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Johnson, Tamar; Siegelman, Noam; Arnon, Inbal – Cognitive Science, 2020
Over the last decade, iterated learning studies have provided compelling evidence for the claim that linguistic structure can emerge from non-structured input, through the process of transmission. However, it is unclear whether individuals differ in their tendency to add structure, an issue with implications for understanding who are the agents of…
Descriptors: Individual Differences, Cognitive Ability, Learning Processes, Language Acquisition
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Poletiek, Fenna H.; Conway, Christopher M.; Ellefson, Michelle R.; Lai, Jun; Bocanegra, Bruno R.; Christiansen, Morten H. – Cognitive Science, 2018
It has been suggested that external and/or internal limitations paradoxically may lead to superior learning, that is, the concepts of "starting small" and "less is more" (Elman, 1993; Newport, 1990). In this paper, we explore the type of incremental ordering during training that might help learning, and what mechanism explains…
Descriptors: Grammar, Artificial Languages, Learning Processes, Teaching Methods
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Lloyd, Kevin; Sanborn, Adam; Leslie, David; Lewandowsky, Stephan – Cognitive Science, 2019
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…
Descriptors: Short Term Memory, Bayesian Statistics, Cognitive Ability, Individual Differences
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Minier, Laure; Fagot, Joël; Rey, Arnaud – Cognitive Science, 2016
Extracting the regularities of our environment is one of our core cognitive abilities. To study the fine-grained dynamics of the extraction of embedded regularities, a method combining the advantages of the artificial language paradigm (Saffran, Aslin, & Newport, [Saffran, J. R., 1996]) and the serial response time task (Nissen & Bullemer,…
Descriptors: Artificial Languages, Cognitive Ability, Language Patterns, Primatology
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Hullinger, Richard A.; Kruschke, John K.; Todd, Peter M. – Cognitive Science, 2015
Humans and many other species selectively attend to stimuli or stimulus dimensions--but why should an animal constrain information input in this way? To investigate the adaptive functions of attention, we used a genetic algorithm to evolve simple connectionist networks that had to make categorization decisions in a variety of environmental…
Descriptors: Attention, Genetics, Environmental Influences, Simulation
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Potter, Christine E.; Wang, Tianlin; Saffran, Jenny R. – Cognitive Science, 2017
Recent research has begun to explore individual differences in statistical learning, and how those differences may be related to other cognitive abilities, particularly their effects on language learning. In this research, we explored a different type of relationship between language learning and statistical learning: the possibility that learning…
Descriptors: Second Language Learning, Learning Experience, Mandarin Chinese, Control Groups
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Salvucci, Dario D. – Cognitive Science, 2013
Previous accounts of cognitive skill acquisition have demonstrated how procedural knowledge can be obtained and transformed over time into skilled task performance. This article focuses on a complementary aspect of skill acquisition, namely the integration and reuse of previously known component skills. The article posits that, in addition to…
Descriptors: Cognitive Ability, Skill Development, Transfer of Training, Task Analysis