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Insights from PISA for Schools and Local Educators

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Over half a million students representing 28 million 15-year-olds in 65 countries/economies took an internationally agreed 2-hour test and responded to questions on their personal background, their ...

Over half a million students representing 28 million 15-year-olds in 65 countries/economies took an internationally agreed 2-hour test and responded to questions on their personal background, their schools and their engagement with learning and school

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  • FIRST POLL QUESTION FOR THE AUDIENCEOnce you have figured out the answer TEXT YOUR ANSWER CODE TO 22333Use small letters and no spacesFor A text: pisa1aFor B text: pisa1bFor C text: pisa1cFor D text: pisa1dFor E text: pisa1eFor those of you watching the live web cast you can submit your answer by email at the address PollEv.com/pisa2012You have one minute starting now to submit your answerANDREAS DON’T GO TO THE NEXT SLIDE UNTIL THE TIME IS UP FOR SUBMITTING ANSWERS
  • OECD – 4/5Mexico – ½Peru – 1/5
  • Scores against 15-year-olds
  • FIRST POLL QUESTION FOR THE AUDIENCEOnce you have figured out the answer TEXT THE ANSWER CODE TO 22333Use small letters and no spacesFor A text: pisa2aFor B text: pisa2bFor C text: pisa2cFor D text: pisa2dFor those of you watching the live web cast you can submit your answer by email at the address PollEv.com/pisa2012You have one minute starting now to submit your answerANDREAS DON’T GO TO THE NEXT SLIDE UNTIL THE TIME IS UP FOR SUBMITTING ANSWERS
  • Coprect answer
  • Scores against 15-year-olds
  • 376 average for Colombia and Qatar in Mathematics – different percentages of resilient students
  • (Fig. II.4.5)
  • It is important to consider that both the cognitive test items (questions) and the student and school questionnaires administered are integral parts of the assessment.
  • The field trialling of test items and the equating studywere conducted before the pilot trial that is described in the presentation.
  • The schools that successfully participated and tested in the pilot received an electronic school report. Each school report contains a summary and the five sections described here. - Only the school authorities and the district-level contacts, if appropriate, received access to the school reports. The OECD did not publicly release the reports or the results for schools without prior and written consent from the participating schools. The information presented in the school reports on students’ achievement, their engagement, and the teaching and learning environment should stimulate further reflection and discussion among school staff and local educational authorities. Active hyperlinks to OECD research, reports and video resources were included in the reports. Example school reports available at the OECD Website.
  • The schools that successfully participated and tested in the pilot received an electronic school report. Each school report contains a summary and the five sections described here. - Only the school authorities and the district-level contacts, if appropriate, received access to the school reports. The OECD did not publicly release the reports or the results for schools without prior and written consent from the participating schools. The information presented in the school reports on students’ achievement, their engagement, and the teaching and learning environment should stimulate further reflection and discussion among school staff and local educational authorities. Specific indices included: ESCS, disciplinary climate, teacher-student relations, instrumental motivation and self-efficacy in mathematics and science
  • Key Messages: SCIENCE results to use for ESCS discussion We see large variation in performance among schools with students from similar socio-economic backgrounds, with average students (starting point) and then looking at students from advantaged backgrounds (animation) as well as schools with disadvantaged students. This is one learning opportunity – what has occurred or is occurring in these schools to make the difference?But just as importantly, we see that some schools that have similar average performance may be doing so with students from very diverse backgrounds (animation – horizontal zoom bar). Here we see schools that have similar performance in science – these may be considered “under-performing schools” as they have average performance below the United States average in science in PISA 2009, but the important point is that these schools are doing so with students from very diverse backgrounds (almost 2 standard deviations). With the new school-level assessment, we are able to look closer at what is occurring in these schools but also to look at differences within and between schools. Let’s take a closer look at this group of schools…. (next slides show results for this selection of “under-performing schools”)
