MBIC-lecture; Larissa K. Samuelson

Abstract:

Infants, children and adults have been shown to track co-occurrence across ambiguous naming situations to infer the referents of new words. The extensive literature on this cross-situational word learning (CSWL) ability has produced support for two theoretical accounts—associative learning (AL) and hypothesis testing (HT)—but no comprehensive model of the behaviour. I will present WOLVES, a neural process account of CSWL grounded in real-time psychological processes of memory and attention that explicitly models the dynamics of looking in CSWL tasks at a moment-to-moment scale and learning across trials. After a brief overview of Dynamic Field Theory, the basis for this modelling work, I will provide an overview of Word Object Learning via Visual Exploration in Space and demonstrate that it is a good model. I will then show how it helps understand word learning at three timescales: the task, learning during the task, and over development. Next, I will provide an evaluation of the model, comparing it to two other accounts of cross-situational word learning and highlight implications for our understanding of word learning. These include showing how visual exploration, selective attention, and memory support word learning and how changes in these processes impact learning over development. Finally, I will discuss ongoing and future work testing predictions of the model and linking word learning to domains such as executive function.