The extraction of cooccurrences between two events, A and B, is a central learning mechanism shared by all species capable of associative learning. Formally, the cooccurrence of events A and B appearing in a sequence is measured by the transitional probability (TP) between these events, and it corresponds to the probability of the second stimulus…

An associative model of serial learning is described based on the assumption that the effective stimulus for a serial-list item is generated by adaptation-level coding of the item's ordinal position. How the model can generate predictions of aspects of serial-learning data is illustrated. (SLD)

Three experiments report additional evidence that it is a mistake to account for all interletter effects solely in terms of sensory variables. These experiments attest to the importance of structural variables such as retina location, array size, and ordinal position. (Author/PN)