PISA 2009 Results: Students On Line

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1 PISA 2009 Results: Students On Line Digital Technologies and Performance (Volume VI)

2 This work is published on the responsibility of the Secretary-General of the. The opinions expressed and arguments employed herein do not necessarily reflect the official views of the Organisation or of the governments of its member countries. Please cite this publication as: (2011), PISA 2009 Results: Students on Line: Digital Technologies and Performance (Volume VI) ISBN (print) ISBN (PDF) The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law. Photo credits: Getty Images Ariel Skelley Getty Images Geostock Getty Images Jack Hollingsworth Stocklib Image Bank Yuri Arcurs Corrigenda to publications may be found on line at: PISA TM, /PISA TM and the PISA logo are trademaks of the Organisation for Economic Co-operation and Development (). All use of trademarks is prohibited without written permission from the You can copy, download or print content for your own use, and you can include excerpts from publications, databases and multimedia products in your own documents, presentations, blogs, websites and teaching materials, provided that suitable acknowledgment of as source and copyright owner is given. All requests for public or commercial use and translation rights should be submitted to Requests for permission to photocopy portions of this material for public or commercial use shall be addressed directly to the Copyright Clearance Center (CCC) at or the Centre français d exploitation du droit de copie (CFC) at

3 Foreword One of the ultimate goals of policy makers is to enable citizens to take advantage of a globalised world economy. This is leading them to focus on the improvement of education policies, ensuring the quality and sustainability of service provision, a more equitable distribution of learning opportunities and stronger incentives for greater efficiency in schooling. Such policies all hinge on reliable information on how well education systems prepare students for life. Most countries monitor students learning and the performance of schools. But in a global economy, the yardstick for success is no longer improvement by national standards alone, but how education systems perform internationally. The has taken that challenge up by developing PISA, the Programme for International Student Assessment, which evaluates the quality, equity and efficiency of school systems in some 70 countries that, together, make up nine-tenths of the world economy. PISA represents a commitment by governments to monitor the outcomes of education systems regularly within an internationally agreed framework and it provides a basis for international collaboration in defining and implementing educational policies. The results from the PISA 2009 assessment reveal wide differences in education outcomes, both within and across countries. The education systems that have been able to secure strong and equitable learning outcomes, and to mobilise rapid improvements, show others what is possible to achieve. Naturally, GDP per capita influences educational success, but this only explains 6% of the differences between average student performance. The other 94% reflect the potential for public policy to make a difference. The stunning success of Shanghai-China, which tops every league table in this assessment by a clear margin, show what can be achieved with moderate economic resources and in a diverse social context. In mathematics, more than a quarter of Shanghai s 15-year-olds can conceptualise, generalise, and creatively use information based on their own investigations and modelling of complex problem situations. They can apply insight and understanding and develop new approaches and strategies for addressing novel situations. In the area, just 3% of students reach that level of performance. While better educational outcomes are a strong predictor of economic growth, wealth and spending on education alone are no guarantee for better educational outcomes. Overall, PISA shows that an image of a world divided neatly into rich and well-educated countries and poor and badly-educated countries is out of date. This finding represents both a warning and an opportunity. It is a warning to advanced economies that they cannot take for granted that they will forever have human capital superior to that in other parts of the world. At a time of intensified global competition, they will need to work hard to maintain a knowledge and skill base that keeps up with changing demands. PISA underlines, in particular, the need for many advanced countries to tackle educational underperformance so that as many members of their future workforces as possible are equipped with at least the baseline competencies and skills that enable them to participate in social and economic development. The high social and economic cost of poor educational performance in advanced economies risks otherwise to become a significant drag on economic development. At the same time, the findings show that poor skills are not an inevitable consequence of low national income an important outcome for countries that need to achieve more with less. But PISA also shows that there is no reason for despair. Countries from a variety of starting points have shown the potential to raise the quality of educational outcomes substantially. Korea s average performance was already high in 2000, but Korean policy makers were concerned that only a narrow elite achieved levels of excellence in PISA. Within less than a decade, Korea was able to double the share of students demonstrating excellence in reading literacy. PISA 2009 Results: Students on Line Volume VI

