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Li, Michael Y.; Callaway, Fred; Thompson, William D.; Adams, Ryan P.; Griffiths, Thomas L. – Cognitive Science, 2023
Humans can learn complex functional relationships between variables from small amounts of data. In doing so, they draw on prior expectations about the form of these relationships. In three experiments, we show that people learn to adjust these expectations through experience, learning about the likely forms of the functions they will encounter.…
Descriptors: Learning Processes, Expectation, Experience, Relationship
Sidhu, David M.; Khachatoorian, Nareg; Vigliocco, Gabriella – Cognitive Science, 2023
Iconicity refers to a resemblance between word form and meaning. Previous work has shown that iconic words are learned earlier and processed faster. Here, we examined whether iconic words are recognized better on a recognition memory task. We also manipulated the level at which items were encoded--with a focus on either their meaning or their…
Descriptors: Recognition (Psychology), Memory, Language Usage, Phonology
Schmid, Samuel; Saddy, Douglas; Franck, Julie – Cognitive Science, 2023
In this article, we explore the extraction of recursive nested structure in the processing of binary sequences. Our aim was to determine whether humans learn the higher-order regularities of a highly simplified input where only sequential-order information marks the hierarchical structure. To this end, we implemented a sequence generated by the…
Descriptors: Learning Processes, Sequential Learning, Grammar, Language Processing
Chunking versus Transitional Probabilities: Differentiating between Theories of Statistical Learning
Emerson, Samantha N.; Conway, Christopher M. – Cognitive Science, 2023
There are two main approaches to how statistical patterns are extracted from sequences: The transitional probability approach proposes that statistical learning occurs through the computation of probabilities between items in a sequence. The chunking approach, including models such as PARSER and TRACX, proposes that units are extracted as chunks.…
Descriptors: Statistics Education, Learning Processes, Learning Theories, Pattern Recognition
Eva Portelance; Michael C. Frank; Dan Jurafsky – Cognitive Science, 2024
Interpreting a seemingly simple function word like "or," "behind," or "more" can require logical, numerical, and relational reasoning. How are such words learned by children? Prior acquisition theories have often relied on positing a foundation of innate knowledge. Yet recent neural-network-based visual question…
Descriptors: Vocabulary, Grammar, Visual Aids, Language Acquisition
Rey, Arnaud; Fagot, Joël; Mathy, Fabien; Lazartigues, Laura; Tosatto, Laure; Bonafos, Guillem; Freyermuth, Jean-Marc; Lavigne, Frédéric – Cognitive Science, 2022
The extraction of cooccurrences between two events, A and B, is a central learning mechanism shared by all species capable of associative learning. Formally, the cooccurrence of events A and B appearing in a sequence is measured by the transitional probability (TP) between these events, and it corresponds to the probability of the second stimulus…
Descriptors: Animals, Learning Processes, Associative Learning, Serial Learning
Cheng, Patricia W.; Sandhofer, Catherine M.; Liljeholm, Mimi – Cognitive Science, 2022
The present paper examines a type of abstract domain-general knowledge required for the process of constructing useable domain-specific causal knowledge, the evident goal of causal learning. It tests the hypothesis that analytic knowledge of "causal-invariance decomposition functions" is essential for this process. Such knowledge…
Descriptors: Preschool Children, Learning Processes, Generalization, Heuristics
Bharadwaj, Avni; Dargue, Nicole; Sweller, Naomi – Cognitive Science, 2022
Research has shown that gesture production supports learning across a number of tasks. It is unclear, however, whether gesture production during encoding can support narrative recall, who gesture production benefits most, and whether certain types of gestures are more beneficial than others. This study, therefore, investigated the effect of…
Descriptors: Nonverbal Communication, Recall (Psychology), Cognitive Processes, Verbal Communication
Fabian Tomaschek; Michael Ramscar; Jessie S. Nixon – Cognitive Science, 2024
Sequence learning is fundamental to a wide range of cognitive functions. Explaining how sequences--and the relations between the elements they comprise--are learned is a fundamental challenge to cognitive science. However, although hundreds of articles addressing this question are published each year, the actual learning mechanisms involved in the…
Descriptors: Sequential Learning, Learning Processes, Serial Learning, Executive Function
Chan, Jenny Yun-Chen; Nagashima, Tomohiro; Closser, Avery H. – Cognitive Science, 2023
Given the recent call to strengthen collaboration between researchers and relevant practitioners, we consider participatory design as a way to advance Cognitive Science. Building on examples from the Learning Sciences and Human-Computer Interaction, we (a) explore "what," "why," "who," "when," and…
Descriptors: Cognitive Science, Learning Processes, Man Machine Systems, Cooperation
Dimov, Cvetomir M.; Anderson, John R.; Betts, Shawn A.; Bothell, Dan – Cognitive Science, 2023
We studied collaborative skill acquisition in a dynamic setting with the game Co-op Space Fortress. While gaining expertise, the majority of subjects became increasingly consistent in the role they adopted without being able to communicate. Moreover, they acted in anticipation of the future task state. We constructed a collaborative skill…
Descriptors: Cooperation, Skill Development, Expertise, Role Playing
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
Eliza L. Congdon; Elizabeth M. Wakefield; Miriam A. Novack; Naureen Hemani-Lopez; Susan Goldin-Meadow – Cognitive Science, 2024
Gestures--hand movements that accompany speech and express ideas--can help children learn how to solve problems, flexibly generalize learning to novel problem-solving contexts, and retain what they have learned. But does it matter who is doing the gesturing? We know that producing gesture leads to better comprehension of a message than watching…
Descriptors: Nonverbal Communication, Predictor Variables, Learning Processes, Generalization
Erdin Mujezinovic; Vsevolod Kapatsinski; Ruben van de Vijver – Cognitive Science, 2024
A word often expresses many different morphological functions. Which part of a word contributes to which part of the overall meaning is not always clear, which raises the question as to how such functions are learned. While linguistic studies tacitly assume the co-occurrence of cues and outcomes to suffice in learning these functions (Baer-Henney,…
Descriptors: Morphology (Languages), Phonology, Morphemes, Cues
Hinano Iida; Kimi Akita – Cognitive Science, 2024
Iconicity is a relationship of resemblance between the form and meaning of a sign. Compelling evidence from diverse areas of the cognitive sciences suggests that iconicity plays a pivotal role in the processing, memory, learning, and evolution of both spoken and signed language, indicating that iconicity is a general property of language. However,…
Descriptors: Japanese, Cognitive Science, Language Processing, Memory