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Teacher Policy and Practice - Insights from PISA

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The Programme for International Student Assessment (PISA) is a triennial international survey which aims to evaluate education systems worldwide by testing the skills and knowledge of 15-year-old students.

In 2015 over half a million students, representing 28 million 15-year-olds in 72 countries and economies, took the internationally agreed two-hour test. Students were assessed in science, mathematics, reading, collaborative problem solving and financial literacy.

The results of the 2015 assessment were published on 6th December 2016.

Published in: Education

Teacher Policy and Practice - Insights from PISA

  1. 1. Teacher policy and practice Insights from PISA Andreas Schleicher Director for Education and Skills
  2. 2. PISA in brief - 2015 In 2015, over half a million students… - representing 28 million 15-year-olds in 72 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 - Total of 390 minutes of assessment material … and responded to questions on… - their personal background, their schools, their well-being and their motivation Parents, principals, teachers and system leaders provided data on: - school policies, practices, resources and institutional factors that help explain performance differences - 89,000 parents, 93,000 teachers and 17,500 principals responded
  3. 3. PISA 2015 OECD Partners
  4. 4. 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
  5. 5. The ‘productivity’ puzzle Making learning time productive so that students can build their academic, social and emotional skills in a balanced way
  6. 6. Learning time and science performance Figure II.6.23 Finland Germany Switzerland Japan Estonia Sweden Netherlands New Zealand Macao (China) Iceland Hong Kong (China) Chinese Taipei Uruguay Singapore Poland United States Israel Bulgaria Korea Russia Italy Greece B-S-J-G (China) Colombia Chile Mexico Brazil Costa Rica Turkey Montenegro Peru Qatar Thailand United Arab Emirates Tunisia Dominican Republic R² = 0.21 300 350 400 450 500 550 600 35 40 45 50 55 60 PISAsciencescore Total learning time in and outside of school OECD average OECD average OECDaverage
  7. 7. Learning time and science performance Figure II.6.23 6 7 8 9 10 11 12 13 14 15 16 0 10 20 30 40 50 60 70 Finland Germany Switzerland Japan Estonia Sweden Netherlands NewZealand Australia CzechRepublic Macao(China) UnitedKingdom Canada Belgium France Norway Slovenia Iceland Luxembourg Ireland Latvia HongKong(China) OECDaverage ChineseTaipei Austria Portugal Uruguay Lithuania Singapore Denmark Hungary Poland SlovakRepublic Spain Croatia UnitedStates Israel Bulgaria Korea Russia Italy Greece B-S-J-G(China) Colombia Chile Mexico Brazil CostaRica Turkey Montenegro Peru Qatar Thailand UnitedArabEmirates Tunisia DominicanRepublic Scorepointsinscienceperhouroftotallearningtime Hours Intended learning time at school (hours) Study time after school (hours) Score points in science per hour of total learning time
  8. 8. Teaching resources
  9. 9. 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% %
  10. 10. 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
  11. 11. 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
  12. 12. -4 -2 0 2 4 6 8 10 HongKong(China) Qatar TrinidadandTobago Macao(China) Belgium Switzerland Bulgaria Greece UnitedArabEmirates Singapore Italy Malta Sweden Germany Turkey Korea Hungary Slovenia Denmark Chile Canada Japan Croatia UnitedStates Jordan OECDaverage Australia Kosovo CABA(Argentina) FYROM Ireland Poland Netherlands Mexico Romania Uruguay Israel Tunisia Luxembourg Latvia Lebanon Indonesia Lithuania Peru Colombia CzechRepublic UnitedKingdom CostaRica France Portugal Thailand DominicanRepublic NewZealand VietNam Brazil Russia Georgia B-S-J-G(China) SlovakRepublic Montenegro Spain Norway Austria Moldova Finland Estonia Iceland ChineseTaipei Algeria Score-pointdifference Student-teacher ratio Class size in language-of-instruction class Students in schools with more students per teacher or larger classes score lower in science Students in schools with more students per teacher or larger classes score higher in science Class size and student-teacher ratio, and science performance Figure II.6.15