  • Key Messages: SCIENCE results to use for ESCS discussion We see large variation in performance among schools with students from similar socio-economic backgrounds, with average students (starting point) and then looking at students from advantaged backgrounds (animation) as well as schools with disadvantaged students. This is one learning opportunity – what has occurred or is occurring in these schools to make the difference?But just as importantly, we see that some schools that have similar average performance may be doing so with students from very diverse backgrounds (animation – horizontal zoom bar). Here we see schools that have similar performance in science – these may be considered “under-performing schools” as they have average performance below the United States average in science in PISA 2009, but the important point is that these schools are doing so with students from very diverse backgrounds (almost 2 standard deviations). With the new school-level assessment, we are able to look closer at what is occurring in these schools but also to look at differences within and between schools. Let’s take a closer look at this group of schools…. (next slides show results for this selection of “under-performing schools”)
  • Herndon High School
  • Langley High School
  • Additional Messages:Tie in with the workshop, the local opportunities for improvement based on evidence and the opportunities to learn not only from the world’s best education systems, but also from each other locally and nationally. In the afternoon session, the workshop will facilitate discussions looking at the specific information provided in the school reports.Indices will be explained and discussed: ESCS, disciplinary climate, teacher-student relations, instrumental motivation and self-efficacy in mathematics and science
  • Additional Messages:Tie in with the workshop, the local opportunities for improvement based on evidence and the opportunities to learn not only from the world’s best education systems, but also from each other locally and nationally. In the afternoon session, the workshop will facilitate discussions looking at the specific information provided in the school reports.Indices will be explained and discussed: ESCS, disciplinary climate, teacher-student relations, instrumental motivation and self-efficacy in mathematics and science

Insights from PISA for Schools and Local Educators Insights from PISA for Schools and Local Educators Presentation Transcript

  • OECD EMPLOYER BRAND Playbook 1 Insights from PISA for Schools and Local Educators Programme for International Student Assessment (PISA) Alejandro Gomez Palma Policy Analyst Organisation for Economic Co-operation and Development (OECD) Presentation for Local Educators from the USA 1 April 2014
  • 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 PISA 2012 in brief • Key principles – ‘Crowd sourcing’ and collaboration • PISA draws together leading expertise and institutions from participating countries to develop instruments and methodologies… … guided by governments on the basis of shared policy interests – Cross-national relevance and transferability of policy experiences • Emphasis on validity across cultures, languages and systems • Frameworks built on well-structured conceptual understanding of academic disciplines and contextual factors – Triangulation across different stakeholder perspectives • Systematic integration of insights from students, parents, school principals and system-leaders – Advanced methods with different grain sizes • A range of methods to adequately measure constructs with different grain sizes to serve different decision-making needs – e.g. PISA for Schools • Productive feedback to fuel improvement at every level of the system .
  • Math teaching and learning ≠ math teaching and learning PISA = reason mathematically and understand, formulate, employ and interpret mathematical concepts, facts and procedures (not curriculum- based but content is important) 4
  • 5 The real world The world of mathematics A real situation Mathematical model Results of the mathematical procedure Real results Understanding the situation, structuring and simplifying it Transforming the problem to be dealt with mathematics Interpreting the mathematical results Employing mathematical tools to solve a problem Validating the results PISA = competencies, skills and content = reason mathematically and use mathematical concepts, procedures, facts and tools A model from reality
