Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 9 |
Since 2016 (last 10 years) | 16 |
Since 2006 (last 20 years) | 33 |
Descriptor
Generalization | 33 |
Classification | 10 |
Learning Processes | 10 |
Models | 10 |
Comparative Analysis | 7 |
Prediction | 7 |
Cognitive Processes | 6 |
Language Acquisition | 6 |
Logical Thinking | 6 |
Bayesian Statistics | 5 |
Learning | 5 |
More ▼ |
Source
Cognitive Science | 33 |
Author
Gelman, Susan A. | 2 |
Griffiths, Thomas L. | 2 |
Lee, Michael D. | 2 |
Wagenmakers, Eric-Jan | 2 |
Ahn, Woo-Young | 1 |
Ambridge, Ben | 1 |
Arbib, Michael | 1 |
Arnoldi, Jakob | 1 |
Arnon, Inbal | 1 |
Austerweil, Joseph L. | 1 |
Baer-Henney, Dinah | 1 |
More ▼ |
Publication Type
Journal Articles | 33 |
Reports - Research | 29 |
Reports - Descriptive | 2 |
Reports - Evaluative | 2 |
Education Level
Higher Education | 1 |
Postsecondary Education | 1 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Tylén, Kristian; Fusaroli, Riccardo; Østergaard, Sara Møller; Smith, Pernille; Arnoldi, Jakob – Cognitive Science, 2023
Capacities for abstract thinking and problem-solving are central to human cognition. Processes of abstraction allow the transfer of experiences and knowledge between contexts helping us make informed decisions in new or changing contexts. While we are often inclined to relate such reasoning capacities to individual minds and brains, they may in…
Descriptors: Abstract Reasoning, Thinking Skills, Problem Solving, Transfer of Training
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
Peters, Uwe; Krauss, Alexander; Braganza, Oliver – Cognitive Science, 2022
Many scientists routinely generalize from study samples to larger populations. It is commonly assumed that this cognitive process of scientific induction is a voluntary inference in which researchers assess the generalizability of their data and then draw conclusions accordingly. We challenge this view and argue for a novel account. The account…
Descriptors: Sciences, Bias, Generalization, Cognitive Processes
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
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
Austerweil, Joseph L.; Sanborn, Sophia; Griffiths, Thomas L. – Cognitive Science, 2019
Generalization is a fundamental problem solved by every cognitive system in essentially every domain. Although it is known that how people generalize varies in complex ways depending on the context or domain, it is an open question how people "learn" the appropriate way to generalize for a new context. To understand this capability, we…
Descriptors: Generalization, Logical Thinking, Inferences, Bayesian Statistics
Dasgupta, Ishita; Guo, Demi; Gershman, Samuel J.; Goodman, Noah D. – Cognitive Science, 2020
As modern deep networks become more complex, and get closer to human-like capabilities in certain domains, the question arises as to how the representations and decision rules they learn compare to the ones in humans. In this work, we study representations of sentences in one such artificial system for natural language processing. We first present…
Descriptors: Natural Language Processing, Man Machine Systems, Heuristics, Sentences
Zhang, Yayun; Yurovsky, Daniel; Yu, Chen – Cognitive Science, 2021
Recent laboratory experiments have shown that both infant and adult learners can acquire word-referent mappings using cross-situational statistics. The vast majority of the work on this topic has used unfamiliar objects presented on neutral backgrounds as the visual contexts for word learning. However, these laboratory contexts are much different…
Descriptors: Cognitive Mapping, Language Acquisition, Linguistic Input, Generalization
Richie, Russell; Bhatia, Sudeep – Cognitive Science, 2021
Similarity is one of the most important relations humans perceive, arguably subserving category learning and categorization, generalization and discrimination, judgment and decision making, and other cognitive functions. Researchers have proposed a wide range of representations and metrics that could be at play in similarity judgment, yet have not…
Descriptors: Classification, Generalization, Decision Making, Cognitive Processes
Ito, Chiyuki; Feldman, Naomi H. – Cognitive Science, 2022
Iterated learning models of language evolution have typically been used to study the emergence of language, rather than historical language change. We use iterated learning models to investigate historical change in the accent classes of two Korean dialects. Simulations reveal that many of the patterns of historical change can be explained as…
Descriptors: Diachronic Linguistics, Sociolinguistics, Comparative Analysis, Models
Sloman, Sabina J.; Goldstone, Robert L.; Gonzalez, Cleotilde – Cognitive Science, 2021
How do people use information from others to solve complex problems? Prior work has addressed this question by placing people in social learning situations where the problems they were asked to solve required varying degrees of exploration. This past work uncovered important interactions between groups' "connectivity" and the problem's…
Descriptors: Cooperative Learning, Problem Solving, Information Utilization, Models
Chin-Parker, Seth; Cantelon, Julie – Cognitive Science, 2017
This paper provides evidence for a contrastive account of explanation that is motivated by pragmatic theories that recognize the contribution that context makes to the interpretation of a prompt for explanation. This study replicates the primary findings of previous work in explanation-based category learning (Williams & Lombrozo, 2010),…
Descriptors: Context Effect, Prompting, Generalization, Classification
Ger, Ebru; You, Guanghao; Küntay, Aylin C.; Göksun, Tilbe; Stoll, Sabine; Daum, Moritz M. – Cognitive Science, 2022
Becoming productive with grammatical categories is a gradual process in children's language development. Here, we investigated this transition process by focusing on Turkish causatives. Previous research examining spontaneous and elicited production of Turkish causatives with familiar verbs attested the onset and early stages of productivity at…
Descriptors: Turkish, Morphology (Languages), Longitudinal Studies, Computational Linguistics
Culicover, Peter W. – Cognitive Science, 2017
In Jackendoff's Parallel Architecture, the well-formed expressions of a language are licensed by correspondences between phonology, syntax, and conceptual structure. I show how this architecture can be used to make sense of the existence of parasitic gap constructions. A parasitic gap is one that is rendered acceptable because of the presence of…
Descriptors: Syntax, Psycholinguistics, Linguistic Theory, Phrase Structure
Silvey, Catriona; Kirby, Simon; Smith, Kenny – Cognitive Science, 2015
Words refer to objects in the world, but this correspondence is not one-to-one: Each word has a range of referents that share features on some dimensions but differ on others. This property of language is called underspecification. Parts of the lexicon have characteristic patterns of underspecification; for example, artifact nouns tend to specify…
Descriptors: Definitions, Learning, Language Usage, Diachronic Linguistics