By Margaret Wu, Hak Ping Tam, Tsung-Hau Jen
This ebook is a worthy learn for a various crew of researchers and practitioners who examine overview info and build try out tools. It specializes in using classical try out idea (CTT) and merchandise reaction concept (IRT), that are frequently required within the fields of psychology (e.g. for measuring mental traits), overall healthiness (e.g. for measuring the severity of disorders), and schooling (e.g. for measuring scholar performance), and makes those analytical instruments available to a broader viewers.
Having taught overview topics to scholars from assorted backgrounds for a few years, the 3 authors have a wealth of expertise in providing academic size subject matters, in-depth thoughts and functions in an obtainable structure. As such, the booklet addresses the desires of readers who use CTT and IRT of their paintings yet don't unavoidably have an in depth mathematical heritage. The publication additionally sheds mild on universal misconceptions in employing dimension versions, and offers an built-in method of diversified size tools, equivalent to contrasting CTT with IRT and multidimensional IRT types with unidimensional IRT types. anywhere attainable, comparisons among types are explicitly made. furthermore, the booklet discusses innovations for try equating and differential merchandise functioning, in addition to Bayesian IRT types and believable values utilizing uncomplicated examples.
This publication can function a textbook for introductory classes on academic size, as supplementary interpreting for complicated classes, or as a invaluable reference advisor for researchers drawn to examining scholar overview data.
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Extra resources for Educational Measurement for Applied Researchers: Theory into Practice
Example text
However, consider the case of mathematical problem solving, where each problem requires a certain amount of reading and mathematics proficiencies to arrive at an answer. If a test consists of problem solving items where each item requires the same “proportional amount” of reading ability and mathematics ability, the test can still be considered “unidimensional”, with a single latent variable called “problem solving”. From this point of view, whether a test is “unidimensional” depends on the extent to which the items are testing the same construct, where the construct can be defined as a composite of abilities (Reckase et al.
Test writers typically have good ideas about the difficulty levels of items, but it is rarely obvious to test writers how discriminating an item may be. Information on discrimination needs to come from item analysis. Scoring schemes can be adjusted based on the empirical discrimination indices obtained after conducting trial tests of items. Alternatively, 34 2 Construct, Framework and Test Development—From IRT Perspectives using the two-parameter IRT model (2-PL) will solve the problem of having to guess the item scores a priori.
While one needs to bear in mind that items should all tap into the same construct, items ought to be independent in the sense that there are not the same question asked in slightly different ways, since we want each item to provide an independent and additional piece of information about a test taker. Further, the answer to a question should not be dependent on the answers for previous questions. Item Format There has been much debate about the pros-and-cons of multiple-choice items over constructed-response items.