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…

Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…

Multilevel models are an increasingly popular method to analyze data that originate from a clustered or hierarchical structure. To effectively utilize multilevel models, one must have an adequately large number of clusters; otherwise, some model parameters will be estimated with bias. The goals for this paper are to (1) raise awareness of the…

To further understand the properties of data-generation algorithms for multivariate, nonnormal data, two Monte Carlo simulation studies comparing the Vale and Maurelli method and the Headrick fifth-order polynomial method were implemented. Combinations of skewness and kurtosis found in four published articles were run and attention was…

This study examined the effects of virtual reality immersion with audio on eye contact, directional focus and focus of attention for novice wind band conductors. Participants (N = 34) included a control group (n = 12) and two virtual reality groups with (n = 10) and without (n = 12) head tracking. Participants completed conducting/score study…

Growth mixture modeling has gained much attention in applied and methodological social science research recently, but the selection of the number of latent classes for such models remains a challenging issue, especially when the assumption of proper model specification is violated. The current simulation study compared the performance of a linear…

This study employed a quasi-experimental design to test the effects of three pedagogies on learning outcomes in a simulated psychology of gender lecture. Results showed that meaning and relational pedagogies, as well as a combination of meaning, relational, and explanatory pedagogies, significantly improved participant learning beyond self-study…

Meta-analyses often include studies that report multiple effect sizes based on a common pool of subjects or that report effect sizes from several samples that were treated with very similar research protocols. The inclusion of such studies introduces dependence among the effect size estimates. When the number of studies is large, robust variance…

In education research, small samples are common because of financial limitations, logistical challenges, or exploratory studies. With small samples, statistical principles on which researchers rely do not hold, leading to trust issues with model estimates and possible replication issues when scaling up. Researchers are generally aware of such…

This study examined the effectiveness of a brief theory-based intervention on muscular strength among adolescents in a physical education setting. The intervention adopted a process-based mental simulation technique. The self-reported frequency of practising for and actual levels of abdominal muscular strength/endurance as one component of…

Utilizing a web-based simulation Statecraft, we explore the relative influence of ideology (realism and idealism) on student behavior and learning. By placing students into ideologically cohesive groups, we are able to demonstrate the effect of their ideology on the goals they pursue and identify the constraints imposed on the system by the…

Interactive learning environments with body-centric technologies lie at the intersection of the design of embodied learning activities and multimodal learning analytics. Sensing technologies can generate large amounts of fine-grained data automatically captured from student movements. Researchers can use these fine-grained data to create a…

It is known that interventions are hard to assign randomly to subjects in social psychological studies, because randomized control is difficult to implement strictly and precisely. Thus, in nonexperimental studies and observational studies, controlling the impact of covariates on the dependent variables and addressing the robustness of the…

Clinical reasoning is a central skill in diagnosing cases. However, diagnosing a clinical case poses several challenges that are inherent to solving multifaceted ill-structured problems. In particular, when solving such problems, the complexity stems from the existence of multiple paths to arriving at the correct solution (Lajoie, 2003). Moreover,…

DIMPACK Version 1.0 for assessing test dimensionality based on a nonparametric conditional covariance approach is reviewed. This software was originally distributed by Assessment Systems Corporation and now can be freely accessed online. The software consists of Windows-based interfaces of three components: DIMTEST, DETECT, and CCPROX/HAC, which…