Preface
This report, published by Pearson and written by the Economist Intelligence Unit, is part of a wide-ranging programme of quantitative and qualitative analysis, entitled The Learning Curve. It seeks to further our understanding of what leads to successful educational outcomes – both economic and social. The design and execution of the programme has benefited from the ongoing advice of some of the world’s leading educational scholars.
This report itself outlines the main findings from analysis of a large body of internationally comparable education data – The Learning Curve Data Bank. It also draws on extensive desk research, as well as in-depth interviews conducted with 16 experts in education. The research was conducted entirely by the Economist Intelligence Unit, and the views expressed in the report do not necessarily reflect those of Pearson. The report was written by Dr Paul Kielstra, and edited by Denis McCauley of the Economist Intelligence Unit.
Sincere thanks go to the interviewees for sharing their insights on this topic. These include the following individuals:
Nahas Angula, Prime Minister of Namibia
Paul Cappon, former President of the Canadian Council on Learning
Claudia Costin, Municipal Secretary of Education, Rio de Janeiro
Chester Finn, President, Thomas Fordham Institute
Eric Hanushek, Paul and Jean Hanna Senior Fellow, Stanford University
Lee Sing Kong, Director, National Institute of Education Singapore
Anthony Mackay, Chair Australian Institute for Teaching and School Leadership
Mamadou Ndoye, former Minister of Basic Education, Senegal
Vibha Parthasarati, educationalist and former Chair, National Commission for Women, India
William Ratteree, former education sector specialist, International Labour Organisation
Andreas Schleicher, Deputy Director for Education, OECD
Robert Schwartz, Francis Keppel Professor of Practice of Educational Policy and Administration, Harvard Graduate School of Education
Brian Stecher, Associate Director, RAND Education
James Tooley, Professor of Education Policy, Newcastle University
Ludger Woessmann, Professor of Economics, University of Munich
Yong Zhao, Associate Dean for Global Education, University of Oregon
The Learning Curve programme has additionally benefited from counsel provided at various stages by an Advisory Panel consisting of prominent education experts. These include:
Sir Michael Barber, Chief Education Advisor, Pearson
Paul Cappon, former President of the Canadian Council on Learning
Eric Hanushek, Paul and Jean Hanna Senior Fellow, Stanford University
Helen Joyce, Sao Paulo Bureau Chief and former International Education Editor, The Economist
Vibha Parthasarati, educationalist and former Chair, National Commission for Women, India
Pamela Sammons, Professor of Education, University of Oxford
Andreas Schleicher, Deputy Director for Education, OECD
November 2012
Executive summary
The goal of improving education today enjoys great prominence among policymakers and other stakeholders in societies worldwide. Although they may not be able to quantify it, governments in most countries recognise a link between the knowledge and skills with which young people enter the workforce and long-term economic competitiveness. For this reason, interest is intense in research which explores the factors that seem to lead in some countries to outstanding educational performance, and ultimately to better qualified workforces.
This report, and the broader Learning Curve programme of which it is part, is aimed at helping policymakers, educators, academics and other specialists to identify some of these factors. At its heart is a significant body of quantitative research. The Learning Curve Data Bank (LCDB), which is accessible online, brings together an extensive set of internationally comparable data on education inputs and outputs covering over 50 countries. This in turn has enabled a wide-ranging correlation analysis, conducted to test the strength of relationships between inputs, outputs and various socio-economic outcomes. It also underpins an initiative to create a comparative index of educational performance which, as will become apparent, is anything but a straightforward exercise.
Educators might hope that this or other similar bodies of research would yield the "holy grail": identification of the input, or set of inputs, that above all else leads to better educational results wherever it is applied. Alas, if this report makes nothing else clear, it is that no such magic bullets exist at an international level – or at least that they cannot, as yet, be statistically proven. Nonetheless, our research – which is also based on insights gathered from experts across the world – provides some definite signposts. Following are its highlights:
Strong relationships are few between education inputs and outputs
The research examined a wide range of education inputs, both quantitative – such as spending on pupils and class size – as well as qualitative – such as level of school choice. It also looked at numerous potential outcomes, ranging from inculcation of cognitive skills to GDP growth. A number of inputs show a statistical link over time with certain outputs, notably between income and results. These are discussed in the chapters that follow, but the most striking result of the exercise is how few correlations there are. Education remains very much a black box in which inputs are turned into outputs in ways that are difficult to predict or quantify consistently. Experts point out that simply pouring resources into a system is not enough: far more important are the processes which use these resources.
Income matters, but culture may matter more
On the surface, money and education seem to create a virtuous circle, with rich countries – and individuals – buying good educations for their children who, in turn, benefit economically. A closer look, though, indicates that both higher income levels and better cognitive test scores are the result of educational strategies adopted, sometimes years earlier, independently of the income levels existing at the time. More important than money, say most experts, is the level of support for education within the surrounding culture. Although cultural change is inevitably complex, it can be brought about in order to promote better educational outcomes.
