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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
Divjak, Dagmar; Milin, Petar – Cognitive Science, 2020
While the effects of pattern learning on language processing are well known, the way in which pattern learning shapes exploratory behavior has long gone unnoticed. We report on the way in which individual differences in statistical pattern learning affect performance in the domain of language along multiple dimensions. Analyzing data from healthy…
Descriptors: Statistics, Pattern Recognition, Behavior, Individual Characteristics