There is a large body of research exploring the difficulties young people experience on the transition to secondary education. However, there has been little comparative research yielding insights into how these experiences vary by institutional context. This article explores differences in school transition difficulties among young people in…

Digital literacy is essential for scientific literacy in a digital world. Although the NGSS Practices include many activities that require digital literacy, most studies have examined digital literacy from a generic perspective rather than a curricular context. This study aimed to develop a self-report tool to measure elements of digital literacy…

A recent study published in "Educational Researcher" by White (2023) examined superintendent gender gaps. This work required 4 years of internet searches to identify and match superintendent names with each of the roughly 13,000 school districts in the United States. Although this study provided important insights into the superintendent…

With the budding interests of structural and functional network characteristics as potential parameters for abnormal brains, an essential and thus simpler representation and evaluations have become necessary. Eigenvector centrality measure of functional magnetic resonance imaging ("fMRI") offer region wise network representations through…

Scale errors are intriguing phenomena in which a child tries to perform an object-specific action on a tiny object. Several viewpoints explaining the developmental mechanisms underlying scale errors exist; however, there is no unified account of how different factors interact and affect scale errors, and the statistical approaches used in the…

The tremendous growth in electronic educational data creates the need to have meaningful information extracted from it. Educational Data Mining (EDM) is an exciting research area that can reveal valuable knowledge from educational databases. This knowledge can be used for many purposes, including identifying dropouts or weak students who need…

Purpose: The purpose of the study is to understand the moderating impact of perceived technological innovativeness (PTI) in terms of gender differences as far as adoption and usage of Open Government Data (OGD) is concerned. Design/methodology/approach: Partial least squares-structural equation modelling (PLS-SEM) methodological approach is used…

The results of total testing from the years 2015-2022 on the mathematical and verbal achievement of Lithuanian pupils (N [approximately equal to] 250,000) are presented. These are the standardised tests from grades 4 to 12. The K-Means method has discovered six types of achievement. The highest achievement type is dominated by girls (61.1%) who…

Over recent years, the sharing of personal data among students is uncontrolled, especially on the social media networks, resulting in widespread data intrusions that compromise their privacy and confidentiality. Against this backdrop, this study was conducted to identify the level of knowledge of personal data protection among students. This…

Americans with more education vote at higher rates. Some studies have found evidence of a causal relationship, while others have not. The available data also tell us little about why and how education increases voting. The authors looked the educational trajectories and adult voting records of students who attend charter schools in Boston. The…

This study examines the return to education in South Korea by comparing metropolitan areas with non-metropolitan areas. It utilizes the Korean Labor and Income Panel Study from 2018 and 2019 for analysis, alongside the Mincer equation. The findings indicate that female workers have a higher return to education compared to male workers. The Oaxaca…

The purpose of this study is to examine the effect of missing data imputation methods, namely regression imputation (RI), multiple imputation (MI) and k-nearest neighbor (kNN) on differential item functioning (DIF). In this regard, the datasets used in the research were created by deleting some of the data via the missing completely at random…

Background: Data missingness can bias interpretation and outcomes resulting from data use. We describe data missingness in the longest-standing US-based youth fitness surveillance system (2006/07-2019/20). Methods: This observational study uses the New York City FITNESSGRAM (NYCFG) database from 1,983,629 unique 4th-12th grade students (9,147,873…

This manuscript focuses on the role of data analytics in mediating how teachers make sense of racial and gender inequity in patterns of student participation in their classrooms. Five middle school mathematics teachers participated in a year-long professional development program, centered on data analytics generated by the EQUIP observation tool.…

Today, modern educational models are concerned with the development of the teacher-student experience and the potential opportunities it presents. User-centric analyses are useful both in terms of the socio-technical perspective on data usage within the educational domain and the positive impact that data-driven methods have. Moreover, the use of…