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== Overview ==
A '''computerized classification test''' (CCT) refers to, as its name would suggest, a test that is administered by [[computer]] for the purpose of classifying examinees. The most common CCT is a mastery test where the test classifies examinees as "Pass" or "Fail," but the term also includes tests that classify examinees into more than two categories. While the term may generally be considered to refer to all computer-administered tests for classification, it is usually used to refer to tests that are interactively administered or of variable-length, similar to [[computerized adaptive testing]] (CAT). Like CAT, variable-length CCTs can accomplish the goal of the test (accurate classification) with a fraction of the number of items used in a conventional fixed-form test.
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2. A starting point
3. An item selection [[algorithm]]
4. A termination criterion and scoring procedure
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This article provides a broad overview. A more detailed overview of IRT-based CCT is found in Thompson (2006) and Eggen and Straetmans (2000). If you are interested in CCT, a bibliography is provided below.
== How a CCT Works ==
A CCT is very similar to a CAT. Items are administered one at a time to an examinee. After the examinee responds to the item, the [[computer]] scores it and determines if the examinee is able to be classified yet. If they are, the test is terminated and the examinee is classified. If not, another item is administered. This process repeats until the examinee is classified or another ending point is satisfied (all items in the bank have been administered, or a maximum test length is reached).
== Psychometric Model ==
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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) 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 nonmaster). If the termination criterion is a [[confidence interval]] approach, a specified starting point on theta must be specified. Usually, this is 0.0, the center of the [[distribution]], but it could also be randomly drawn from a certain distribution if the parameters of the examinee distribution are known. Also, previous information regarding an individual examinee, such as their score the last time they took the test (if re-taking) may be used.
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== Termination criterion ==
There are three termination criteria commonly used for CCTs. Bayesian decision theory methods offer great flexibility by presenting an infinite choice of loss/utility structures and evaluation considerations, but also introduce greater arbitrariness. A confidence interval approach calculates a confidence interval around the examinee's current theta estimate at each point in the test, and classifies the examinee when the interval falls completely within a region of theta that defines a classification. This was originally known as adaptive mastery testing (Kingsbury & Weiss, 1983), but does not necessarily require adaptive item selection, nor is it limited to the two-classification mastery testing situation. The [[sequential probability ratio test]] (Reckase, 1983) defines the classification problem as a [[hypothesis test]] that the examinee's theta is equal to a specified point above the cutscore or a specified point below the cutscore.
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