A new approach to the development of the item characteristic curve (ICC) is presented, in which knowledge states, decision processes and other circumstances underlying responding to objective tests receivea prioriconsideration. Earlier work on finite state models of objective test performance provides the basis for deriving expressions for ICCs that directly account for factors such as examinee willingness to guess, mode of test administration, number of options per item, and the response strategy of the examinees. This approach utilizes a parameterization of ability different from that used in conventional item response theory (IRT) and yields ICCs that are polynomial functions of ability. The degree and coefficients of these polynomials depend in part on psychological/circumstantial factors such as those just mentioned or others that may readily be introduced. Examples are provided to show how differing assumptions about objective test responding lead to variation in the shapes of the resulting ICCs. The advantages that IRT could gain from adoption of these ICCs are discussed, and the work that remains to be done before finite state polynomic ICCs can be used in practice is outlined. Some possible extensions to the finite state approach are also discussed.