Showing papers in "Educational technology research in 2005"

A noniterative item parameter solution in each EM cycle of the continuous response model

Abstract: In thiS research, we focused on the normal density type of the continuous response model (CRM; Samejima, 1973, 19741 Wang & Zeng, 1998), and proposed a method to estimate item parameters for this type of CRM by rnarginal maximum likelihood estimation method wit,h the EM algorithm (Dempster, Laird & Rubin, 1977). The proposed method did not require any numerical approximation in the expectation step. Moreover, we showed that exact solutions could easily be obtained in the maximization step when flat priors of item parameters were assumed, Therefore, our method could be noniteratlvely completed through each EM cycle, In addition, we examined the performance of the proposed method using simulation data. We then confirmed the accuracy of our method by only taking flat priors into consideration.