By Margaret Wu, Hak Ping Tam, Tsung-Hau Jen
This ebook is a priceless learn for a various team of researchers and practitioners who examine overview information and build attempt tools. It specializes in using classical attempt thought (CTT) and merchandise reaction idea (IRT), that are usually required within the fields of psychology (e.g. for measuring mental traits), healthiness (e.g. for measuring the severity of disorders), and schooling (e.g. for measuring pupil performance), and makes those analytical instruments available to a broader viewers.
Having taught evaluation matters to scholars from various backgrounds for a few years, the 3 authors have a wealth of expertise in featuring academic size themes, in-depth ideas and purposes in an obtainable structure. As such, the publication addresses the desires of readers who use CTT and IRT of their paintings yet don't unavoidably have an intensive mathematical historical past. The booklet additionally sheds mild on universal misconceptions in utilizing size versions, and provides an built-in method of diversified size equipment, equivalent to contrasting CTT with IRT and multidimensional IRT versions with unidimensional IRT versions. at any place attainable, comparisons among types are explicitly made. moreover, the e-book discusses suggestions for attempt equating and differential merchandise functioning, in addition to Bayesian IRT versions and believable values utilizing uncomplicated examples.
This publication can function a textbook for introductory classes on academic size, as supplementary interpreting for complex classes, or as a useful reference consultant for researchers attracted to examining scholar overview data.
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Additional info for Educational Measurement for Applied Researchers: Theory into Practice
2 Student numeracy scores distributions (NAPLAN 2010) Summary About Measuring Individuals The main message is that a one-off test does not provide very accurate information at the individual student level other than an indicative level of whether a student is below average, at average or above average. This lack of accuracy should not surprise us. If ever one single test of 30 items is used for high-stakes purposes such as selection into colleges or awarding certiﬁcates, we should be very wary of the results.
For example, if we only want to divide students into three ability groups with roughly the same range, a 30-item test will provide sufﬁcient precision for that, as shown in Fig. 1. But at the same time, teacher judgements probably can provide us that information with sufﬁcient accuracy already. Suppose the purpose of our test is to monitor student growth. We need to ﬁrst make a guesstimate of the magnitude of the growth before we can design instruments to measure that growth with sufﬁcient accuracy.
For example, if the latent variable is proﬁciency in geometry, then the items are individual questions about speciﬁc knowledge or skills in geometry. The arrows (from the latent variable to the observed indicators) in Fig. 1 indicate that the level of the latent variable influences the likely responses to the items. It is important to note the direction of the arrows. That is, the item response pattern is driven by the level of the latent variable. It is not the other way round that the latent variable is deﬁned by the item responses.
Educational Measurement for Applied Researchers: Theory into Practice by Margaret Wu, Hak Ping Tam, Tsung-Hau Jen