Content deleted Content added
Olexa Riznyk (talk | contribs) m →Bibliography of CCT research: Fixing style/layout errors |
Olexa Riznyk (talk | contribs) →Psychometric model: Adding a wikilink |
||
Line 18:
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 "non-masters" might be sampled to determine the difficulty and discrimination for each, but doing so requires that you be able to easily identify a distinct set of people that are in each group. IRT, on the other hand, assumes a trait model; the knowledge or ability measured by the test is a continuum. The classification groups will need to be more or less arbitrarily defined along the continuum, such as the use of a cutscore to demarcate masters and non-masters, but the specification of item parameters assumes a trait model.
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>{{cite journal|last=Frick|first=T.|year=1992|title=Computerized Adaptive Mastery Tests as Expert Systems|journal=Journal of Educational Computing Research|volume=8|issue=2|pages=187-213|doi=10.2190/J87V-6VWP-52G7-L4XX}}</ref> for a description of a CTT-based CCT. Most CCTs, however, utilize IRT. IRT offers greater [[Specificity (test)|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 ==
| |||