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In:Usage-based Perspectives on Language and Language Acquisition: In honour of Heike Behrens
Edited by Karin Madlener-Charpentier, Marjolijn H. Verspoor, Mirjam Weder and Annelies Häcki Buhofer
[Trends in Language Acquisition Research 35] 2026
► pp. 111–140

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Chapter 4
Explaining individual differences in children’s vocabulary growth

Insights from the Language 0–5 Project

Authors
 | Max Planck Institute for Psycholinguistics | Donders Institute for Brain, Cognition and Behaviour
 | Nottingham Trent University
 | Great Ormond Street Hospital for Children NHS Foundation Trust
 | Liverpool John Moores University
 | University of Liverpool
 | University of Manchester
 | University of Liverpool
 | University of Liverpool
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Available under the Creative Commons Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND) 4.0 license.

For any use beyond this license, please contact the publisher at [email protected].

Published online: 21 May 2026
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https://doi.org/10.1075/tilar.35.04row
Abstract
Our goal in this chapter was to test a usage-based computational model of vocabulary learning (CLASSIC). CLASSIC simulates variation in vocabulary growth as a product of interactions between linguistic input quantity and the child’s current knowledge state, using an associative learning mechanism with a fixed capacity limited processing window. We directly compared the model’s results to those from children taking part in a number of empirical tasks and showed that, simply by varying the amount of input received by the model, we can successfully simulate a number of effects that we see in the children’s performance: individual differences in the rate of vocabulary growth between 19 and 30 months of age; correlations between vocabulary size, familiar word processing speed (as measured by Looking-While-Listening tasks) and phonological working memory capacity (as measured by non-word repetition tasks), and the effect of processing speed and non-word repetition performance on subsequent vocabulary growth. The results suggest that exposure to linguistic input, read through a fixed capacity processing constraint, leads learners to store phonological knowledge in chunks of information of varying size, and it is this stored knowledge that, at least partially, determines familiar word processing speed, non-word repetition performance, and vocabulary growth.
Article outline
  • 1.Introduction
    • 1.1Why do children differ in the speed with which they learn words?
    • 1.2Introducing CLASSIC
    • 1.3The present study
  • 2.Method
    • 2.1Participants
    • 2.2Stimuli and procedure
    • 2.3CLASSIC training
    • 2.4Comparing children and models
    • 2.5Coding
  • 3.Results
    • 3.1Vocabulary growth
    • 3.2NWR tasks and vocabulary size
    • 3.3Processing speed task (LWL) and vocabulary size
    • 3.4Processing speed (LWL) and NWR tasks
    • 3.5Predicting vocabulary growth from NWR performance
    • 3.6Predicting vocabulary growth from speed of processing
  • 4.Discussion
  • 5.Conclusion
  • Acknowledgments
  • Notes
  • References
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