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Calls for increased monitoring and evaluation of education policies and practices have not, so far, included widespread and consistent assessments of the inclusiveness of education settings. Measuring inclusion in education has proven to be a challenging exercise, due not only to the complexity and different uses of the concept, but also to its holistic nature. Indeed, measuring inclusion implies analysing a variety of policy areas within education systems, while also considering the different roles of the system, the school and the classroom. This paper discusses the application of the input-process-outcome model to the measurement of inclusion in education, and key indicators that can be adopted by education systems and schools to this end. It makes considerations relevant to policy makers when designing indicators to measure inclusion, such as the extent of their application, the constraints related to data disaggregation and the relevance of intersectional approaches to inclusion.

Digital technologies are increasingly present in young children's lives. How can early education systems get the best out of digitalisation while minimising its risks? This is especially urgent as the COVID-19 pandemic has accelerated our reliance on digital tools -- tools that enabled young children to continue learning when early education centres and primary schools closed down. It is in this context that the OECD conducted a policy survey covering 34 countries and jurisdictions. It investigates how digital technologies were used to provide distance education for young children in 2020, which challenges arose and what policy changes are in the pipeline for early education. [The Kingdom of Saudi Arabia provided financial support for this report.]

This Report Card offers an assessment of child well-being in the context of sustainable development across 41 countries of the European Union (EU) and the Organisation for Economic Co-operation and Development (OECD). Specifically, this report seeks to bring the SDG [Sustainable Development Goal] targets for children in high-income countries into meaningful operation (while staying true to the ambitions of the global agenda) and to establish a point of departure for reviewing the SDG framework in these contexts. It focuses on those goals and targets with most direct relevance to the well-being of children in high-income settings. Where appropriate, it adapts the agreed SDG indicator, the better to reflect the problems facing children in such countries. The results therefore highlight the new challenges set by the SDGs.

Governments recognise that careers guidance, underpinned by accurate labour market information, can help learners make post-secondary education choices that match their interests, aptitudes and abilities, and lead to rewarding employment. For this reason, they have invested in building linked education/employment information systems and other information resources which are displayed on websites targeted to learners and their families. However, researchers and governments agree that these efforts are often ineffective in informing learners' decisions -- access to information is not sufficient to provide effective support to student choice. Drawing upon the insights of behavioural economics, this paper examines how learners access and use information, and what this implies for the design of public study and career choice websites that aim to effectively support student choice. The report also takes stock of the career guidance websites in use in the majority of OECD countries, and sets out to provide actionable advice for policy makers to guide the design of effective information policy levers that support student choice.

On average in OECD countries, private sources account for a significant share of investment in tertiary educational institutions. Private expenditure on tertiary educational institutions increased faster than public expenditure between 2010 and 2016 on average across OECD countries, although this varies from country to country. Participation in tertiary education is not correlated to the funding model in tertiary institutions and high levels of private expenditure at tertiary education are not necessarily associated with lower enrolment. Financial support mechanisms in the form of grants or loans help alleviate the financial burden to households, particularly in countries where private spending on tertiary education is high.

As the data in this new edition of the Innocenti Report Card series show, in the past five years, rising numbers of children and their families have experienced difficulty in satisfying their most basic material and educational needs. Most importantly, the Great Recession is about to trap a generation of educated and capable youth in a limbo of unmet expectations and lasting vulnerability. League Tables, the flagship tool of the Innocenti Report Card series, rank the change, since the onset of the crisis, in the poverty levels of children and the impact of the recession on youth. The Report also explores the effects of the recession on youth seeking to enter or remain in the labour force in the middle of a recession. [Support for this report was provided by the Government of Italy.]

Good health is a benefit in many domains, such as work, studies or social relationships. Fostering a sound knowledge on healthy habits and the implications of risk-taking behaviours is a key to shaping societies with healthier lifestyles.

Teachers are the most important school resource. In every country, teachers' salaries and training represent the greatest share of expenditure on education; and this investment in teachers can have significant returns. Research shows that being taught by the best teachers can make a real difference in the learning and life outcomes of otherwise similar students. But not all students are equal when it comes to access to high-quality teaching. In fact, PISA data show that there are inequities in access to experienced and qualified teachers in many countries, and that they are related to the gap in learning outcomes between advantaged and disadvantaged students.

While the benefits of early childhood education and care (ECEC) services to better learning are now widely acknowledged, a widespread and accessible provision for these services also helps support gender equality in the workforce. In particular, the availability, intensity, reliability and affordability of ECEC play an important role in engaging women full time in the labour market. While ECEC has experienced a surge of policy attention over the last decades, wide variations still exist across countries and its costs remains a barrier to accessing paid work for poor families and lone parents, mostly mothers. More efforts are needed to increase the provision and accessibility of free ECEC services, especially for children under the age of 3.

