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Showing all 13 results Save | Export
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Eva Viviani; Michael Ramscar; Elizabeth Wonnacott – Cognitive Science, 2024
Ramscar, Yarlett, Dye, Denny, and Thorpe (2010) showed how, consistent with the predictions of error-driven learning models, the order in which stimuli are presented in training can affect category learning. Specifically, learners exposed to artificial language input where objects preceded their labels learned the discriminating features of…
Descriptors: Symbolic Learning, Learning Processes, Artificial Intelligence, Prediction
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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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Švábenský, Valdemar; Baker, Ryan S.; Zambrano, Andrés; Zou, Yishan; Slater, Stefan – International Educational Data Mining Society, 2023
Students who take an online course, such as a MOOC, use the course's discussion forum to ask questions or reach out to instructors when encountering an issue. However, reading and responding to students' questions is difficult to scale because of the time needed to consider each message. As a result, critical issues may be left unresolved, and…
Descriptors: Generalization, Computer Mediated Communication, MOOCs, State Universities
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Dyson, Bronwen – Second Language Research, 2023
This article enters the debate about the complex and dynamical nature of second language acquisition (SLA) by discussing and commenting on Pallotti's critique of Complex Dynamic Systems Theory (CDST). Pallotti's critique brings to the fore the argument that, due to its anti-reductionist stance, CDST research fails to observe three fundamental…
Descriptors: Second Language Learning, Language Processing, Linguistic Theory, Language Research
Jennifer Hu – ProQuest LLC, 2023
Language is one of the hallmarks of intelligence, demanding explanation in a theory of human cognition. However, language presents unique practical challenges for quantitative empirical research, making many linguistic theories difficult to test at naturalistic scales. Artificial neural network language models (LMs) provide a new tool for studying…
Descriptors: Linguistic Theory, Computational Linguistics, Models, Language Research
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Lui, Kelvin F. H.; Lo, Jason C. M.; Maurer, Urs; Ho, Connie S.-H.; McBride, Catherine – Developmental Science, 2021
Research on what neural mechanisms facilitate word reading development in non-alphabetic scripts is relatively rare. The present study was among the first to adopt a multivariate pattern classification analysis to decode electroencephalographic signals recorded for primary school children (N = 236) while performing a Chinese character decision…
Descriptors: Decoding (Reading), Chinese, Cognitive Processes, Elementary School Students
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Radulescu, Silvia; Wijnen, Frank; Avrutin, Sergey – Language Learning and Development, 2020
From limited evidence, children track the regularities of their language impressively fast and they infer generalized rules that apply to novel instances. This study investigated what drives the inductive leap from memorizing specific items and statistical regularities to extracting abstract rules. We propose an innovative entropy model that…
Descriptors: Linguistic Input, Language Acquisition, Grammar, Learning Processes
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Ambridge, Ben; Blything, Ryan P. – Journal of Child Language, 2016
A central question in language acquisition is how children build linguistic representations that allow them to generalize verbs from one construction to another (e.g., "The boy gave a present to the girl" ? "The boy gave the girl a present"), whilst appropriately constraining those generalizations to avoid non-adultlike errors…
Descriptors: Child Language, Language Acquisition, Verbs, Generalization
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Wigestrand, Mattis B.; Schiff, Hillary C.; Fyhn, Marianne; LeDoux, Joseph E.; Sears, Robert M. – Learning & Memory, 2017
Distinguishing threatening from nonthreatening stimuli is essential for survival and stimulus generalization is a hallmark of anxiety disorders. While auditory threat learning produces long-lasting plasticity in primary auditory cortex (Au1), it is not clear whether such Au1 plasticity regulates memory specificity or generalization. We used…
Descriptors: Memory, Brain Hemisphere Functions, Stimuli, Generalization
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Lawson, Chris A.; Fisher, Anna V.; Rakison, David H. – Journal of Cognition and Development, 2015
Young children are able to categorize animals on the basis of unobservable features such as shared biological properties (e.g., bones). For the most part, children learn about these properties through explicit verbalizations from others. The present study examined how such input impacts children's learning about the properties of categories. In a…
Descriptors: Toddlers, Animals, Classification, Prediction
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Lowie, Wander; van Dijk, Marijn; Chan, Huiping; Verspoor, Marjolijn – Studies in Second Language Learning and Teaching, 2017
A large body studies into individual differences in second language learning has shown that success in second language learning is strongly affected by a set of relevant learner characteristics ranging from the age of onset to motivation, aptitude, and personality. Most studies have concentrated on a limited number of learner characteristics and…
Descriptors: Second Language Learning, Individual Differences, Learning Motivation, Personality Traits
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Ahn, Woo-Young; Busemeyer, Jerome R.; Wagenmakers, Eric-Jan; Stout, Julie C. – Cognitive Science, 2008
It is a hallmark of a good model to make accurate "a priori" predictions to new conditions (Busemeyer & Wang, 2000). This study compared 8 decision learning models with respect to their generalizability. Participants performed 2 tasks (the Iowa Gambling Task and the Soochow Gambling Task), and each model made a priori predictions by estimating the…
Descriptors: Prediction, Generalization, Models, Comparative Analysis
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
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…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection