This article introduces an innovative sampling scheme, the median sampling (MS), utilizing individual observations over time to efficiently estimate the mean of a process characterized by a symmetric (non-uniform) probability distribution. The mean estimator based on MS is not only unbiased but also boasts enhanced precision compared to its simple…

Multiple choice questions (MCQs) are a common way to assess reading comprehension. Every MCQ needs a set of distractor answers that are incorrect, but plausible enough to test student knowledge. However, good distractors are hard to create. Distractor generation (DG) models have been proposed, and their performance is typically evaluated using…

Over the past decade, a large number of literature reviews have explored the effectiveness of virtual reality technology as applied to children with autism spectrum disorder (ASD), but there has been a lack of scope focus on different types of virtual reality systems in assessment and intervention for children aged 3-12 years and a lack of…

This technical report provides detailed information about the sample, survey instruments, and resultant data for the Fall 2024 Pre-Kindergarten Teacher Survey (PKTS) which was administered via RAND's American Teacher Panel (ATP). The ATP is a nationally representative sample of public school teachers and part of the broader American Educator…

Consider the conventional multilevel model Y=C[gamma]+Zu+e where [gamma] represents fixed effects and (u,e) are multivariate normal random effects. The continuous outcomes Y and covariates C are fully observed with a subset Z of C. The parameters are [theta]=([gamma],var(u),var(e)). Dempster, Rubin and Tsutakawa (1981) framed the estimation as a…

When performing an aggregate data meta-analysis of a continuous outcome, researchers often come across primary studies that report the sample median of the outcome. However, standard meta-analytic methods typically cannot be directly applied in this setting. In recent years, there has been substantial development in statistical methods to…

Predicting student performance using educational data is a significant area of machine learning research. However, class imbalance in datasets and the challenge of developing interpretable models can hinder accuracy. This study compares different variations of the Synthetic Minority Oversampling Technique (SMOTE) combined with classification…

Data are everywhere. Data collected from samples are often reported in the form of polls, medical studies, and advertisement information and an understanding of sampling distributions and statistical inference is important for evaluating data-based claims (Bargagliotti et al., 2020). Despite the importance of understanding statistical inference…

A simulation study was conducted to examine the efficacy of nine frequently-used HOV tests, including Levene's tests with squared residuals and with absolute residuals, Brown and Forsythe (BF) test, Bootstrap BF test, O'Brien test, Z-variance test, Box-Scheffé (BS) test, Bartlett test, and Pseudo jackknife test under comprehensive simulation…

When scores are used to make decisions about respondents, it is of interest to estimate classification accuracy (CA), the probability of making a correct decision, and classification consistency (CC), the probability of making the same decision across two parallel administrations of the measure. Model-based estimates of CA and CC computed from the…

The partial correlation coefficient quantifies the relationship between two variables while taking into account the effect of one or multiple control variables. Researchers often want to synthesize partial correlation coefficients in a meta-analysis since these can be readily computed based on the reported results of a linear regression analysis.…

This article aims to describe the influence of parental involvement on the success of achieving the Pancasila Student Profile through school effectiveness. This research was conducted in elementary schools throughout East Java. The stages include the following: (1) testing validity and reliability; (2) testing the feasibility of the model which is…

Recent research has suggested that students prefer restudying over retrieval practice when learning difficult materials, despite the latter being a more effective learning strategy. The current study investigated whether an instructional intervention can improve the use of retrieval practice for both easy and difficult materials. In Experiment 1,…

Interactive computer simulations are commonly used as pedagogical tools to support students' statistical reasoning. This paper examines whether and how these simulations enable their intended effects. We begin by contrasting two theoretical frameworks--"dual processes" and "grounded cognition"--in the context of people's…

In describing how people generalize from observed samples of data to novel cases, theories of inductive inference have emphasized the learner's reliance on the contents of the sample. More recently, a growing body of literature suggests that different assumptions about how a data sample was generated can lead the learner to draw qualitatively…