There is no substitute for good teachers
Good teachers exercise a profound influence: having a better one is statistically linked not only to higher income later in life but to a range of social results including lower chances of teenage pregnancy and a greater tendency to save for their own retirement. The problem is that there is no agreed list of traits to define or identify an excellent teacher, let alone a universal recipe for obtaining them. That said, successful school systems have a number of things in common: they find culturally effective ways to attract the best people to the profession; they provide relevant, ongoing training; they give teachers a status similar to that of other respected professions; and the system sets clear goals and expectations but also lets teachers get on with meeting these. Higher salaries, on the other hand, accomplish little by themselves.
When it comes to school choice, good information is crucial
Recent research indicates that countries with greater choice of schools have better education outcomes. Presumably, allowing parents to choose the best schools rewards higher quality and leads to overall improvement. In practice, however, finding the mechanism to make this happen is difficult. Extensive studies of voucher programmes and charter schools in the United States indicate that, while both can be beneficial, neither is a magic formula. On the other hand, for-profit private education is providing students in some of the least developed areas of the world an alternative to poor state provision and showing the potential benefits of choice and accountability. Ultimately, as in any market or quasi-market, the real value of choice comes from people having the right information to select the option that is truly superior.
There is no single path to better labour market outcomes
Education seems to correlate with a host of personal benefits, from longer life to higher income. At a national level, too, education and income appear to go together. Finding the type of education that leads to the best economic outcomes, however, is far from straightforward. Different strategies have distinct pros and cons. For example, some countries – but far from all – place considerable emphasis on vocational training as preparation for employment. Similarly, education systems cannot simply educate for the present: leading ones look at what skills will be needed in future and how to inculcate them.
A global index can help highlight educational strengths and weaknesses
An important output of the Learning Curve programme is the Global Index of Cognitive Skills and Educational Attainment. Covering 40 countries, it is based on results in a variety of international tests of cognitive skills as well as measures of literacy and graduation rates. The top performers in the Index are Finland and South Korea. In some ways, it is hard to imagine two more different systems: the latter is frequently characterised as test-driven and rigid, with students putting in extraordinary work time; the Finnish system is much more relaxed and flexible. Closer examination, though, shows that both countries develop high-quality teachers, value accountability and have a moral mission that underlies education efforts.
Five lessons for education policymakers
1. There are no magic bullets: The small number of correlations found in the study shows the poverty of simplistic solutions. Throwing money at education by itself rarely produces results, and individual changes to education systems, however sensible, rarely do much on their own. Education requires long-term, coherent and focussed system-wide attention to achieve improvement.
2. Respect teachers: Good teachers are essential to high-quality education. Finding and retaining them is not necessarily a question of high pay. Instead, teachers need to be treated as the valuable professionals they are, not as technicians in a huge, educational machine.
3. Culture can be changed: The cultural assumptions and values surrounding an education system do more to support or undermine it than the system can do on its own. Using the positive elements of this culture and, where necessary, seeking to change the negative ones, are important to promoting successful outcomes.
4. Parents are neither impediments to nor saviours of education: Parents want their children to have a good education; pressure from them for change should not be seen as a sign of hostility but as an indication of something possibly amiss in provision. On the other hand, parental input and choice do not constitute a panacea. Education systems should strive to keep parents informed and work with them.
5. Educate for the future, not just the present: Many of today’s job titles, and the skills needed to fill them, simply did not exist 20 years ago. Education systems need to consider what skills today’s students will need in future and teach accordingly.
Education inputs and outputs: it's complicated
Education has always mixed the local and the global. The survival of Latin in Europe as a language of learning, long after its disappearance almost everywhere else in society, reflected an ideal of the universality of knowledge. On the other hand, state education provision has long been closely associated with local needs and the preservation of local cultures: in many federal systems, it falls to the state or province rather than the national government. As currently delivered, says Andreas Schleicher, the OECD’s Deputy Director for Education, “education is very inward looking, a very local activity. A lot of walls exist between countries.”
Since the 1990s, the interaction between the parochial and the international has taken on a new form. Comparative tests such as Progress in International Reading Literacy Study (PIRLS), Trends in International Mathematics and Science Study (TIMSS), and the Programme for International Student Assessment (PISA) manifest a growing emphasis on benchmarking the performance of different systems and on understanding what sets apart the highest achievers. In Professor Schleicher’s words, education debates are no longer about “improvement by national standards. Best performing countries now set the tone.”
He also believes that PISA has fundamentally challenged the idea that education should be valued largely on the volume of spending and other inputs, and the premise that more investment is always better. “The shift from inputs to outcomes [as the focus of study] has been a significant impact” of the tests, he says. Such research has also made clear that, for policymakers, more than children’s grades are at stake: economists have found a close relationship between economic growth and certain population-wide outputs of education such as cognitive skills.[1]
The Data Bank and what it reveals
The Learning Curve Data Bank (LCDB) – created by the Economist Intelligence Unit as part of the broader Learning Curve programme – is an effort to advance study in this area. It is a purpose-built, substantial collection of data which includes more than 60 comparative indicators gathered from over 50 countries. Many of these indicators in turn rely on multiple pieces of information, so that, even with some inevitable gaps, the LCDB encompasses over 2,500 individual data points. These go well beyond traditional education metrics, such as teacher-student ratios and various spending metrics, to cover a broad range of educational inputs and possible outputs, from the degree to which parents demand good results of schools to the proportion of adults who end up in jail. The appendix to this report describes the LCDB and the rest of the Quantitative Component, and the methodology behind them, in detail.
