Constraining Item Exposure in Computerized Adaptive Testing with Shadow Tests (CT-02-03)
by Wim J. van der Linden, Bernard P. Veldkamp, University of Twente, Enschede, The Netherlands
A potential danger in computerized adaptive testing (CAT) is that the item selection algorithm may overuse the items with the most attractive statistical characteristics, and the security of these items may be thereby compromised. Therefore, item exposure constraints that assure that none of the items in an item pool are overexposed are an important component of a CAT item selection algorithm. In this paper an alternative to the currently widely applied Sympson-Hetter item exposure control method is presented, which is based on decisions about the eligibility of the items in the pool before the test taker takes the test. If an item is eligible it remains in the pool; if it is ineligible it is removed from the pool for the test taker. These decisions are based on the outcomes of a probabilistic experiment with probabilities of eligibility that constrain the item-exposure rates to be below the target value.