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…

The drift diffusion model (DDM) is a widely applied computational model of decision making that allows differentiation between latent cognitive and residual processes. One main assumption of the DDM that has undergone little empirical testing is the level of independence between cognitive and motor responses. If true, widespread incorporation of…

In Automated Essay Scoring (AES) systems, many previous works have studied group fairness using the demographic features of essay writers. However, individual fairness also plays an important role in fair evaluation and has not been yet explored. Initialized by Dwork et al., the fundamental concept of individual fairness is "similar people…

Unlearning is a recurrent theme in Japan. To further understanding of what this entails, we focus on the view of learning laid out by a revered 13th century Zen-inspired playwright. For Zeami, learning involved a movement from the acquisition to unlearning of skills, punctuated by an experience of "mushin," followed by creative…

Understanding vocational learning and transfer is vital to European citizens. We need to understand how transfer works, which factors influence it, and how these factors affect employee behaviour. Research in online training specific to Southern Europe is needed to move the field forward. The Unified Model of Motivation for Training Transfer (MTT)…

A compelling demonstration of implicit learning is the human ability to unconsciously detect and internalize statistical patterns of complex environmental input. This ability, called statistical learning, has been investigated in people with dyslexia using various tasks in different orthographies. However, conclusions regarding impaired or intact…

In Germany enrolment in majors is of considerable interest to academic departments, because their budget depends on the number of enrolled students. Besides observed factors, we presume that unobserved latent variables influence the major-choice decision of students. Using stated preferences data from a discrete choice experiment among students…

Over the past decade, identifying how schools might reduce student absenteeism has moved to the forefront of education policy. Yet little research has examined whether school type itself is important. We focus on the influence of Catholic schools using data from the past decade--the most relevant policy context for addressing absenteeism. The…

The study of mind-wandering is popular since it is linked to the emotional problems and working/learning performance. In terms of education, it impacts comprehension during learning which affects academic success. Therefore, we sought to develop a machine learning model for an embedded portable device that can categorize mind-wandering state to…

Language is a quintessentially human trait. Many decades of neurolinguistic research provided evidence of neural structures which specialize in complex linguistic and cognitive processes supporting human communications. Because the world is multilingual, (Crystal, 2010; de Bot, 2019) a prominent question related to brain processes supporting…

This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…

Suicide is a major cause of death in American youth. Suicide risk assessment is a promising suicide prevention strategy; however, little is known about school-based suicide risk assessment practices. The purpose of this study was to examine the scope of standardization, comprehensiveness, and follow-up procedures as part of the suicide risk…

Computational models of child language development can help us understand the cognitive underpinnings of the language learning process, which occurs along several linguistic levels at once (e.g., prosodic and phonological). However, in light of the replication crisis, modelers face the challenge of selecting representative and consolidated infant…

Adjacent category logit models are ordered regression models that focus on comparisons of adjacent categories. These models are particularly useful for ordinal response variables with categories that are of substantive interest. In this article, we consider unconstrained and constrained versions of the partial adjacent category logit model, which…

This paper concerns an investigation of the manner in which typicality constrains graded membership in antonymous dimensional adjectives such as "short/tall" and "cheap/expensive" using the conceptual spaces framework. In this framework, items are organized in a space comprised of one or more dimensions along which they can be…