Classifications are a basic tool for research, which allow summarizing the diversity of objects in a number of categories that fits the cognitive abilities of the human mind. Their relevance for higher education is emphasized by the differentiation of institutional profiles. Yet, unlike in the US, there is currently no classification of European…

The COVID-19 pandemic constrained higher education institutions to switch to online teaching, which led to major changes in students' learning behavior, affecting their overall performance. Thus, students' academic performance needs to be meticulously monitored to help institutions identify students at risk of academic failure, preventing them…

A remarkable amount of perceptual development occurs in the first year after birth. In this article, we spotlight the case of color perception. We outline how within just 6 months, infants go from very limited detection of color as newborns to a more sophisticated perception of color that enables them to make sense of objects and the world around…

Recently, Bayesian diagnostic classification modeling has been becoming popular in health psychology, education, and sociology. Typically information criteria are used for model selection when researchers want to choose the best model among alternative models. In Bayesian estimation, posterior predictive checking is a flexible Bayesian model…

The Cognitive Theory of Multimedia Learning (CTML) suggests humans learn through visual and auditory sensory channels. Haptics represent a third channel within CTML and a missing component for experiential learning. The objective was to measure visual and haptic behaviors during spatial tasks. The haptic abilities test (HAT) quantifies results in…

We report findings of this replication study, examining the internalizing subscale (SRSS-I4) of the revised version of the Student Risk Screening Scale for Internalizing and Externalizing behavior (SRSS-IE 9) and the internalizing subscale of the Teacher Report Form (TRF). Using the sample from 13 elementary schools across three U.S. states with…

In China, formal school groupings known as 'education collectives' have become one of the most common forms of school-to-school collaboration, promoted by policymakers to narrow the achievement gap between schools and optimise resource allocation. Previous research has focused on the purposes and achievements of education collectives rather than…

This paper reports a validation study based on descriptive multidimensional item response theory (DMIRT), implemented in the R package "D3mirt" by using the ERS-C, an extended version of the Relevance subscale from the Moral Foundations Questionnaire including two new items for collectivism (17 items in total). Two latent models are…

The present research examined lie detection abilities of a rarely investigated group, namely offenders. Results of the studies conducted thus far indicated a better performance of offenders compared to non-offenders when discriminating between true and false messages. With two new studies, we aimed at replicating offenders' superior abilities in…

Oftentimes in many fields of the social and natural sciences, data are obtained within a nested structure (e.g., students within schools). To effectively analyze data with such a structure, multilevel models are frequently employed. The present study utilizes a Monte Carlo simulation to compare several novel multilevel classification algorithms…

This article analyses and discusses dilemmas, ambivalences and problematic issues related to research ethics. This is done firstly by making a distinction between procedural research ethics and particularistic research ethics. Such a distinction reflects a theoretical construction and generalization. In practice, there can be a very close…

Simulation studies involving mixture models inevitably aggregate parameter estimates and other output across numerous replications. A primary issue that arises in these methodological investigations is label switching. The current study compares several label switching corrections that are commonly used when dealing with mixture models. A growth…

Over the past decade, transdisciplinary research has been faced with increasing demands by research policy and funding bodies to make its contribution to dealing with complex societal problems more transparent. In the literature, there is a range of methodological attempts to trace and describe the effects of transdisciplinary research, but these…

Cognitive scientists have long used distributional semantic representations of categories. The predominant approach uses distributional representations of category-denoting nouns, such as "city" for the category city. We propose a novel scheme that represents categories as prototypes over representations of names of its members, such as…

Statistical learning allows us to discover myriad structures in our environment, which is saturated with information at many different levels--from items to categories. How do children learn different levels of information--about regularities that pertain to items and the categories they come from--and how does this differ from adults? Studies on…