Statistical and Chunking Processes in Adults’ Visual Sequence Learning


Much research has documented learners’ ability to segment auditory and visual input into its component units. Two types of models have been designed to account for this phenomena: statistical models, in which learners represent statistical relations between elements, and chunking models, in which learners represent statistically coherent units of information. In a series of three experiments, we investigated how adults’ performance on a visual sequence-learning task aligned with the predictions of these two types of models. Experiments 1 and 2 examined learning of embedded items and Experiment 3 examined learning of illusory items. The pattern of results obtained was most consistent with the competitive chunking model of Servan-Schreiber and Anderson (1990). Implications for theories and models of statistical learning are discussed.

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