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Improving equity in Sweden
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This presentation by Andreas Schleicher, presented on 3 April 2017, takes a closer look at the PISA 2015 results for Sweden and what can be done to improve equity in its education system.
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Improving equity in Sweden
- OECD EMPLOYER BRAND Playbook 11 Improving equity in Sweden Andreas Schleicher 3 April 2017
- The context The rise in non-standard work contributed to higher inequality. 33% It is not only about poverty, it is about the bottom 40%. High wealth concentration limits investment opportunities. Rising inequality drags down economic growth. Social mobility is lowered. More women in the workforce means less household income inequality Inequality has reached record highs in most OECD countries
- Trends in science performance (PISA) 2006 2009 2012 2015 OECD 450 470 490 510 530 550 570 OECD average Studentperformance
- Trends in science performance (PISA) 450 470 490 510 530 550 570 2006 2009 2012 2015 OECD average
- Singapore Japan EstoniaChinese Tapei Finland Macao (China) CanadaViet Nam Hong Kong (China)B-S-J-G (China) KoreaNew ZealandSlovenia Australia United KingdomGermany Netherlands Switzerland Ireland Belgium DenmarkPolandPortugal NorwayUnited StatesAustriaFrance Sweden Czech Rep. Spain Latvia Russia Luxembourg Italy Hungary LithuaniaCroatia Iceland IsraelMalta Slovak Rep. Greece Chile Bulgaria United Arab EmiratesUruguay Romania Moldova Turkey Trinidad and Tobago ThailandCosta Rica QatarColombia Mexico MontenegroJordan Indonesia Brazil Peru Lebanon Tunisia FYROM Kosovo Algeria Dominican Rep. (332) 350 400 450 500 550 Meanscienceperformance Higherperfomance Science performance and equity in PISA (2015) Some countries combine excellence with equity High performance High equity Low performance Low equity Low performance High equity High performance Low equity More equity
- Students expecting a career in science Figure I.3.2 0 5 10 15 20 25 30 35 40 45 50 DominicanRep.12 CostaRica11 Jordan6 UnitedArabEm.11 Mexico6 Colombia8 Lebanon15 Brazil19 Peru7 Qatar19 UnitedStates13 Chile18 Tunisia19 Canada21 Slovenia16 Turkey6 Australia15 UnitedKingdom17 Malaysia4 Kazakhstan14 Spain11 Norway21 Uruguay17 Singapore14 TrinidadandT.13 Israel25 CABA(Arg.)19 Portugal18 Bulgaria25 Ireland13 Kosovo7 Algeria12 Malta11 Greece12 NewZealand24 Albania29 Estonia15 OECDaverage19 Belgium16 Croatia17 FYROM20 Lithuania21 Iceland22 Russia19 HKG(China)20 Romania20 Italy17 Austria23 Moldova7 Latvia19 Montenegro18 France21 Luxembourg18 Poland13 Macao(China)10 ChineseTaipei21 Sweden21 Thailand27 VietNam13 Switzerland22 Korea7 Hungary22 SlovakRepublic24 Japan18 Finland24 Georgia27 CzechRepublic22 B-S-J-G(China)31 Netherlands19 Germany33 Indonesia19 Denmark48 % Percentage of students who expect to work in science-related professional and technical occupations when they are 30 Science-related technicians and associate professionals Information and communication technology professionals Health professionals Science and engineering professionals %ofstudentswithvag ueormissingexpectati ons
- Singapore Canada Slovenia Australia United Kingdom Ireland Portugal Chinese Taipei Hong Kong (China) New Zealand Denmark Japan Estonia Finland Macao (China) Viet Nam B-S-J-G (China) Korea Germany Netherlands Switzerland Belgium Poland Sweden Lithuania Croatia Iceland Georgia Malta United States Spain Israel United Arab Emirates Brazil Bulgaria Chile Colombia Costa Rica Dominican Republic Jordan Kosovo Lebanon Mexico Peru Qatar Trinidad and Tobago Tunisia Turkey Uruguay Above-average science performance Stronger than average beliefs in science Above-average percentage of students expecting to work in a science-related occupation Norway Multipleoutcomes
- 0 10 20 30 40 50 300 400 500 600 700 Percentageofstudentsexpectinga careerinscience Score points in science Low enjoyment of science High enjoyment of science Students expecting a career in science by performance and enjoyment of learning Figure I.3.17
- Inequity in opportunity Outcomes
- Poverty is not destiny - Science performance by international deciles of the PISA index of economic, social and cultural status (ESCS) 280 330 380 430 480 530 580 630 DominicanRepublic40 Algeria52 Kosovo10 Qatar3 FYROM13 Tunisia39 Montenegro11 Jordan21 UnitedArabEmirates3 Georgia19 Lebanon27 Indonesia74 Mexico53 Peru50 CostaRica38 Brazil43 Turkey59 Moldova28 Thailand55 Colombia43 Iceland1 TrinidadandTobago14 Romania20 Israel6 Bulgaria13 Greece13 Russia5 Uruguay39 Chile27 Latvia25 Lithuania12 SlovakRepublic8 Italy15 Norway1 Spain31 Hungary16 Croatia10 Denmark3 OECDaverage12 Sweden3 Malta13 UnitedStates11 Macao(China)22 Ireland5 Austria5 Portugal28 Luxembourg14 HongKong(China)26 CzechRepublic9 Poland16 Australia4 UnitedKingdom5 Canada2 France9 Korea6 NewZealand5 Switzerland8 Netherlands4 Slovenia5 Belgium7 Finland2 Estonia5 VietNam76 Germany7 Japan8 ChineseTaipei12 B-S-J-G(China)52 Singapore11 Scorepoints Bottom decile Second decile Middle decile Ninth decile Top decile Figure I.6.7 % of students in the bottom international deciles of ESCS OECD median student
- 300 350 400 450 500 550 600 650 700 -1 -0.5 0 0.5 1 1.5 PISA index of economic, social and cultural status Public schools Private schools Relationship between school performance and schools’ socio-economic profile Scorepoints
- -100 -80 -60 -40 -20 0 20 40 60 Turkey Singapore VietNam Japan Tunisia Italy ChineseTaipei Thailand Greece Switzerland CzechRepublic UnitedStates Estonia Uruguay France Austria CABA(Argentina) Kosovo Mexico HongKong(China) Indonesia Luxembourg Sweden Hungary Malta DominicanRepublic Latvia OECDaverage B-S-J-G(China) Portugal Slovenia Spain UnitedKingdom SlovakRepublic Norway Australia Croatia Denmark Peru Jordan CostaRica Colombia Chile Netherlands Korea NewZealand Canada Lithuania Ireland Georgia TrinidadandTobago FYROM Germany Finland Lebanon Belgium Poland Brazil UnitedArabEmirates Qatar Score-pointdifference After accounting for socio-economic status Before accounting for socio-economic status Public and private schools, and students’ science performance Figure II.4.14 Students in private schools perform better Students in public schools perform better
- Variation in science performance between and within schools Figure I.6.11 120 100 80 60 40 20 0 20 40 60 80 Netherlands114 B-S-J-G(China)119 Bulgaria115 Hungary104 TrinidadandTobago98 Belgium112 Slovenia101 Germany110 SlovakRepublic109 Malta154 UnitedArabEmirates110 Austria106 Israel126 Lebanon91 CzechRepublic101 Qatar109 Japan97 Switzerland110 Singapore120 Italy93 ChineseTaipei111 Luxembourg112 Turkey70 Brazil89 Croatia89 Greece94 Chile83 Lithuania92 OECDaverage100 Uruguay84 CABA(Argentina)82 Romania70 VietNam65 Korea101 Australia117 UnitedKingdom111 Peru66 Colombia72 Thailand69 HongKong(China)72 FYROM80 Portugal94 DominicanRepublic59 Indonesia52 Georgia92 Jordan79 NewZealand121 UnitedStates108 Montenegro81 Tunisia47 Sweden117 Mexico57 Albania69 Kosovo57 Macao(China)74 Algeria54 Estonia88 Moldova83 CostaRica55 Russia76 Canada95 Poland92 Denmark91 Latvia75 Ireland88 Spain86 Norway103 Finland103 Iceland93 % Between-school variation Within-school variation Total variation as a proportion of the OECD average OECD average 69% OECD average 30% 6 percentage point rise since 2006 38% of between-school performance variation due to social background (OECD 27%)
- Declining overall performance between 2006 and 2012 Rising social inequality (biggest rise after Finland and Korea) Growing share of low performers (+5.3%) Rising between-school variation Declining academic inclusion (-5.6) (biggest drop after Israel) Some improvement in learning outcomes since 2012
