With many pretreatment covariates and treatment factors, the classical factorial experiment often fails to balance covariates across multiple factorial effects simultaneously. Therefore, it is intuitive to restrict the randomization of the treatment factors to satisfy certain covariate balance criteria, possibly conforming to the tiers of…

A systematic review and meta-analysis is an important step in evidence synthesis. The current paradigm for meta-analyses requires a presentation of the means under a random-effects model; however, a mean with a confidence interval provides an incomplete summary of the underlying heterogeneity in meta-analysis. Prediction intervals show the range…

School leaders today are making important decisions regarding education innovations based on published average effect sizes, even though few understand exactly how effect sizes are calculated or what they mean. This article explains how average effect sizes are determined in meta-analyses and the importance of including measures of variability…

Two recent publications in "Educational and Psychological Measurement" advocated that researchers consider using the a priori procedure. According to this procedure, the researcher specifies, prior to data collection, how close she wishes her sample mean(s) to be to the corresponding population mean(s), and the desired probability of…

Unusual response similarity among test takers may occur in testing data and be an indicator of potential test fraud (e.g., examinees copy responses from other examinees, send text messages or pre-arranged signals among themselves for the correct response, item pre-knowledge). One index to measure the degree of similarity between two response…

This report aims to showcase the value of implementing a Bayesian framework to analyse and report results from international large-scale surveys and provide guidance to users who want to analyse the data using this approach. The motivation for this report stems from the recognition that Bayesian statistical inference is fast becoming a popular…

Several international large-scale assessments were conducted at the turn of the new century, and during the past two decades the Programme for International Student Assessment (PISA) completed seven cycles of assessment to facilitate practitioners' policy debates and governance. This study reviews PISA-related articles published in English and…

This article describes an extension to the use of heteroskedastic ordered probit (HETOP) models to estimate latent distributional parameters from grouped, ordered-categorical data by pooling across multiple waves of data. We illustrate the method with aggregate proficiency data reporting the number of students in schools or districts scoring in…

Recently Burkholder "et al." argued that class normalized gains over the entire population of courses is approximated by a Cauchy distribution, not by a normal distribution, and therefore should not be used to compare different classes because means and standard deviations cannot be calculated. They argued that multiple linear regression…

Conceptual challenge is often considered a necessary ingredient for promoting deep learning in an inquiry-based environment. However, challenge alone does not support conceptual development. In this paper, we draw on complexity theory as a theoretical lens to explore how a primary teacher facilitated students' conceptual change through repeated…

In multisite trials, learning about treatment effect variation across sites is critical for understanding where and for whom a program works. Unadjusted comparisons, however, capture "compositional" differences in the distributions of unit-level features as well as "contextual" differences in site-level features, including…

Principal stratification is a widely used framework for addressing post-randomization complications. After using principal stratification to define causal effects of interest, researchers are increasingly turning to finite mixture models to estimate these quantities. Unfortunately, standard estimators of mixture parameters, like the MLE, are known…

Sampling distributions are fundamental for statistical inference, yet their abstract nature poses challenges for students. This research investigates the development of high school students' conceptions of sampling distribution through informal significance tests with the aid of digital technology. The study focuses on how technological tools…

Due to the difficulty of chemical compounds to visualize, augmented reality (AR) integrated with mobile learning has been developed as an alternative media for studying chemistry. This study aims to analyze the use of AR-integrated mobile learning in chemistry education from a bibliometric perspective in the last decade. A total of 225 articles…

In order to investigate the influence of separation of grade distributions and ratio of common items on the precision of vertical scaling, this simulation study chooses common item design and first grade as base grade. There are four grades with 1,000 students each to take part in a test which has 100 items. Monte Carlo simulation method is used…