  • 6 Climbing Mount Fuji Mount Fuji is a famous dormant volcano in Japan. Mount Fuji is only open to the public for climbing from 1 July to 27 August each year. About 200 000 people climb Mount Fuji during this time. On average, about how many people climb Mount Fuji each day? A. 340 (answer code: pisa1a) B. 710 (answer code: pisa1b) C. 3400 (answer code: pisa1c) D. 7100 (answer code: pisa1d) E. 7400 (answer code: pisa1e) PISA 2012 Sample Question
  • 7 Climbing Mount Fuji Correct Answer: C. 3400 This item belongs to the quantity category. The notion of quantity may be the most pervasive and essential mathematical aspect of engaging with, and functioning in, our world. It incorporates the quantification of attributes of objects, relationships, situations and entities in the world, understanding various representations of those quantifications, and judging interpretations and arguments based on quantity. SCORING: Description: Identify an average daily rate given a total number and a specific time period (dates provided) Mathematical content area: Quantity Context: Societal Process: Formulate PISA 2012 Sample Question 1
  • 9 Helen the Cyclist Helen has just got a new bike. It has a speedometer which sits on the handlebar. The speedometer can tell Helen the distance she travels and her average speed for a trip. Helen rode 6 km to her aunt’s house. Her speedometer showed that she had averaged 18 km/h for the whole trip. Which one of the following statements is correct? A. It took Helen 20 minutes to get to her aunt’s house. (answer code: pisa2a) B. It took Helen 30 minutes to get to her aunt’s house. (answer code: pisa2b) C. It took Helen 3 hours to get to her aunt’s house. (answer code: pisa2c) D. It is not possible to tell how long it took Helen to get to her aunt’s house. (answer code: pisa2d) PISA 2012 Sample Question 2
  • 10 Correct Answer: A. It took Helen 20 minutes to get to her aunt’s house. This item belongs to the change and relationships category. This involves understanding fundamental types of change and recognising when they occur in order to use suitable mathematical models to describe and predict change. SCORING: Description: Calculate time travelled given average speed and distance travelled Mathematical content area: Change and relationships Context: Personal Process: Employ Helen the Cyclist PISA 2012 Sample Question 2
  • 11 Percent of 15-year-olds who scored Level 3 or Above Shanghai-China Singapore HongKong-China Korea ChineseTaipei Macao-China Japan Liechtenstein Switzerland Estonia Netherlands Finland Canada Poland Vietnam Germany Belgium Austria Ireland Denmark Australia CzechRepublic Slovenia NewZealand France UnitedKingdom Iceland OECDaverage Latvia Norway Luxembourg Portugal Spain Italy RussianFederation SlovakRepublic Sweden Lithuania UnitedStates Hungary Israel Croatia Greece Serbia Turkey Bulgaria Romania UnitedArabEmirates Kazakhstan Chile Thailand Malaysia Uruguay Montenegro Mexico Albania Qatar CostaRica Brazil Argentina Tunisia Jordan Peru Colombia Indonesia 0 10 20 30 40 50 60 70 80 90 100 PISA 2012 Sample Question 2
  • Singapore Hong Kong-ChinaChinese Taipei Korea Macao-China Japan Liechtenstein Switzerland Netherlands Estonia Finland Canada Poland Belgium Germany Viet Nam Austria Australia IrelandSlovenia DenmarkNew Zealand Czech Republic France United Kingdom Iceland LatviaLuxembourg Norway Portugal ItalySpain Russian Fed.Slovak Republic United States LithuaniaSwedenHungary Croatia Israel Greece SerbiaTurkey Romania Bulgaria U.A.E. Kazakhstan Thailand Chile Malaysia Mexico 410 420 430 440 450 460 470 480 490 500 510 520 530 540 550 560 570 580 Mean score High mathematics performance Low mathematics performance … Shanghai-China performs above this line (613) … 12 countries perform below this line Average performance of 15-year-olds in Mathematics Fig I.2.13 US Massachusetts Connecticut Florida 26% of American 15-year-olds do not reach PISA Level 2 (OECD average 23%, Shanghai 4%, Japan 11%, Canada 14%, Some estimate long-term economic cost to be US$72 trillion )
  • Socially equitable distribution of learning opportunities High mathematics performance Low mathematics performance Average performance of 15-year-olds in mathematics Strong socio-economic impact on student performance Singapore Hong Kong-ChinaChinese Taipei Korea Macao-China Japan Liechtenstein Switzerland Netherlands Estonia Finland Canada Poland Belgium Germany Viet Nam Austria Australia IrelandSlovenia DenmarkNew Zealand Czech Republic France United Kingdom Iceland LatviaLuxembourg Norway Portugal ItalySpain Russian Fed.Slovak Republic United States LithuaniaSwedenHungary Croatia Israel Greece SerbiaTurkey Romania Bulgaria U.A.E. Kazakhstan Thailand Chile Malaysia Mexico
