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Title: What forms the chunks in a subject's performance? Lessons from the CHREST computational model of learning
Authors: Lane, PCR
Gobet, F
Cheng, PCH
Keywords: Computational modeling
magical number
short-term memory
visual short-term memory
Publication Date: 2001
Publisher: Cambridge University Press
Citation: Behavioural and Brain Sciences, 24, 128-129.
Abstract: Computational models of learning provide an alternative technique for identifying the number and type of chunks used by a subject in a specific task. Results from applying CHREST to chess expertise support the theoretical framework of Cowan and a limit in visual short-term memory capacity of 3-4 items. An application to learning from diagrams illustrates different identifiable forms of chunk.
Appears in Collections:Design
School of Engineering and Design Research papers
Advanced Manufacturing and Enterprise Engineering (AMEE)
Dept of Life Sciences Research Papers

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