- Inequity in opportunity Resources
- Spending per student from the age of 6 to 15 and science performance Figure II.6.2 Luxembourg Switzerland NorwayAustria Singapore United States United Kingdom Malta Sweden Belgium Iceland Denmark Finland Netherlands Canada Japan Slovenia Australia Germany Ireland FranceItaly Portugal New Zealand Korea Spain Poland Israel Estonia Czech Rep. LatviaSlovak Rep. Russia Croatia Lithuania Hungary Costa Rica Chinese Taipei Chile Brazil Turkey Uruguay Bulgaria Mexico Thailand Montenegro Colombia Dominican Republic Peru Georgia 11.7, 411 R² = 0.01 R² = 0.41 300 350 400 450 500 550 600 0 20 40 60 80 100 120 140 160 180 200 Scienceperformance(scorepoints) Average spending per student from the age of 6 to 15 (in thousands USD, PPP)
- Differences in educational resources between advantaged and disadvantaged schools Figure I.6.14 -3 -2 -2 -1 -1 0 1 1 CABA(Argentina) Mexico Peru Macao(China) UnitedArabEmirates Lebanon Jordan Colombia Brazil Indonesia Turkey Spain DominicanRepublic Georgia Uruguay Thailand B-S-J-G(China) Australia Japan Chile Luxembourg Russia Portugal Malta Italy NewZealand Croatia Ireland Algeria Norway Israel Denmark Sweden UnitedStates Moldova Belgium Slovenia OECDaverage Hungary ChineseTaipei VietNam CzechRepublic Singapore Tunisia Greece TrinidadandTobago Canada Romania Qatar Montenegro Kosovo Netherlands Korea Finland Switzerland Germany HongKong(China) Austria FYROM Poland Albania Bulgaria SlovakRepublic Lithuania Estonia Iceland CostaRica UnitedKingdom Latvia Meanindexdifferencebetweenadvantaged anddisadvantagedschools Index of shortage of educational material Index of shortage of educational staff Disadvantaged schools have more resources than advantaged schools Disadvantaged schools have fewer resources than advantaged schools UK England: Pupil Premium (2011) Netherlands: School funding formulae; sensitive to socio- economic background students
- -40 -30 -20 -10 0 10 Staff resisting change Teachers being too strict with students Teachers not meeting individual students’ needs Teacher absenteeism Teachers not being well prepared for classes Student use of alcohol or illegal drugs Students intimidating or bullying other students Students skipping classes Student truancy Students lacking respect for teachers Score-pointdifference After accounting for students' and schools' socio-economic profile Before accounting for students' and schools' socio-economic profile Student and teacher behaviour hindering learning and science performance Figure II.3.10
- -20 0 20 40 60 80 100 -10 0 10 20 30 40 50 UnitedArabEmirates CABA(Argentina) Malta Lebanon Uruguay DominicanRepublic Jordan Mexico Qatar Spain Brazil Peru Colombia Chile Singapore Australia B-S-J-G(China) Japan VietNam Greece Israel Georgia TrinidadandTobago Russia HongKong(China) Ireland Kosovo Denmark FYROM Montenegro France Portugal Austria Switzerland Sweden OECDaverage UnitedStates Hungary Belgium Netherlands Macao(China) Korea Finland Slovenia Moldova Latvia Thailand SlovakRepublic Algeria Italy UnitedKingdom Germany Tunisia Canada Luxembourg Turkey Iceland Indonesia Lithuania CzechRepublic Estonia NewZealand Romania Bulgaria Croatia ChineseTaipei Poland Norway CostaRica Percentage-pointdifference %Percentage-point difference between advantaged and disadvantaged schools Index of school autonomy (%) Index of school autonomy, by schools’ socio-economic status Figure II.4.7 Advantaged schools have more school autonomy Disadvantaged schools have more school autonomy
- Challenges 15% migrant background > OECD 11.2% High concentration in disadvantaged schools (23%) • Cannot explain decline in Sweden overall results. Policies in place: Swedish reception classes; additional $$; NAE programmes Funding is unequal partly due to decentralisation.
- Policy responses • to ensure that they are effectively targeted to education and respond to equity and quality objectives, Review current funding mechanisms • are evaluated and followed up for effectiveness. Ensure funding strategies • to local authorities to enhance their capacity to design and deliver programmes that target equity. Provide support
- • The type of mechanism used reflects the degree of budget autonomy given to the different administration levels and given policy priorities. Funding of school education can be : – Specified for particular purposes [Earmarked grants] (e.g., teacher salaries, support for students with SEN, transportation to school) – Weighted student funding schemes are based on two main elements: funding follows the student on a per-student basis and this amount depends on the social characteristics and educational needs of each student – Discretion of lower levels of administration, as long as they are dedicated to specific cost types [Block grants and restricted block grants] (e.g., non-teacher staff salaries, operating costs) – Discretion of lower levels of administration that decide how to allocate funds to other levels of administration/ schools [Lump sum transfer] • Allocation mechanisms relying on transparent funding formulas can play a critical role in promoting greater efficiency and equity Countries use a mix of various allocation mechanisms
- Establish guiding principles when designing funding formulas to distribute resources to individual schools Align funding formulas with government policy and establish evaluation criteria accordingly (e.g., efficiency, equity, transparency, sensitivity to local conditions) Reflect different per student costs in the provision of education, while addressing equity challenges (allocate funds weighing additional costs of specific educational provision or location, student supplementary needs) Set incentives for budgetary discipline Ensure periodic review and evaluation of funding formulas Some principles
- • Manage the risks of needs-based or input allocation mechanisms – Avoid excessive labelling of students (can be stigmatising for individuals and lead to cost inflation) – Apply transparent and impartial criteria for assessing students having physical/learning impairments – Incentivise school boards and school communities to scrutinise provision for students with SEN and its impact on their learning • Share experience about funding formulas developed at sub-national levels for system learning – Avoid duplication of efforts by sharing knowledge – Identify and promote best practices in funding allocation across the system, through central-level initiatives Some principles
- Inequity in opportunity Policy and practice
- Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.3 Australia Austria Belgium Canada Chile Czech Rep. Denmark Estonia Finland GermanyGreece Hungary Iceland Ireland Israel Italy JapanKorea Luxembourg Mexico Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK USA R² = 0.1735 30 40 50 60 70 80 90 100 School competition More social inclus Less social inclusion % School competition and social inclusion, PISA 2012School choice and social inclusion
- 2 7 27 Square school choice with equity Financial incentives for schools Assistance for disadvantaged parents Controlled choice Financial incentives Inform parents Foster collaboration among teachers and schools Use student and school assessments
- • Schools practicing selective admission tend to attract students with higher ability and socio-economic status, regardless of their educational quality • Given that high-ability students are less costly to educate and can increase a school’s attractiveness to parents, controlling their intake can provide schools with a competitive advantage – Allowing private schools to select their students therefore provides them with an incentive to compete on the basis of exclusiveness rather than their value added, which can undermine the dynamics of competition diminish the positive effects it may otherwise have on quality. • Selective admission also a source of increased stratification. Selective admission
- • Student sorting occurs not only based on explicit admission criteria but also based on parental self- selection, selective expulsion and more subtle barriers to entry. – Policies seeking to reduce segregation should therefore also identify and address overly complex application procedures, expulsion practices, information deficits and other factors that prevent some students from exercising school choice. Selective admission
- • Across 18 education systems where parents in PISA were asked why they choose a school parents were more likely to consider important or very important that: – there is a safe school environment, that the school has a good reputation and that the school has an active and pleasant climate – even more so than the academic achievement of the students in the school. Parental choice – outcomes often don’t come first
- • Parents whose children attended disadvantaged schools considered distance more important – And children of parents who assigned more importance to distance scored lower in PISA • Students whose parents considered low expenses important scored worse – And in most countries the parents of children attending disadvantaged and public schools were more likely to consider low expenses important Parental choice – social background matters
- Challenges for Sweden Open school choice : first come first served. Growing segregation no better results. Free schools not fully integrated in education planning.