PISA 2015 data show that, on average across OECD countries, as many as three out of four students from the lowest quarter of socio-economic status reach, at best, only the baseline level of proficiency (Level 2) in reading, mathematics or science. While in Canada, Denmark, Estonia, Finland, Germany, Hong Kong (China), Ireland, Japan, Korea, the Netherlands, Norway, Singapore, Slovenia and Viet Nam, more than 30% of disadvantaged students scored at Level 3 or above in all PISA subjects in 2015, and can thus be considered "academically resilient". Students who perform at Level 3 begin to demonstrate the ability to construct the meaning of a text and form a detailed understanding from multiple independent pieces of information when reading. They can work with proportional relationships and engage in basic interpretation and reasoning when solving mathematics problems; and they can handle unfamiliar topics in science. Such skills are the foundations for success and further learning later in life. PISA data collected over a decade (in 2006, 2009, 2012 and 2015) show that several countries have been able to increase the share of academically resilient students among those in the bottom quarter of socio-economic status. [This work was supported by a contribution to the PISA programme of work from Vodafone Germany Foundation.]

Resilience refers to the capacity of individuals to prosper despite encountering adverse circumstances. This paper defines academic resilience as the ability of 15-year-old students from disadvantaged backgrounds to perform at a certain level in the Programme for International Student Assessment (PISA) in reading, mathematics and science that enables them to play an active role in their communities and prepares them to make the most of lifelong-learning opportunities. Using data from the most recent PISA cycles, this paper explores changes in the share of resilient students over time (2006-2015); highlights the importance of school environments and resources in mitigating the risk of low achievement for disadvantaged students; and identifies school-level factors that are associated with the likelihood of academic resilience among socio-economically disadvantaged students. Analyses reveal that several countries were able to increase the share of resilient students over time, reflecting improvements in the average performance of students, or a weaker relationship between socio-economic status and performance. In the vast majority of education systems examined, the likelihood of academic resilience among disadvantaged students is lower in schools where students report a negative classroom climate. The paper concludes by exploring school policies and practices that are associated with a positive classroom climate. [This work was supported by a contribution to the PISA programme of work from Vodafone Germany Foundation.]

Across OECD countries, more and more individuals have attained tertiary education and the share of those with less education has declined. Although there are more tertiary-educated individuals than ever before, they still achieve good labour market outcomes. This confirms that labour market demand is generally keeping pace with rising educational attainment. Only in about one-quarter of OECD countries, the employment advantage of tertiary-educated adults over adults with upper-secondary or post-secondary education has declined over the past two decades, which may be a sign that demand for tertiary-educated people is slowing down. Countries also need to address the situation of young men and women who have not completed upper secondary school and who face low employment prospects.

In this study, we investigated how empirical indicators of test-taking engagement can be defined, empirically validated, and used to describe group differences in the context of the Programme of International Assessment of Adult Competences (PIAAC). The approach was to distinguish between disengaged and engaged response behavior by means of response time thresholds. Constant thresholds of 3000 ms and 5000 ms were considered, as well as item-specific thresholds based on the visual inspection of (bimodal) response time distributions (VI method) and the proportion correct conditional on response time (P+>0% method). Overall, the validity checks comparing the proportion correct of engaged and disengaged response behavior by domain and by item showed that the P+>0% method performed slightly better than the VI method and the methods assuming constant thresholds. The results for Literacy and Numeracy by module revealed that there was an increase from Module 1 to Module 2 in the proportion of disengaged responses, suggesting a drop in test-taking engagement. The investigation of country differences in test-taking engagement by domain using the P+>0% method showed that the proportion of responses classified as disengaged was quite low. For Literacy, the proportion was well below 5% for the majority of countries; in Numeracy, the proportion was even smaller than 1% for almost all countries; while for Problem solving, the proportion of disengaged responses was more than 5% but usually well below 10%. There were significant differences in test-taking engagement between countries; the obtained effect sizes were small to medium. Population differences in test-taking engagement were highly correlated between the three domains, suggesting that test-taking engagement can be conceived as a consistent characteristic. Furthermore, there was a clear negative association between test-taking disengagement and proficiency in Literacy, Numeracy and Problem solving, respectively. Finally, subgroup differences for gender, age, educational attainment, and language proved to be insignificant or very small. Results suggest that males tend to be more disengaged, that disengagement increases with age in Problem solving, with lower educational attainment and when the test language is not the same as a testee's native language. Appended are: (1) Country differences in test-taking engagement; and (2) Subgroup differences in test-taking engagement.

Using the 2012 PIAAC data, our analysis confirms that there are significantly higher earnings and employment returns to "both" increasing levels of formally recognised education, and to increasing levels of numeracy, literacy and information and communication technologies (ICT) skills proficiencies controlling for the level of education. Unsurprisingly, the labour market returns to changes in formally recognised levels of education in general exceed the labour market returns associated with increasing levels of skills proficiency. In the case of literacy and numeracy proficiencies, improved literacy and numeracy skills narrow the labour market outcomes gap between individuals with different levels of formally recognised education, but do not close it completely. The analysis demonstrates more substantial returns to ICT skills. Furthermore, possession of higher levels of ICT skills and lower levels of formally recognised qualification are often associated with higher returns compared to individuals with higher levels of formally recognised education but lower ICT proficiency levels. In other words, ICT skills proficiencies often entirely compensate for lower formally recognised qualifications in the labour market. Contains the following annexes: (1) Country Literacy and Numeracy Profiles; and (2) Demographic Control Variables.