Chart 1: Structure of The Learning Curve Quantitative Component
Source: Economist Intelligence Unit.
Beyond providing a useful tool for researchers, a goal of the Quantitative Component and Data Bank has been to make possible a search for correlations between inputs and outputs that endure over time. The ultimate hope is to uncover, where possible, any interventions which might have a positive effect not only on the development of cognitive skills and scholastic achievement, but also on societal outcomes such as higher employment. The methodology appendix also describes how these correlations have been sought.
The data suggest a small handful of strong links. Two correlations show a connection between national income and aspects of academic success: higher GDP seems related to better Grade 8 PISA results; and a better score on the Human Development Index (of the United Nations Development Program – UNDP) and its Income Index are associated with higher upper secondary graduation rates. LCDB data also suggest a link between more years in school on average and higher labour productivity in a country. (One apparently strong link – that the higher a country’s average school life expectancy, the greater the proportion of students will graduate – is almost tautological given the time requirements involved in most diplomas and degrees.)
Still a black box
These findings will be discussed in the chapters that follow, but the most striking result of the search for correlations is the overall paucity of clear linkages. In this, our study is not alone. Ludger Woessmann, Professor of Economics at the University of Munich, explains that a lack of “any relationship between inputs and outputs mirrors the extensive academic literature on this topic. If you try to go beyond simple correlations, the general result is nearly always the same.” Chester Finn, President of the Thomas Fordham Institute, an education research organisation, and former United States Assistant Secretary of Education, agrees. “What works,” he says, “takes place inside a black box that has inputs coming in and outputs going out; but the inputs do not predict the results and what goes on in the black box is hard to quantify.”
The research does, though, at least point to some of the difficulties of seeing inside the black box. The first, says Paul Cappon, former President of the Canadian Council on Learning, is that in the study of education “we measure just a few things, usually inputs more than outputs because they are simpler and easier to measure, not because they are more significant – they are not.” Vibha Parthasarathi, a distinguished Indian educationalist, adds that successful outcomes arise from “the interplay of several factors, some tangible, others intangible. What I’ve seen in any number of surveys is you measure what is measurable. The softer inputs of education get left out.” These inputs, however, can be crucial, such as the cultural context in which education occurs.
Chart 2: Selected strong correlations from The Learning Curve Data Bank
Note: Strong correlations, such as those shown here, are above a threshold of 0.65. Correlation tests were conducted between two variables over time (on an annual basis). Each correlation refers to a minimum of 15 countries out of the sample
Source: Economist Intelligence Unit.
Second, straightforward correlations are difficult to find because education involves complex, interrelated processes rather than simple activities. Nahas Angula, Prime Minister of Namibia who, as education minister, oversaw the post-apartheid reconstruction of that country’s education system, says that achieving good outcomes “is not really a question of spending money, money, money. The question is how to get the most out of the money you have spent.” Dr Finn agrees: “Processes, more than inputs, are important. It is like having a good cook versus a bad one: the ingredients might be identical, but one produces something worth eating.” If education itself is so complex, teasing out its impact on broader societal phenomenon, like economic growth, is harder still.
This does not mean that education is a complete mystery. Some key elements are apparent. Professor Schleicher explains that “We have a good sense of what makes a good education system. That doesn’t answer how you do it, but you can say these are the key factors.” The rest of this study will explore the most important of those factors, bearing in mind that there is no single best way to address them in every country. As with cuisine, a variety of approaches may bring success. For example, as we will discuss later, education in Finland and South Korea – two of the world’s top-performing countries in many benchmarks – seem to have few similarities other than high academic achievement.
The main message of the lack of strong correlations, though, should be humility. Brian Stecher, Associate Director at RAND Education, says: “We use jargon that seems to explain student behaviour, but we really don’t understand the way students learn and the complex mix of inputs – family, community and learning – that lead to skills and temperaments. If you compare research in education to research in healthcare, you see a dramatic difference in our knowledge of cause and effect.” Claudia Costin, Rio de Janeiro’s Municipal Secretary of Education, adds that “Reforming education requires more than figures and analysis. You need to avoid arrogance and the feeling of having a technocratic approach.”
Rather than being able to pronounce the last word, then, education research is still learning how to promote better outcomes. The Data Bank itself is only one step in an effort that is hoped to last many years. The discussion which follows will look at several major issues relating to successful educational outcomes, including national income, culture, teaching quality and questions of choice and accountability. In doing so, it seeks to be part of an on-going deepening of knowledge about education, and to illuminate the key issues meriting further investigation.
[1]Eric A. Hanushek and Ludger Woessmann, “Education and Economic Growth”, in Dominic J. Brewer and Patrick J. McEwan, eds. Economics of Education (2010).
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