Statistical learning refers to the ability to identify structure in the input based on its statistical properties. For many linguistic structures, the relevant statistical features are distributional: They are related to the frequency and variability of exemplars in the input. These distributional regularities have been suggested to play a role in…

A theory for storage and retrieval of associative information is presented. Items or events are represented as random vectors. Convolution is used as the storage operation, correlation as the retrieval operation. A distributed memory system is assumed. The theory applies to recognition and recall and covers both accuracy and latency. (Author/RD)

Twenty-nine reports yielding 112 studies were analyzed with Glass's meta-analysis technique, and results were compared with predictions from Ausubel's model of assimilative learning. Overall, advance organizers were shown to be associated with increased learning and retention of material to be learned. (Author)

A model of association formation, storage, and retrieval is described. Experiments which test new predictions derived from the model against human recall are reported. The model is applied to previous findings: prototype abstraction, the A-B A-D paradigm and the Osgood transfer surface. Previous models of memory are discussed. (Author/RD)

The cascade model of information processing is compatible with the relation between time and accuracy in speed-accuracy trade-off experiments. Findings regarding the additive factors methods led to reexamination of conclusions drawn from several studies about the locus of perceptual and attentional effects on processing. (Author/RD)