  • AustraliaAustria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US Singapore Hong Kong-ChinaChinese Taipei Macao-China Liechtenstein Viet Nam Latvia Russian Fed. Lithuania Croatia Serbia Romania Bulgaria United Arab Emirates Kazakhstan Thailand Malaysia 02468101214161820222426 2012 Shanghai-China Socially equitable distribution of learning opportunities Strong socio-economic impact on student performance
  • AustraliaAustria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US Australia Austria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US 2012 Socially equitable distribution of learning opportunities Strong socio-economic impact on student performance
  • AustraliaAustria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US Australia Austria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US
  • AustraliaAustria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US Australia Austria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US Singapore Shanghai Singapore 2003 - 2012
  • AustraliaAustria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US Australia Austria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US Singapore 2003 - 2012
  • AustraliaAustria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US Australia Austria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US Singapore 2003 - 2012 Brazil, Italy, Macao- China, Poland, Portugal, Russian Federation, Thailand and Tunisia saw significant improvements in math performance between 2003 and 2012 (adding countries with more recent trends results in 25 countries with improvements in math)
  • AustraliaAustria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US Australia Austria Belgium Canada Chile Czech Rep. Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Israel Italy Japan Korea Luxembourg Mexico Netherlands New Zealand Norway Poland Portugal Slovak Rep. Slovenia Spain Sweden Switzerland Turkey UK US Singapore 2003 - 2012 Norway, the United States and Switzerland improved equity between 2003 and 2012
  • Of the 65 countries… …45 improved in at least one subject 22
  • Mathematics, reading and science Israel, Poland, Portugal, Turkey, Brazil, Dubai (UAE), Hong Kong-China, Macao-China, Qatar, Singapore, Tunisia Mathematics and reading Chile, Germany, Mexico, Albania, Montenegro, Serbia, Shanghai-China Mathematics and science Italy, Kazakhstan, Romania Reading and science Japan, Korea, Latvia, Thailand Mathematics only Greece, Bulgaria, Malaysia, United Arab Emirates (ex. Dubai) Reading only Estonia, Hungary, Luxembourg, Switzerland, Colombia, Indonesia, Liechtenstein, Peru, Russian Federation, Chinese Taipei Science only Ireland Improvement in mathematics, reading or science23
  • 340 360 380 400 420 440 460 480 500 520 540 560 580 600 Shanghai-China Singapore HongKong-China ChineseTaipei VietNam Macao-China Korea Japan Liechtenstein Poland Switzerland Estonia Netherlands Germany Belgium Finland Canada Portugal Austria CzechRepublic NewZealand Latvia France Slovenia Ireland Australia OECDaverage Turkey SlovakRepublic Spain Hungary Luxembourg Italy RussianFederation UnitedKingdom Denmark Lithuania Croatia UnitedStates Norway Sweden Iceland Romania Israel Serbia Thailand Greece Bulgaria Chile Uruguay Malaysia Kazakhstan Cyprus5,6 Mexico CostaRica UnitedArab… Brazil Montenegro Tunisia Indonesia Peru Argentina Colombia Jordan Qatar Meanmathematicsscore Mean score at the country level before adjusting for socio-economic status Mean score at the country level after adjusting for socio economic status Mathematics performance in a level playing field Mean mathematics performance after accounting for socio-economic status Fig II.3.3 24
  • 0 2 4 6 8 10 12 14 16 18 20 Shanghai-China HongKong-China Macao-China VietNam Singapore Korea ChineseTaipei Japan Liechtenstein Switzerland Estonia Netherlands Poland Canada Finland Belgium Portugal Germany Turkey OECDaverage Italy Spain Latvia Ireland Australia Thailand Austria Luxembourg CzechRepublic Slovenia UnitedKingdom Lithuania France Norway Iceland NewZealand RussianFed. UnitedStates Croatia Denmark Sweden Hungary SlovakRepublic Mexico Serbia Greece Israel Tunisia Romania Malaysia Indonesia Bulgaria Kazakhstan Uruguay Brazil CostaRica Chile Colombia Montenegro U.A.E. Argentina Jordan Peru Qatar % Percentage of resilient students More than 10 % resilient Between 5%-10% of resilient students Less than 5% Fig II.2.4 25 A resilient student is situated in the bottom quarter of the PISA index of economic, social and cultural status (ESCS) in their own country and yet performs in the top quarter of students among all countries, after accounting for socio-economic status. 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 high-achievers.
