Premium
A Conditional Exposure Control Method for Multidimensional Adaptive Testing
Author(s) -
Finkelman Matthew,
Nering Michael L.,
Roussos Louis A.
Publication year - 2009
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.1745-3984.2009.01070.x
Subject(s) - computerized adaptive testing , item response theory , set (abstract data type) , computer science , statistics , selection (genetic algorithm) , control (management) , population , econometrics , mathematics , artificial intelligence , psychometrics , demography , sociology , programming language
In computerized adaptive testing (CAT), ensuring the security of test items is a crucial practical consideration. A common approach to reducing item theft is to define maximum item exposure rates, i.e., to limit the proportion of examinees to whom a given item can be administered. Numerous methods for controlling exposure rates have been proposed for tests employing the unidimensional 3‐PL model. The present article explores the issues associated with controlling exposure rates when a multidimensional item response theory (MIRT) model is utilized and exposure rates must be controlled conditional upon ability. This situation is complicated by the exponentially increasing number of possible ability values in multiple dimensions. The article introduces a new procedure, called the generalized Stocking‐Lewis method, that controls the exposure rate for students of comparable ability as well as with respect to the overall population. A realistic simulation set compares the new method with three other approaches: Kullback‐Leibler information with no exposure control, Kullback‐Leibler information with unconditional Sympson‐Hetter exposure control, and random item selection.