Learning to be inaccurate like an adult: Using computational cognitive modeling to investigate the acquisition of pronoun interpretation in Spanish

Abstract

When children behave differently from adults in language tasks, it is often unclear if the underlying cause is non-adult-like representation of relevant information, non-adult-like deployment of adult-like representations, or both non-adult-like representations and non-adult-like deployment. We show how computational cognitive modeling can be used to identify which options could lead to specific non-adult-like language behavior, using the case study of Spanish subject pronoun interpretation by typically developing children. In a picture-selection task, children interpret subject pronouns differently from adults; modeling results suggest that both child and adult pronoun interpretation behavior is best captured by inaccuracy somewhere in the pronoun interpretation process, though how exactly children are inaccurate differs from how exactly adults are inaccurate. So, to become adult-like, children need to learn how to be inaccurate in adult-like ways. We discuss the promise and limitations of the computational cognitive modeling approach demonstrated here for evaluating specific hypotheses about the underlying cognitive computations leading to observed language behavior.