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Effective scheduling of looking and talking during rapid automatized naming.
Author(s) -
Peter C. Gordon,
Renske S. Hoedemaker
Publication year - 2015
Publication title -
journal of experimental psychology human perception and performance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.691
H-Index - 148
eISSN - 1939-1277
pISSN - 0096-1523
DOI - 10.1037/xhp0000171
Subject(s) - ran , rapid automatized naming , sentence , eye movement , cognitive psychology , cognition , reading (process) , psychology , cognitive resource theory , task (project management) , literacy , computer science , linguistics , phonological awareness , natural language processing , computer network , pedagogy , philosophy , management , neuroscience , economics
Rapid automatized naming (RAN) is strongly related to literacy gains in developing readers, reading disabilities, and reading ability in children and adults. Because successful RAN performance depends on the close coordination of a number of abilities, it is unclear what specific skills drive this RAN-reading relationship. The current study used concurrent recordings of young adult participants' vocalizations and eye movements during the RAN task to assess how individual variation in RAN performance depends on the coordination of visual and vocal processes. Results showed that fast RAN times are facilitated by having the eyes 1 or more items ahead of the current vocalization, as long as the eyes do not get so far ahead of the voice as to require a regressive eye movement to an earlier item. These data suggest that optimizing RAN performance is a problem of scheduling eye movements and vocalization given memory constraints and the efficiency of encoding and articulatory control. Both RAN completion time (conventionally used to indicate RAN performance) and eye-voice relations predicted some aspects of participants' eye movements on a separate sentence reading task. However, eye-voice relations predicted additional features of first-pass reading that were not predicted by RAN completion time. This shows that measurement of eye-voice patterns can identify important aspects of individual variation in reading that are not identified by the standard measure of RAN performance. We argue that RAN performance predicts reading ability because both tasks entail challenges of scheduling cognitive and linguistic processes that operate simultaneously on multiple linguistic inputs.

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