Aiming at many problems of school multimedia classroom management, a remote control system for multimedia classroom based on cloud computing is developed. The system includes cloud computing management platform, network switch, single-chip microcomputer and equipment in the multimedia classrooms. It uses VMware desktop virtualization technology to…

This paper compares the use of confidence intervals (CIs) and a sensitivity analysis called the number needed to disturb (NNTD), in the analysis of research findings expressed as 'effect' sizes. Using 1,000 simulations of randomised trials with up to 1,000 cases in each, the paper shows that both approaches are very similar in outcomes, and each…

Scores estimated from multidimensional item response theory (IRT) models are not necessarily comparable across dimensions. In this article, the concept of aligned dimensions is formalized in the context of Rasch models, and two methods are described--delta dimensional alignment (DDA) and logistic regression alignment (LRA)--to transform estimated…

School rabbi-teachers are responsible for both the religious education and the daily classroom routines of their pupils. There are many conflicts that arise from the tension between these dual roles and although rabbi-teachers face such conflicts in school daily, they are not adequately trained to deal with them. The aim of the present study was…

The aim of this research is to determine the trends in the field of educational technology by analyzing the bibliometric analysis of the articles about Educational Technology published in the Web of Science Core database in the last 20 years. In this framework, a bibliometric analysis of the articles on educational technology published 2000-2019…

This study shows that residual variation can cause problems related to scaling in exponential random graph models (ERGM). Residual variation is likely to exist when there are unmeasured variables in a model--even those uncorrelated with other predictors--or when the logistic form of the model is inappropriate. As a consequence, coefficients cannot…

Collaboration is a complex, multidimensional process; however, details of how multimodal features intersect and mediate group interactions have not been fully unpacked. Characterizing and analyzing the temporal patterns based on multimodal features is a challenging yet important work to advance our understanding of computer-supported collaborative…

There is a demand for an overhaul of undergraduate nursing education curricula to better prepare students who can provide safe, quality care in an increasing complex health care system. Simulation use has provided an avenue for nurse educators to consider when deciding appropriate and reliable teaching and learning strategies to guide students…

With the availability of low-cost high-quality head-mounted displays (HMDs) since 2013, there is a growing body of literature investigating the impact of immersive virtual reality (IVR) technology on education. This meta-analysis aims to synthesize the findings on the overall effects of IVR using HMDs compared to less immersive desktop virtual…

A log-linear model (LLM) is a well-known statistical method to examine the relationship among categorical variables. This study investigated the performance of LLM in detecting differential item functioning (DIF) for polytomously scored items via simulations where various sample sizes, ability mean differences (impact), and DIF types were…

Scaffolding is a mechanism for helping novice learners to solve a problem or complete a task that is beyond their current skill set. Prior research on immersive virtual reality (IVR) environments with scaffolding has mainly focused on the effectiveness of scaffolding for conceptual understanding and information processing. However, research on…

Multiple imputation methods can generally be divided into two broad frameworks: joint model (JM) imputation and fully conditional specification (FCS) imputation. JM draws missing values simultaneously for all incomplete variables using a multivariate distribution, whereas FCS imputes variables one at a time from a series of univariate conditional…

In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to…

Meta-analyses often include only a small number of studies ([less than or equal to]5). Estimating between-study heterogeneity is difficult in this situation. An inaccurate estimation of heterogeneity can result in biased effect estimates and too narrow confidence intervals. The beta-binominal model has shown good statistical properties for…

With this article, we propose using a Bayesian multilevel latent class (BMLC; or mixture) model for the multiple imputation of nested categorical data. Unlike recently developed methods that can only pick up associations between pairs of variables, the multilevel mixture model we propose is flexible enough to automatically deal with complex…