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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.

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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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