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This study presents a modular connectionist model of the development of seriation in children. The model makes use of the cascade-correlation generative algorithm. The algorithm builds its own network topology as is required to solve the task. This model develops in a stage-like manner and goes beyond the previous rule based models by successfully capturing both the variability in strategies used and the sensitivity to differences in size increments. The application of a systematic operational procedure to a subset of the elements in the series is identified as a source of empirical seriation. Finally, the model predicts that the degree of disorder of the array under construction is a significant factor in determining the observed seriating behavior. A follow-up study involving 4- to 7-year-old children finds that the degree of disorder is a significant factor in children's abilities to recognize a completed series.