Factor analysis of ordered categorical indicators in kinesiology is pervasive. However, some assumptions made regarding the indicators within methods commonly used in this research may increase analytic errors. Methods that relax these assumptions have been available for decades, but uptake has been slow. Therefore, the methodological focus of…

Mean or median student growth percentiles (MGPs) are a popular measure of educator performance, but they lack rigorous evaluation. This study investigates the error in MGP due to test score measurement error (ME). Using analytic derivations, we find that errors in the commonly used MGP are correlated with average prior latent achievement: Teachers…

The residual gain score has been of historical interest, and its percentile rank has been of interest more recently given its close correspondence to the popular Student Growth Percentile. However, these estimators suffer from low accuracy and systematic bias (bias conditional on prior latent achievement). This article explores three…

When estimating an average treatment effect with observational data, it's possible to get an unbiased estimate of the causal effect if all confounding variables are observed and reliably measured. In education, confounding variables are often latent constructs. Covariate selection methods used in causal inference applications assume that all…

This article reviews all (quasi)experimental studies appearing in the first 19 volumes (1997-2015) of "Language Teaching Research" (LTR). Specifically, it provides an overview of how statistical analyses were conducted in these studies and of how the analyses were reported. The overall conclusion is that there has been a tight adherence…

R and Python are commonly used software languages for data analytics. Using these languages as the course software for the introductory course gives students practical skills for applying statistical concepts to data analysis. However, the reliance upon the command line is perceived by the typical nontechnical introductory student as sufficiently…

Error analysis is an instructional strategy that can assist teachers to identify learners' areas of weakness in mathematics and that can point to remediation of those errors. This article explores the errors learners exhibit when solving quadratic equations by completing the square using Newman's Error Analysis Model. A research study explored the…

Background: Concept inventories (CIs) are commonly used in engineering disciplines to assess students' conceptual understanding and to evaluate instruction, but educators often use CIs without sufficient evidence that a structured approach has been applied to validate inferences about student thinking. Purpose: We propose an analytic framework for…

The current study proposes novel methods to predict multistage testing (MST) performance without conducting simulations. This method, called MST test information, is based on analytic derivation of standard errors of ability estimates across theta levels. We compared standard errors derived analytically to the simulation results to demonstrate the…

Meta-analysis multiplicity, the concept of conducting multiple tests of statistical significance within one review, is an underdeveloped literature. We address this issue by considering how Type I errors can impact meta-analytic results, suggest how statistical power may be affected through the use of multiplicity corrections, and propose how…

Error analysis is proposed as a means to supplement diagnostic techniques with exceptional children. A purpose and definition of error analysis are provided. Also, procedures to use error analysis are explained along with basic guidelines to prevent abuse of error analytic techniques. (Author/CL)

Meta-analytic models for dependent effect sizes have grown increasingly sophisticated over the last few decades, which has created challenges for a priori power calculations. We introduce power approximations for tests of average effect sizes based upon several common approaches for handling dependent effect sizes. In a Monte Carlo simulation, we…

There is growing interest in creating learning analytics feedback interfaces that support students directly. While dashboards and other visualizations are proliferating, the evidence is that many fail to provide meaningful insights that help students reflect productively. The contribution of this article is qualitative and quantitative evidence…

English teachers, especially those who teach summary writing to students with relatively lower proficiency in English face difficulty in teaching summary writing and while assessing their students' performances. In the classroom context, an analytic rubric is pedagogically more helpful than a holistic rubric because the teacher can confirm the…

Pair programming (PP), as a mode of collaborative problem solving (CPS) in computer programming education, asks two students work in a pair to co-construct knowledge and solve problems. Considering the complex multimodality of pair programming caused by students' discourses, behaviors, and socio-emotions, it is of critical importance to examine…