Abstract
Successful communication often involves comprehension of both spoken language and observed actions with and without objects. Even very young infants can learn associations between actions and objects as well as between words and objects. However, in daily life, children are usually confronted with both kinds of input simultaneously. Choosing the critical information to attend to in such situations might help children structure the input, and thereby, allow for successful learning. In the current study, we therefore, investigated the developmental time course of children’s and adults’ word and action learning when given the opportunity to learn both word-object and action-object associations for the same object. All participants went through a learning phase and a test phase. In the learning phase, they were presented with two novel objects which were associated with a distinct novel name (e.g., “Look, a Tanu”) and a distinct novel action (e.g., moving up and down while tilting sideways). In the test phase, participants were presented with both objects on screen in a baseline phase, then either heard one of the two labels or saw one of the two actions in a prime phase, and then saw the two objects again on screen in a recognition phase. Throughout the trial, participants’ target looking was recorded to investigate whether participants looked at the target object upon hearing its label or seeing its action, and thus, would show learning of the word-object and action-object associations. Growth curve analyses revealed that 12-month-olds showed modest learning of action-object associations, 36-month-olds learned word-object associations, and adults learned word-object and action-object associations. These results highlight how children attend to the different information types from the two modalities through which communication is addressed to them. Over time, with increased exposure to systematic word-object mappings, children attend less to action-object mappings, with the latter potentially being mediated by word-object learning even in adulthood. Thus, choosing between different kinds of input that may be more relevant in their rich environment encompassing different modalities might help learning at different points in development.
Highlights
The fetus can hear the rhythm and intonation of voices in the immediate surrounding [1], might feel the mother move, and moves by itself [2], thereby experiencing language and movement during the latter period of gestation
Given the focus of the current study, we focus here exclusively on the learning of word-object and action-object associations, and do not include the extensive literature on the learning of word-action associations, i.e., verb learning, we note it is possible that both word-object and actionobject associations are likely to be impacted by verb learning
We explored the developmental trajectory of children learning to associate words and actions with objects
Summary
The fetus can hear the rhythm and intonation of voices in the immediate surrounding [1], might feel the mother move, and moves by itself [2], thereby experiencing language and movement during the latter period of gestation. As soon as the infant enters this world, she is confronted with a complex, multimodal environment encompassing both of these information types [3, 4]. This rich environment can help familiarize the child with the conceptual and social aspects of their world where successful communication encompasses both the comprehension of spoken language and observed actions. While infants seem to show similar patterns of learning for wordobject and word-action mappings [5], word-object and action-object mappings have only been examined in older age groups (e.g., 30-month-olds; [6]). We examine children’s learning of word-object and action-object associations throughout infancy and early childhood. Our aim is to compare learning from these different domains, since information from these domains are present in the input that is provided to the child from early on and at least early learning of such associations can be captured by comparably simple associative learning
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