  13. 13. Different approaches
  14. 14. Overall science scale, 532 Content knowledge, 538 Procedural and epistemic knowledge, 528 480 490 500 510 520 530 540 550 560 ChineseTaipei Score points Comparing countries and economies on the different science knowledge subscales Figure I.2.30
  15. 15. Overall science scale, 556 Overall science scale, 532 Content knowledge, 553 Content knowledge, 538 Procedural and epistemic knowledge, 558 Procedural and epistemic knowledge, 528 480 490 500 510 520 530 540 550 560 SingaporeChineseTaipei Score points Comparing countries and economies on the different science knowledge subscales Figure I.2.30
  16. 16. Overall science scale, 556 Overall science scale, 532 Overall science scale, 495 Content knowledge, 553 Content knowledge, 538 Content knowledge, 501 Procedural and epistemic knowledge, 558 Procedural and epistemic knowledge, 528 Procedural and epistemic knowledge, 490 480 490 500 510 520 530 540 550 560 Singapore Chinese TaipeiAustria Score points Comparing countries and economies on the different science knowledge subscales Figure I.2.30
  17. 17. Overall science scale, 556 Overall science scale, 532 Overall science scale, 496 Content knowledge, 553 Content knowledge, 538 Content knowledge, 490 Procedural and epistemic knowledge, 558 Procedural and epistemic knowledge, 528 Procedural and epistemic knowledge, 501 480 490 500 510 520 530 540 550 560 Singapore Chinese Taipei United States Score points Comparing countries and economies on the different science knowledge subscales Figure I.2.30
  18. 18. UnitedKingdom Italy Australia Israel Malta Lebanon Spain Qatar Singapore UnitedStates Finland Norway UnitedArabEmirates Greece Canada HongKong(China) Russia Jordan NewZealand Macao(China) Portugal CABA(Argentina) Poland B-S-J-G(China) Georgia Moldova Luxembourg Ireland OECDaverage Iceland Uruguay Netherlands Thailand Mexico ChineseTaipei Germany France Croatia Switzerland Denmark Brazil Kosovo Austria Chile Romania Colombia TrinidadandTobago Hungary Sweden Latvia DominicanRepublic Belgium Tunisia VietNam Peru Japan Algeria FYROM Estonia CzechRepublic Turkey Lithuania SlovakRepublic CostaRica Bulgaria Montenegro Indonesia Korea -10 0 10 20 30 40 50 60 70 Score-pointdifference After accounting for socio-economic status Before accounting for socio-economic status Teacher-directed instruction: demonstrating scientific ideas Table II.2.18 Students who reported that their science teacher explains scientific ideas in many lessons or every lesson perform better in science
  19. 19. Norway Netherlands UnitedArabEmirates Qatar Denmark Finland Singapore Australia Sweden UnitedKingdom Iceland Germany Bulgaria Portugal Latvia Israel Brazil Russia B-S-J-G(China) HongKong(China) Chile Canada Turkey OECDaverage CzechRepublic Ireland Colombia Poland NewZealand Macao(China) Estonia Lithuania Switzerland Thailand DominicanRepublic SlovakRepublic Uruguay UnitedStates CostaRica Korea Greece Montenegro Hungary Mexico Croatia Italy France Spain Belgium Tunisia Luxembourg Peru Japan Austria ChineseTaipei -2 0 2 4 6 8 10 12 14 16 18 Score-pointdifference Score-point difference associated with the index of adaptive instruction Adaptive instruction and science performance Figure II.3.16 Students who reported that their science teacher adapts more frequently their lessons to students’ needs and knowledge perform better in science
  20. 20. Enquiry-based teaching practices and science performance Figure II.2.20 -65 -55 -45 -35 -25 -15 -5 5 15 25 Theteacherexplainshowascience ideacanbeappliedtoanumberof differentphenomena Theteacherclearlyexplainsthe relevanceofscienceconceptsto ourlives Studentsaregivenopportunitiesto explaintheirideas Studentsareaskedtodraw conclusionsfromanexperiment theyhaveconducted Studentsarerequiredtoargue aboutsciencequestions Thereisaclassdebateabout investigations Studentsspendtimeinthe laboratorydoingpractical experiments Studentsareaskedtodoan investigationtotestideas Studentsareallowedtodesigntheir ownexperiments Score-pointdifference After accounting for students' and schools' socio- economic profile Before accounting for students' and schools' socio- economic profile The following happen in "most" or "all" science lessons“
  21. 21. Teacher policies