4 Foreword A major overhaul of Poland s school system helped to dramatically reduce performance variability among schools, reduce the share of poorly performing students and raise overall performance by the equivalent of more than half a school year. Germany was jolted into action when PISA 2000 revealed below-average performance and large social disparities in results, and has been able to make progress on both fronts. Israel, Italy and Portugal have moved closer to the average and Brazil, Chile, Mexico and Turkey are among the countries with impressive gains from very low levels of performance. But the greatest value of PISA lies in inspiring national efforts to help students to learn better, teachers to teach better, and school systems to become more effective. A closer look at high-performing and rapidly improving education systems shows that these have much in common that transcends differences in their history, culture and economic evolution. First, while most nations declare their commitment to education, the test comes when these commitments are weighed against others. How do they reward teachers compared to the way they pay other highly-skilled workers? How are education credentials weighed against other qualifications when people are being considered for jobs? Would you want your child to be a teacher? How much attention do the media pay to schools and schooling? Which matters more, a community s standing in the sports leagues or its standing in the student academic achievement league tables? Are parents more likely to encourage their children to study longer and harder or to want them to spend more time with their friends or playing sports? In the most successful education systems, the political and social leaders have persuaded their citizens to make the choices needed to show that they value education more than other things. But placing a high value on education will get a country only so far if the teachers, parents and citizens of that country believe that only some subset of the nation s children can or need to achieve world class standards. This report shows clearly that education systems built around the belief that students have different pre-ordained professional destinies to be met with different expectations in different school types tend to be fraught with large social disparities. In contrast, the best-performing education systems embrace the diversity in students capacities, interests and social background with individualised approaches to learning. Second, high-performing education systems stand out with clear and ambitious standards that are shared across the system, focus on the acquisition of complex, higher order thinking skills, and are aligned with high stakes gateways and instructional systems. In these education systems, everyone knows what is required to get a given qualification, in terms both of the content studied and the level of performance that has to be demonstrated to earn it. Students cannot go on to the next stage of their life be it work or further education unless they show that they are qualified to do so. They know what they have to do to realise their dream and they put in the work that is needed to achieve it. Third, the quality of an education system cannot exceed the quality of its teachers and principals, since student learning is ultimately the result of what goes on in classrooms. Corporations, professional partnerships and national governments all know that they have to pay attention to how the pool is established from which they recruit; how they recruit; the kind of initial training their recruits get before they present themselves for employment; how they mentor new recruits and induct them into their service; what kind of continuing education they get; how their compensation is structured; how they reward their best-performers and how they improve the performance of those who are struggling; and how they provide opportunities for the best-performers to acquire more status and responsibility. Many of the world s best-performing education systems have moved from bureaucratic command and control environments towards school systems in which the people at the frontline have much more control of the way resources are used, people are deployed, the work is organised and the way in which the work gets done. They provide considerable discretion to school heads and school faculties in determining how resources are allocated, a factor which the report shows to be closely related to school performance when combined with effective accountability systems. And they provide an environment in which teachers work together to frame what they believe to be good practice, conduct field-based research to confirm or disprove the approaches they develop, and then assess their colleagues by the degree to which they use practices proven effective in their classrooms. Last but not least, the most impressive outcome of world class education systems is perhaps that they deliver highquality learning consistently across the entire education system such that every student benefits from excellent learning opportunity. To achieve this, they invest educational resources where they can make the greatest difference, they attract the most talented teachers into the most challenging classrooms, and they establish effective spending choices that prioritise the quality of teachers PISA 2009 Results: Students on Line Volume VI