  • Comparisons of performance Table I.2.3b Peru 22 years vs Indonesia 45 yearsQatar 13 years vs Tunisia 35 yearsBrazil 42 years vs Kazakhstan 9 years 0 100 200 300 400 500 600 700 800 2003 2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037 2039 2041 2043 2045 2047 MeanPerformanceinMathematics Catching up to the OECD Average in Mathematics Qatar Tunisia OECD 0 100 200 300 400 500 600 700 800 900 2006 2009 2012 2015 2018 2021 2024 2027 2030 2033 2036 2039 2042 2045 2048 2051 2054 MeanPerformanceinScience Catching up to the OECD Average in Science Brazil Kazakhsta n 0 100 200 300 400 500 600 700 2000 2003 2006 2009 2012 2015 2018 2021 2024 2027 2030 2033 2036 2039 2042 2045 2048 2051 2054 2057 MeanPerformanceinReading Catching up to the OECD Average in Reading Peru Indonesia OECD 26
  • Studentperformance AdvantagePISA Index of socio-economic backgroundDisadvantage 700 200 493 -3 -2 -1 0 1 2 3 School performance and socio-economic background: United States 27 Student performance and students’ socio-economic background School performance and schools’ socio-economic background Private school Public school in rural area Public school in urban area Student performance and students’ socio-economic background within schools Schools with similiar socio-economic backgrounds
  • 200 494 -3 -2 -1 0 1 2 3 School performance and socio-economic background: Viet Nam28 AdvantagePISA Index of socio-economic backgroundDisadvantage Student performance and students’ socio-economic background School performance and schools’ socio-economic background Private school Public school in rural area Public school in urban area Student performance and students’ socio-economic background within schools Studentperformance 700
  • -2.00 -1.50 -1.00 -0.50 0.00 0.50 Peru CostaRica Mexico Brazil Indonesia Thailand Colombia NewZealand Turkey Argentina UnitedStates Uruguay Australia Chile VietNam Jordan Shanghai-China U.A.E. Romania Sweden Israel Bulgaria ChineseTaipei Malaysia Ireland Greece Tunisia Poland Canada Japan Macao-China OECDaverage Luxembourg Qatar RussianFed. Iceland Belgium France Switzerland Portugal HongKong-China Spain Lithuania Denmark Kazakhstan Italy CzechRepublic Netherlands Estonia Hungary Slovenia Austria Singapore Latvia SlovakRepublic Montenegro Korea Germany Serbia UnitedKingdom Norway Croatia Finland Liechtenstein Albania Meanindexdifference Difference between socio-economically disadvantaged and socio-economically advantaged schools Educational resources are more problematic in disadvantaged schools, also in public schools in most countries Advantaged and private schools reported better educational resources Disadvantaged and public schools reported better educational resources Fig IV.3.8 29
  • 0 10 20 30 40 HongKong-China Korea+ Liechtenstein Macao-China+ Japan Switzerland Belgium- Netherlands- Germany Poland+ Canada- Finland- NewZealand- Australia- Austria OECDaverage2003- France CzechRepublic- Luxembourg Iceland- SlovakRepublic Ireland Portugal+ Denmark- Italy+ Norway- Hungary UnitedStates Sweden- Spain Latvia RussianFederation Turkey Greece Thailand Uruguay- Tunisia Brazil Mexico Indonesia % 2012 2003 Percentage of top performers in mathematics in 2003 and 2012 Fig I.2.23 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
  • Gender differences in reading performance -80 -70 -60 -50 -40 -30 -20 -10 0 Jordan Qatar Bulgaria Montenegro Finland Slovenia U.A.E. Lithuania Thailand Latvia Sweden Iceland Greece Croatia Norway Serbia Turkey Germany Israel France Estonia Poland Romania Malaysia RussianFed. Hungary SlovakRepublic Portugal Italy CzechRepublic Argentina OECDaverage Austria Kazakhstan Switzerland Macao-China Uruguay Canada Australia NewZealand ChineseTaipei Singapore Belgium VietNam UnitedStates Denmark Tunisia Brazil Luxembourg Spain Ireland Indonesia Netherlands HongKong-China CostaRica UnitedKingdom Liechtenstein Japan Shanghai-China Mexico Korea Chile Peru Colombia Albania Score-pointdifference(boys-girls) In all countries and economies girls perform better than boys Fig I.4.12 31
  • The share of immigrant students in OECD countries increased from 9% in 2003 to 12% in 2012… …while the performance disadvantage of immigrant students shrank by 11 score points during the same period (after accounting for socio-economic factors) 32
  • -40 -20 0 20 40 60 80 100 Hungary- Australia- Macao-China SlovakRepublic- Turkey NewZealand- Ireland Canada Latvia HongKong-China UnitedKingdom UnitedStates Thailand RussianFederation CzechRepublic OECDaverage2003- Luxembourg Portugal Norway Italy+ Liechtenstein Greece Iceland Spain Germany- Brazil Netherlands Sweden Austria Belgium- Switzerland- Denmark France Mexico Finland Scorepointdifference(without-withimmig.) 2012 2003 Students without an immigrant background perform better Students with an immigrant background perform better Change between 2003 and 2012 in immigrant students' mathematics performance – before accounting for students’ socio-economic status Fig II.3.5 33