  22. 22. -30 -20 -10 0 10 20 30 40 50 60 CzechRepublic Slovenia SlovakRepublic Switzerland Chile Australia Canada Mexico Belgium DominicanRep. OECDaverage Algeria Turkey Thailand FYROM Jordan Brazil Tunisia Peru ChineseTaipei Lithuania Uruguay CostaRica Indonesia Croatia Japan Korea Israel Greece France Spain Italy rinidad&Tobago Estonia Latvia Colombia Lebanon Netherlands After accounting for students' and schools' socio-economic profile Before accounting for students' and schools' socio-economic profile Score-point difference in science when principals reported that school teachers cooperate by exchanging ideas or material Teacher collaboration and science performance Table II.6.21
  23. 23. 0 10 20 30 40 50 60 70 80 90 100 Discussindividual students Shareresources Teamconferences Collaboratefor common standards Teamteaching CollaborativePD Jointactivities Classroom observations Percentageofteachers Average Shanghai (China) Professional collaboration Percentage of lower secondary teachers who report doing the following activities at least once per month Teacher co-operation Exchange and co-ordination
  24. 24. Teachers Self-Efficacy and Professional Collaboration 11.40 11.60 11.80 12.00 12.20 12.40 12.60 12.80 13.00 13.20 13.40 Never Onceayearorless 2-4timesayear 5-10timesayear 1-3timesamonth Onceaweekormore Teacherself-efficacy(level) Teach jointly as a team in the same class Observe other teachers’ classes and provide feedback Engage in joint activities across different classes Take part in collaborative professional learning Less frequently More frequently
  25. 25. External forces exerting pressure and influence inward on an occupation Internal motivation and efforts of the members of the profession itself 25 Professionalism Professionalism is the level of autonomy and internal regulation exercised by members of an occupation in providing services to society
  26. 26. Policy levers to teacher professionalism Knowledge base for teaching (initial education and incentives for professional development) Autonomy: Teachers’ decision- making power over their work (teaching content, course offerings, discipline practices) Peer networks: Opportunities for exchange and support needed to maintain high standards of teaching (participation in induction, mentoring, networks, feedback from direct observations) Teacher professionalism
  27. 27. Teacher professionalism Knowledge base for teaching (initial education and incentives for professional development) Autonomy: Teachers’ decision- making power over their work (teaching content, course offerings, discipline practices) Peer networks: Opportunities for exchange and support needed to maintain high standards of teaching (participation in induction, mentoring, networks, feedback from direct observations)
  28. 28. 0 1 2 3 4 5 6 7 8 9 10 Spain Japan France Brazil Finland Flanders Norway Alberta(Canada) Australia Denmark Israel Korea UnitedStates CzechRepublic Shanghai(China) Latvia Netherlands Poland England NewZealand Singapore Estonia Networks Autonomy Knowledge Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.3 2828 TALIS Teacher professionalism index
  29. 29. Status of the profession Teachers’ perception of the extent to which teaching is valued as a profession Satisfaction with the profession Teachers’ report on the extent to which teachers are happy with their decision to become a teacher. Satisfaction with work environment Teachers’ report on the extent to which teachers are happy with their current schools. Self-efficacy Teachers’ perception of their capabilities (e.g. controlling disruptive behaviour, use a variety of assessment strategies, etc.). 2 2929 Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.3 2929 Teacher outcomes
  30. 30. 0 10 20 30 40 50 60 70 Low professionalism High professionalism Mean mathematics performance, by school location, after accounting for socio-economic status Fig II.3.3 3030 Teacher professionalism index and teacher outcomes Perceptions of teachers’ status Satisfaction with the profession Satisfaction with the work environment Teachers’ self-efficacy Predicted percentile
  31. 31. Find out more about our work at www.oecd.org/pisa – All publications – The complete micro-level database Email: Andreas.Schleicher@OECD.org Twitter: SchleicherOECD Wechat: AndreasSchleicher Thank you

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