- 37 Revise school-choice arrangements • to ensure a more diverse distribution of students in schools. Introduce controlled choice schemes • To encourage a culture of collaboration and peer learning, consider defining national guidelines to ensure that municipalities integrate independent schools in their planning, improvement and support strategies. National guidelilnes • about schools and support them in making informed choices Improve access to information
- • As of 2009, 9 out of 22 OECD countries with available data facilitated the attendance of government- dependent private primary schools with vouchers. – In five of these, the voucher programme was restricted to students with lower socio-economic background. • At the lower secondary level, 11 out of 24 countries reported to operate voucher schemes, – 7 of which targeted disadvantaged students. Voucher policies
- • Vouchers that are available for all students can help to expand the choice of schools available to parents and promote competition among schools. • School vouchers that target only disadvantaged students can help improve equity in access to schools. • PISA data show that, when comparing systems with similar levels of public funding for privately managed schools, the difference between the socio- economic profiles of publicly managed schools and privately managed schools is twice as large in education systems that use universal vouchers as in systems that use targeted vouchers • Regulating private school pricing and admission criteria seem to have a positive impact on the ability of voucher schemes to go hand in hand with limited social inequity Impact of voucher policies
- Examples of systems with high levels of school choice • Parents and students get to choose up to four schools from a list of schools in their geographical area. • Inter-Network Enrolment Commission, steers the selection process, allocates students according to their priorities, and weighted geographical and educational criteria. • Awards 80% of the places by the ranking, while ensuring that the remaining places are awarded to students from disadvantaged primary schools. Flanders •National Knowledge Centre for Mixed Schools produces knowledge & provides procedures for school choice and information to parents •.In Nijmegen, central subscription system to assign students for primary schools, to reach 30% of disadvantaged students in each school. Primary schools have central subscription system, based on the distribution of students. •In case of oversubscription, priority is given to siblings and proximity. To reach the required balance, subsequent priority is given to either advantaged or disadvantaged students by a lottery system. Netherlands •Government-dependent private schools cannot select students based on academic or socio-economic criteria until the end of primary education •Complemented with a weighted voucher system, providing an extra per-student subsidy for disadvantaged students. Chile
- 41 41 Thank you Find out more about our work at www.oecd.org/edu – All publications – The complete micro-level database Discover PISA 2015 results by country www.compareyourcountry.org/pisa Email: Andreas.Schleicher@OECD.org Twitter: SchleicherOECD
- Student-teacher ratios and class size Figure II.6.14 CABA (Argentina) Jordan Viet Nam Poland United States Chile Denmark Hungary B-S-G-J (China) Turkey Georgia Chinese Taipei Mexico Russia Albania Hong Kong (China) Japan Belgium Algeria Colombia Peru Macao (China) Switzerland Malta Dominican Republic Netherlands Singapore Brazil Kosovo Finland Thailand R² = 0.25 5 10 15 20 25 30 15 20 25 30 35 40 45 50 Student-teacherratio Class size in language of instruction High student-teacher ratios and small class sizes Low student-teacher ratios and large class sizes OECD average OECDaverage
- Quality assurance and improvement actions at school: evaluations Figure II.4.27 20 30 40 50 60 70 80 90 100 UnitedArabEmirates Thailand Montenegro FYROM Russia Singapore Romania Portugal UnitedKingdom Qatar NewZealand Albania Luxembourg Latvia Moldova Bulgaria Ireland HongKong(China) Iceland ChineseTaipei Croatia Poland Indonesia Estonia Colombia Malta Israel Brazil Korea Belgium Netherlands UnitedStates Kosovo DominicanRepublic Australia Lithuania Jordan B-S-J-G(China) Turkey Macao(China) Chile Japan Hungary OECDaverage TrinidadandTobago Mexico Spain VietNam Germany Georgia Denmark Peru Tunisia Switzerland Sweden Norway Canada CostaRica SlovakRepublic CzechRepublic CABA(Argentina) France Finland Lebanon Algeria Slovenia Uruguay Austria Italy Greece % Internal evaluation/Self-evaluation External evaluation
- Quality assurance and improvement actions at school: Feedback from students and teacher mentoring Figure II.4.27 20 30 40 50 60 70 80 90 100 Singapore Russia Montenegro Qatar Indonesia SlovakRepublic Thailand Jordan UnitedKingdom Peru Estonia VietNam Australia UnitedArabEmirates NewZealand Algeria Israel Albania UnitedStates Moldova CzechRepublic B-S-J-G(China) Croatia Korea FYROM Poland Kosovo Romania Tunisia Brazil Norway Macao(China) Malta ChineseTaipei Netherlands Greece Canada CABA(Argentina) Portugal TrinidadandTobago Ireland HongKong(China) Japan Lebanon Slovenia Belgium Hungary Luxembourg DominicanRepublic Latvia Sweden OECDaverage Colombia Switzerland Austria France Bulgaria CostaRica Uruguay Finland Denmark Turkey Mexico Lithuania Chile Georgia Spain Germany Italy Iceland % Teacher mentoring Seeking written feedback from students
Editor's Notes
- We did our last PISA assessment of learning outcomes in science in 2006, and it was a quite different world then. It is hard to imagine but we did not have the iphone then. Twitter was still a sound, Skype for most people was a typographical error in those times, the amazon was still a river, there was no android, no video streaming. But science learning outcomes in the industrialised world remained entirely flat during those years. And the world moved on, streetmaps became dynamic, cars became electric and started to drive automatically, drones started to fly, and crowdfunding hugely amplified the potential of each of us individually and of us collectively. But again, this did not translate into improved learning outcomes. And in just the last few years, so many things have happened, virtual reality brought the whole world to each of us in real time, 3D printers can produce right where we are, robotics is changing the lives of people, or think about big data, the cloud, biogenetics and our capacity to affect life as such. But science performance of students remained unfazed by all of this. When you see that, you might be tempted to drop the idea of improving education, as an agenda that is too big, too complex and too politically charged and too entrenched in vested interests to warrant real progress. But dont give up yet, the PISA data also show some amazing success stories.
