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Early childhood education and care (ECEC) policies can have a major role in levelling the playing field in education and society by providing all children, and especially those from disadvantaged backgrounds, with opportunities to participate in high-quality early learning and development experiences. Countries face different challenges in promoting equity and inclusion in ECEC depending on the particular aspects of social, economic and cultural diversity that are salient in their contexts. Examining the prevalence of different dimensions of diversity in ECEC centres and their associations with indicators of quality, this policy brief points to directions that policymakers can take to ensure that ECEC systems address the needs of children from all backgrounds.

The provision of high-quality early childhood education and care (ECEC) is widely seen as a strategy to promote a more equitable and inclusive society due to its potential to give all children, and especially those from disadvantaged backgrounds, a strong basis for early development and well-being. This requires approaches that address the needs of the increasingly diverse populations of children participating in ECEC. A first step in this direction is to assess the prevalence of different dimensions of diversity (e.g., socio-economic disadvantage, special education needs, different first language, and refugee status) across ECEC centres, and the extent to which the quality of ECEC varies between more and less diverse centres. This working paper uses data from the TALIS Starting Strong 2018 survey to examine these questions in the nine participating countries, and to derive policy pointers to ensure that ECEC systems promote equity and inclusion in response to the diversity of children’s needs.

Upper secondary education in Lithuania stands out internationally with one of the highest attainment rates across OECD countries. Yet the country and its young people receive relatively modest returns in terms of learning outcomes for the country's high rates of upper secondary completion. To address this issue, Lithuania is currently undertaking a series of reforms at the upper secondary education level. This report explores how Lithuania, and its young people can achieve higher returns on its investment in upper secondary education and provides Lithuania with policy recommendations to help improve it by strengthening vocational education pathways and by consolidating upper secondary certification.

This analytical report was prepared by the OECD Higher Education Policy Team as part of the Education and Innovation Practice Community (EIPC), an action of the European Union’s New European Innovation Agenda, flagship 4 on 'Fostering, attracting and retaining deep tech talent'. EIPC seeks to bring together peers from policy and practice to advance understanding of the competencies that can trigger and shape innovation for the digital and green transitions, and the mechanisms through which higher education can contribute to their development in secondary education (Strand 1), higher education (Strand 2), and adult upskilling and reskilling (Strand 3). This report for EIPC Strand 1 examines how higher education institutions (HEIs) can support teachers and school leaders in secondary schools to help their students develop competencies for innovation. Drawing on research evidence, practical examples and insights from the EIPC network and a wide range of OECD and EU education systems, it offers five options for consideration by education policy makers on how to strengthen HEIs’ role in supporting secondary education to develop human capacity for innovation.

As artificial intelligence (AI) expands its scope of applications across society, understanding its impact becomes increasingly critical. The OECD's AI and the Future of Skills (AIFS) project is developing a comprehensive framework for regularly measuring AI capabilities and comparing them to human skills. The resulting AI indicators should help policymakers anticipate AI’s impacts on education and work. This volume describes the second phase of the project: exploring three different approaches to assessing AI. First, the project explored the use of education tests for the assessment by asking computer experts to evaluate AI’s performance on OECD’s tests in reading, mathematics and science. Second, the project extended the rating of AI capabilities to tests used to certify workers for occupations. These tests present complex practical tasks and are potentially useful for understanding the application of AI in the workplace. Third, the project explored measures from direct AI evaluations. It commissioned experts to develop methods for selecting high-quality direct measures, categorising them according to AI capabilities and systematising them into single indicators. The report discusses the advantages and challenges in using these approaches and describes how they will be integrated into developing indicators of AI capabilities.

This analytical report was prepared by the OECD Higher Education Policy Team as part of the Education and Innovation Practice Community (EIPC), an action of the European Union’s New European Innovation Agenda, flagship 4 on 'Fostering, attracting and retaining deep tech talent'. EIPC seeks to bring together peers from policy and practice to advance understanding of the competencies that can trigger and shape innovation for the digital and green transitions, and the mechanisms through which higher education can contribute to their development in secondary education (Strand 1), higher education (Strand 2), and adult upskilling and reskilling (Strand 3). This report for EIPC Strand 1 examines how higher education institutions (HEIs) can support the integration of competencies for innovation into secondary school curricula. Drawing on research evidence, practical examples and insights from the EIPC network and a wide range of OECD and EU education systems, it offers six options for consideration by education policy makers on how to strengthen HEIs’ role in supporting effective curriculum development in schools.

Education systems around the world are increasingly recognising that social and emotional skills (SES) are essential for students and societies. This paper contributes to the Innovative approaches to measuring social and emotional skills project, which aims to complement self-report measures of SES with more direct assessments. It addresses criticisms of the OECD framework for SES used by the OECD Survey on Social and Emotional Skills and discusses the use of the Big Five model as an underlying structure for organising SES. The paper then examines the teachability of SES through a comprehensive literature review. In addition, it reviews the evidence for the relationship between different SES and key life outcomes. The paper also seeks to reconcile divergent conceptual understandings in the literature by providing a clear definition of SES and highlighting discrepancies in skill definitions. The conclusions of the paper identify gaps in current research, highlight teachable skills with notable predictive value SES relevant for educators and policy makers, and support the development of direct SES assessments.

Module A of the OECD Higher Education Policy Survey (HEPS) 2022 elicited information on policies to promote digitalisation of higher education in OECD member and accession countries. In total, 30 jurisdictions responded, providing comparative information on various areas of digitalisation policy, from regulation and governance to financial and human resources. The survey results provide insight into the role of public authorities in guiding, coordinating and resourcing the digital transformation of higher education institutions. The analysis and comparative tables in this working paper provide insights that can support the development of strategic digitalisation policies.

Intersectionality highlights that different aspects of individuals’ identities are not independent of each other. Instead, they interact to create unique identities and experiences, which cannot be understood by analysing each identity dimension separately or in isolation from their social and historical contexts. Intersectional approaches in this way question the common classification of individuals into groups (male vs. female, immigrant vs. native etc.), which raises important implications for the policy-making process. In education, analyses with an intersectional lens have the potential to lead to better tailored and more effective policies and interventions related to participation, learning outcomes, students’ attitudes towards the future, identification of needs, and socio-emotional well-being. Consequently, as elaborated in this paper, some countries have adjusted their policies in the areas of governance, resourcing, developing capacity, promoting school-level interventions and monitoring, to account for intersectionality. Gaps and challenges related to intersectional approaches are also highlighted.

The OECD AI Principles call for AI actors to be accountable for the proper functioning of their AI systems in accordance with their role, context, and ability to act. Likewise, the OECD Guidelines for Multinational Enterprises aim to minimise adverse impacts that may be associated with an enterprise’s operations, products and services. To develop ‘trustworthy’ and ‘responsible’ AI systems, there is a need to identify and manage AI risks. As calls for the development of accountability mechanisms and risk management frameworks continue to grow, interoperability would enhance efficiency and reduce enforcement and compliance costs. This report provides an analysis of the commonalities of AI risk management frameworks. It demonstrates that, while some elements may sometimes differ, all the risk management frameworks analysed follow a similar and sometimes functionally equivalent risk management process.