Proceedings of the Annual Meeting of the Cognitive Science Society

Study of cognitive development on the balance scale task has inspired a wide range of human and computational work. The task requires that children predict the outcome of placing a discrete number of weights at various distances on either side of a fulcrum. The current project examined the adequacy of the symbolic learning algorithm C4.5 as a model of cognitive transition on this task. Based on a set of novel assumptions, our C4.S simulations were able to exhibit regularities found in the human data including orderly stage progression, U-shaped development, and the torque difference effect. Unlike previous successful models of the task, the current model used a single free parameter, is not restricted in the size of the balance scale that it can accommodate, and does not require the assumption of a highly structured output representation or a training environment biased towards weight or distance information. The model makes a number of predictions differing from those of previous computational efforts.