Temperament is a widely researched trait that significantly influences children's lives. Still, theorists differ in their perspectives on the construct. With their nine dimensions of temperament and three "categories" of children--"easy," "difficult," or "slow to warm up"--Thomas and colleagues (1968) laid…

This note is concerned with the study of temporal development in several indices reflecting clustering effects in multilevel designs that are frequently utilized in educational and behavioral research. A latent variable method-based approach is outlined, which can be used to point and interval estimate the growth or decline in important functions…

Regression discontinuity (RD) designs are increasingly used for causal evaluations. However, the literature contains little guidance for conducting a moderation analysis within an RDD context. The current article focuses on moderation with a single binary variable. A simulation study compares: (1) different bandwidth selectors and (2) local…

The rapid advancement of Library and Information Science requires thoroughly examining emerging trends and evolving research priorities. This study seeks to uncover key themes within the field by applying Clustering Analysis and Keyword Frequency techniques. The objective is to analyze interdisciplinary connections and shifts in focus areas such…

The random intercept cross-lagged panel model (RICLPM) decomposes longitudinal associations between two processes X and Y into stable between-person associations and temporal within-person changes. In a recent study, Bailey et al. demonstrated through a simulation study that the between-person variance components in the RICLPM can occur only due…

Online collaborative discussion (OCD) focuses on promoting individual knowledge inquiry and group knowledge construction through active peer interactions and communications. In practice, it is necessary to explore how different modes of OCD come into play, in which student engagement can function as an evaluating indicator. To identify student…

The "k"-means clustering method, while widely embraced in college student typology research, is often misunderstood and misapplied. Many researchers regard "k"-means as a near-universal solution for uncovering homogeneous student groups, believing its success hinges primarily on the selection of an appropriate "k."…

Research on self-assessment has overwhelmingly conceptualized it as a product and treated students as a homogeneous group, restraining our understanding of the topic. To address this gap, this study aimed to identify different student profiles based on their self-assessment and to examine how it related to their learning achievement over time.…

Learning programming has become increasingly popular, with learners from diverse backgrounds and experiences requiring different support. Programming-process analysis helps to identify solver types and needs for assistance. The study examined students' behavior patterns in programming among beginners and non-beginners to identify solver types,…

Cluster-randomized trials have been widely used to evaluate the treatment effects of interventions on student outcomes. When interventions are implemented by teachers, researchers need to account for the nested structure in schools (i.e., students are nested within teachers nested within schools). Schools usually have a very limited number of…

Solving organic chemistry reactions requires reasoning with multiple concepts and data (i.e., multivariate reasoning). However, studies have reported that organic chemistry students typically demonstrate univariate reasoning. Case comparisons, where students compare two or more tasks, have been reported to support students' multivariate reasoning.…

As ideas from data science become more prevalent in secondary curricula, it is important to understand secondary teachers' content knowledge and reasoning about complex data structures and modern visualizations. The purpose of this case study is to explore how secondary teachers make sense of mappings between data and visualizations, especially…

Simulation studies are the basic tools of quantitative methodologists used to obtain empirical solutions to statistical problems that may be impossible to derive through direct mathematical computations. The successful execution of many simulation studies relies on the accurate generation of correlated multivariate data that adhere to a particular…

The purpose of the current paper is to provide a step-by-step tutorial for employing the list experiment to control for Social Desirability Bias (SDB). Sport management scholars routinely rely on self-report data in cross-sectional settings to test research hypotheses. However, concerns exist regarding the use of self-reports without adjusting for…

Meta-analytic studies of second language (L2) learning typically employ a classic approach to meta-analysis. Although the classic approach can clarify findings, a multivariate, multilevel meta-analysis (3M) approach increases transparency by accounting for (a) dependencies in the evidence presented by primary studies, (b) methodological…