Abstract
Item selection algorithms in computerized adaptive testing. The aim of this paper is to compare the efficacy of three different item selection algorithms in computerized adaptive testing (CAT). These algorithms are based as follows: the first one is based on Item Information, the second one on Entropy, and the last algorithm is a mixture of the two previous ones. The CAT process was simulated using an emotional adjustment item bank. This item bank contains 28 graded items in six categories, calibrated using Samejima (1969) Graded Response Model. The initial results show that the mixed criterium algorithm performs better than the other ones.
