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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
Hu, Mingjia; Nosofsky, Robert M. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
In a novel version of the classic dot-pattern prototype-distortion paradigm of category learning, Homa et al. (2019) tested a condition in which individual training instances never repeated, and observed results that they claimed severely challenged exemplar models of classification and recognition. Among the results was a dissociation in which…
Descriptors: Classification, Recognition (Psychology), Computation, Models
Lyniesha Chanell Wright – ProQuest LLC, 2020
Effectively mastering organic chemistry means having the ability to recognize structural patterns, identify properties or behaviors as a result of patterns, manipulate and transform representations, and predict future outcomes. Often students rely on rote memorization of seemingly disconnected information instead of developing a sound…
Descriptors: Organic Chemistry, Science Instruction, Visualization, Models
French, Robert M.; Addyman, Caspar; Mareschal, Denis – Psychological Review, 2011
Individuals of all ages extract structure from the sequences of patterns they encounter in their environment, an ability that is at the very heart of cognition. Exactly what underlies this ability has been the subject of much debate over the years. A novel mechanism, implicit chunk recognition (ICR), is proposed for sequence segmentation and chunk…
Descriptors: Infants, Probability, Learning Processes, Pattern Recognition
Dunphy, Bruce C.; Williamson, Stacey L. – Advances in Health Sciences Education, 2004
Firstly, the many characteristics of expertise are examined: they include aspects of pattern recognition, knowledge, skill, flexibility, metacognitive monitoring, available cognitive space and teaching abilities. Secondly, three educational models from different domains(Nursing, Surgical Education, Education) are analysed, compared and contrasted,…
Descriptors: Expertise, Pattern Recognition, Learning Processes, Teaching Methods
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers