazil Indonesia Luxembourg Tunisia Albania Colombia UAE Argentina Peru 350 Qatar 300-1.5-1 -0.5 0 0.5 1 1.5 Index of school responsibility for curriculum and assessment (index points) 51 Source: PISA 2012
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 485 480 475 470 465 460 455 Less school autonomy Shared math policy No shared math policy More school autonomy
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 478 476 474 472 470 468 466 464 School data public Less school autonomy School data not public More school autonomy
Schools with more autonomy perform better than schools with less autonomy in systems with more collaboration Fig IV.1.17 School autonomy for resource allocation x System's level of teachers participating in school management Across all participating countries and economies 485 Score points 480 475 470 465 460 455 Less school autonomy Teachers participate in management Teachers don't participate in management More school autonomy
55 Quality assurance and school improvement Fig IV.4.14 ercentage 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 0 20 40 60 80 100 %
Lessons from high performers Low impact on outcomes 56 High impact on outcomes Must haves Quick wins Commitment to universal achievement Investing resources where they can make most of a difference Capacity at point of delivery Alignment of resources Resources with key challenges (e.g. attracting the most where talented they yield teachers 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
Mathematics performance (score points) 57 Align the resources with the challenges 700 650 Countries with better performance in mathematics tend to allocate educational resources more equitably Shanghai-China 600 550 500 450 400 Costa Rica Peru Mexico Chinese Taipei Viet Nam Korea Singapore R² = 0.19 Hong Kong-China Estonia Japan Poland Switzerland Slovenia Canada Latvia Finland Belgium Macao-China Germany New Zealand Ireland Iceland France Slovak UK Rep. Austria Australia Denmark Romania Croatia USA Turkey Sweden Israel Spain Hungary Greece Bulgaria Portugal Italy Norway Thailand Serbia Chile Malaysia Uruguay Kazakhstan Brazil Jordan Indonesia UAE Montenegro Colombia Argentina Tunisia Luxembourg 350 300 1.5 1 Qatar 0.5 Adjusted by per capita GDP 0-0.5 Less equity Equity in resource allocation (index points) Greater equity Source: PISA 2012
Korea Estonia Israel Latvia Slovenia Italy Poland Singapore Argentina Netherlands Portugal Colombia France Finland Tunisia Macao-China Spain Greece Switzerland Norway Russian Fed. Japan Austria Montenegro Croatia Canada OECD average Germany Denmark Hungary United Kingdom Luxembourg Hong Kong-China Belgium Iceland Viet Nam Ireland United States Chile Czech Republic Serbia Turkey Mexico Indonesia Uruguay Shanghai-China Slovak Republic Sweden Brazil New Zealand Australia Chinese Taipei Mean index difference 58 Adequate resources to address disadvantage 1.5 A shortage of qualified teachers is more of concern in disadvantaged schools Difference between socio-economically disadvantaged and socio-economically advantaged schools 1.3 1.1 0.9 0.7 Disadvantaged schools reported more teacher shortage 0.5 0.3 0.1-0.1-0.3 Advantaged schools reported more teacher shortage -0.5
Lessons from high performers Low impact on outcomes 59 Must haves High impact on outcomes Commitment to universal achievement Quick wins 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 Low feasibility Consistency of implementation Fidelity of implementation (without excessive control) Resources where they yield most A learning system Gateways, instructional systems High feasibility Incentive structures and accountability Money pits Low hanging fruits
Lessons from high performers Low impact on outcomes 60 Must haves High impact on outcomes Commitment to universal achievement Quick wins Capacity at point of delivery Low feasibility Coherence Resources where they yield most A learning system Gateways, instructional systems High feasibility Incentive structures and accountability Money pits Low hanging fruits
Lessons from high performers 61 What it all means The old bureaucratic system Student inclusion The modern enabling system Some students learn at high levels All students need to learn at high levels Curriculum, instruction and assessment Routine cognitive skills Conceptual understanding, complex ways of thinking, ways of working Teacher quality Standardisation and compliance High-level professional knowledge workers Work organisation Tayloristic, hierarchical Flat, collegial Accountability Primarily to authorities Primarily to peers and stakeholders
Lessons from high performers 62 62 Thank you Find out more about our work at www.oecd.org All publications The complete micro-level database Email: Andreas.Schleicher@OECD.org Twitter: SchleicherEDU and remember: Without data, you are just another person with an opinion 62