5 Foreword These are, of course, not independently conceived and executed policies. They need to be aligned across all aspects of the system, they need to be coherent over sustained periods of time, and they need to be consistently implemented. The path of reform can be fraught with political and practical obstacles. Moving away from administrative and bureaucratic control toward professional norms of control can be counterproductive if a nation does not yet have teachers and schools with the capacity to implement these policies and practices. Pushing authority down to lower levels can be as problematic if there is not agreement on what the students need to know and should be able to do. Recruiting high-quality teachers is not of much use if those who are recruited are so frustrated by what they perceive to be a mindless system of initial teacher education that they will not participate in it and turn to another profession. Thus a county s success in making these transitions depends greatly on the degree to which it is successful in creating and executing plans that, at any given time, produce the maximum coherence in the system. These are daunting challenges and devising effective education policies will become ever more difficult as schools needs to prepare students to deal with more rapid change than ever before, for jobs that have not yet been created, to use technologies that have not yet been invented and to solve economic and social challenges that we do not yet know will arise. But those school systems that do well today, as well as those that have shown rapid improvement, demonstrate that it can be done. The world is indifferent to tradition and past reputations, unforgiving of frailty and complacency and ignorant of custom or practice. Success will go to those individuals and countries that are swift to adapt, slow to complain and open to change. The task of governments will be to ensure that countries rise to this challenge. The will continue to support their efforts. *** The report is the product of a collaborative effort between the countries participating in PISA, the experts and institutions working within the framework of the PISA Consortium, and the Secretariat. This volume of the report was drafted by a team led by Juliette Mendelovits with guidance from the PISA Reading Expert Group and the PISA team, led by Andreas Schleicher. Contributing authors were Alla Berezner, John Cresswell, Miyako Ikeda, Irwin Kirsch, Dominique Lafontaine, Tom Lumley, Christian Monseur, Johannes Naumann, Soojin Park and Jean-François Rouet. Editorial and analytical support were provided by Francesca Borgonovi, Michael Davidson, Maciej Jakubowski, Guillermo Montt, Oscar Valiente, Sophie Vayssettes, Elisabeth Villoutreix and Pablo Zoido of the PISA team. Further advice was provided by Marilyn Achiron, Simone Bloem, Marika Boiron, Simon Breakspear, Henry Braun, Nihad Bunar, Jude Cosgrove, Aletta Grisay, Tim Heemsoth, Donald Hirsch, David Kaplan, Henry Levin, Barry McCrae, Dara Ramalingam, Wolfgang Schnotz, Eduardo Vidal- Abarca and Allan Wigfield. Administrative support was provided by Juliet Evans and Diana Tramontano. The PISA assessment instruments and the data underlying the report were prepared by the PISA Consortium, under the direction of Raymond Adams at the Australian Council for Educational Research (ACER) and Henk Moelands from the Dutch National Institute for Educational Measurement (CITO). The expert group that guided the preparation of the reading assessment framework and instruments was chaired by Irwin Kirsch. The development of the report was steered by the PISA Governing Board, which is chaired by Lorna Bertrand (United Kingdom), with Beno Csapo (Hungary), Daniel McGrath (United States) and Ryo Watanabe (Japan) as vice chairs. Annex C of the volumes lists the members of the various PISA bodies, as well as the individual experts and consultants who have contributed to this report and to PISA in general. Intel Corporation provided a generous financial contribution towards publishing this volume. Angel Gurría Secretary-General PISA 2009 Results: Students on Line Volume VI

