Fig. 1. The data available for everyday learning changes with development.

Statistical learning depends on the data – the training trials experiences of the learner – and the learner’s cognitive machinery that does the learning. Contemporary research is focused on the nature of the learning machinery and uses two approaches: (a) In human laboratory experiments, researchers test hypotheses about internal cognitive processes by creating experimental training sets and testing human learners’ abilities to learn from them. (b) In human computational studies, researchers build models that instantiate their ideas about the learning machinery and feed those models training sets created by the experimenter to tests the model’s ability to find the regularities in the input data. Every day learning by infants (c) differs substantially from these approaches in the nature of the data for learning. Infants encounter data for learning from a specific vantage point that depends on where they the location, the body’s posture, and behavior of the infant. Because infant locations, postures, and behaviors change systematically with development, the data sets for learning change systematically with development. The infants developing abilities – sitting up, crawling, walking – open and close gates or visual experiences with different content and different statistical structure.