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Academic Paper

Title: Clusters of word properties as predictors of elementary school children's performance on two word tasks
Author: Agnes Tellings
Institution: Radboud Universiteit Nijmegen
Author: Karien Coppens
Institution: Radboud Universiteit Nijmegen
Author: John Gelissen
Institution: Tilburg University
Author: Robert Schreuder
Institution: Radboud Universiteit Nijmegen
Linguistic Field: Psycholinguistics
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.


This article appears IN Applied Psycholinguistics Vol. 34, Issue 3, which you can READ on Cambridge's site or on LINGUIST .

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