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7 Table of Contents Executive summary...19 Introduction to PISA...23 Reader s Guide...29 Chapter 1 Context of the PISA digital reading assessment...31 New technologies for text, new ways of reading...32 Differences in the readability and usability of text...33 New features of digital texts...34 Impact of digital texts on reading literacy...36 Which aspects of reading are affected by digital text?...36 Some issues for assessing digital reading...37 Conclusions...38 Chapter 2 Student Performance in Digital and Print reading...39 Digital reading...40 Texts...40 Cognitive processes...42 Situation...44 How the PISA 2009 reading results are reported...44 How the PISA 2009 digital reading tests were designed, analysed and scaled...44 What students can do in digital reading...49 Students reading the different levels of proficiency on the digital reading scale...49 Average level of proficiency...51 Gender differences in performance on the digital reading scale...52 Examples of digital reading items from the PISA 2009 assessment...54 IWANTTOHELP...54 Smell...60 Job search...66 Similarities and differences between digital and print reading assessment...71 Framework characteristics and test construct...71 Test design and operational characteristics...73 A comparison of performance in digital and print reading...74 Students reaching the different levels of proficiency...74 Average level of proficiency...76 Gender differences in performance on the digital and print reading scales...78 A composite scale for digital and print reading...80 Students reaching the different levels of proficiency on the composite reading scale...82 Average level of proficiency...83 Gender differences in performance on the composite reading scale...85 Conclusions...86 PISA 2009 Results: Students on Line Volume VI

8 Table of Contents Chapter 3 Navigation in the PISA 2009 digital reading assessment...89 General patterns in the relationship between navigation and performance in digital and print reading...90 Relevance of pages...91 Indicators used to describe navigation...91 Distribution of navigation indices at the country level...93 Relationships among navigation, print and digital reading...97 Correlations between navigation and performance...97 Regression of digital reading performance on print reading and navigation...98 Non-linear effects of navigation on digital reading performance Case studies: Navigation behaviour of students in selected digital reading tasks Tasks analysed in the case studies IWANTTOHELP Smell Job search Conclusions ChapTEr 4 relationships BetWEEn Digital reading Performance and Student Background, Engagement and Reading Strategies Family background Socio-economic background Immigrant status Languages spoken at home Performance differences within and between schools Student engagement and attitudes Engagement in reading and digital reading proficiency Do students who enjoy reading read better on line? The association between the diversity of print material students read and digital reading proficiency Online reading practices Gender differences in online reading practices Online reading practices and digital reading proficiency Reading strategies Awareness of strategies to understand and remember information Awareness of effective strategies to summarise information Model for the relationship between reading performance and student background characteristics Parents occupation Parents education Number of books in the home Cultural possessions Home educational resources Conclusions Chapter 5 Students familiarity with information and Communication technologies Students access to ICT The number of students who have never used a computer Students access to a computer and the Internet at home Students access to computers and the Internet at school How students use technology at school and at home Students use of ICT at home Students use of ICT at school Students attitudes towards and self-confidence in using computers Students attitudes towards using computers Students confidence in computer use and technical proficiency Conclusions PISA 2009 Results: Students on Line Volume VI

9 Table of Contents Chapter 6 Students use of information and communication technologies and their PErformance in Digital reading Access to and use of computers and performance Access to and use of computers at home Computer access and use at school Different types of computer use and performance Use of computers at home and performance Use of computers at school and performance Relationship between selected computer activities and performance in digital reading, in detail Computer use at home Computer use at school Navigation and computer use at home and at school Students self-confidence in doing ICT tasks Students self-confidence in using computers and performance Students self-confidence in doing ICT tasks and activities Conclusions Chapter 7 Some aspects related to digital reading proficiency Variation in student reading performance Socio-economic aspects Student socio-economic background school socio-economic background Attitudes towards reading Enjoyment of reading Diversity of reading materials Use of computers Computer use at home Computer use at school Online reading practices Searching-information activities Social activities Learning strategies Awareness of strategies to understand and remember information Awareness of effective strategies to summarise information Gender Variation explained by the model Conclusions Policy Implications Helping students develop effective skills in reading digital texts Addressing underperformance of boys Improving access to ICT Enabling effective use of ICT in schools References Annex A Technical Background Annex A1a: Construction of digital reading scales and indices from the student, school and ICT questionnaires Annex A1b: Construction of navigation indices Annex A2: The PISA target population, the PISA samples and the definition of schools Annex A3: Standard errors, significance tests and sub-group comparisons PISA 2009 Results: Students on Line Volume VI

