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== Psychometric model ==
Two approaches are available for the psychometric model of a CCT: [[classical test theory]] (CTT) and [[item response theory]] (IRT). Classical test theory assumes a state model because it is applied by determining item parameters for a sample of examinees determined to be in each category. For instance, several hundred "masters" and several hundred "
There are advantages and disadvantages to each. CTT offers greater conceptual simplicity. More importantly, CTT requires fewer examinees in the sample for calibration of item parameters to be used eventually in the design of the CCT, making it useful for smaller testing programs. See Frick (1992)<ref>Frick, T. (1992). Computerized Adaptive Mastery Tests as Expert Systems. Journal of Educational Computing Research, 8(2), 187-213.</ref> for a description of a CTT-based CCT. Most CCTs, however, utilize IRT. IRT offers greater specificity, but the most important reason may be that the design of a CCT (and a CAT) is expensive, and is therefore more likely done by a large testing program with extensive resources. Such a program would likely use IRT.
== Starting point ==
A CCT must have a specified starting point to enable certain algorithms. If the [[sequential probability ratio test]] is used as the termination criterion, it implicitly assumes a starting ratio of 1.0 (equal probability of the examinee being a master or
== Item selection ==
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