Chapter 2. Dynamic systems methods in the study of language acquisition

Language acquisition is viewed as an example of a dynamic system. It consists of many components that interact with each other. The components show trajectories over time, the properties of which result from the dynamics of the interaction. A large variety of components can be taken as potential indicators of underlying mechanisms of change and acquisition. Examples of such indicators are the number of one-, two-, three- and more word sentences, the number of spatial prepositions, and many others. These and other observable aspects may be used as stochastic indicators of underlying processes such as transitions between qualitatively distinct generative mechanisms, discontinuities, and so forth. Insights into the dynamics of language acquisition may be obtained, first, by modeling the dynamic interactions between the components at issue and by comparing qualitative properties of data simulated by those models with properties of empirical data. A second approach to obtaining more insight into the dynamics of language acquisition is by applying flexible smoothing techniques to time-serial language data and to determine the eventual changes in the amount of fluctuation in the data. Both the smoothed curves and fluctuation data can provide indirect evidence of underlying processes, such as continuities or discontinuities and regressions. The modeling, smoothing, and fluctuation techniques are primarily quantitative and should be seen as an addition to qualitative analyses.