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Effects of Practical Constraints on Item Selection Rules at the Early Stages of Computerized Adaptive Testing
Author(s) -
Chen ShuYing,
Ankenman Robert D.
Publication year - 2004
Publication title -
journal of educational measurement
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.917
H-Index - 47
eISSN - 1745-3984
pISSN - 0022-0655
DOI - 10.1111/j.1745-3984.2004.tb01112.x
Subject(s) - computerized adaptive testing , selection (genetic algorithm) , item response theory , statistics , equating , trait , item analysis , function (biology) , computer science , mathematics , psychology , artificial intelligence , psychometrics , biology , evolutionary biology , rasch model , programming language
The purpose of this study was to compare the effects of four item selection rules—(1) Fisher information (F), (2) Fisher information with a posterior distribution (FP), (3) Kullback‐Leibler information with a posterior distribution (KP), and (4) completely randomized item selection (RN)—with respect to the precision of trait estimation and the extent of item usage at the early stages of computerized adaptive testing. The comparison of the four item selection rules was carried out under three conditions: (1) using only the item information 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 outperform F at extreme trait levels in Condition 1. However, in more realistic settings, it could not be 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.