01734nas a2200145   4500008004100000020001400041245006700055210006500122300001200187490000700199520125900206100001901465700001201484856009201496       1996                        eng d  a0146-621600aA global information approach to computerized adaptive testing0 aglobal information approach to computerized adaptive testing  a213-2290 v203 abased on Fisher information (or item information). At each stage, an item is selected to maximize the Fisher information at the currently estimated trait level (&thetas;). However, this application of Fisher information could be much less efficient than assumed if the estimators are not close to the true &thetas;, especially at early stages of an adaptive test when the test length (number of items) is too short to provide an accurate estimate for true &thetas;. It is argued here that selection procedures based on global information should be used, at least at early stages of a test when &thetas; estimates are not likely to be close to the true &thetas;. For this purpose, an item selection procedure based on average global information is proposed. Results from pilot simulation studies comparing the usual maximum item information item selection with the proposed global information approach are reported, indicating that the new method leads to improvement in terms of bias and mean squared error reduction under many circumstances. Index terms: computerized adaptive testing, Fisher information, global information, information surface, item information, item response theory, Kullback-Leibler information, local information, test information.1 aChang, Hua-Hua1 aYing, Z  uhttp://mail.iacat.org/content/global-information-approach-computerized-adaptive-testing