We propose a new method for analyzing and visualizing information on a large collection of personal networks to uncover the socio-centric structure of relationships among aggregated actors that we clustered into categories. The network of categories identifies the links between groups of sampled ego actors sharing a given attribute (e.g.,…

Background: This study examines the engagement of knowledge users in knowledge mobilisation (KMb) research on Canadian K-12 teaching and education policy. Research on and around KMb has grown in the decade since this field was first assessed comprehensively. Thus, it is timely to re-evaluate if current knowledge producer-user relationships in KMb…

The purpose of this study is to develop a valid and reliable scale to determine and evaluate the different dimensions of data literacy at school. The study is a quantitative descriptive survey model. The sampling for exploratory factor analysis was formed of 307 and confirmatory factor analysis 338 teachers and school administrators who are on…

The COVID pandemic highlighted the increasing deployment of digital technologies in educational institutions, defined as 'edtech'. The most visible edtech was video conferencing software, but a swathe of edtech startups have sought to roll out their products and services to educational institutions. We focus specifically on the deployment of…

This study examined the data science career preference, data science skills, and core competencies of 416 students from fourteen Nigerian universities using a Google Forms-created structured online questionnaire. A convenience sampling technique was adopted to select the participants. Data were analysed using both descriptive and inferential…

In our data-driven society, it is essential for students to become statistically literate. A core domain within Statistical Literacy is Statistical Inference, the ability to draw inferences from sample data. Acquiring and applying inferences is difficult for students and, therefore, usually not included in the pre-10th-grade curriculum. However,…

In the context of digital transformation processes in schools, the introduction of technology is often discussed in terms of the individualization and optimization of teaching, learning and school management. However, it is often neglected that technologies are preconfigured and provide socio-material offers that invite certain actions and thus…

Starting with the question of why there is so much religiously motivated resistance against compulsory sex education, this article explores and discusses entanglements of norms about sexuality, gender, and religion in education. Based on predominantly Swedish data, the aim of the paper is to offer perspectives on connections between religiosity…

Data science education in Japan extends from elementary to high school students. However, some studies show that this has not enhanced interest or curiosity in data science. Therefore, gamification appears to be an efficient method for encouraging high school students' interest in data science, with research indicating that video games are…

This systematic review presents the first synthesis of the scientific literature on estimating school and teacher/class effects on student academic performance using random-effects (RE) models with three or more levels. The review delves into the theoretical framework underpinning the estimation of educational effects, the associated statistical…

The application of big data in education sparks debates on its effects. Researchers explore its impact on learning outcomes, with divergent views on neural networks' potential and negative consequences. This study assesses big data's influence on basic literacy skills in music education for 5th graders. Using clustering and k-density analyses,…

This paper examines and builds on an earlier contribution to this journal focusing on private supplementary tutoring -- widely known as shadow education -- in Francophone West and Central Africa. Drawing on wider literature about research methods in this domain, it examines the basis for the numerical estimates presented in the original article…

Maternal, neonatal, and child health play crucial roles in achieving the objectives of Sustainable Development Goal (SDG) 2030, particularly in promoting health and wellbeing. However, maternal, neonatal, and child services in Moroccan public hospitals face challenges, particularly concerning mortality rates and inefficient resource allocation,…

Data Envelopment Analysis (DEA) is a widely adopted non-parametric technique for evaluating R&D performance. However, traditional DEA models often struggle to provide reliable solutions in the presence of data uncertainty. To address this limitation, this study develops a novel robust super-efficiency DEA approach to evaluate R&D…

Data- driven decision making DDDM in school settings is often guided and influenced by various sources of data that assist in improving students' outcomes. School principals as the main educational leaders, play a pivotal role in DDDM using the available school data. Semi-structured interviews with 24 school principals were conducted to…