Based on 52 studies with samples mostly from English-speaking countries, the current study used Bayesian network meta-analysis to investigate the intervention effectiveness of different reading comprehension strategy combinations on reading comprehension among students with reading difficulties in 3rd through 12th grade. We focused on commonly…

In relational event networks, the tendency for actors to interact with each other depends greatly on the past interactions between the actors in a social network. Both the volume of past interactions and the time that has elapsed since the past interactions affect the actors' decision-making to interact with other actors in the network. Recently…

Raven's Standard Progressive Matrices (SPM) test and related matrix-based tests are widely applied measures of cognitive ability. Using Bayesian Item Response Theory (IRT) models, I reanalyzed data of an SPM short form proposed by Myszkowski and Storme (2018) and, at the same time, illustrate the application of these models. Results indicate that…

The present paper introduces a general multidimensional model to measure individual differences in learning within a single administration of a test. Learning is assumed to result from practicing the operations involved in solving the items. The model accounts for the possibility that the ability to learn may manifest differently for correct and…

Based on 52 studies with samples mostly from English-speaking countries, the current study used Bayesian network meta-analysis to investigate the intervention effectiveness of different reading comprehension strategy combinations on reading comprehension among students with reading difficulties in 3rd through 12th grade. We focused on commonly…

Previous research indicates that long-term memory (LTM) may contribute to performance in working memory (WM) tasks. Across 3 experiments, we investigated the extent to which active maintenance in WM can be replaced by relying on information stored in episodic LTM, thereby freeing capacity for additional information in WM. First, participants…

The evaluation of learning in mathematics is a worldwide problem, therefore, new methods are required to assess the understanding of mathematical concepts. In this paper, we propose to use the Item Response Theory to analyze the understanding level of undergraduate students about the real function mathematical concept. The Bayesian approach was…

Algorithms for approximate Bayesian inference, such as those based on sampling (i.e., Monte Carlo methods), provide a natural source of models of how people may deal with uncertainty with limited cognitive resources. Here, we consider the idea that individual differences in working memory capacity (WMC) may be usefully modeled in terms of the…

This study examined whether instructional humor (IH) was not just another type of seductive detail when covariates such as humor pre-disposition, prior-knowledge, and working memory capacity were controlled. Participants were students (N = 228) from universities who were randomly assigned two stimuli conditions in the classic experimental design.…