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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
Matusevych, Yevgen; Schatz, Thomas; Kamper, Herman; Feldman, Naomi H.; Goldwater, Sharon – Cognitive Science, 2023
In the first year of life, infants' speech perception becomes attuned to the sounds of their native language. This process of early phonetic learning has traditionally been framed as phonetic category acquisition. However, recent studies have hypothesized that the attunement may instead reflect a perceptual space learning process that does not…
Descriptors: Infants, Phonetics, Language Acquisition, Speech Communication
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
Morse, Anthony F.; Cangelosi, Angelo – Cognitive Science, 2017
Most theories of learning would predict a gradual acquisition and refinement of skills as learning progresses, and while some highlight exponential growth, this fails to explain why natural cognitive development typically progresses in stages. Models that do span multiple developmental stages typically have parameters to "switch" between…
Descriptors: Vocabulary Development, Language Acquisition, Language Processing, Learning Theories
Ecker, Ullrich K. H.; Brown, Gordon D. A.; Lewandowsky, Stephan – Cognitive Science, 2015
Is consolidation needed to account for retroactive interference in free recall? Interfering mental activity during the retention interval of a memory task impairs performance, in particular if the interference occurs in temporal proximity to the encoding of the to-be-remembered (TBR) information. There are at least two rival theoretical accounts…
Descriptors: Interference (Learning), Cognitive Processes, Recall (Psychology), Task Analysis
Temperley, David – Cognitive Science, 2008
This study presents a probabilistic model of melody perception, which infers the key of a melody and also judges the probability of the melody itself. The model uses Bayesian reasoning: For any "surface" pattern and underlying "structure," we can infer the structure maximizing P(structure [vertical bar] surface) based on knowledge of P(surface,…
Descriptors: Expectation, Intervals, Probability, Information Retrieval
Son, Lisa K.; Sethi, Rajiv – Cognitive Science, 2006
The notion of optimality is often invoked informally in the literature on metacognitive control. We provide a precise formulation of the optimization problem and show that optimal time allocation strategies depend critically on certain characteristics of the learning environment, such as the extent of time pressure, and the nature of the uptake…
Descriptors: Metacognition, Educational Environment, Time Management, Competence

Rumelhart, David E.; Zipser, David – Cognitive Science, 1985
Reports results of studies with an unsupervised learning paradigm called competitive learning which is examined using computer simulation and formal analysis. When competitive learning is applied to parallel networks of neuron-like elements, many potentially useful learning tasks can be accomplished. (Author)
Descriptors: Artificial Intelligence, Cognitive Processes, Computer Simulation, Input Output