  • -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 Japan HongKong-China Luxembourg Norway CzechRepublic Iceland Korea Indonesia Thailand Mexico Denmark Liechtenstein Italy Austria Macao-China Turkey Belgium Canada Portugal Poland Spain OECDaverage2003 Switzerland Brazil UnitedStates Greece SlovakRepublic Netherlands RussianFederation Hungary Ireland NewZealand Australia Uruguay Sweden Latvia France Finland Germany Tunisia Meanindexchange Change between 2003 and 2012 in disciplinary climate in schools In most countries and economies, the disciplinary climate in schools improved between 2003 and 2012 Disciplinary climate declined Disciplinary climate improved Fig IV.5.13
  • Motivation to learn mathematics Percentage of students who reported "agree" or "strongly agree" with the following statements: 0 10 20 30 40 50 60 70 I enjoy reading about mathematics I look forward to my mathematics lessons I do mathematics because I enjoy it I am interested in the things I learn in mathematics % United States Shanghai-China Fig III.3.9 35
  • United States Poland Hong Kong-China Brazil New Zealand Greece Uruguay United Kingdom Estonia Finland Albania Croatia Latvia Slovak Republic Luxembourg Germany Lithuania Austria Czech Republic Chinese Taipei France Thailand Japan Turkey Sweden Hungary Australia Israel Canada IrelandBulgaria Jordan Chile Macao-China U.A.E. Belgium Netherlands Spain Argentina Indonesia Denmark Kazakhstan Peru Costa Rica Switzerland Montenegro Tunisia Iceland Slovenia Qatar Singapore Portugal Norway Colombia Malaysia Mexico Liechtenstein Korea Serbia Russian Fed. Romania Viet Nam Italy Shanghai-China R² = 0.36 300 350 400 450 500 550 600 650 -0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00 1.20 Meanmathematicsperformance Mean index of mathematics self-efficacy OECDaverage Countries where students have stronger beliefs in their abilities perform better in mathematics36 Fig III.4.5
  • Schools with more autonomy perform better than schools with less autonomy in systems with more accountability arrangements School data not public School data public 464 466 468 470 472 474 476 478 Less school autonomy More school autonomy Score points School autonomy for curriculum and assessment x system's level of posting achievement data publicly Fig IV.1.16 37
  • No mathematics standards Central mathematics…455 460 465 470 475 480 485 Less school autonomy More school autonomy Schools with more autonomy perform better than schools with less autonomy in systems with more accountability arrangements Score points School autonomy for curriculum and assessment x System's extent of implementing a standardised policy Fig IV.1.16
  • Attract • Attract the best students to the teaching profession (Examples: Brazil, Korea, Israel, United Kingdom) • Create incentives to encourage experienced teachers to work in disadvantaged schools (Examples: Brazil, Estonia, Shanghai) Train • Provide quality training that combines acquiring knowledge and skills (Examples: Finland, Japan, Turkey) • Prepare teachers to address specific problems of students, assess and use appropriate remedial methods (Examples: Germany, Poland, Canada) Accompany • Provide mentoring programs for young teachers (Examples: Germany, Singapore) • Give young teachers the opportunity early in their career to return to university and improve their skills (Examples: Finland, Germany) Retain • Develop continuous professional development, which is as important, if not more than initial training (Examples: Brazil, Canada, Mexico, Singapore) • Provide career advancement opportunities (Examples: Quebec, Portugal) 39 Summary of insights regarding teachers from countries with high performance and equity in PISA:
  •  Provides information on the competencies, knowledge, skills and engagement of students, and the learning environment at the school  comparable to PISA scales  Tool in support of research and the benchmarking efforts for improvement  Can be used by schools, networks of schools and districts …To support local improvement OECD Test for Schools (based on PISA) Uses of the assessment tool
  • Is not… • A mandated standardised test • Intended to influence – in of itself – everyday teaching practices • An alternative to national, regional PISA participation • Intended to align completely with the content and curricular standards of a specific country, although there is overlap • A tool for “rankings” or “league tables” OECD Test for Schools (based on PISA) Uses of the assessment tool
