Problem solving is considered an essential ability for becoming an expert in physics, and individualized feedback on the structure of problem-solving processes is a key component to support students in developing this ability. Problem-solving processes consist of multiple elements whose order forms the sequential structure of these processes.…

Sir Ronald Fisher's venerable experiment "The Lady Tasting Tea" is revisited from a Bayesian perspective. We demonstrate how a similar tasting experiment, conducted in a classroom setting, can familiarize students with several key concepts of Bayesian inference, such as the prior distribution, the posterior distribution, the Bayes…

Location tracking devices are becoming increasingly popular in practice to study movement of customers or track inventory. However, using location tracking devices in education contexts is quite novel. In this paper, we present a robust Bayesian nonparametric mixture model that clusters location data. We successfully apply this model on location…

If cues from different sensory modalities share the same cause, their information can be integrated to improve perceptual precision. While it is well established that adults exploit sensory redundancy by integrating cues in a Bayes optimal fashion, whether children under 8 years of age combine sensory information in a similar fashion is still…

This manuscript builds on a novel, automatic, freely-available Bayesian approach to extract information in abstracts and titles to classify research topics by quartile. This approach is demonstrated for all N= 149,129 ISI-indexed publications in biological sciences journals during 2017. A Bayesian multinomial inverse regression approach is used to…

In standardized educational testing, test items are reused in multiple test administrations. To ensure the validity of test scores, the psychometric properties of items should remain unchanged over time. In this article, we consider the sequential monitoring of test items, in particular, the detection of abrupt changes to their psychometric…

In the context of Bayesian factor analysis, it is possible to compute plausible values, which might be used as covariates or predictors or to provide individual scores for the Bayesian latent variables. Previous simulation studies ascertained the validity of mean plausible values by the mean squared difference of the mean plausible values and the…

Purpose: Our audio--vocal system involves a negative feedback system that functions to correct for fundamental frequency (f[subscript 0]) errors in production. Therefore, automatic and opposing responses appear when an unexpected change in voice pitch is present in auditory feedback. This study explores following responses to pitch perturbation in…

Uncertainty is ubiquitous in science, but scientific knowledge is often represented to the public and in educational contexts as certain and immutable. This contrast can foster distrust when scientific knowledge develops in a way that people perceive as a reversals, as we have observed during the ongoing COVID-19 pandemic. Drawing on research in…

Reward is thought to attenuate forgetting through the automatic effect of dopamine on hippocampal memory traces. Here we report a conceptual replication of previous results where we did not observe this effect of reward. Participants encoded eight lists of pictures and recalled picture content immediately or the next day. They were informed that…

When working with multimodal Bayesian posterior distributions, Markov chain Monte Carlo (MCMC) algorithms have difficulty moving between modes, and default variational or mode-based approximate inferences will understate posterior uncertainty. And, even if the most important modes can be found, it is difficult to evaluate their relative weights in…

An online learning system has the capacity to offer customized content that caters to individual learner's need and has seen growing interest from industry and academia alike in recent years. Different from traditional computerized adaptive testing setting which has a well-calibrated item bank with new items periodically added, online learning…

The deviance information criterion (DIC) is widely used to select the parsimonious, well-fitting model. We examined how priors impact model complexity (pD) and the DIC for Bayesian CFA. Study 1 compared the empirical distributions of pD and DIC under multivariate (i.e., inverse Wishart) and separation strategy (SS) priors. The former treats the…

Structural equation modeling (SEM) is being applied to ever more complex data types and questions, often requiring extensions such as regularization or novel fitting functions. To extend SEM, researchers currently need to completely reformulate SEM and its optimization algorithm -- a challenging and time-consuming task. In this paper, we introduce…

This study evaluates various scoring methods including number-correct scoring, IRT theta scoring, and hybrid scoring in terms of scale-score stability over time. A simulation study was conducted to examine the relative performance of five scoring methods in terms of preserving the first two moments of scale scores for a population in a chain of…