Feature economy vs. logical complexity in phonological pattern learning

Complexity has been linked to ease of learning. This article explores the roles of two measures of complexity – feature economy and logical complexity – in the acquisition of sets of signs, taken from a small sign language that serves as an analogue of plosive inventories in spoken language. In a learning experiment, participants acquired data sets that varied in feature economy and logical complexity. The results from this study suggest that ease of learning is best predicted by logical complexity, and that a considerable number of learners unintentionally reduce the complexity of their input.