The dynamic nature of knowledge: insights from a dynamic field model of children's novel noun generalization

Abstract

This paper examines the tie between knowledge and behavior in a noun generalization context. An experiment directly comparing noun generalizations of children at the same point in development in forced-choice and yes/no tasks reveals task-specific differences in the way children's knowledge of nominal categories is brought to bear in a moment. To understand the cognitive system that produced these differences, the real-time decision processes in these tasks were instantiated in a dynamic field model. The model captures both qualitative and quantitative differences in performance across tasks and reveals constraints on the nature of children's accumulated knowledge. Additional simulations of developmental change in the yes/no task between 2 and 4 years of age illustrate how changes in children's representations translate into developmental changes in behavior. Together, the empirical data and model demonstrate the dynamic nature of knowledge and are consistent with the perspective that knowledge cannot be separated from the task-specific processes that create behavior in the moment.

Figure 1

Stimuli used in the Experiment.

Figure 2

Data from the experiment. The left panels show the proportion of shape choices for deformable and rigid exemplars following demonstrations of related and arbitrary properties in the forced choice task. The right panels show the corresponding proportions of yes responses to the shape-, color-, and material matching test objects in the yes/no task. There were no effects of relatedness so the figure collapses across this factor.

Figure 3

Comparison of performance in the forced choice and yes/no tasks of the experiment. Yes/no data were converted to proportion shape choices via the Luce Choice Rule.

Figure 4

Dynamic Field Model used to simulate differences in performance in forced choice and yes/no tasks. Model consists of an input field (top field in panel A) and decision field (bottom field Panel A). The x-axis of each field represents a set of neurons arranged by “similarity”. Activation of each neuron is plotted along the y-axis. Time is shown along the z-axis as the sequence of events in a single trial unfold. Panel A depicts a forced choice trial. The top two fields in Panel B depict a yes/no trial with similar inputs, the bottom two fields, a yes/no trial with dissimilar inputs. See text for further details.

Figure 5

Interaction functions for the decision field when the model performed the forced choice (solid line) and yes/no (dashed line) tasks. The solid line at 0 marks the difference between excitatory interactions and inhibitory interactions. Bars indicate magnitude of parameter values given in Table 2. See text for details.

Figure 6

Model inputs for the deformable and rigid sets that result from the final input parameters. Relative overall similarity is represented along the x-axis, activation along the y-axis. Solid lines represent deformable inputs, dashed lines represent rigid inputs. Each set of inputs includes an exemplar (leftmost peaks), a shape-matching test object (center peaks), and a material-matching test object (rightmost peaks).

Figure 7

Mean proportion of times the model (white bars) selected the shape-matching test object in the forced choice task as well as the mean proportion of yes responses to the shape and material-matching test objects in the yes/no task for the deformable and rigid stimulus sets. The corresponding data from children in the experiment are also presented (black bars).

Figure 8

Mean Proportion of yes responses by 2-, 2.5-, 3-, and 4-year-old children (black bars), and the DF model (white bars) to shape- and material-matching test objects in the yes/no task for deformable and rigid stimulus sets. Thirty-two month-old data are from the current paper. Two , three- and four-year-old data are from Samuelson, Horst, Schutte, & Dobbertin (2008).

Fig. 9

Change in noise strength (q) and shape strength parameters across simulated developmental levels relative to simulations of 2.5-year-old children.