Modeling Cognitive Development of the Balance Scale Task Using ANN

In this paper we describe a Artificial Neural Network model of children's development on the balance scale task. In balance scale experiments, the child is asked to predict the outcome of placing certain numbers of equal weights at various distances to the left or right of a fulcrum. Both stage progressions and information salience effects have been found with children on this task. Artificial Neural Network provided better fits to these human data than did previous models, whether rule-based or connectionist. The ANN network model was used to generate a variety of novel predictions for psychological research. The dataset was collected from UCI Machine learning repository. The model was trained and validated using Just Neural Network Tool. The accuracy rate was 93%