10 Table of Contents Annex A4: Quality assurance for the digital reading assessment Annex A5: Development of the PISA assessment instruments for print and digital reading Annex A6: Tables showing the relationships between ICT activities and performance in print reading, mathematics and science Annex B Tables of results Annex B1: Results for countries and economies Annex B2: Results for regions within countries Annex C The development and implementation of Pisa A collaborative effort This book has... StatLinks 2 A service that delivers Excel files from the printed page! Look for the StatLinks at the bottom left-hand corner of the tables or graphs in this book. To download the matching Excel spreadsheet, just type the link into your Internet browser, starting with the prefix. If you re reading the PDF e-book edition, and your PC is connected to the Internet, simply click on the link. You ll find StatLinks appearing in more books PISA 2009 Results: Students on Line Volume VI

11 Table of Contents Boxes Box VI.A Key features of PISA Box VI.3.1 Box VI.3.2 Example of navigation indices...91 How the findings are organised...92 Box VI.4.1 Box VI.4.2 Box VI.4.3 Box VI.4.4 A cycle of engagement in reading activities, reading strategies and reading performance The association between reading engagement, awareness of reading strategies and reading performance Interpreting PISA indices Relationship between online reading, print reading and enjoyment of reading Box VI.5.1 Box VI.5.2 How information on students familiarity with ICT was collected Indices to analyse frequency of ICT use Box VI.6.1 Box VI.6.2 Box VI.6.3 Labels for each group of students: Students use of computers Relationship between ICT activities and performance in print reading, mathematics and science Labels for each group of students: Students self-confidence in using computers Figures Figure VI.A Figure VI.1.1 A map of PISA countries and economies...27 Comparison of print and digital texts...33 Figure VI.2.1 Digital reading tasks by environment...40 Figure VI.2.2 Digital reading tasks by text format...41 Figure VI.2.3 Digital reading tasks by text type...41 Figure VI.2.4 Digital reading tasks by aspect...42 Figure VI.2.5 Relationship between text processing and navigation in digital reading tasks...43 Figure VI.2.6 Digital reading tasks by situation...44 Figure VI.2.7 Relationship between questions and students on a proficiency scale...45 Figure VI.2.8 Summary descriptions for four levels of proficiency in digital reading...46 Figure VI.2.9 Map of selected digital reading questions in PISA 2009, illustrating the proficiency levels...48 Figure VI.2.10 How proficient are students in digital reading?...49 Figure VI.2.11 Comparing countries performance in digital reading...51 Figure VI.2.12 Where countries rank in digital reading performance...52 Figure VI.2.13 Gender differences in digital reading performance...53 Figure VI.2.14 How proficient are girls and boys in digital reading?...53 Figure VI.2.15 Distribution of score points in digital and print reading assessments, by text format...71 Figure VI.2.16 Distribution of score points in digital and print reading assessments, by text type...72 Figure VI.2.17 Distribution of score points in digital and print reading assessments, by aspect...73 Figure VI.2.18 Similarities and differences between digital and print reading assessments in PISA Figure VI.2.19 A comparison of performance levels on the digital and print reading scales...75 Figure VI.2.20 Percentage of students at each proficiency level on the digital and print reading scales...76 Figure VI.2.21 Comparison of mean performance in digital and print reading...77 Figure VI.2.22 Where countries rank in digital and print reading performance...78 Figure VI.2.23 Comparison of gender gaps in digital and print reading...79 Figure VI.2.24 Alignment between the described levels for digital and print reading and composite reading...80 Figure VI.2.25 Summary descriptions for the composite reading scale (digital and print combined)...81 Figure VI.2.26 How proficient are students on the composite reading scale?...82 Figure VI.2.27 Comparing countries performance on the composite reading scale...84 Figure VI.2.28 Where countries rank on the composite reading scale...84 Figure VI.2.29 Gender differences on the composite reading scale...85 Figure VI.2.30 How proficient are girls and boys on the composite reading scale?...86 PISA 2009 Results: Students on Line Volume VI

