Item Response Theory: An Introduction to Latent Trait Models to Test and Item Development

Abstract

Testing in educational system perform a number of functions, the results from a test can be used to make a number of decisions in education. It is therefore well accepted in the education literature that, testing is an important element of education. To effectively utilize the tests in educational policies and quality assurance its validity and reliability estimates are necessary. There are two generally acceptable frameworks used in evaluating the quality of test in educational and psychological measurements, these are; Classical Test Theory (CTT) and Item Response Theory (IRT). The estimates of test items validity and reliability depend on a particular measurement model used. It is vital for a test developer to be familiar with the different test development and item analysis methods in order to facilitate the development of a new test. The CTT is a traditional approach which was widely criticise in the measurement community for its shortcomings such as sample dependency of coefficient measures and estimates of measurement error. However, the IRT is a modern approach which provides solutions to most of the CTT"s identified shortcomings. This paper therefore, provides a comprehensive overview of the IRT and its procedures as applied to test item development and analysis. The paper concludes with some suggestions for test developers and test specialists at all levels to adopt IRT for its identified crucial theoretical and empirical gains over CTT. IRT based parameter estimates should be superior and reliable than CTT based parameter estimates. With these features, IRT can help resolve the problems associated with test design based on CTT Keyword:Classical Test Theory Item Response Theory Reliability Validity

Comparative Analysis of Classical Test Theory and Item Response Theory using Chemistry Test Data

“…Using IRT-based statistics 14 items were considered "faulty" or "problematic" and the remaining 26 items classified as "good" items. Similarly, both the two frameworks commonly identified 13 items as "problematic" or "faulty" these were items 2,3,9,14,18,20,25,26,29,30,32,34,35 and 40. Items 9, 14, 30 and 35 have negative discrimination indices.…”

“…The two popular models used in educational, psychological and behavioural measurements are the Classical Test Theory (CTT) and Item Response Theory (IRT). The major difference within the two theories can best be understood from the underlying statistical analyses inherent it [9]. A brief discussion is given to understand the theories as it relates to this work.…”

An Item Response Theory Analysis of the Korean Version of the CRAFFT Scale for Alcohol Use Among Adolescents in Korea

“…IRT, which developed from CTT, has some advantages over CTT. First, IRT computes item statistics that are independent of the sample from which they were estimated [18]. Second, a respondent's scores in a measure are independent of item difficulty [18], that is, independent of the particular choice of item.…”

“…First, IRT computes item statistics that are independent of the sample from which they were estimated [18]. Second, a respondent's scores in a measure are independent of item difficulty [18], that is, independent of the particular choice of item. Third, in IRT, the standard error of measurement is not assumed to have a constant value regardless of the respondent's location on the range of a scale [18].…”

“…Second, a respondent's scores in a measure are independent of item difficulty [18], that is, independent of the particular choice of item. Third, in IRT, the standard error of measurement is not assumed to have a constant value regardless of the respondent's location on the range of a scale [18]. This means that a measure is not equally precise across the full range of possible item scores [19].…”