Modeling socioeconomic status effects on language development

Socioeconomic status (SES) is an important environmental predictor of language and cognitive development, but the causal pathways by which it operates are unclear. We used a computational model of development to explore the adequacy of manipulations of environmental information to simulate SES effects in English past-tense acquisition, in a data set provided by Bishop (2005). To our knowledge, this is the first application of computational models of development to SES. The simulations addressed 3 new challenges: (a) to combine models of development and individual differences in a single framework, (b) to expand modeling to the population level, and (c) to implement both environmental and genetic/intrinsic sources of individual differences. The model succeeded in capturing the qualitative patterns of regularity effects in both population performance and the predictive power of SES that were observed in the empirical data. The model suggested that the empirical data are best captured by relatively wider variation in learning abilities and relatively narrow variation in (and good quality of) environmental information. There were shortcomings in the model's quantitative fit, which are discussed. The model made several novel predictions, with respect to the influence of SES on delay versus giftedness, the change of SES effects over development, and the influence of SES on children of different ability levels (gene-environment interactions). The first of these predictions was that SES should reliably predict gifted performance in children but not delayed performance, and the prediction was supported by the Bishop data set. Finally, the model demonstrated limits on the inferences that can be drawn about developmental mechanisms on the basis of data from individual differences.