Oral language development is a key outcome of elementary school, and it is important to identify factors that predict it most effectively. Commonly researchers use ordinary least squares regression with conclusions restricted to average performance conditional on relevant covariates. Quantile regression offers a more sophisticated alternative.…

There is mounting evidence of substantial "teacher quality gaps" (TQGs) between advantaged and disadvantaged students but practically no empirical evidence about their history. We use longitudinal data on public school students, teachers, and schools from two states--North Carolina and Washington--to provide a descriptive history of the…

We investigated whether a set of indicators of the employability dimensions proposed by Fugate, Kinicki, and Asforth (i.e., career identity, personal adaptability, and human and social capital) are related to university graduates' employment status and five indicators of the quality of their jobs (pay, hierarchical level, vertical and horizontal…

The purpose of this study was to investigate the extent to which leadership styles predict school climate, in order to identify whether a relationship exists between principals' perceived practices of instructional and distributed leadership and their perceptions of school climate (mutual respect and school delinquency), controlling for a net of…

While the number of postgraduate students is increasing, the writing of a master's dissertation still poses numerous challenges to them. The outcome of this work depends just as much on technical and methodological skills as on affects, self-regulation, and the relationship to the supervisor. In order to test a comprehensive model including all…

The doctoral dissertation is a key component of postgraduate education that plays an important role for knowledge production and hence the development of a discipline. Swedish human geography currently lacks an overview of dissertations. This article fills this knowledge gap by reporting findings from a unique database covering all doctoral…

Lord's Wald test for differential item functioning (DIF) has not been studied extensively in the context of the multidimensional item response theory (MIRT) framework. In this article, Lord's Wald test was implemented using two estimation approaches, marginal maximum likelihood estimation and Bayesian Markov chain Monte Carlo estimation, to detect…

Bayesian Knowledge Tracing (BKT) is a commonly used approach for student modeling, and Long Short Term Memory (LSTM) is a versatile model that can be applied to a wide range of tasks, such as language translation. In this work, we directly compared three models: BKT, its variant Intervention-BKT (IBKT), and LSTM, on two types of student modeling…

The main objective of the study was to explore the main predictors that influence academic stress among fourth-grade elementary school students using data from the Panel Study on Korean Children via a least absolute shrinkage and selection operator (LASSO) regularized penalty regression model. The study examined 280 explanatory variables using the…

The COVID-19 pandemic has brought the rapid transition to online quantitative education, leading to unique challenges and opportunities in assessments for both students and instructors. Focusing on undergraduate students and teaching staff at a Canadian university, this study investigates and compares their experiences and perspectives regarding…

Learning a second language (L2) is dependent upon numerous external and internal factors, among which motivation plays a relevant role. In fact, motivation has been recognized as crucial in the L2 learning process (Ushioda, 2012). Such has been its importance that interest in L2 motivation has led to the development of theories such as the L2…

The poor level of engagement in learning mathematics is primarily caused by ineffective methods of instruction. Therefore, the purpose of this study was to investigate how context-based problem-posing and solving instructional approaches influence students' engagement in learning data handling using a concurrent embedded quasi-experimental…

Scientific Data Analysis Toolkit (SDAT) is a rigorous, versatile, and user-friendly data analysis add-in application for Microsoft Excel for Windows (PC). SDAT uses the familiar Excel environment to carry out most of the analytical tasks used in data analysis. It has been designed for student use in manipulating and analyzing data encountered in…

In medical sciences, a disease condition is typically associated with multiple risk and protective factors. Although many studies report results of multiple factors, nearly all meta-analyses separately synthesize the association between each factor and the disease condition of interest. The collected studies usually report different subsets of…

Network meta-analysis (NMA) is gaining popularity for comparing multiple treatments in a single analysis. Generalized linear mixed models provide a unifying framework for NMA, allow us to analyze datasets with dichotomous, continuous or count endpoints, and take into account multiarm trials, potential heterogeneity between trials and network…