Proceedings of the Annual Meeting of the Cognitive Science Society

Both children and adults are able to extract several intended word-referent mappings from a series of scenes con-taining multiple words and objects. Known as cross-situational learning, this ability is thought to be an important means ofacquiring language. Proposed models of this ability range from hypothesis-testing accounts to associative accounts, but mostformal models assume learners store one or more feasible word-referent mappings per experience, and that the correct map-pings emerge through consistent co-occurrence. These theories would all predict that presenting unambiguous evidence for acorrect pair would benefit learning, but recent evidence indicates the reverse is true: giving unambiguous evidence for incorrectpairs improves subsequent cross-situational learning (Fitneva and Christiansen, 2015). With some nuances, we replicate theseresults, and show why future models may need to include an error-driven learning mechanism to explain word learning.