Item response theory: A basic concept | Zendy

Mahmud Jumailiyah | Zendy

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Item response theory: A basic concept

Author(s) -

Mahmud Jumailiyah

Publication year - 2017

Publication title -

educational research and reviews

Language(s) - English

Resource type - Journals

ISSN - 1990-3839

DOI - 10.5897/err2017.3147

Subject(s) - item response theory , classical test theory , a priori and a posteriori , psychometrics , maximum likelihood , test theory , computer science , estimation , econometrics , key (lock) , maximum a posteriori estimation , estimation theory , cognitive psychology , psychology , statistics , machine learning , artificial intelligence , mathematics , algorithm , epistemology , engineering , philosophy , computer security , systems engineering

With the development in computing technology, item response theory (IRT) develops rapidly, and has become a user friendly application in psychometrics world. Limitation in classical theory is one aspect that encourages the use of IRT. In this study, the basic concept of IRT will be discussed. In addition, it will briefly review the ability parameter estimation, particularly maximum likelihood estimation (MLE) and expected a posteriori (EAP). This review aims to describe the fundamental understanding of IRT, MLE and EAP which likely facilitates evaluators in the psychometrics to recognize the characteristics of test participants. Key words: Expected A Posteriori, Item Response Theory, Maximum Likelihood Estimation

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