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…

Response process data have the potential to provide a rich description of test-takers' thinking processes. However, retrieving insights from these data presents a challenge for educational assessments and educational data mining as they are complex and not well annotated. The present study addresses this challenge by developing a computational…

Children with autism spectrum disorder (ASD) sometimes have difficulties learning categories. Past computational work suggests that such deficits may result from atypical representations in cortical maps. Here we use neural networks to show that idiosyncratic transformations of inputs can result in the formation of feature maps that impair…

Most natural domains can be represented in multiple ways: we can categorize foods in terms of their nutritional content or social role, animals in terms of their taxonomic groupings or their ecological niches, and musical instruments in terms of their taxonomic categories or social uses. Previous approaches to modeling human categorization have…

Many theories of human cognition postulate that people are equipped with a repertoire of strategies to solve the tasks they face. This theoretical framework of a cognitive toolbox provides a plausible account of intra- and interindividual differences in human behavior. Unfortunately, it is often unclear how to rigorously test the toolbox…

Recent literature has argued that whereas remembering the past and imagining the future make use of shared cognitive substrates, simulating future events places heavier demands on executive resources. These propositions were explored in 3 experiments comparing the impact of imagery and concurrent task demands on speed and accuracy of past event…

Signal detection theory forms the core of many current models of cognition, including memory, choice, and categorization. However, the classic signal detection model presumes the a priori existence of fixed stimulus representations--usually Gaussian distributions--even when the observer has no experience with the task. Furthermore, the classic…

This article introduces "expertise-based training" (XBT) as an instructional design theory that draws on the theories, findings, and methods of expertise research in order to create instructional strategies that can hasten the development of advanced learners into experts. The central tenants of XBT are: 1) Key cognitive sub-skills that…

A biologically detailed computational model is described of how categorization judgments become automatic in tasks that depend on procedural learning. The model assumes 2 neural pathways from sensory association cortex to the premotor area that mediates response selection. A longer and slower path projects to the premotor area via the striatum,…

Three developmental connectionist models simulate a purported shift from "featural" to "correlational" processing in infant categorization (models: Gureckis & Love, 2004/this issue; Shultz & Cohen, 2004/this issue; Westermann & Mareschal, 2004/this issue; empirical data: Cohen & Arthur, 2003; Younger, 1985; Younger & Cohen, 1986). In this article,…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…