Predicting Pragmatic Cue Integration in Adults' and Children's Inferences About Novel Word Meanings

Language is learned in complex social settings where listeners must reconstruct speakers' intended meanings from context. To navigate this challenge, children can use pragmatic reasoning to learn the meaning of unfamiliar words. A critical challenge for pragmatic reasoning is that it requires integrating multiple information sources, which have typically been studied separately. Here we study this integration process. First, we experimentally isolate two sources of pragmatic information: expectations about informative communication and common ground. Next, we use a probabilistic model of conversational reasoning to formalize how these information sources should be combined and how this process might develop. We use this model to generate quantitative predictions, which we test against new experimental data from 3- to 5-year-old children (N = 243) and adults (N = 694). Results show close alignment between model predictions and data. Furthermore, the model provided a better explanation of the data compared with simpler alternative models assuming that participants selectively ignore one information source. This work integrates distinct sets of findings regarding information sources for early language learning and suggests that pragmatic reasoning models can provide a quantitative framework for understanding developmental changes in language learning.