, items are selected from strata
with lower discrimination indices. These items are less informative, and tend
to have low exposure rates. Limiting item selection to these strata increases
the exposure rates of these items and reduces the problems of underexposure.
The best results with exposure control problems have been obtained when
methods for dealing with over exposure were combined with methods that
deal with underexposure. Veldkamp, Verschoor e Eggen (2010) therefore
proposed a method that combined both approaches.
Item selection in CAT has been an important research topic for many years,
also because the adaptive item selection process is what makes CAT different from
administering linear test forms. This paragraph only covers a small part of the
literature on it. Most of the existing papers are about CAT with dichotomously
scored items that are calibrated with a unidimensional IRT model. Nowadays, the
focus is shifting more towards developing methods for CAT with more complex
item types that are calibrated with more complicated, often multidimensional, IRT
models. Even though impressive results have been obtained, there are still many
more areas that have to be studied.