Date of Award


Document type


Access Type

Open Access Dissertation

Degree Name

Doctor of Education (EdD)

Degree Program

Education (also CAGS)

First Advisor

Ronald K. Hambleton

Second Advisor

Craig S. Wells

Third Advisor

Aline G. Sayer

Subject Categories



IRT, also referred as "modern test theory", offers many advantages over CTT-based methods in test development. Specifically, an IRT information function has the capability to build a test that has the desired precision of measurement for any defined proficiency scale when a sufficient number of test items are available. This feature is extremely useful when the information is used for decision making, for instance, whether an examinee attain certain mastery level. Computerized adaptive testing (CAT) is one of the many examples using IRT information functions in test construction. The purposes of this study were as follows: (1) to examine the consequences of improving the test quality through the addition of more discriminating items with different item formats; (2) to examine the effect of having a test where its difficulty does not align with the ability level of the intended population; (3) to investigate the change in decision consistency and decision accuracy; and (4) to understand changes in expected information when test quality is either improved or degraded, using both empirical and simulated data. Main findings from the study were as follows: (1) increasing the discriminating power of any types of items generally increased the level of information; however, sometimes it could bring adverse effect to the extreme ends of the ability continuum; (2) it was important to have more items that were targeted at the population of interest, otherwise, no matter how good the quality of the items may be, they were of less value in test development when they were not targeted to the distribution of candidate ability or at the cutscores; (3) decision consistency (DC), Kappa statistic, and decision accuracy (DA) increased with better quality items; (4) DC and Kappa were negatively affected when difficulty of the test did not match with the ability of the intended population; however, the effect was less severe if the test was easier than needed; (5) tests with more better quality items lowered false positive (FP) and false negative (FN) rate at the cutscores; (6) when test difficulty did not match with the ability of the target examinees, in general, both FP and FN rates increased; (7) polytomous items tended to yield more information than dichotomously scored items, regardless of the discriminating parameter and difficulty of the item; and (8) the more score categories an item had, the more information it could provide. Findings from this thesis should help testing agencies and practitioners to have better understanding of the item parameters on item and test information functions. This understanding is crucial for the improvement of the item bank quality and ultimately on how to build better tests that could provide more accurate proficiency classifications. However, at the same time, item writers should be conscientious about the fact that the item information function is merely a statistical tool for building a good test, other criteria should also be considered, for example, content balancing and content validity.


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