- Portugal kept moving on from poor to adequate, despite a difficult financial crisis. Singapore kept advancing from good to great. The UK held its ground. So there is hope
- But then, doing well in science is only part of the story. Here you see the share of students who want to go on to a science career, so students who see science as opening life opportunities. And while students in Vietnam do well in science, they dont relate science to their future lives. So something is missing here. And the same is true for other high performing education systems too. Conversely, students in the United States are keen on a science career, but they dont have the skills to realise their dreams. So do we have to choose between good outcomes and strong motivation?
- The point is that we have to get several things right to speak of a good education. Success in science is about performance, but its also about having students trust in the methods of science And about students wanting to pursue science in their own lives. Singapore is a country that gets all of that right, and at a lower level you can see that also in … Chinese Taipei…
- Without confidence intervals
- Or consider this chart. Here you see student learning outcomes by decile of social background. The red square signals the performance of the 10% most disadvantaged students in the Dominican Republic, and the green triangle the performance of the 10% most privileged students in that country. So there is a big achievement gap in the Dominican Republic. And people who see this often conclude that poverty is simply destiny. But when you look at this across countries, you can see how students from similar social backgrounds show very different performance levels depending on the country where they go to school. Consider that the learning outcomes among the 10% most disadvantaged students in Viet Nam compared still favourably to the average student in the Western world. Consider that in most countries we find educational excellence among some of the most disadvantaged schools. And consider that many of the world’s leading education systems have not held this position since long. So it can be done.
- Policy action 1.4: Revise school choice arrangements to ensure quality with equity. Improve disadvantaged families’ access to information about schools and support them in making informed choices. In addition, introduce controlled choice schemes that combine parental choice and ensure a more diverse distribution of students at schools. Consider defining national guidelines to ensure that municipalities integrate independent schools in their planning, improvement and support strategies to encourage a culture of collaboration and peer learning.
- School choice is common in the Netherlands, with control applied at the local level to mitigate imbalances in school composition or weighted student funding to support greater social diversity in schools. In Nijmegen, a central subscription system to assign students exists for primary schools, to reach a share of 30% of disadvantaged students in each school. All the primary schools have agreed on a central subscription system, based on the distribution of students in different categories. In the event of oversubscription, priority is given to siblings and children who live nearby. In order to reach the required balance, subsequent priority is given to either advantaged or disadvantaged students by a lottery system (Musset, 2012). The National Knowledge Centre for Mixed Schools (Kenniscentrum Gemengde Scholen) produces knowledge and influences work on school choice. This centre also provides procedures for school choice and information on the topic to parents (OECD, 2015b). In the Netherlands, school budgets depend on enrolment and vary according to demand, but students from less privileged backgrounds receive more public money. This scheme was adopted for all primary schools in the Netherlands in 1985, and schools with substantial numbers of weighted students received more funds. Once the level of funding for each school is determined, based on the need of individual students, there is no requirement that schools use these extra resources directly for these students. They can, for example, choose to reduce the number of students per class. The weighting for each student is determined by his or her parents’ educational level (Musset, 2012). Empirical research conducted by Ladd and Fiske (2011) shows that this system succeeded in distributing differentiated resources to schools according to their different needs: primary schools with a high proportion of weighted students have, on average, about 58% more teachers per student, and also more support staff. Similarly, the Chilean education system adopted a weighted voucher system in 2008, providing an extra per-student subsidy for disadvantaged students. The voucher for children with low socio-economic status and indigenous children is 50% higher than for children that are not considered priority. Financing schemes like this provide the right type of incentives for schools to enrol more disadvantaged children and therefore reduce segregation. They can also mitigate the stratifying effects of unrestrained universal voucher programmes (Elacqua, 2009).
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