Model selection is important in any statistical analysis, and the primary goal is to find the preferred (or most parsimonious) model, based on certain criteria, from a set of candidate models given data. Several recent publications have employed the deviance information criterion (DIC) to do model selection among different forms of multilevel item…

This article reports an eye-movement experiment in which participants scanned continuous sequences of Landolt-Cs for target circles to examine the visual and oculomotor constraints that might jointly determine where the eyes move in a task that engages many of the perceptual and motor processes involved in Chinese reading but without lexical or…

The negative hypergeometric distribution is often not formally studied in secondary or collegiate statistics in contexts other than drawing cards without replacement. We present a different context with the potential of engaging students in simulating and exploring data.

There is limited research using small-scale simulation in applied behavior analysis. We used small-scale simulation to train firearm safety skills to 3- to 5-year-old children and assessed whether the skills generalized to the natural environment through in situ assessment. Three participants completed the training, and all participants learned…

There is a need for effect sizes that are readily interpretable by a broad audience. One index that might fill this need is [pi], which represents the proportion of scores in one group that exceed the mean of another group. The robustness of estimates of [pi] to violations of normality had not been explored. Using simulated data, three estimates…

Past research indicates that individuals respond adaptively to contextual factors in multiattribute choice tasks. Yet it remains unclear how this adaptation is cognitively governed. In this article, empirically testable implementations of two prominent competing theoretical frameworks are developed and compared across two multiattribute choice…

The DeGroot model has emerged as a credible alternative to the standard Bayesian model for studying learning on networks, offering a natural way to model naive learning in a complex setting. One unattractive aspect of this model is the assumption that the process starts with every node in the network having a signal. We study a natural extension…

Model selection is important in any statistical analysis, and the primary goal is to find the preferred (or most parsimonious) model, based on certain criteria, from a set of candidate models given data. Several recent publications have employed the deviance information criterion (DIC) to do model selection among different forms of multilevel item…

UV-vis absorption spectroscopy is one of the most accessible spectroscopic techniques at the high school educational level, and it is usually introduced in analytical chemistry courses due to its high versatility and to the wide range of applications in many fields of chemistry. Within this framework, we have developed an easy-to-use"…

Social workers have an important role in the field of mental health, and social work programs have a responsibility to prepare students for practice in the field. This scoping review mapped and synthesized the literature on mental health, addictions, and suicide in social work education and training. We found 51 articles that examined social work…

In this study, different degrees of synchronous and asynchronous online social interactions are investigated in the context of an online educational roleplaying simulation game that is played across multiple classrooms simultaneously to teach argumentation skills and social studies. Results from 45 K-12 middle school social studies teachers and…

Differential item functioning (DIF) is often used to examine validity evidence of alternate form test accommodations. Unfortunately, traditional approaches for evaluating DIF are prone to selection bias. This article proposes a novel DIF framework that capitalizes on regression discontinuity design analysis to control for selection bias. A…

Response process data have the potential to provide a rich description of test-takers' thinking processes. However, retrieving insights from these data presents a challenge for educational assessments and educational data mining as they are complex and not well annotated. The present study addresses this challenge by developing a computational…

This study aims to examine the effects of mixture item response theory (IRT) models on item parameter estimation and classification accuracy under different conditions. The manipulated variables of the simulation study are set as mixture IRT models (Rasch, 2PL, 3PL); sample size (600, 1000); the number of items (10, 30); the number of latent…

This paper presents an application of the Kalman filter in signal processing in instrumentation systems when the conditions of the environment generate a large amount of interference for the acquisition of signals from measurement systems. The unwanted interferences make important use of the instrumentation system resources and do not represent…