New model of IRT item parameter estimation based on neural networks
一种新的基于神经网络的IRT项目参数估计模型

A new modeling method based on general regression neural networks(GRNN) of item parameter estimation within IRT(Item Response Theory) was discussed. The methods about how to construct the output pattern of neural networks, and especially the input pattern by using Monte Carlo method were described. Methods about how to improve the learning efficiency and generalization ability have been proposed. Simulation experiments denote that it is feasible to fit the nonlinear relationship of item parameters between CTT(Classical Test Theory) and IRT given any precision. Comparisons of this method to other methods have been done at last, which suggested it somewhat advantageous.