UO5d1

Posted: March 27th, 2020

UO5d1

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UO5d1

When using the classical test theory, the set cut scores have their basis being the test taker’s performance across all items on the examination. The person taking the assessment has to demonstrate that he or she has the targeted attributes in order to pass the test. When using the item response theory, renowned experts determine the minimum level of difficulty of taking a test. The items are verified and each is then associated with a certain intensity of complexity. The test taker passes the test if he or she answers the items that are above the set minimum level of difficulty.

IRT theory is preferred on matters concerning test fairness. The hypothesis is mostly favored because of its ability to adapt the test based on the person undertaking the assessment. The classical test theory can have some bias whereby the levels of difficulty can fluctuate based on the test taker. Concentrating on individuals taking the test ensures that bias does not occur because of factors such as gender, age, or culture. The use of item-characteristic curves in IRT is useful in providing information about the relationship between the performance of individual items and the presumed ability or trait of the test taker (Champlain, 2009). CTT is useful when dealing with a small sample since only smaller trial dimensions are necessary.

CTT theory also uses relatively simple mathematical models. On the other hand, the tests that are developed using this theory are longer and they may require more items. In addition, the psychometric properties of a test depend on the samples responsible for the assessment (Drasgow, 2015). Advantages of using ITR include greater precision in measurement because the advanced psychometric tools and the statistics used in testing do not depend on the samples that have undergone the examination. However, the theory has disadvantages including the fact that the sample size used has to be large, and that the techniques used in testing are complicated and uncommon to many researchers.

Advances in technology will ensure that the measurements used are precise and free from bias. It will be possible to use large sample sizes and complicated mathematical applications with a decreased chance of error.

References

Champlain, A. (2009). A primer on classical test theory and item response theory for assessment in medical education. Retrieved from https://onlinelibrary.wiley.com/doi/full/10.1111/j.1365-2923.2009.03425.x

Drasgow, F. (2015). Technology and testing: Improving educational and psychological measurement. New York, NY: Routledge