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LEXICAL AND SYNTACTIC PREDICTION WITHIN A NOISY CHANNEL MODEL OF LANGUAGE COMPREHENSION

Colvin, Michelle B. (2017) LEXICAL AND SYNTACTIC PREDICTION WITHIN A NOISY CHANNEL MODEL OF LANGUAGE COMPREHENSION. Master's Thesis, University of Pittsburgh. (Unpublished)

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Abstract

The present paper explored adaptation of prediction within a noisy channel framework of language comprehension. Three experiments examined whether adaptation of reliance on lexical and/or syntactic predictive cues occurs across contexts in which there is a change in the informativity of these cues. Within a single experimental session (Exp. 1, n=44) and across experiments (Exp. 2, n= 45; Exp. 3, n= 92), there was no evidence that participants adapted their reliance on a lexical cue, as subjects predicted specific words within highly-constraining sentences at an equal rate across contexts which supported and violated this expectation. Furthermore, it was found that participants only adapted and relied less on a syntactic cue in the violating context within Experiment 3, in which a stronger violating cue was used for the expectation of an either...or sentence structure than the violating cue used in the first two experiments. Results suggest that the combination of a strong predictive cue and a strong violation of that cue is necessary to elicit adaptation. Further research is needed to investigate how and when readers adapt their prediction during language comprehension.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Colvin, Michelle B.mbh32@pitt.edumbh320000-0002-6594-9474
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairWarren, Tessatessa@pitt.edu
Committee MemberDickey, Michaelmdickey@pitt.edu
Committee MemberFraundorf, Scottsfraundo@pitt.edu
Date: 15 June 2017
Date Type: Publication
Defense Date: 22 February 2017
Approval Date: 15 June 2017
Submission Date: 3 April 2017
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 64
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Psychology
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: adaptation, comprehension, prediction
Date Deposited: 15 Jun 2017 22:24
Last Modified: 19 Jul 2024 19:05
URI: http://d-scholarship.pitt.edu/id/eprint/31196

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