12 Table of Contents Figure VI.3.1 Figure VI.3.2 Figure VI.3.3 Figure VI.3.4 Figure VI.3.5 Figure VI.3.6 Figure VI.3.7 Figure VI.3.8 Figure VI.3.9 Illustration of the relationship between number of relevant pages visited and digital reading performance...93 Distribution of the number of pages and visits, aggregated across countries...94 Relationship between the number of relevant pages visited and digital reading performance...94 Relationship between the number of visits to relevant pages and digital reading performance...95 Relationship between the number of page visits and digital reading performance...95 Relationship between standard deviation and mean of the number of relevant pages visited...96 Relationship between standard deviation of the number of relevant pages visited and digital reading performance...97 Relationship between the number of visits to relevant pages (centred) and digital reading performance, average Summary of characteristics of digital reading tasks analysed in this section Figure VI.3.10 Relevant pages for IWANTTOHELP Question Figure VI.3.11 Extremes of student behaviour for IWANTTOHELP Question Figure VI.4.1 Figure VI.4.2 Figure VI.4.3 Figure VI.4.4 Figure VI.4.5 Figure VI.4.6 Figure VI.4.7 Figure VI.4.8 Figure VI.4.9 Strength of socio-economic gradient and reading performance Student performance in digital reading and immigrant status Variation in performance in digital and print reading explained by students and schools socio-economic backgrounds Relationship between enjoyment of reading and digital reading performance Relationship between diversity of reading and digital reading performance Index of online searching-information activities, by gender Index of online social activities, by gender Relationship between online searching-information activities and digital reading performance Relationship between online social activities and digital reading performance Figure VI.4.10 Single-level model to explain performance in digital and print reading, average Figure VI.5.1 Percentage of students who reported that they have never used a computer, by socio-economic background Figure VI.5.2 Percentage of students who reported having a computer at home in PISA 2000 and Figure VI.5.3 Percentage of students who reported having a computer at home, by socio-economic background Figure VI.5.4 Change in the percentage of students who reported having a computer at home between 2000 and 2009, by socio-economic background Figure VI.5.5 Percentage of students who reported having access to the Internet at home in 2000 and Figure VI.5.6 Percentage of students who reported having access to the Internet at home, by socio-economic background Figure VI.5.7 Change in the percentage of students who reported having access to the Internet at home between 2000 and 2009, by socio-economic background Figure VI.5.8 Computers-per-student ratio in 2000 and Figure VI.5.9 Percentage of students with access to computers at school Figure VI.5.10 Percentage of students with access to the Internet at school Figure VI.5.11 Percentage of students who reported using a computer at home and at school Figure VI.5.12 Percentage of students who reported using a computer at home and at school, by socio-economic background Figure VI.5.13 Percentage of students who reported using the Internet at home and at school Figure VI.5.14 Percentage of students in schools where the principal reported shortage or inadequacy of computers for instruction, by socio-economic background Figure VI.5.15 Percentage of students who reported that they did the following activities at home for leisure at least once a week, average Figure VI.5.16 Index of computer use at home for leisure, by gender and socio-economic background Figure VI.5.17 Percentage of students who reported that they did the following activities at home for schoolwork at least once a week, average Figure VI.5.18 Index of computer use at home for schoolwork-related tasks, by gender and socio-economic background Figure VI.5.19 Percentage of students who reported that they did the following activities at school at least once a week, oecd average Figure VI.5.20 Index of computer use at school, by gender and socio-economic background Figure VI.5.21 Percentage of students who reported that they use a computer during regular classroom lessons at least some time during a typical week, average Figure VI.5.22 Intensity of computer use during language-of-instruction lessons PISA 2009 Results: Students on Line Volume VI

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