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Clusters of word properties as predictors of elementary school children's performance on two word tasks

Published online by Cambridge University Press:  21 December 2011

AGNES TELLINGS ,
KARIEN COPPENS ,
JOHN GELISSEN  and
ROB SCHREUDER
AGNES TELLINGS*
Affiliation:
Radboud University
KARIEN COPPENS
Affiliation:
Radboud University
JOHN GELISSEN
Affiliation:
Tilburg University
ROB SCHREUDER
Affiliation:
Radboud University
*
ADDRESS FOR CORRESPONDENCE Agnes Tellings, Behavioural Science Institute, Radboud University, Montessorilaan 3, P.O. Box 9104, 6500 HE Nijmegen, The Netherlands. E-mail: a.tellings@ru.nl
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Abstract

Often, the classification of words does not go beyond “difficult” (i.e., infrequent, late-learned, nonimageable, etc.) or “easy” (i.e., frequent, early-learned, imageable, etc.) words. In the present study, we used a latent cluster analysis to divide 703 Dutch words with scores for eight word properties into seven clusters of words. Each cluster represents a group of words that share a particular configuration of word properties. This model was empirically validated with three data sets from Grades 2 to 4 children who made either a lexical decision task or a use decision task with a selection of the words. Significant differences were found between the clusters of words within the three data sets. Implications for further study and for practice are discussed.

Type
Articles
Information
Applied Psycholinguistics , Volume 34 , Issue 3 , May 2013 , pp. 461 - 481
Copyright
Copyright © Cambridge University Press 2011 

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