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choice against a stored answer key scores an MCQ More complex scoring rules can evaluate complex patterns or relationships among choices of actions (eg scoring not only the correct actions, but also the sequence in which they were chosen) Arti cial intelligence algorithms and neural nets can also be used to score constrained segments of written and spoken text Obviously, these more complicated scoring mechanisms add complexity to the test delivery driver and tend to exponentially increase the real-time system performance demands It is here that some of the connectivity and data transmission issues (discussed earlier) become highly relevant Aggregate scoring is essential for most types of computerized adaptive test (CAT) That is, a score is needed in order to sequentially tailor the test to the examinee Many commercial test delivery drivers provide the capability to score a test using number-correct scoring or scoring based on the one-, two-, or three-parameter IRT models (See Hambleton and Swaminathan, 1985, for a description of IRT scoring under these models) The test delivery driver needs access to scored responses and the IRT item statistics for the items administered These latter data are typically stored in the resource le noted earlier When called, the scoring algorithm then uses number-correct scoring, maximum likelihood estimation or Bayesian estimation to calculate the test taker s score Most computer-based tests are timed Although timing introduces potential speededness effects, the need for timing controls is usually unavoidable as a way to standardize the conditions of testing and as a means of controlling computer seat time In a well designed test delivery driver, the test timer can be applied to any test unit That is, the total test may have a global time limit However, sections or even testlets may also have time limits imposed There is limited empirical evidence that segmenting a longer test into shorter time blocks actually facilitates pacing for some examinees (Hadadi and Luecht, 1998) The last standard function for the test delivery driver is test unit selection It is important to keep in mind that test unit selection may apply to an item, an item set, a testlet/module, or a full test There are actually three general ways that a test delivery driver can select the next test unit One way is to simply select the next unit in an ordered list The second method is to select randomly from a list of two or more test units The nal method is rule-based selection A CAT uses a particular item selection rule that computes the precision (statistical information) for each unselected item at the current provisional score for the test taker and chooses the item with the maximum precision More elaborate selection rules are possible, including the possibility of implementing formal ATA algorithms that incorporate content balancing heuristics and exposure control mechanisms (Stocking and Swanson, 1993; van der Linden, 2000) It is important to realize that increasingly more complex test unit selection rules tend to (a) require more data to be stored in the resource le, (b) add to the programming complexity of the test delivery driver, and (c) lead to system performance degradation or QC problems under less-than-optimal connectivity con gurations (eg low-bandwidth transmission channels). vb.net code 128 reader VB . NET Barcode Reader - How to Scan & Read Barcode in VB . NET ...
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