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

Agnes Tellings*, Karien Coppens, John Gelissen, Rob Schreuder

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


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.
Original languageEnglish
Pages (from-to)461-481
JournalApplied Psycholinguistics
Issue number3
Publication statusPublished - Jul 2013
Externally publishedYes

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