How do we decide what to say to ensure our meanings will be understood? The Rational Speech Act model (RSA; Frank & Goodman, 2012 ) asserts that speakers plan what to say by comparing the informativity of words in a particular context. We present the first example of an RSA model of sentence-level (who-did-what-to-whom) meanings. In these contexts, the set of possible messages must be abstracted from entities in common ground (people and objects) to possible events (Jane eats the apple, Marco peels the banana), with each word contributing unique semantic content. How do speakers accomplish the transformation from context to compositional, informative messages? In a communication game, participants described transitive events (e.g., Jane pets the dog), with only two words, in contexts where two words either were or were not enough to uniquely identify an event. Adults chose utterances matching the predictions of the RSA even when there was no possible fully “successful” utterance. Thus we show that adults’ communicative behavior can be described by a model that accommodates informativity in context, beyond the set of possible entities in common ground. This study provides the first evidence that adults’ language production is affected, at the level of argument structure, by the graded informativity of possible utterances in context, and suggests that full-blown natural speech may result from speakers who model and adapt to the listener’s needs.

Many important questions about children’s early abilities and learning mechanisms remain unanswered not because of their inherent scientific difficulty but because of practical challenges: recruiting an adequate number of children, reaching special populations, or scheduling repeated sessions. Additionally, small participant pools create barriers to replication while differing laboratory environments make it difficult to share protocols with precision, limiting the reproducibility of developmental research. Here we introduce a new platform, “Lookit,” that addresses these constraints by allowing families to participate in behavioral studies online via webcam. We show that this platform can be used to test infants (11–18 months), toddlers (24–36 months), and preschoolers (36–60 months) and reliably code looking time, preferential looking, and verbal responses, respectively; empirical results of these studies are presented in Scott, Chu, and Schulz ( 2017 ). In contrast to most laboratory-based studies, participants were roughly representative of the American population with regards to income, race, and parental education. We discuss broad technical and methodological aspects of the platform, its strengths and limitations, recommendations for researchers interested in conducting developmental studies online, and issues that remain before online testing can fulfill its promise.

To help address the participant bottleneck in developmental research, we developed a new platform called “Lookit,” introduced in an accompanying article (Scott & Schulz, 2017 ), that allows families to participate in behavioral studies online via webcam. To evaluate the viability of the platform, we administered online versions of three previously published studies involving different age groups, methods, and research questions: an infant ( M = 14.0 months, N = 49) study of novel event probabilities using violation of expectation, a study of two-year-olds’ ( M = 29.2 months, N = 67) syntactic bootstrapping using preferential looking, and a study of preschoolers’ ( M = 48.6 months, N = 148) sensitivity to the accuracy of informants using verbal responses. Our goal was to evaluate the overall feasibility of moving developmental methods online, including our ability to host the research protocols, securely collect data, and reliably code the dependent measures, and parents’ ability to self-administer the studies. Due to procedural differences, these experiments should be regarded as user case studies rather than true replications. Encouragingly, however, all studies with all age groups suggested the feasibility of collecting developmental data online and the results of two of three studies were directly comparable to laboratory results.