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Foundations of Vocabulary : = Does Statistical Segmentation of Events Contribute to Word Learning?

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Foundations of Vocabulary :/
Reminder of title:	Does Statistical Segmentation of Events Contribute to Word Learning?
Author:	Levine, Dani F.
Description:	1 online resource (94 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 79-05(E), Section: B.
Contained By:	Dissertation Abstracts International79-05B(E).
Subject:	Psychology. -
Online resource:	click for full text (PQDT)
ISBN:	9780355588743

Foundations of Vocabulary : = Does Statistical Segmentation of Events Contribute to Word Learning?
Levine, Dani F.

Foundations of Vocabulary :Does Statistical Segmentation of Events Contribute to Word Learning? - 1 online resource (94 pages)

Source: Dissertation Abstracts International, Volume: 79-05(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

This dissertation evaluates the untested assumption that the individuation of events into units matters for word learning, particularly the learning of terms which map onto relational event units (Gentner & Boroditsky, 2001; Maguire et al., 2006). We predicted that 3-year-old children's statistical action segmentation abilities would relate to their verb comprehension and to their overall vocabulary knowledge (Research Question 1). We also hypothesized that statistical action segmentation would facilitate children's learning of novel verbs (Research Question 2).

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355588743Subjects--Topical Terms:

555998
Psychology.
Index Terms--Genre/Form:

554714
Electronic books.

Foundations of Vocabulary : = Does Statistical Segmentation of Events Contribute to Word Learning?
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100 1 $a Levine, Dani F. $3 1184045
245 1 0 $a Foundations of Vocabulary : $b Does Statistical Segmentation of Events Contribute to Word Learning?
264 0 $c 2017
300 $a 1 online resource (94 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 79-05(E), Section: B.
500 $a Adviser: Kathy Hirsh-Pasek.
502 $a Thesis (Ph.D.) $c Temple University $d 2017.
504 $a Includes bibliographical references
520 $a This dissertation evaluates the untested assumption that the individuation of events into units matters for word learning, particularly the learning of terms which map onto relational event units (Gentner & Boroditsky, 2001; Maguire et al., 2006). We predicted that 3-year-old children's statistical action segmentation abilities would relate to their verb comprehension and to their overall vocabulary knowledge (Research Question 1). We also hypothesized that statistical action segmentation would facilitate children's learning of novel verbs (Research Question 2).
520 $a Largely confirming our first prediction, children who were better able to statistically segment novel action sequences into reliable units had more sophisticated overall vocabularies and were quicker to select the correct referents of overall vocabulary items and verb vocabulary items; nevertheless, they did not have larger verb vocabularies. Unexpectedly, statistical action segmentation did not facilitate children's learning of verbs for statistically consistent action units. However, children showed greater learning of verbs labeling statistical action part-units than verbs labeling statistical action non-units, providing some evidence for our second prediction. In sum, this dissertation takes an important step towards understanding how event segmentation may contribute to vocabulary acquisition.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Psychology. $3 555998
650 4 $a Developmental psychology. $3 557458
650 4 $a Cognitive psychology. $3 556029
650 4 $a Linguistics. $3 557829
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710 2 $a Temple University. $b Psychology. $3 1184046
773 0 $t Dissertation Abstracts International $g 79-05B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10641522 $z click for full text (PQDT)