  • OECD Test for Schools (based on PISA) What does the actual assessment look like?  Experience for students similar to that of the main PISA tests: ~ 3.25 hours (with breaks and student questionnaire)  Three areas (domains) equally represented (over 90 minutes of assessment items)  Student sample size per school (target): 75 (some schools tested over 100 students)  Contextual information  questionnaires for students and school authorities  Paper and pencil for first phase…
  • Content of school reports provided I. Introduction: Understanding your school’s results II. What students at Your School Know and Can Do in Reading, Mathematics and Science III. Student Engagement and the Learning Environment at Your School IV. Your School Compared with Similar Schools in Your Country V. Your School’s Results in an International Context Annexes School name School District State United States How your school compares internationally OECD Test for Schools Pilot Trial 2012 OECD Test for Schools (based on PISA) Overview of school reports
  • School-specific results provided  Performance on PISA scales  Relative performance based on background of students (socio-economic status - ESCS)  Learning environment at school OECD Test for Schools (based on PISA) Overview of school reports • Teacher-student relations • Disciplinary climate in English and Mathematics lessons • Student confidence and attitudes towards mathematics and science http://youtu.be/tnhLrGM81eI?t=1m58s
  • PerformanceonPISAscale OECD Test for Schools (based on PISA) Overview of results (from the pilot) 300 400 500 600 700 Schools in the United States Schools in the Shanghai-China Schools in Mexico PISA 2009 Results North Star Academy 300 400 500 600 700 Pilot Results 10% above 25% above 50% above/below 25% below 10% below 10% above 25% above 50% above/below 25% below 10% below 10% above 25% above 50% above/below 25% below 10% below Reading 300 400 500 600 700 300 400 500 600 700 300 400 500 600 700 Woodson HS 300 400 500 600 700 BASIS Scottsdale 300 400 500 600 700 Langley High School 300 400 500 600 700 Oakton High School 300 400 500 600 700 BASIS Tucson 300 400 500 600 700
  • OECD Test for Schools (based on PISA) Overview of results (from the pilot) What does the same mean mean? 0%20%40%60%80%100% Brazil Mexico United States OECD average United Kingdom Germany Poland Singapore Japan Canada Korea Finland Shanghai-China Langley High school Oakton High School 0% 20% 40% 60% 80% 100% Brazil Mexico United States OECD average United Kingdom Germany Poland Singapore Japan Canada Korea Finland Shanghai-China Langley High school Oakton High School 543 and 543 Reading Level 1 and be`low Level 2 Level 3 Level 4 Level 5 Level 6
  • OECD Test for Schools School Reports Disciplinary climate and reading performancce
  • http://youtu.be/tnhLrGM81eI?t=1m36s Disciplinary climate and reading performancce
  • Disciplinary climate and mathematics lessons
  • Quality of teacher-student relations http://youtu.be/1MzGhxJ5HOg?t=3m17s
  • Performance and teacher-student relations
  • Motivation of students to learn science
  • Self-belief of students in science
  • Instrumental motivation and self-efficacy of students and performance at your school
  • OECD Test for Schools School Reports
  •  Performance needs to be considered not in absolute terms but in terms of equity and relative effectiveness of schools  International benchmarking supported by the assessment is a process – the “real work” begins after receiving the results…  Performance should also be considered in the context of the quality of the learning environment at schools  Importance of peer-to-peer learning opportunities – – and the opportunity to share good practices to help identify “what works” OECD Test for Schools (based on PISA) What now? Current cycle of testing in the USA
  •  America Achieves – key partners in the USA  EdLeader21 – key partners in the USA  CTB/McGraw-Hill – currently accredited service provider  Spain has finished pilot in four official languages (224 schools)  In UK: England, Wales and Norther Ireland  International Learning Network – Australia…. OECD Test for Schools (based on PISA) Availability in the United States and Internationally
  • OECD EMPLOYER BRAND Playbook 58 PISA Insights for Schools and Local Educators Thank you very much www.pisa.oecd.org • All national and international publications • The complete micro-level database • Documents and Presentations of PISA for Development