Background: Cognitive rehabilitation is a complex and specialized area of practice, as it aims to support individuals with diverse neuropsychological profiles, personal characteristics, and intersectionalities in achieving meaningful, functional change in personally relevant aspects of their everyday lives. In many ways, cognitive rehabilitation…

The challenge posed by algebra story problems creates a significant hurdle for many students, transcending both the mathematical content of the problem and the specific instructional background received. This study offers a distinctive contribution to the existing literature by focusing on the cognitive conditions essential for comprehension in…

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…

Though efforts have been made for centuries, how concepts are represented in the brain is still elusive. The embodiment view claims that the sensory, motor and other brain areas through which people acquire concept information during life experiences represent this information during concept retrieval. Some compelling neurobiological evidence…

Criticisms about psychometric paradigms currently used in healthcare professions education include claims of reductionism, objectification, and poor compliance with assumptions. Nevertheless, perhaps the most crucial criticism comes from learners' difficulty in interpreting and making meaningful use of summative scores and the potentially…

Behavioral evidence for the COVIS dual-process model of category learning has been widely reported in over a hundred publications (Ashby & Valentin, 2016). It is generally accepted that the validity of such evidence depends on the accurate identification of individual participants' categorization strategies, a task that usually falls to…

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…

Although Diagnostic Classification Models (DCMs) were introduced to education system decades ago, it seems that these models were not employed for the original aims upon which they had been designed. Using DCMs has been mostly common in analyzing large-scale non-diagnostic tests and these models have been rarely used in developing Cognitive…

Feedback on student answers and even during intermediate steps in their solutions to open-ended questions is an important element in math education. Such feedback can help students correct their errors and ultimately lead to improved learning outcomes. Most existing approaches for automated student solution analysis and feedback require manually…

Cognitive diagnosis models are diagnostic models used to classify respondents into homogenous groups based on multiple categorical latent variables representing the measured cognitive attributes. This study aims to present longitudinal models for cognitive diagnosis modeling, which can be applied to repeated measurements in order to monitor…

The development of visual expertise is accompanied by enhanced visual object recognition memory within an expert domain. We aimed to understand the relationship between expertise and memory by modeling cognitive mechanisms. Participants with a measured range of birding expertise were recruited and tested on memory for birds (expert domain) and…

We investigated the classification accuracy of learning disability (LD) identification methods premised on the identification of an intraindividual pattern of processing strengths and weaknesses (PSW) method using multiple indicators for all latent constructs. Known LD status was derived from latent scores; values at the observed level identified…

Existing personalized learning systems (PLSs) have primarily focused on providing learning analytics using data from learners. In this paper, we extend the capability of current PLSs by incorporating data from instructors. We propose a latent factor model that analyzes instructors' preferences in explicitly "excluding" particular…

There has been considerable debate in the literature about the relative merits of information processing versus dynamical approaches to understanding cognitive processes. In this article, we explore the relationship between these two styles of explanation using a model agent evolved to solve a relational categorization task. Specifically, we…

Linguistic and non-linguistic pattern learning have been studied separately, but we argue for a comparative approach. Analogous inductive problems arise in phonological and visual pattern learning. Evidence from three experiments shows that human learners can solve them in analogous ways, and that human performance in both cases can be captured by…