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Anton Rogachev; Tatiana Logvinenko; Anna Rebreikina; Olga Sysoeva – Cognitive Science, 2025
Visual statistical learning (visual SL) is the ability to implicitly extract statistical patterns from visual stimuli. Visual SL could be assessed using online measures, evaluating reaction times (RTs) to stimuli during task performance, and offline measures, which assess recognition of the presented patterns. We examined 96 children aged 3-9…
Descriptors: Visual Learning, Visual Stimuli, Statistics, Reaction Time
Stefan Depeweg; Contantin A. Rothkopf; Frank Jäkel – Cognitive Science, 2024
More than 50 years ago, Bongard introduced 100 visual concept learning problems as a challenge for artificial vision systems. These problems are now known as Bongard problems. Although they are well known in cognitive science and artificial intelligence, only very little progress has been made toward building systems that can solve a substantial…
Descriptors: Visual Learning, Problem Solving, Cognitive Science, Artificial Intelligence
Siegelman, Noam; Bogaerts, Louisa; Kronenfeld, Ofer; Frost, Ram – Cognitive Science, 2018
From a theoretical perspective, most discussions of statistical learning (SL) have focused on the possible "statistical" properties that are the object of learning. Much less attention has been given to defining what "learning" is in the context of "statistical learning." One major difficulty is that SL research has…
Descriptors: Statistics, Learning Processes, Visual Learning, Learning Modalities
Shufaniya, Amir; Arnon, Inbal – Cognitive Science, 2018
Humans are capable of extracting recurring patterns from their environment via statistical learning (SL), an ability thought to play an important role in language learning and learning more generally. While much work has examined statistical learning in infants and adults, less work has looked at the developmental trajectory of SL during childhood…
Descriptors: Statistics, Mathematics Education, Multisensory Learning, Aural Learning
Primativo, Silvia; Reilly, Jamie; Crutch, Sebastian J – Cognitive Science, 2017
The Abstract Conceptual Feature (ACF) framework predicts that word meaning is represented within a high-dimensional semantic space bounded by weighted contributions of perceptual, affective, and encyclopedic information. The ACF, like latent semantic analysis, is amenable to distance metrics between any two words. We applied predictions of the ACF…
Descriptors: Semantics, Prediction, Abstract Reasoning, Eye Movements
Moreton, Elliott; Pater, Joe; Pertsova, Katya – Cognitive Science, 2017
Linguistic and non-linguistic pattern learning have been studied separately, but we argue for a comparative approach. Analogous inductive problems arise in phonological and visual pattern learning. Evidence from three experiments shows that human learners can solve them in analogous ways, and that human performance in both cases can be captured by…
Descriptors: Phonology, Concept Formation, Learning Processes, Difficulty Level
Giustolisi, Beatrice; Emmorey, Karen – Cognitive Science, 2018
This study investigated visual statistical learning (VSL) in 24 deaf signers and 24 hearing non-signers. Previous research with hearing individuals suggests that SL mechanisms support literacy. Our first goal was to assess whether VSL was associated with reading ability in deaf individuals, and whether this relation was sustained by a link between…
Descriptors: Deafness, Hearing Impairments, Task Analysis, Correlation

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