The purpose of this study was to compare the effects of four item selection rules-( 1 ) Fisher information (F), (2) Fisher informution with a posterior distribution (FP), (3) Kullhack-Leibler information with a posterior distribution (KP), and (4) cotnpletely randomized item selection (RN)-nith respect to the precision of trait estimation and the extent of item usage at the early stages of computerized adaptive testing. The comparison ofthe four item selection rules was carried out under three conditions: (1) using only the item informatiorz function as the item selection criterion; (2) using both the item information function and content balancing; and (3) using the item information function, content balancing, and item exposure control. When test length was less than 10 items, FP and KP tended to outper$orm F at extreme trait levels in Condition 1. However, in more realistic settings, it could not he concluded that FP and KP outperformed F, especially when item exposure control was imposed. When test length was greater than 10 items, the three nonrandom item selection procedures performed similarly no matter what the condition was, while F had slightly higher item usage.
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