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An Efficiency Balanced Information Criterion for Item Selection in Computerized Adaptive Testing
Author(s) -
Han Kyung T.
Publication year - 2012
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.1745-3984.2012.00173.x
Subject(s) - computerized adaptive testing , computer science , selection (genetic algorithm) , control (management) , item bank , item response theory , quality (philosophy) , statistics , machine learning , artificial intelligence , psychometrics , mathematics , philosophy , epistemology
Successful administration of computerized adaptive testing (CAT) programs in educational settings requires that test security and item exposure control issues be taken seriously. Developing an item selection algorithm that strikes the right balance between test precision and level of item pool utilization is the key to successful implementation and long‐term quality control of CAT. This study proposed a new item selection method using the “efficiency balanced information” criterion to address issues with the maximum Fisher information method and stratification methods. According to the simulation results, the new efficiency balanced information method had desirable advantages over the other studied item selection methods in terms of improving the optimality of CAT assembly and utilizing items with low a‐values while eliminating the need for item pool stratification.