Preserved category-based inferences for word learning in school-aged children with Developmental Language Disorder

Word learning difficulties are often found in children with Developmental Language Disorder (DLD). Lexical patterns of difficulties appear to be well described in the context of DLD but very little research focuses on their underlying causes. Word learning is known to be an inference-based process, constrained by categorization, which helps the extension of new words to unfamiliar referents and situations. These processes appear integrated in Bayesian models of cognition, which supposes that learning relies on an inductive inference process that recruits prior knowledge and principles of statistical learning (detection of regularities). Taken together, these mechanisms remain underexplored in DLD. Our study aims to define whether children with DLD can draw inductive inferences in a word learning context using categorization. Twenty children with DLD (between 6;0 and 12;6), and 20 language-matched and 16 age-matched controls were exposed to a word learning task where they were given exemplars of objects associated with pseudo-words. The objects belonged to six categories spread across three hierarchical levels. For each item, the children chose which one(s), among a set of test objects from the same categories, could be labelled the same way (word extension). Results showed that school-aged children with DLD could extend new words to broader categories as well as their typically developing (TD) peers. Nevertheless, none of the DLD or TD children showed a specification of their categorization of familiar instances that referred to more restricted instances. Our study suggests preserved abilities in using conceptual knowledge in order to learn new words, which could be used as a compensative strategy in the context of therapy. Further studies are needed to investigate this ability in more complex learning contexts.