Recently, there has been increasing interest in comparing educational leadership measures, such as principal school leadership, using International Large-Scale Assessments (ILSAs) data. However, there are doubts about the uniformity of measurement across countries participating in the ILSAs. There are concerns that the robustness and psychometric characteristics of measures are adversely affected by socio-cultural, economic, political, and linguistic diversity across countries. The current study examines the uniformity of cross-cultural model data for the “principal instructional leadership scale” using the framework and data supplied by the Organization for Economic Cooperation and Development (OECD)’s Teaching and Learning International Surveyis employed to estimate the conceptual measurement model and test measurement invariance across forty-eight countries. Countries are then divided countries into more homogenous groups, based on their socio-demographic characteristics, to test measurement invariance within these sub-groups. The results of this study reveal that, when testing for the fourty-eight countries together, the scale measuring principals’ school leadership is invariant across all countries only at an intermediate level (i.e. metric). This means the factor structures and the factor loadings are equivalent across countries, but the item intercepts are not. However, when testing within sub-groups, improvements in cross-cultural comparability are found. This paper concludes by making suggestions on scale improvement, discussing the implications of this study for policymaking and making recommendations for future research.

Distributed leadership (DL) is defined as the degree of contact and involvement of various people in making choices or carrying out responsibilities, and is an increasingly used concept among researchers, policymakers, and educationalists worldwide. However, few studies have investigated the cross-cultural comparability of the distributed leadership scale for school principals, and few have ranked countries according to their levels of distributed leadership. This study employs an innovative alignment optimisation approach to compare the latent means of distributed leadership, as perceived by school principals, across 40 countries, using data from the OECD Teaching and Learning International Survey (TALIS, 2018). We found that South Korea, Colombia, Shanghai (China), and Lithuania had the highest levels of distributed leadership in school decisions, from the perspective of school principals. In contrast, the Netherlands, Belgium, Argentina, and Japan had the lowest levels. Our findings may serve as guidance for education stakeholders over which nations they could learn from in order to enhance school principal distributed leadership.

It has been claimed that there is a lack of theory-driven constructs and a lack of cross-country comparability in International Large-Scale Assessment (ILSA)’s socio-economic background scales. To address these issues, a new socio-economic background scale was created based on Pierre Bourdieu’s cultural reproduction theory, which distinguishes economic, cultural and social capital. Secondly, measurement invariance of this construct was tested across countries participating in the Programme for International Student Assessment (PISA). After dividing the countries which participated in PISA 2015 into three groups, i.e., Latin American, European, and Asian, a Multi-Group Confirmatory Factor Analysis was carried out in order to examine the measurement invariance of this new socio-economic scale. The results of this study revealed that this questionnaire, which measures the socio-economic background, was not found to be utterly invariant in the analysis involving all countries. However, when analysing more homogenous groups, measurement invariance was verified at the metric level, except for the group of Latin American countries. Further, implications for policymakers and recommendations for future studies are discussed.

This study examines how principals perceive the potential benefits and challenges of artificial intelligence (AI) for students’ learning and teachers’ work across 12 countries, utilizing data from the 2023 International Computer and Information Literacy Study (ICILS 2023). We utilized latent network models, which allow for a flexible, network-based understanding of latent constructs, to examine the structural relationships between variables related to principals’ perceptions of AI. The findings revealed that while many school leaders recognize AI's potential to enhance student engagement and support teaching, they also express worries about its impact on academic integrity, teacher workload, and instructional practices. Those who view AI as beneficial for students tend to see similar advantages for teachers, whereas concerns about increased workload often accompany negative perceptions of AI's role in education. These insights emphasize the importance of developing balanced AI integration strategies that optimize benefits while mitigating potential challenges for educators. We suggest that policymakers design professional learning opportunities for school leaders that address both the benefits and effective integration of AI in teaching and learning, as well as strategies to mitigate potential negative consequences, such as increased workload or unethical use (e.g. cheating).